How Australia Compares, Second Edition

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How Australia Compares Second Edition

How Australia Compares is a fascinating reference that compares Australia with 17 developed countries across a wide range of social, economic and political dimensions. It gives not only snapshot comparisons from the present, but charts trends over recent decades or even longer. Encyclopaedic in scope, this book provides statistics for a huge range of human activity, from taxation to traffic accidents, homicide rates to health expenditure, interest rates to internet usage. Countries compared are:

r r r r r r r r r r r r r r r r r

Austria Belgium Canada Denmark Finland France Germany Ireland Italy Japan Netherlands New Zealand Norway Sweden Switzerland United Kingdom United States of America

This new edition is fully revised and updated, and includes new or expanded sections on the impact of the Howard years, advertising, broadband internet access, childcare, income inequality and crime rates. Rodney Tiffen is Professor, Government and International Relations, University of Sydney. Ross Gittins is Economics Editor, Sydney Morning Herald.

How Australia Compares Second Edition Rodney Tiffen and Ross Gittins

CAMBRIDGE UNIVERSITY PRESS

Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo, Delhi, Dubai, Tokyo Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK Published in the United States of America by Cambridge University Press, New York www.cambridge.org Information on this title: www.cambridge.org/9780521712453 © Rodney Tiffen and Ross Gittins 2009 This publication is in copyright. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published in print format 2009

ISBN-13

978-0-521-71245-3

Paperback

Cambridge University Press has no responsibility for the persistence or accuracy of urls for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate. Reproduction and communication for educational purposes The Australian Copyright Act 1968 (the Act) allows a maximum of one chapter or 10% of the pages of this work, whichever is the greater, to be reproduced and/or communicated by any educational institution for its educational purposes provided that the educational institution (or the body that administers it) has given a remuneration notice to Copyright Agency Limited (CAL) under the Act. For details of the CAL licence for educational institutions contact: Copyright Agency Limited Level 15, 233 Castlereagh Street Sydney NSW 2000 Telephone: (02) 9394 7600 Facsimile: (02) 9394 7601 E-mail: [email protected] Information regarding prices, travel timetables and other factual information given in this work are correct at the time of first printing but Cambridge University Press does not guarantee the accuracy of such information thereafter.

CONTENTS List of tables and figures Preface to the second edition Acknowledgements Reading the tables Abbreviations Introduction

page ix xxiii xxiv xxv xxvi ??

1 People

4

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 1.10

5 7 9 11 13 15 17 19 21 23

Global population Population growth Life expectancy Birth rates and the ageing society Immigration flows Settlement of immigrants Refugees – a global perspective Asylum seekers Urbanisation Religious tradition

2 Government and politics 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 2.11

Constitutional history Heads of state and heads of government Federalism Parliamentary structures Governments, ministers and parliaments Electoral systems Party systems and electoral choice Types and duration of governments Partisan colour of governments Women in public life Political participation

3 Economics 3.1 3.2 3.3 3.4 3.5 3.6 3.7

National prosperity Long-term economic growth Contemporary economic performance Inflation and interest rates International trade and investment Exchange rates Agriculture

24 25 27 29 31 33 35 37 39 41 43 45 46 47 49 51 53 55 57 59

CONTENTS

v

3.8 3.9 3.10 3.11 3.12 3.13

Industry and manufacturing Services Trade and current account balances Saving and borrowing Productivity Global perspectives on income and growth

4 Work and labour 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8

Labour force participation Males and females in the labour force Unemployment Youth, education and unemployment Part-time work Working hours Women, work and gender equity Trade unions

5 Government taxes and spending 5.1 Government spending and taxation 5.2 Tax methods 5.3 Government debt and budget balances

72 73 75 77 79 81 83 85 87 88 89 91 93

6 Health

94

6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11 6.12 6.13

95 97 99 101 103 105 107 109 111 113 115 117 119

Total health spending Public and private health spending Doctors, nurses and drugs Hospitals Medical technology Improved life expectancy Deaths from external causes Deaths from circulatory diseases Deaths from cancer HIV and AIDS Obesity Tobacco Global perspectives on life expectancy

7 Education 7.1 Educational attainment 7.2 Expenditure on education 7.3 Public and private spending on education vi

61 63 65 67 69 71

CONTENTS

120 121 123 125

7.4 7.5 7.6 7.7 7.8

Universities Students’ reading literacy Students’ mathematical and scientific literacy Excellence and equity Schools and learning environments

8 Inequality and social welfare 8.1 8.2 8.3 8.4 8.5 8.6

Income inequality Rich and poor Poverty Social expenditure and redistribution Old age poverty and pensions Child poverty and single parents

127 129 131 133 135 136 137 139 141 143 145 147

9 International relations

148

9.1 Military spending 9.2 Foreign aid

149 151

10 Environment 10.1 10.2 10.3 10.4 10.5 10.6

Biodiversity Global warming Greenhouse gas emissions Energy Waste, recycling and pollution control Ecological footprint

11 Science and technology

152 153 155 157 159 161 163 164

11.1 Investment in knowledge 11.2 Business research and development 11.3 Outputs – patents, publications, products

165 167 169

12 Telecommunications and computing

170

12.1 12.2 12.3 12.4 12.5

Personal computers, mobile phones and internet The telecommunications market Mobile telephony The internet Broadband – access, speed, costs

13 Media 13.1 Newspapers 13.2 Advertising

171 173 175 177 179 180 181 183

CONTENTS

vii

13.3 13.4 13.5 13.6

Television Public broadcasting New media Cinema

14 Family

192

14.1 14.2 14.3 14.4 14.5 14.6

193 195 197 199 201 203

Marriage Children Families and households Mothers and employment Child care and early education Family policies and maternity leave

15 Lifestyles and consumption 15.1 15.2 15.3 15.4 15.5

204

Housing Food Alcohol National transport patterns Urban mobility and transport

205 207 209 211 213

16 Crime and social problems

214

16.1 16.2 16.3 16.4 16.5 16.6 16.7 16.8

Crime rates Homicide and violent crime Policing Victim support and public fears Imprisonment and execution Suicide Car accidents Corruption

215 217 219 221 223 225 227 229

17 The search for scoreboards

230

17.1 17.2 17.3 17.4 17.5

Human Development Index Gender development and empowerment Global competitiveness and economic freedom Most liveable cities Globalisation

18 The Howard impact Sources and references

viii

185 187 189 191

CONTENTS

231 233 235 237 239 240 254

TABLES AND FIGURES 1 People 1.1 Global population Table 1.1 World population milestones Table 1.2 Global population sizes 1.2 Population growth Table 1.3 20th century populations Table 1.4 Area and population density Table 1.5 Population growth rates 1.3 Life expectancy Table 1.6 Life expectancy 1900–2000 Figure 1.1 Male life expectancy Figure 1.2 Female life expectancy 1.4 Birth rates and the ageing society Table 1.7 Fertility rates Table 1.8 Distribution of age groups 1960 Table 1.9 Distribution of age groups 2005 1.5 Immigration flows Table 1.10 Scale of immigration Table 1.11 Net migration rate Table 1.12 Components of population growth Table 1.13 Categories of immigration intake 1.6 Settlement of immigrants Table 1.14 Unemployment rates among native and foreign born Table 1.15 Over-qualification rates of native and foreign born populations Table 1.16 Native born and immigrant students’ reading literacy Table 1.17 Educational attainment of native born and immigrants 1.7 Refugees – a global perspective Table 1.18 World totals of refugees Table 1.19 Countries receiving refugees Table 1.20 National origins of refugees Table 1.21 Internally displaced persons 1.8 Asylum seekers Table 1.22 Asylum seekers since the 1980s Table 1.23 Asylum seekers in 2005 Table 1.24 Acceptance of asylum seekers 1.9 Urbanisation Table 1.25 Urbanisation Table 1.26 Biggest city

4 4 6 6 6 8 8 8 10 10 10 12 12 12 12 14 14 14 14 16 16 16 16 18 18 18 20 20

TABLES AND FIGURES

ix

1.10 Religious tradition Table 1.27 Religious tradition

22

2 Government and politics 2.1 Constitutional history Table 2.1 Constitutional history Table 2.2 Male suffrage Table 2.3 Female suffrage 2.2 Heads of state and heads of government Table 2.4 Heads of state and heads of government 2.3 Federalism Table 2.5 Federal and unitary state structures Table 2.6 Taxation by level of government 2.4 Parliamentary structures Table 2.7 Parliamentary structures 2.5 Governments, ministers and parliaments Table 2.8 Governments, ministers and parliaments 2.6 Electoral systems Table 2.9 Electoral systems Table 2.10 Number of national elections 2.7 Party systems and electoral choice Table 2.11 Party systems Table 2.12 Electoral choice and government formation 2.8 Types and duration of governments Table 2.13 Types of governments Table 2.14 Duration of governments Table 2.15 Early Cabinet terminations Table 2.16 Outcomes of elections 2.9 Partisan colour of governments Table 2.17 Partisan colour of governments 1950–2000 2.10 Women in public life Table 2.18 Women in parliament Table 2.19 Female Cabinet ministers Table 2.20 Female heads of government 2.11 Political participation Table 2.21 Electoral participation Table 2.22 Membership of political parties

x

TABLES AND FIGURES

24 24 24 26 28 28 30 32 34 34 36 36 38 38 38 38 40 42 42 42 44 44

3 Economics 3.1 National prosperity Table 3.1 Income per capita Table 3.2 Income per capita 1870–1998 3.2 Long-term economic growth Table 3.3 Economic growth 1820–1998 Table 3.4 Economic growth 1889–1939 3.3 Contemporary economic performance Table 3.5 Contemporary economic growth 3.4 Inflation and interest rates Table 3.6 Inflation Table 3.7 Long-term interest rates 3.5 International trade and investment Table 3.8 Exports Table 3.9 Imports Table 3.10 Inward foreign direct investment Table 3.11 Outward foreign direct investment 3.6 Exchange rates Table 3.12 Exchange rates Table 3.13 Big Mac Index 3.7 Agriculture Table 3.14 Employment in agriculture Table 3.15 Agriculture’s share of the economy Table 3.16 Trade in agriculture Table 3.17 Support for agriculture 3.8 Industry and manufacturing Table 3.18 Employment in industry Table 3.19 Exports of high-technology manufacturing Table 3.20 Industry and manufacturing’s share of the economy 3.9 Services Table 3.21 Employment in services Table 3.22 Services’ share of the economy Table 3.23 Employment within the services sector 3.10 Trade and current account balances Table 3.24 External trade balance Table 3.25 Current account balance

46 46 48 48 50 52 52 54 54 54 54 56 56 58 58 58 58 60 60 60 62 62 62 64 64

TABLES AND FIGURES

xi

3.11 Saving and borrowing Table 3.26 Household saving Table 3.27 Household debt Table 3.28 Gross national saving 3.12 Productivity Table 3.29 Labour productivity Table 3.30 Multi-factor productivity 3.13 Global perspectives on income and growth Table 3.31 Global income per capita Table 3.32 Global economic growth

66 66 66 68 68 70 70

4 Work and labour 4.1 Labour force participation Table 4.1 Labour force participation Table 4.2 Aged dependency ratio Table 4.3 Life expectancy at retirement 4.2 Males and females in the labour force Table 4.4 Male labour force participation Table 4.5 Female labour force participation Table 4.6 Labour force participation among males aged 55–64 Table 4.7 Labour force participation among females aged 55–64 4.3 Unemployment Table 4.8 Unemployment Table 4.9 Long-term unemployment 4.4 Youth, education and unemployment Table 4.10 Youth unemployment Table 4.11 Youths not in education or employment Table 4.12 Education and unemployment 4.5 Part-time work Table 4.13 Part-time employment Table 4.14 Female share of part-time employment Table 4.15 Involuntary part-time work 4.6 Working hours Table 4.16 Annual hours worked Table 4.17 Weekly working hours Table 4.18 Weekly hours of full-time workers Table 4.19 Weeks worked per year

xii

TABLES AND FIGURES

72 72 72 74 74 74 74 76 76 78 78 78 80 80 80 82 82 82 82

4.7 Women, work and gender equity Table 4.20 Gender wage gap Table 4.21 Gender and hourly pay Table 4.22 Women doctors Table 4.23 Division of housework 4.8 Trade unions Table 4.24 Trade union membership Table 4.25 Industrial disputes

84 84 84 84 86 86

5 Government taxes and spending 5.1 Government spending and taxation Table 5.1 Government spending Table 5.2 Tax revenues 5.2 Tax methods Table 5.3 Components of taxation Table 5.4 Broad components of taxation 5.3 Government debt and budget balances Table 5.5 Government deficits and surpluses Table 5.6 Government debt

88 88 90 90 92 92

6 Health 6.1 Total health spending Table 6.1 Health spending Table 6.2 Increases in health expenditure Figure 6.1 Per capita funding of health 6.2 Public and private health spending Table 6.3 Public expenditure on health Table 6.4 Private share of health funding Table 6.5 Out-of-pocket payments for health 6.3 Doctors, nurses and drugs Table 6.6 Doctors Table 6.7 Public consultations with doctors Table 6.8 Expenditure on pharmaceuticals Table 6.9 Nurses 6.4 Hospitals Table 6.10 Acute care hospital beds Table 6.11 Average length of stay in hospital Table 6.12 Hospital bed days Table 6.13 All hospital beds

94 94 94 96 96 96 98 98 98 98 100 100 100 100

TABLES AND FIGURES

xiii

6.5 Medical technology Table 6.14 Magnetic resonance imaging units Table 6.15 Dialysis Table 6.16 Kidney transplants Table 6.17 Births by caesarean section 6.6 Improved life expectancy Table 6.18 Infant mortality Table 6.19 Maternal mortality Table 6.20 Life expectancy at 60 Table 6.21 Healthy life expectancy 6.7 Deaths from external causes Table 6.22 Deaths from external causes Figure 6.2 Potential Years of Life Lost – external causes males Figure 6.3 Potential Years of Life Lost – external causes females 6.8 Deaths from circulatory diseases Table 6.23 Deaths from circulatory diseases Figure 6.4 Potential Years of Life Lost – circulatory diseases males Figure 6.5 Potential Years of Life Lost – circulatory diseases females 6.9 Deaths from cancer Table 6.24 Deaths from cancer Figure 6.6 Potential Years of Life Lost – cancer males Figure 6.7 Potential Years of Life Lost – cancer females 6.10 HIV and AIDS Table 6.25 Deaths from HIV/AIDS Table 6.26 Incidence of AIDS Table 6.27 Global deaths from HIV/AIDS 6.11 Obesity Table 6.28 Obese males Table 6.29 Obese females Table 6.30 Overweight males Table 6.31 Overweight females 6.12 Tobacco Table 6.32 Male daily smokers Table 6.33 Female daily smokers Table 6.34 Tobacco consumption 6.13 Global perspectives on life expectancy Table 6.35 Global life expectancy Table 6.36 Global infant mortality

xiv

TABLES AND FIGURES

102 102 102 102 104 104 104 104 106 106 106 108 108 108 110 110 110 112 112 112 114 114 114 114 116 116 116 118 118

Table 6.37 Access to improved drinking water Table 6.38 Doctors – a global perspective

118 118

7 Education 7.1 Educational attainment Table 7.1 Educational attainment of adult population Table 7.2 Labour market entrants with tertiary qualifications Figure 7.1 Male and female adults with upper secondary education Figure 7.2 Male and female adults with tertiary education 7.2 Expenditure on education Table 7.3 Total education spending Table 7.4 Changes in real expenditure per student Table 7.5 Student-staff ratios Table 7.6 Teachers’ salaries 7.3 Public and private spending on education Table 7.7 Public expenditure on education Table 7.8 Public and private shares of education expenditure Table 7.9 Public share of tertiary education expenditure Table 7.10 Public expenditure on public and private education institutions 7.4 Universities Table 7.11 Total spending on tertiary education Table 7.12 Public expenditure on tertiary education Table 7.13 Education levels and earnings inequality Table 7.14 International students in tertiary institutions 7.5 Students’ reading literacy Table 7.15 Students’ reading literacy Figure 7.3 Reading proficiency levels 7.6 Students’ mathematical and scientific literacy Table 7.16 Students’ maths literacy Table 7.17 Students’ science literacy Figure 7.4 Science proficiency levels 7.7 Excellence and equity Table 7.18 Range of literacy performance Table 7.19 Gender differences Table 7.20 Socio-cultural inequalities and literacy standards 7.8 Schools and learning environments Table 7.21 Student time studying subjects at school Table 7.22 Student time studying lessons outside school

120 120 120 120 122 122 122 122 124 124 124 124 126 126 126 126 128 128 130 130 130 132 132 132 134 134

TABLES AND FIGURES

xv

Table 7.23 Student time spent studying subjects by self Table 7.24 Variance in performance

134 134

8 Inequality and social welfare 8.1 Income inequality Table 8.1 Income inequality Table 8.2 Trends in real household income 8.2 Rich and poor Table 8.3 Income levels and structure Table 8.4 Income shares Table 8.5 The richest 1% 8.3 Poverty Table 8.6 Poverty Table 8.7 Persistent poverty Table 8.8 Poverty and material deprivation 8.4 Social expenditure and redistribution Table 8.9 Social expenditure Table 8.10 Net social expenditure Table 8.11 Level of unemployment benefits Table 8.12 Redistributive effect of public policies 8.5 Old age poverty and pensions Table 8.13 Old age poverty Table 8.14 Cost of old age pensions Table 8.15 Level of old age pensions 8.6 Child poverty and single parents Table 8.16 Child poverty Table 8.17 Households, employment and child poverty Table 8.18 Poverty risk of jobless single parents

136 136 138 138 138 140 140 140 142 142 142 142 144 144 144 146 146 146

9 International relations 9.1 Military spending Table 9.1 Military spending Table 9.2 Size of armed forces Table 9.3 Global arms spending and trade 9.2 Foreign aid Table 9.4 Foreign aid Table 9.5 Targeting of foreign aid Table 9.6 Commitment to development aid Table 9.7 Comparative spending on arms and aid

xvi

TABLES AND FIGURES

148 148 148 150 150 150 150

10 Environment 10.1 Biodiversity Table 10.1 Mammals Table 10.2 Birds Table 10.3 Reptiles Table 10.4 Protected areas 10.2 Global warming Table 10.5 Global greenhouse gas emissions 10.3 Greenhouse gas emissions Table 10.6 Changes in total greenhouse gas emissions Table 10.7 Greenhouse gas emissions 10.4 Energy Table 10.8 Energy usage per person Table 10.9 Means of electricity generation 10.5 Waste, recycling and pollution control Table 10.10 Spending on pollution control Table 10.11 Generation of waste Table 10.12 Glass recycling Table 10.13 Paper recycling 10.6 Ecological footprint Table 10.14 Ecological footprint

152 152 152 152 154 156 156 158 158 160 160 160 160 162

11 Science and technology 11.1 Investment in knowledge Table 11.1 Investment in knowledge Table 11.2 Research and development Table 11.3 Researchers 11.2 Business research and development Table 11.4 Business investment in R&D Table 11.5 Researchers in business Table 11.6 Sectors of business R&D Table 11.7 Big and small business R&D 11.3 Outputs – patents, publications, products Table 11.8 Patents Table 11.9 Scientific articles Table 11.10 Product innovations

164 164 164 166 166 166 166 168 168 168

12 Telecommunications and computing 12.1 Personal computers, mobile phones and internet Table 12.1 Personal computers

170

TABLES AND FIGURES

xvii

12.2

12.3

12.4

12.5

Table 12.2 Mobile telephones Table 12.3 Internet users The telecommunications market Table 12.4 Telecommunications revenue Table 12.5 Telecommunications revenue per person Table 12.6 Employment in ICT Figure 12.1 Telephone charges Mobile telephony Table 12.7 Share of mobile phones in telecommunications revenue Table 12.8 Cellular mobile phone revenue per subscriber Table 12.9 Share of pre-paids in mobile phone subscriptions Table 12.10 Competitive structure of mobile telephony The internet Table 12.11 Internet hosts Table 12.12 Secure servers Table 12.13 Business use of the internet Table 12.14 Dial-up and broadband internet Broadband – access, speed, costs Table 12.15 Broadband penetration Table 12.16 Broadband speed Table 12.17 Data caps on broadband subscribers Table 12.18 Broadband costs

170 170 172 172 172 172 174 174 174 174 176 176 176 176 178 178 178 178

13 Media 13.1 Newspapers Table 13.1 Newspaper circulation Table 13.2 Number of newspapers Table 13.3 Newspaper revenue 13.2 Advertising Table 13.4 Advertising Table 13.5 Advertising expenditure shares 13.3 Television Table 13.6 Television’s institutional basis Table 13.7 Number of channels available Table 13.8 Average television viewing hours 13.4 Public broadcasting Table 13.9 Audience share of public service television Table 13.10 Public broadcasters’ funding

xviii

TABLES AND FIGURES

180 180 180 182 182 184 184 184 186 186

13.5 New media Table 13.11 Table 13.12 13.6 Cinema Table 13.13 Table 13.14

Distribution platforms of television Digital terrestrial television transition

188 188

Cinema attendance National origin of films

190 190

14 Family 14.1 Marriage Table 14.1 Age at first marriage Table 14.2 Divorce Table 14.3 Duration of marriage at divorce 14.2 Children Table 14.4 Mother’s age at birth of first child Table 14.5 Births outside marriage Table 14.6 Births to adolescent women Table 14.7 Abortions 14.3 Families and households Table 14.8 Household size Table 14.9 Households and relationships Table 14.10 Child households and sole-parent families 14.4 Mothers and employment Table 14.11 Income of different family types Table 14.12 Women’s employment and motherhood Table 14.13 Mothers and part-time work 14.5 Child care and early education Table 14.14 Children in child care and pre-school Table 14.15 Public expenditure on child care and pre-school Table 14.16 Child care fees Table 14.17 Net costs of attending child care 14.6 Family policies and maternity leave Table 14.18 Public spending on family benefits Table 14.19 Maternity leave Table 14.20 Spending on maternity and parental leave payments

192 192 192 194 194 194 194 196 196 196 198 198 198 200 200 200 200 202 202 202

15 Lifestyles and consumption 15.1 Housing Table 15.1 Home ownership

204

TABLES AND FIGURES

xix

15.2

15.3

15.4

15.5

Table 15.2 Housing tenure Table 15.3 Changes in real house prices Table 15.4 Housing affordability Food Table 15.5 Food Table 15.6 Fat Table 15.7 Proteins Table 15.8 Fruit and vegetables Alcohol Table 15.9 Alcohol consumption Table 15.10 Types of alcoholic beverages consumed National transport patterns Table 15.11 Cars Table 15.12 Price of petrol Table 15.13 Travel by train Table 15.14 Travel by car Urban mobility and transport Table 15.15 City size and density Table 15.16 Modes of daily transport Table 15.17 Car travel in cities Table 15.18 Public transport availability

204 204 204 206 206 206 206 208 208 210 210 210 210 212 212 212 212

16 Crime and social problems 16.1 Crime rates Table 16.1 Victims of crime Table 16.2 Total official crime rate 16.2 Homicide and violent crime Table 16.3 Homicides Table 16.4 Gun ownership Table 16.5 Robbery with weapons Table 16.6 Assaults 16.3 Policing Table 16.7 Number of police Table 16.8 Reporting crime to the police Table 16.9 Satisfaction with police response Table 16.10 Perceptions of police performance 16.4 Victim support and public fears Table 16.11 Public fear of burglary Table 16.12 Public feeling of safety

xx

TABLES AND FIGURES

214 214 216 216 216 216 218 218 218 218 220 220

Table 16.13 Support for victims 16.5 Imprisonment and execution Table 16.14 Imprisonment rates Table 16.15 Capital punishment 16.6 Suicide Table 16.16 Suicide Figure 16.1 Male suicide rates Figure 16.2 Female suicide rates Figure 16.3 Suicides and age groups 16.7 Car accidents Table 16.17 Motor vehicle deaths Table 16.18 Injuries from road traffic accidents 16.8 Corruption Table 16.19 Corruption Perceptions Index Table 16.20 Bribery Payers’ Index

220 222 222 224 224 224 224 226 226 228 228

17 The search for scoreboards 17.1 Human Development Index Table 17.1 Human Development Index (HDI) Table 17.2 Globally lowest ranking countries on HDI Table 17.3 Greatest improvement in HDI Table 17.4 Worst deterioration in HDI 17.2 Gender development and empowerment Table 17.5 Gender Development Index (GDI) Table 17.6 Gender Empowerment Measure (GEM) Table 17.7 Difference in GDI and HDI ranks Table 17.8 Global lowest scores on gender empowerment 17.3 Global competitiveness and economic freedom Table 17.9 Global Competitiveness Index Table 17.10 Economic freedom 17.4 Most liveable cities Table 17.11 Most liveable city (1) Table 17.12 Most liveable city (2) 17.5 Globalisation Table 17.13 Globalisation (1) Table 17.14 Globalisation (2) Table 17.15 Globalisation (3)

230 230 230 230 232 232 232 232 234 234 236 236 238 238 238

TABLES AND FIGURES

xxi

18 The Howard impact Table 18.1 Economic growth, 1950–1973 Table 18.2 The Economist’s house-price indicators Table 18.3 Public expenditure on tertiary education Figure 18.1 Economic growth Figure 18.2 Unemployment Figure 18.3 Inflation Figure 18.4 Long-term interest rates Figure 18.5 Taxation Figure 18.6 Government spending Figure 18.7 Budget surpluses and deficits Figure 18.8 Government debt Figure 18.9 Multi-factor productivity increases Figure 18.10 Current account balance Figure 18.11 Household debt Figure 18.12 Public share of education expenditure Figure 18.13 Public share of tertiary education expenditure Figure 18.14 Investment in knowledge

xxii

TABLES AND FIGURES

241 249 251 241 241 243 243 243 245 245 245 247 247 249 251 251 251

PREFACE TO THE SECOND EDITION he aims and strategy of this second edition are essentially the same as the first. However, several changes have been made, a few due to necessity because of the unavailability of recent data, but mainly through our efforts to improve the book and its usefulness. Not only have we tried to update all chapters, but we have often extended and restructured our efforts to try to bring more enlightening information and such analysis. We have added two new chapters. The first, The search for scoreboards, concentrates on some of the ambitious attempts to produce more encompassing composite indicators. The last chapter, The Howard impact, brings together data and analysis on the comparative performance of the Howard Government. Some readers of the first edition wanted more graphs as well as tables, while others

T

said they wanted comparisons with other countries as well as the 18 advanced democracies. While the basic format and approach of the book have remained the same, we have accommodated these suggestions to a limited extent. In addition to the 329 tables in the book, there are also now 31 graphs, and while the bulk of the tables still concentrate on the 18 democracies, 19 tables now present global data. Many of the tables and sections from the first edition which are not included in this edition can be found at the website Australia Policy Online: www.apo.org.au. In addition, that website contains the detailed tabular data behind the graphs in the book, plus some other discussions of our findings. Any errata that come to light will also be noted there.

PREFACE TO THE SECOND EDITION

xxiii

ACKNOWLEDGEMENTS or this edition, we are again pleased to be working with Cambridge University Press, and thank especially Kim Armitage, Susan Hanley and Jodie Howell. Again we have drawn extensively on the resources of Sydney University’s Fisher Library. In addition, we would like to acknowledge the professionalism and assistance of several researchers in the organisations from whose data we have drawn, especially Max Ladique, Michael di Looper and Taylor Reynolds at the OECD and of Sue Thomson at ACER.

F

xxiv

ACKNOWLEDGEMENTS

Rod gratefully acknowledges the excellent research assistance of Erin Kelly. Erin’s work on this book was made possible through a collaborative ARC grant to the website Australia Policy Online, directed by the Institute of Social Research at Swinburne University of Technology. We thank the ARC and the APO team at Swinburne, especially Peter Browne. Our deepest acknowledgements are unrevised. Once again, we dedicate this book to our families with love and thanks – to Kathryn, Paul and Ruth and to Claudia, Sandy and Katie.

READING THE TABLES Rankings. When tables are not presented in alphabetical order, they are ordered according to one of the data columns in the table to facilitate comprehension. Most often this is according to the final column because this represents data for the most recent year. More occasionally, it is by the first date column. Mean. All means given in the tables are unweighted arithmetic means. That is, all 18 countries contribute equally to calculating the mean, and it takes no account of the differing sizes of countries. Because our central purpose is comparison, this is the appropriate measure. Mean D18. The term ‘Mean D18’ is used, especially in graphs, to designate the mean of the 18 selected democracies that we are comparing. Often the Australian figure is compared with the D18 mean, and then it should be remem-

bered that Australia contributed 1/18 to the D18 value. We always simply use the expression ‘D18’ even when there is data missing for one or two countries. Germany. All 18 countries have had fairly stable boundaries over the last half century or more except for Germany. West and East Germany formally re-united on 3 October 1990. At that time, West Germany’s population was 62 million and East Germany’s was 16 million. As is the custom in most international statistics, in this book, unless otherwise indicated, figures for Germany up until 1990 are for West Germany and figures after 1990 are for the whole of Germany. .. Two dots in a table indicates missing data. NA indicates that data would not be applicable for that country for that category.

READING THE TABLES

xxv

ABBREVIATIONS ABC ABS AGPS AIHW ANU ATM BBC BMI BPI CAT CIA DCI ECEC EFTPOS EIRO EU FAO FDI GATT GDI GDP GEM GNI GNP GST HDI HMSO HREOC ICT ICVS

xxvi

Australian Broadcasting Corporation Australian Bureau of Statistics Australian Government Publishing Service Australian Institute of Health and Welfare Australian National University automatic teller machine British Broadcasting Corporation Body Mass Index Bribe Payers’ Index computer assisted technology Central Intelligence Agency Christian Democratic Party early childhood education and care electronic funds transfer at point of sale European Industrial Relations Observatory European Union Food and Agriculture Organisation foreign direct investment General Agreement on Tariffs and Trade Gender Development Index Gross Domestic Product Gender Empowerment Measure Gross National Income Gross National Product goods and services tax Human Development Index Her Majesty’s Stationery Office Human Rights and Equal Opportunity Commission Information and Communications Technology International Crime Victims Survey

ABBREVIATIONS

IEA ILO IMF IT LAY LIC LIS LLCD MFP MRI NAFTA ODA OECD OPEC PAC PBS PC PISA PPP PR PYLL R&D SBS SIPRI SME TI UN UNDP UNHCR WHO WTO

International Energy Agency International Labour Organisation, Geneva International Monetary Fund information technology latest available year low-income country Luxembourg Income Study least developed countries multi-factor productivity magnetic resonance imaging North American Free Trade Agreement Official Development Assistance Organisation for Economic Co-operation and Development Organisation of Petroleum Exporting Countries pollution abatement and control Public Broadcasting Service personal computer Programme for International Student Assessment purchasing power parity proportional representation Potential Years of Life Lost research and development Special Broadcasting Service Stockholm Institute for Peace Research Incorporated small- and medium-sized enterprise Transparency International United Nations United Nations Development Programme United Nations High Commissioner for Refugees World Health Organization World Trade Organization

INTRODUCTION ustralia is the best country in the world.’ When people feel strongly about something, they often express themselves by making a comparative claim, but usually without taking the comparison seriously. Every country seems to invent myths about its own uniqueness (‘Australia is the most egalitarian country in the world’), myths typically based on an ignorance of others. Mostly such casual comparisons flatter the country they are describing. More occasionally they indulge in self-flagellation (‘Australia is the most overgoverned country in the world, with the world’s worst politicians’) or express a cultural cringe (‘We are always 10 years behind America’). This book makes comparison its central purpose. It systematically compares Australia with 17 other countries, all affluent and stable liberal democracies, on a wide range of important social, economic and political phenomena. Moreover, it seeks, whenever possible, not just to make snapshot comparisons from the present, but to chart trends. While there is value in presenting comparisons frozen at a single point of time, it is more instructive to trace common or contrasting trajectories – whether all these countries are experiencing greater unemployment, increased health spending, rising crime rates etc. There is an industry of politicians, journalists and market analysts devoted to intensively reporting short-term changes, and sometimes exaggerating their significance. There is much less public effort devoted to analysing the medium term and long term. This book aims to go beyond the myopic preoccupation with the present that marks political controversies and most journalism to examine trends over the last decades and where possible even longer. Such a procedure allows us more perspective on the extent (and sometimes the limits) of the change we have already experienced. More cautiously it gives us some, although a very imperfect, basis for considering future developments. The future is rarely a simple extrapolation from the past, but charting secular trends is one tool for

‘A

projecting future scenarios, and hence for planning and making policy decisions to give societies a greater mastery of their destiny. The 18 countries chosen all share central socio-economic characteristics. All have conquered – at least for the majority of their populations – the basic struggle for life, so that the average life expectancy in them all is at least 75 years. The bulk of their populations has access to sufficient nutrition, safe drinking water and adequate shelter. All have close to 100% basic literacy. All are among the most affluent societies in the world. All have capitalist mixed economies, with a strong public sector. All have been stable liberal democracies since at least the late 1940s, with constitutionally governed, largely non-violent political competition with different parties alternating in power while central institutions remain stable, and where the government is by some minimal criteria representative and publicly accountable. In addition a further condition of minimum size was imposed – that the countries have populations of at least three million. This criterion excluded Iceland (population 270 000) and Luxembourg (population 418 000), which otherwise would have been included. The comparative strategy chosen for this book can be labelled bounded comparison, selecting a fairly large range of countries with sufficiently similar political, economic and social characteristics to make comparison illuminating. This of course does not mean these countries are identical with Australia. (It is a common fallacy for people to say two situations are not comparable when they mean they are not identical.) Rather it means that the similarities are sufficient to make the pattern of commonalities and contrasts interesting, and to illuminate policy choices and institutional differences. Why compare? Comparison serves three major purposes. Firstly it helps us to see ourselves more clearly. As Rudyard Kipling wrote a century ago – albeit in a somewhat different spirit – ‘What do they know of England, who only England know?’ In social science terms

INTRODUCTION

1

it allows us to delineate the individual case more precisely, to make explicit what might otherwise have remained unexamined. What we imagine to be unique may be common to many societies, while what we take for granted as the natural or only way of doing things may in fact be unusual or even unique. Secondly, comparison expands our universe of possibilities. It increases our knowledge that there are alternatives – alternative policies, different institutional arrangements, contrasting cultural assumptions. Most policy discussions take place within a restricted frame of reference. Domestic contention tends to focus upon our hopeless politicians, obstructive trade unions or rapacious corporations, looking only inwards when looking outwards can suggest policy and social alternatives beyond the framework within which domestic politicians are casting the problem. Equally, while the focus of comparison tends to concentrate on differences and contrasts, commonalities are often just as important and interesting. When trends and problems are broadly shared among a number of countries the causes are unlikely to be solely home-grown. Thirdly, comparison is the social scientist’s substitute for the experiment. We cannot subject whole societies to experimental testing, so disciplined comparison is our means for testing generalisations. The study of commonalities and contrasts allows us to be more disciplined in ascribing explanations and examining relationships. By charting similarities and differences, we can be more precise in our descriptions and more discriminating in our analyses. While the potential value of comparative work is great, so unfortunately are the obstacles confronting it. One problem, common to all social science research, is particularly pronounced in comparative research – namely many of the most interesting and subtle aspects of socio-political life defy quantification or the construction of valid indicators to summarise simply their trends and differences. There is often truth in the charge that comparative measures are too crude to be meaningful. We do not claim that the tables in the following pages 2

HOW AUSTRALIA COMPARES

exhaust all there is to say about the quality of social and political life in these countries, but they offer data that can offer the parameters in which such qualitative discussions can proceed in a more informed way. In terms of data quality, the two most central problems of comparative research are reliability and equivalence. Different countries often measure the same concept in different ways (or in some countries with problematic accuracy), making apparently comparable data in fact incomparable. The problem of equivalence means that comparing some isolated measure of behaviour may have very different meanings when put in its larger social context. Although these problems are still pertinent, fortunately they have been greatly reduced over the last few decades. Care must still be taken with problems of comparability, but today’s scholar has access to many more, and more extensive and harmonised, data banks than used to be the case. International bodies such as the United Nations and its member agencies, the World Bank, the International Monetary Fund, the European Union, as well as commercial organisations and academics, have laboured to produce valid and reliable comparative data. In particular the many sections of the Organisation for Economic Cooperation and Development (OECD) have produced a range of high-quality data on the relevant countries. Their work is the central resource for all interested in the comparative study of these advanced democracies, and we would like to think this book is testament to the importance and value of their work. Although as will be evident we have been the beneficiaries of the competent work done by the professionals in these organisations, the frustrations have still been considerable. Discrepancies in data between different organisations often seemed inexplicable. One always had to be alert to changes or inconsistencies in the basis of measurement. Missing data for individual countries, often for no apparent reason, was another frequent irritant. As far as possible, we have only included tables, where

data was available for all 18 countries, to keep the basis for comparison as constant as possible. However, we have often had to depart from this standard when the interest of the data outweighed its incompleteness. This book differs from the two most common types of books calling themselves comparative, firstly in focussing consistently upon the same set of countries throughout and making comparison the key within each part. In academic studies, edited books calling themselves ‘comparative’ are more accurately described as ‘juxtapositions’, as different authors tackle different countries in different ways, and the genuinely comparative element is minimal. Or else there may be comparative work, but the comparisons are based upon convenience, without a consistent or theoretically bounded set of countries being compared. While most academic studies focus intensively on one narrow area, our aim has been to produce an encyclopaedic source book. We have sought to provide a reference source offering comparative data on as many aspects of social life as possible, from taxation to traffic accidents, homicide rates to health expenditure, from interest rates to internet usage. We have tracked economic indicators, but also demographic and social ones, and where possible different institutional and policy settings. The second major source of comparative data is found in compendia of statistical information. Most are done by international agencies (sometimes constrained by diplomatic considerations to present their data in a neutral and non-controversial way), or by individuals whose primary aim is to put on record comprehensive data. These compilations often provide valuable data. However, they are commonly not reader-friendly. Nor do they make any

effort to explain for the non-specialist the value and limits of the measures they are reporting. In contrast, in this book, we have very deliberately exercised an editorial hand in the presentation of data. For example, we have been selective not comprehensive about the years for which data is presented (trying to keep tables clear, and making judgements about when added detail would add more clutter than extra meaning). Similarly rather than invariably presenting tables with countries in alphabetical order, we have often listed them in hierarchical order according to the phenomenon being studied, so that the main ordering and differences between countries are more quickly apparent. (In such ‘league tables’ most people focus on rankings and differences, but, as indicated earlier, what is often at least as important is how they have moved in common.) Most importantly this is not just a book of tables, but rather each table is accompanied by a commentary about the meaning of the data, including sometimes a discussion of its limits. In this way we have sought to provide the reader not only with reliable and pertinent data, but with some discussion of its interpretation and significance. We try to probe the meaning of different measures, look at both common trends and countries which have performed quite differently from the norm, and sometimes seek to see whether there are any patterns in the differential performance of countries. However, in these discussions, as the title How Australia Compares indicates, we have always tried to put Australian experience into comparative perspective, invariably returning to the implications of these facts for considering Australia’s performance, policies and prospects.

INTRODUCTION

3

Chapter 1 PEOPLE

Table 1.1 World population milestones World population

Year reached

1 billion 2 billion 3 billion 4 billion 5 billion 6 billion 7 billion 8 billion 9 billion

4

Table 1.2 Global population sizes Population 2008

1804 1927 1960 1974 1987 1999 2013 (projected) 2028 (projected) 2054 (projected)


Global rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 37 38 43 47 50 54 59 76 88 92 95 106 109 112 115 124 125

Country

Population (millions)

China India United States Indonesia Brazil Pakistan Bangladesh Russia Nigeria Japan Mexico Philippines Vietnam Germany Egypt Ethiopia Turkey Congo Iran Thailand France United Kingdom Italy South Korea Burma Ukraine Colombia South Africa Argentina Spain Canada Afghanistan Iraq North Korea Taiwan Australia Netherlands Belgium Sweden Austria Switzerland Papua New Guinea Denmark Finland Norway New Zealand Ireland

1330.0 1148.0 303.8 237.5 191.9 167.7 153.5 140.7 138.2 127.3 110.0 92.7 86.1 82.4 81.7 78.3 71.9 66.5 65.9 65.9 64.1 60.9 58.1 49.2 47.8 46.0 45.0 43.8 40.7 40.5 33.2 32.7 28.2 23.5 22.2 21.4 16.6 10.4 9.0 8.2 7.6 5.9 5.5 5.2 4.6 4.2 4.2

1.1 Global population he pace of population growth is dramatically apparent in Table 1.1. It took tens of thousands of years for the earth’s population to reach one billion, while the next billion then took 123 years to add, but the third billion took only 33 years. Between 1987 and 1999, when the earth’s population reached six billion, it took only 12 years to add a billion people. According to Nobel Prize-winning economist Robert Fogel, the increase in the world’s population between 1900 and 1990 was four times as great as the increase during the whole previous history of mankind. This population explosion is testimony to mankind’s success. It was the mastery of agriculture, the ability to live in cities, and the ability to reduce disease and other threats to longevity that made the increase possible. However, the success threatens to bring its own problems. In particular, six billion people – especially experiencing a much higher standard of living – have a far greater impact on the earth’s environment. If current trends in population growth are projected forward, they could threaten the planetary carrying capacity. However, projecting forward is problematic. The United Nations Population Division, from whose data the table is drawn, sees the current rate of growth continuing in the near future, but thinks it will slow considerably by the middle of the 21st century, and from then on. They forecast that the global population will grow from seven to eight billion in 15 years, but then take 26 years to grow to nine billion. But then they predict it will take fully 129 years to reach 10 billion, in the year 2183. Obviously, the further in the future they are projecting, the more one should view the figures with caution. As the earth’s population has been growing, so have the political structures into which they are divided. The International Database of the US Census Bureau lists 226 entities. The word ‘entities’ is used because the list includes a handful of entries which are still colonies or

T

which have a distinctive history, such as the Special Autonomous Region of Hong Kong, or whose status is contested, such as Taiwan. Countries come in all sizes. Of the 226, 11 have populations greater than 100 million, while fully 70 have populations of less than one million. Table 1.2 therefore has to be selective. It includes the 30 most populous countries, our 18 selected democracies, and a few others which may be of particular interest. Australia now ranks 54th globally, in the top quarter in terms of population. Since 1980, it has been overtaken by Malaysia, Iraq, Uganda, Mozambique and Ghana. It would take a peculiarly wrong-headed patriotism to be concerned by this. The most obvious message from the table is how little population size has to do with national destiny. The list shows no correlation with national prosperity, except perhaps that many of the smallest countries are more economically vulnerable. Size of population does correlate somewhat more with military strength and international power, but this is also very limited. The tendency has been for population growth rates to decline as prosperity increases. The two most populous countries, China and India, especially the former, have slowed their rate of growth considerably, as a result of both official policies and rising living standards. The other factor affecting the rankings is how nation states break up or combine. Nation states are not eternal or natural entities. They typically embody a sense of common destiny, ‘imagined communities’, in the phrase of the scholar Benedict Anderson. Karl Deutsch expressed a similar idea more sardonically – ‘a group of people united by a common error about their ancestry and a common dislike of their neighbours’. Most spectacularly, in the last quarter century, the Soviet Union, then the third most populous country in the world, broke into 15 different countries, while what was Yugoslavia more violently dissolved into seven different countries.

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5

Table 1.3 20th century populations

Table 1.4 Area and population density

Millions Country

1900

1950

2000

Country

United States Japan Germany United Kingdom France Italy Canada Australia Netherlands Belgium Sweden Austria Switzerland Denmark Finland Norway Ireland New Zealand

76.0 43.8 56.1 36.7 38.9 32.4 5.4 3.8 5.2 6.7 5.1 5.8 3.3 2.4 2.7 2.2 3.1 0.8

152.3 83.8 68.4 50.1 41.8 47.1 14.0 8.3 10.1 8.6 7.0 6.9 4.7 4.3 4.0 3.3 3.0 1.9

282.6 126.6 82.8 59.5 59.3 57.6 31.3 19.2 15.9 10.2 8.9 8.1 7.3 5.3 5.2 4.5 3.8 3.8

Australia Canada Norway New Zealand Finland Sweden United States Ireland Austria France Denmark Switzerland Italy Germany United Kingdom Japan Belgium Netherlands

Population per square kilometre (2005)

Area (thousands square kilometres)

3 3 14 15 16 20 32 59 98 111 126 180 193 231 245 338 342 400

7687 9976 324 269 338 450 9372 70 84 549 43 41 301 357 245 378 31 41

Table 1.5 Population growth rates Average annual growth rate (%) (2000–2010 is projected) Country Ireland Australia New Zealand Canada United States Switzerland France Norway Austria Italy Sweden United Kingdom Belgium Denmark Finland Netherlands Germany Japan Mean

6

1950–1960

1960–1970

1970–1980

1980–1990

1990–2000

2000–2010

−0.5 2.3 2.2 2.7 1.7 1.3 0.9 0.9 0.2 0.6 0.7 0.4 0.6 0.7 1.0 1.3 0.6 1.2

0.4 2.0 1.7 1.8 1.3 1.5 1.1 0.8 0.6 0.7 0.7 0.6 0.5 0.7 0.4 1.3 0.7 1.1

1.4 1.6 1.2 1.2 1.1 0.2 0.6 0.5 0.1 0.5 0.3 0.1 0.2 0.4 0.4 0.8 0.0 1.1

0.3 1.5 0.7 1.2 0.9 0.6 0.5 0.4 0.2 0.1 0.3 0.2 0.1 0.0 0.4 0.6 0.2 0.6

0.8 1.2 1.3 1.0 1.2 0.7 0.4 0.6 0.4 0.0 0.4 0.3 0.3 0.4 0.4 0.6 0.3 0.3

1.4 1.2 1.0 0.9 0.9 0.7 0.6 0.6 0.5 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.1 0.0

1.0

1.0

0.6

0.5

0.6

0.6


1.2 Population growth opulation was one of the first concerns of the Australian Federation. A Royal Commission was established in the first decade of the 20th century to see ‘whether we shall be able to people the vast areas of the continent which are capable of supporting large populations’. World War II brought a new intensity of concern. In 1948, Australia’s first Minister for Immigration, Arthur Calwell, asserted that ‘Additional population is Australia’s greatest need. For security in wartime, for full development and prosperity in peacetime, our vital need is more Australians.’ These tables both confirm and qualify Australians’ traditional fears of being ‘underpopulated’. Table 1.3 shows that in 1900 Australia’s population was only 3.8 million, and Table 1.4 shows that even now its population density is the most sparse among the selected countries, with only three people per square kilometre. At the other extreme, the Netherlands has 400, and Belgium and Japan more than 300, persons per square kilometre. However, the differences in population density suggest that to some extent at least geography is destiny. The seven countries with the lowest population density all have substantial areas inhospitable to human settlement, with mountains, desert or arctic wastes. On the other hand, in terms of population size, Australia is certainly not a minnow. It ranks in the top half of these 18 countries, and, as we saw from Table 1.2, it ranks within the top quarter globally. Historically, the most important reason for the preoccupation is the contrast with the Asian giants. As Table 1.2 also showed, eight of the world’s most populous 15 nations are in Asia. The starkest aspect about proposals to increase Australia’s population as a solution to either its security or economic problems is the lack of realism about scale. No conceivable amount of population growth is going to change the crucial equations. Neither is it likely Australia will ever rank anywhere but near the bottom of league tables on population

P

density. Merely to catch up with Norway’s 14 people per square kilometre Australia’s population would have to increase to an improbable 107 million. Nor is any increase in population size possible such that it would become easier to compete with trading blocs such as the European Union, which has allowed member nations to exploit economies of scale far beyond their individual size. Nevertheless different rates of population growth do make a difference, especially when sustained over a long period of time. During the 20th century, and especially in its second half, the four English-speaking New World democracies had substantially higher growth rates than the West European countries and Japan. Australia’s population by the year 2000 was five times what it had been in 1900. (Canada, the fastest growing of the countries, increased 5.8 times.) In contrast, nine of the European countries had populations that were less than double what they had been a century earlier. In 1950, Australia’s population was just less than Belgium’s, by 0.3 million. Fifty years later, Australia had nine million more people than Belgium. Table 1.5 shows average annual growth rates for the 60 years from 1950, based on the US Census Bureau’s International Database; the last column based on their projections for each country’s 2010 population. It shows the rate of growth has slowed considerably. In the 1950s and 1960s, it was almost double what it has been in the four subsequent decades. Several of the countries in the bottom half of the table have had decades where their growth rate has been close to zero. Australia – and the other New World English-speaking democracies – has been close to the highest rate of growth in all periods. The fastest growing country in the first decade of the 21st century, Ireland, is the country with the most variable rate. It exhibited negative population growth in the 1950s, but its recent prosperity has attracted a surge of immigration.

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7

Table 1.6 Life expectancy 1900–2000 Life expectancy at birth by years Country

1900

1950

2000

Japan Australia Sweden Switzerland Canada Italy France Norway Netherlands Belgium New Zealand Austria United Kingdom Finland Germany United States Ireland Denmark

44.5 56.5 55.8 50.7 .. 44.5 47.0 56.3 56.1 47.1 59.4 40.1 50.5 46.7 46.6 49.3 49.5 54.6

63.9 69.6 71.8 69.2 69.1 66.0 66.5 72.7 72.1 67.5 69.6 65.7 69.2 66.3 67.5 69.0 66.9 71.0

80.7 79.8 79.6 79.6 79.4 79.0 78.8 78.7 78.3 77.8 77.8 77.7 77.7 77.4 77.4 77.1 76.8 76.5

Mean

50.3

68.5

78.3

Figure 1.1 Male life expectancy (years) 88 84 80 76 72 68 64 1980

Australia

2004

D18 Mean

Figure 1.2 Female life expectancy (years) 88 84 80 76 72 68 64 1980 Australia

8


2004 D18 Mean

1.3 Life expectancy oliticians and social commentators are increasingly talking of the problems caused by an ageing society. Although there are substantial policy issues posed by this demographic trend, it should be remembered that its most basic cause is good news – people are living longer. An ageing society was a problem cavemen never had to contend with. The figures in Table 1.6 tell a great success story. During the course of the 20th century, average life expectancy in the advanced democracies rose by more than half – from around 50 to nearly 80 years. Indeed, according to Nobel Prize-winning economist Robert Fogel, the increase in life expectancies during the 20th century was more than double what it had been during the previous 200 000 years. Part of the explanation has been the improving life chances of the poorest groups. Fogel points out that for the cohort born in Britain about 1875, the upper classes had a life expectancy around 17 years greater than the working classes. Today the gap has narrowed to around four years. This reminds us that the table’s figures offer the mean life expectancy for each country, and can conceal substantial differences between sub-groups. Most dramatically in Australia’s case, in 2001, the life expectancy for Aboriginal women was 65 years and for Aboriginal men 59 years, in both cases a difference of more than 15 years from the white population. Overall, as the table shows, Australia ranked second in the year 2000 – with life expectancy at birth touching 80 years – the same rank it had had a century earlier. The rise in life expectancy was most dramatic in Japan, which went from the lowest in 1900 to the highest in 2000. It was particularly with its post-World War II prosperity and democracy that Japanese increases in life expectancy out-paced the other countries. However, the most notable aspect of the data is the commonality between the countries. Life expectancy in all of them increased

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substantially (somewhat less so in some of the already long-living Northwest European countries). In 2000, life expectancy in all 18 countries was closely grouped, all falling within a range of just over four years. Moreover, as Figures 1.1 and 1.2 show, over the last quarter century all have continued trending upward. The mean for females rose by 4.5 years, and for males by almost six years. Female life expectancy is on average around six years greater than males’. The accompanying web tables show that in all these countries, women live longer than men, as they have for all the periods where there is data. Among both males and females, Australia ranks near the top, but again the outstanding feature of the tables is the countries’ close grouping and the shared trends towards greater life expectancy among both sexes and across all countries. The OECD notes that these gains have been made possible by rising standards of living, improved working conditions, public health interventions and progress in medical care. It explains that improvements in life expectancy at birth actually reflect a decline in mortality rates at all ages, ranging from a sharp reduction in infant mortality to higher survival rates at older ages. Fogel emphasises the virtuous circle between increased nutrition and stronger, more robust bodies, and shows how increasing average height has correlated with increasing life expectancy. The Australian Bureau of Statistics observed that in Australia longer life expectancy in the first half of the 20th century was because of a decline in deaths from infectious diseases, due to cleaner water and better sewerage systems, as well as initiatives like mass immunisation. Rises in life expectancy slowed in the decades after World War II largely because of increases in cardiovascular disease. While earlier it was the increasing number surviving into old age that raised the mean, more recently the major source of increase is that older people are living longer.

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Table 1.7 Fertility rates Average number of children borne by a woman during her lifetime at each year Country

1900

1950

1970

2000

2005

United States New Zealand France Ireland Norway Australia Denmark Finland United Kingdom Sweden Netherlands Belgium Canada Switzerland Austria Germany Italy Japan

3.8 .. 2.8 .. 4.1 3.4 4.0 4.8 3.4 3.9 4.5 4.0 4.8 3.3 4.9 4.8 4.4 5.2

3.4 3.5 2.7 3.3 2.6 3.2 2.6 3.0 2.2 2.2 3.0 2.3 3.7 2.3 2.1 2.2 2.3 3.6

2.5 3.3 2.5 3.9 2.5 2.9 2.0 1.8 2.4 1.9 2.6 2.3 2.3 2.1 2.3 2.0 2.4 2.1

2.1 2.0 1.9 1.9 1.9 1.8 1.8 1.7 1.7 1.5 1.7 1.7 1.5 1.5 1.3 1.4 1.2 1.4

2.1 2.0 1.9 1.9 1.8 1.8 1.8 1.8 1.8 1.8 1.7 1.7 1.5 1.4 1.4 1.3 1.3 1.3

Mean

4.1

2.8

2.4

1.7

1.7

Table 1.9 Distribution of age groups 2005 Percentage of population in each age group, 2005

Table 1.8 Distribution of age groups 1960 Percentage of population in each age group, 1960 Under 15

15–64

65 and over

Under 15

15–64

65 and over

Japan Finland Canada New Zealand United States Australia Netherlands Italy Ireland Norway Denmark Switzerland Germany France Belgium United Kingdom Austria Sweden

30 30 34 33 31 30 30 23 31 26 25 23 21 26 24 23 22 22

64 62 59 58 60 61 61 68 59 63 64 66 68 62 65 65 66 66

6 7 8 9 9 9 9 9 11 11 11 11 11 12 12 12 12 12

Ireland New Zealand United States Australia Canada Netherlands Denmark Norway Austria Finland France Switzerland United Kingdom Belgium Sweden Germany Italy Japan

21 22 21 20 18 19 19 20 16 17 18 16 18 17 17 14 14 14

68 66 67 67 69 68 66 66 68 67 65 68 66 66 65 67 67 66

11 12 12 13 13 14 15 15 16 16 16 16 16 17 17 19 19 20

Mean

27

63

10

Mean

18

67

16

10


Country

Country

1.4 Birth rates and the ageing society part from increased life expectancy, the other cause of the ageing society is that people are having fewer children. Despite the glacial pace of such demographic revolutions, their long-term impact is a dramatic change in the age composition of society. Table 1.7 shows the reduction in the number of children each woman is having – from a mean across the selected countries of 4.1 in 1900 to 1.7 in 2005. There was a fall of around one-third between 1900 and 1950 in the overall mean, and another of around 40% in the second half of the 20th century. The decline was steeper in the last decades of the century, although it plateaued in the first five years of the 21st century. In all the countries, except the United States, the fertility rate is now below the natural replacement level of 2.1 children per woman. In other words, if this rate continues, and without immigration, all these countries will eventually experience a declining population. (It should be remembered that apparently small movements in the fertility rate can have large demographic consequences. According to the ABS, a change of 0.1 in the rate in either direction, if consistently sustained until 2050, would raise or lower Australia’s population by around one million people.) While the secular trend towards a declining fertility rate is clear and indisputable, it has not followed a smooth, linear progression. The discussion of the ageing society has become so prominent in recent years because the demographic hump of baby boomers, born in the decade and a half following World War II, is now reaching retirement age. In contrast, birth rates during the economic hardship of the 1930s depression and especially during the upheavals and suffering of World War II had been reduced. For example, demographer Jean Chesnais’s detailed figures show that Australia’s birth rate bottomed in 1934 at 16.4 per 1000 population, in the depths of the depres-

A

sion. It did not reach such a low again until the mid-1970s, but then continued to decline for around three decades. This is what makes the current dramatic decline in fertility historically unique. Normally falls in fertility have been associated with poverty and uncertainty, but this prolonged fall is happening amid unprecedented affluence. Clearly, however, all sorts of other factors – including the changed aspirations of women, the financial pressures of contemporary society, and the availability of reliable contraception – are also pertinent. The inevitable result of increased longevity and reduced fertility is a change in the generational balance of society. Tables 1.8 and 1.9 show the proportion of age groups in the selected societies in 1960 and 2005. As can be seen the proportion of young people aged under 15 has dropped by a third, from 27 to 18% overall, while the proportion of older people, aged 65 and over, has risen by more than half, from 10 to 16%. The trend is in the same direction in all 18 countries, although to varying degrees. Australia, like the other New World democracies and Ireland, remains a relatively young country in its age structure. On the whole, having children has remained somewhat more popular in these countries. Japan now has one in five people aged over 65, while Italy and Germany are just behind. These countries combine high rates of longevity with low fertility rates. The ageing society brings changes and challenges, but there is considerable fuzziness in the framing of the issues. One concern is the increased ratio of dependent to economically productive members of society, but the proportion participating in the labour force is not simply a matter of demography, but also one of social institutions and attitudes. The labour force participation rate (see chapter 4) is now at an historic peak because of the greatly increased proportion of women working.

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Table 1.10 Scale of immigration Percentage of population, 2005 % foreign Total Foreign- Foreign- Nativeborn who foreign born born born have become born nationals foreigners foreigners citizens

Country Australia Switzerland New Zealand Canada Austria United Kingdom Germany Sweden Belgium Ireland Netherlands France United States Norway Denmark Italy Finland Japan

23.0 22.4 19.5 19.3 12.5 12.3 12.1 12.0 10.7 10.4 10.1 10.0 8.3 7.3 6.8 3.9 2.5 1.2

15.7 6.5 .. 14.0 5.1 5.7 .. 7.5 4.3 4.7 6.6 5.3 .. 3.5 2.7 1.9 1.0 ..

7.2 15.8 .. 5.3 7.4 6.6 .. 4.5 6.3 5.7 3.5 4.7 .. 3.8 4.0 2.1 1.5 1.2

0.2 4.8 .. .. 1.4 .. .. 0.8 1.9 0.2 0.6 0.9 .. 0.5 0.8 0.3 0.2 ..

68 29 .. 73 41 46 .. 63 41 45 65 53 .. 48 40 48 42 ..

Mean

11.4

6.0

5.3

1.1

50

Table 1.11 Net migration rate Net migration intake per 1000 population, 2000–2005 Country

Net intake

Ireland Italy Canada Australia Switzerland New Zealand Austria United States Sweden Norway United Kingdom Germany Netherlands France Denmark Finland

9.5 7.1 6.8 5.8 5.7 5.3 4.6 4.0 3.2 2.9 2.5 2.2 1.9 1.6 1.4 1.2

Mean

4.1

No data on Belgium or Japan.

Table 1.12 Components of population growth Numbers added per 1000 population, 2004

Table 1.13 Categories of immigration intake Percentage of immigrants in each category of entry, 2005

Country

Total

Natural increase

Net migration

Country

Ireland Australia New Zealand Italy United States Canada Switzerland Austria Norway France Netherlands Sweden Finland Denmark Japan Germany

19.91 11.32 11.08 9.87 9.55 9.45 7.10 6.85 6.10 5.98 4.67 3.89 3.25 2.41 1.38 −0.35

8.36 6.08 7.39 0.28 5.88 3.25 1.69 0.61 3.27 4.25 3.50 1.11 2.10 1.48 0.85 −1.36

11.55 5.24 3.69 9.59 3.67 6.20 5.41 6.24 2.83 1.73 1.17 2.78 1.15 0.93 0.53 1.01

7.03

3.05

3.98

Mean

No data on Belgium or United Kingdom.

12


Work

Family

Humanitarian

Other

Netherlands United Kingdom Norway Canada Sweden United States Austria Belgium Australia France New Zealand Denmark Germany Switzerland Italy Japan

25 45 29 23 26 10 30 39 33 13 29 42 33 42 37 25

45 32 54 60 57 70 58 53 57 62 62 44 45 47 58 33

29 19 17 16 15 13 10 9 9 8 8 6 5 4 3 0

.. 5 0 0 2 7 1 .. 1 17 .. 7 18 7 2 41

Mean

30

52

11

8

No data on Finland or Ireland.

1.5 Immigration flows ccording to the United Nations, in the year 2000 there were around 175 million international migrants in the world; other estimates now put it at around 200 million, or just under 3% of the world’s population. By far the greatest recipient of this huge movement of people has been the United States. Again according to UN figures, in 2000 it had 35 million people of migrant stock which was almost 20% of the world total. In 1970, it had 10 million migrants, or 12% of the world total. So America’s traditional reputation as a melting pot not only has contemporary resonance, but its relative attractiveness as a destination has increased still further. Nevertheless on a proportional basis, Australia’s intake of migrants has been even greater. According to the ABS, since 1945 around 6.5 million people arrived in Australia as new settlers. As Table 1.10 shows, the result is that in 2005 almost one in four Australians was foreign born. Moreover as Table 1.11 shows, Australia’s high rate of migration is continuing. Interestingly, in the first years of the 21st century, the list is headed by Ireland and Italy, two countries which have traditionally had very low immigration intakes and sometimes had net emigration. All countries have people emigrating as well as immigrating. While Australia had high net immigration, it should also be remembered that by some estimates there are now one million Australians residing long-term in other countries. As the natural rate of population growth has declined, migration has become a more important source of population increase. In Table 1.12, the countries with the highest annual population increase – Ireland, Australia and New Zealand – combined a relatively high natural rate of increase as well as relatively high net immigration. In contrast, Germany had a net population loss in 2004. Japan combined a very low birth rate with a long-standing antipathy to immigration. Some European countries, particularly Austria and Italy, owed their population growth almost entirely to migration.

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Apart from showing very different rates of the foreign born, Table 1.10 shows other important differences between the countries in their attitudes to immigration. Comparing the top two countries, Australia and Switzerland, shows that while nearly seven in 10 of the foreign born in Australia have become citizens, only three in 10 of those in Switzerland have, the majority of their foreign-born residents remain foreign. One in 20 of Switzerland’s population was actually born in their country, but with foreign parents, and so have not gained Swiss citizenship, a figure that is also relatively high for Belgium and would be for Germany and Japan if data were available. For Australia, Canada, New Zealand and the United States, immigration has been part of their nation-building strategies, and their high rates of granting citizenship reflects this. Most of these countries have more people wanting to enter than they are prepared to admit, and they have developed categories and quotas of intake. The figures in Table 1.13 show that the highest proportion of immigrants to the selected countries is based upon family links. Unfortunately, systematic comparative data is not available but this figure includes both families accompanying those immigrating for work reasons and those reuniting with family members already resident in the country. In Australia’s case, more than half the family category were accompanying immigrating workers, but in the United States they were less than one in five. Putting the two together makes it clear that Australia places primary emphasis on what is officially labelled the ‘skill stream’, which grew proportionately under the Howard Government. The residual other category in the last column largely comprises nationals born overseas returning to Japan and Germany, while in France one large group consists of people from other countries choosing to reside there in retirement. The Netherlands has the highest proportion based upon humanitarian reasons, where Australia ranks just below the mean.

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Table 1.14 Unemployment rates among native and foreign born Unemployment rates (% labour force in each group) 2003–2004

Country Japan Netherlands Sweden United States Norway United Kingdom Australia Canada Denmark New Zealand Switzerland Ireland Austria Germany Italy France Belgium Finland Mean

Table 1.15 Over-qualification rates of native and foreign born populations Proportion in each group in occupations for which they are over-qualified 2003–2004

Male native born

Female native born

Male foreign born

Female foreign born

5.1 2.0 3.1 6.3 3.5 5.6 7.7 7.8 3.2 6.6 2.2 9.2 5.4 7.4 9.4 10.0 7.1 12.0

4.1 3.5 2.7 4.5 2.7 5.5 6.1 7.0 3.9 7.6 3.1 7.6 5.8 8.0 14.6 14.1 12.4 12.2

5.7 6.6 8.6 8.9 9.6 6.0 8.5 6.9 8.2 8.6 5.5 11.8 11.1 17.7 9.3 17.7 16.4 23.3

5.8 6.9 6.9 7.5 7.6 7.9 8.0 8.2 8.3 9.5 10.2 10.7 11.3 16.2 18.4 22.0 26.4 30.6

6.3

7.0

6.6

10.6

Australia Ireland Canada New Zealand United Kingdom France Austria United States Norway Netherlands Sweden Italy Germany Denmark Switzerland Belgium

514 520 532 526 499 495 499 503 491 515 514 473 510 500 515 515

521 .. 532 519 492 459 420 481 .. 454 486 .. 427 436 467 434

514 506 512 507 455 449 451 453 427 449 446 404 440 422 430 413

7 .. 0 −7 −7 −36 −79 −22 .. −61 −29 .. −83 −64 −48 −81

0 −14 −19 −19 −44 −45 −48 −50 −63 −65 −68 −69 −70 −79 −85 −101

Mean

507

471

455

−39

−52

14


Ratio

Total

United Kingdom Switzerland Finland Australia France United States Belgium Ireland Denmark Germany Austria Canada Norway Sweden Italy

15.3 10.0 14.3 19.0 11.2 13.4 15.6 15.7 10.4 11.4 10.3 5.9 8.4 6.5 6.4

17.8 12.5 19.2 24.6 15.5 18.1 21.6 23.8 18.6 20.3 21.1 13.2 20.3 16.1 23.5

1.2 1.3 1.3 1.3 1.4 1.4 1.4 1.5 1.8 1.8 2.0 2.2 2.4 2.5 3.6

15.5 10.5 14.4 20.4 11.6 14.0 16.2 16.6 10.9 12.3 11.5 7.2 9.2 7.6 7.0

Mean

11.6

19.1

1.8

12.3

Table 1.17 Educational attainment of native born and immigrants Proportions of each group in each category

Difference 1st difference native and native and Native 2nd 1st 2nd 1st born generation generation generation generation

No data on Finland or Japan. US figure is from 2003 PISA data.

Foreign born

No data on Japan, Netherlands or New Zealand.

Table 1.16 Native born and immigrant students’ reading literacy Mean scores for each group in reading literacy PISA 2006

Country

Native born

Country

Native upper secondary

Foreign upper secondary

Native tertiary

Foreign tertiary

Australia Ireland Canada United Kingdom New Zealand Norway Japan United States Sweden Switzerland Belgium Denmark Finland France Netherlands Germany Italy Austria

46 48 32 51 30 21 25 22 25 26 47 41 40 46 41 24 64 33

38 30 30 41 19 18 26 40 30 42 54 49 53 55 53 44 54 49

39 23 31 20 27 23 27 27 23 18 23 19 23 17 19 19 8 11

43 41 38 35 31 31 30 26 24 24 22 19 19 18 18 15 12 11

Mean

37

40

22

25

Country

1.6 Settlement of immigrants hile immigration has increased greatly in a more globalised world, immigrants are often stepping into an uncertain future. There are variations in how well they settle in their countries of destination and how welcoming those countries are. Often migrants who leave their country of birth in search of a better future can become a relatively deprived group in their new societies. Table 1.14 shows the relative unemployment rates of native-born and immigrant men and women. The countries vary substantially, but overall female immigrants are the group with highest unemployment, markedly more than other groups in Finland, Belgium and France. Among males, immigrants have considerably higher rates of unemployment in Germany and Finland, while in Italy and France females have considerably higher rates of unemployment than males among both native and foreign born. Nevertheless in many countries, including Australia, the differences between the groups was relatively small. Apart from the policy framework relating specifically to immigration, conditions of close to full employment make it easier for newcomers to adapt. After the ability of immigrants to get work at all, the next issue is whether they can get jobs for which they are qualified. The last column of Table 1.15 reveals that among all groups Australians are the most likely to be over-qualified for the jobs they have, with Italians the least so. However, in all countries the foreign born are more likely to be over-qualified for their jobs. In five countries, they are twice as likely to be so. Immigrants are often thinking not only of improving their own lives but especially those of their children. So the relative educational performance of immigrant children is both a key to their parents’ hopes and perhaps an indicator of long-term adaptation to their new home. Table 1.16 reports the performance of the native born, of first generation children who are immigrants, and of second generation immigrants i.e. born in the country to immigrant parents. The results come from the

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Programme for International Student Assessment carried out in 2006. (See more information in chapter 7.) They report each country’s mean scores on reading literacy, scaled so that the average for the OECD is 500. Reading is a domain where immigrants are more likely to lag if their native language is not the same as that of their new country. These results show that Australia has virtually no difference between native-born and immigrant children. This is in direct contrast to most other countries, and nine of the countries have a difference of 50 points or more. Even more pertinent is that in the countries at the bottom of the table – Belgium, Switzerland, Denmark and Germany – the difference is very substantial for the second generation as well as first generation immigrants. One part of the explanation for Australia’s relatively good performance here would lie with the educational system. But another part may lie with the composition of the immigrant population. As noted in Table 1.13 on the previous page, Australia’s immigration intake is relatively skewed towards work-oriented settlers, although not more so than countries such as Belgium and Switzerland, which rank towards the bottom of Table 1.16. One might expect that countries with a higher emphasis on humanitarian intake are also assuming a more difficult educational task, but the Netherlands, Britain and Canada all do relatively well. Further perspective is added by Table 1.17, which shows, contrary to the old stereotype of immigrants as an uneducated underclass, that on average immigrants have slightly higher educational qualifications than the population of the societies they are moving to. Australia ranks first in the proportion of immigrants with tertiary qualifications, and like most others has a fairly close match between the qualifications of the native born and immigrants. However, a few – most notably Ireland and the United Kingdom – have a substantial ‘brain gain’, attracting more immigrants with tertiary qualifications than they have produced domestically.

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Table 1.18 World totals of refugees Total persons Internally of concern Asylum displaced Year (millions) Refugees % seekers % persons % 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

20.0 20.1 20.8 22.1 20.0 20.9 17.0 19.5 21.0 32.9

60 57 56 55 61 51 56 49 41 30

5 5 5 5 5 5 6 4 4 2

23 25 19 27 25 22 25 28 32 39

Table 1.19 Countries receiving refugees Top 15 countries of asylum according to number of refugees 2007 (thousands) Country Pakistan Iran United States Syria Germany Jordan Tanzania United Kingdom China Chad Kenya Uganda Saudi Arabia Congo Sudan

Refugees 1044 968 843 702 605 500 485 302 301 286 273 272 241 208 196

Table 1.20 National origins of refugees Top 16 countries for refugees leaving, mid-2007 (thousands)

Table 1.21 Internally displaced persons Persons, protected/assisted by UNHCR, mid-2007, top 18 countries (thousands)

Country

Country

IDPs

Colombia Iraq Uganda Sudan Congo Ivory Coast Azerbaijan Sri Lanka Somalia Georgia Serbia Lebanon Russian Federation East Timor Central African Republic Bosnia & Herzegovina Afghanistan Chad

3000 1834 1586 1325 1075 709 687 469 400 246 228 200 159 155 147 135 129 113

Refugees

Afghanistan Iraq Sudan Somalia Congo Burundi Vietnam Palestine Turkey Angola Myanmar Bosnia and Herzegovina Eritrea Serbia Liberia Russia

16


2107 1450 686 464 401 397 374 334 227 207 202 200 194 174 161 159

1.7 Refugees – a global perspective n 1951, the United Nations adopted a Convention relating to the Status of Refugees, which has been further refined since. It was embraced by many countries, including Australia, in the aftermath of the Holocaust suffered by the Jews under Nazi Germany, and with hundreds of thousands fleeing communist rule in Eastern Europe. Since then the nature of refugees has changed – from being principally a European phenomenon to one occurring mainly in the Third World. Moreover the number of refugees is on a scale that no-one envisaged in 1951. Table 1.18 gives the total numbers of concern to the United Nations High Commissioner for Refugees (UNHCR) for the 10 most recent years of published data. In all but two years, there were more than 20 million people of concern worldwide, and in 2006 the total increased to almost 33 million. The other columns in the table give the proportion in each of the UNHCR’s categories of people of concern. In most years, the largest number is refugees, who have fled from their own country to a neighbouring one. In 2006, for the first time, a larger category was internally displaced persons, people who have had to flee their homes but have remained elsewhere in their own country, and whom UNHCR are now trying to protect and care for. The proportions do not add up to 100, because a final, residual category – other persons of concern – is not shown here. It consists principally of people living close to combat zones or other dangerous areas, or former refugees who have returned home, but about whose fate there are still grounds for fear. The great majority of refugees flee to a neighbouring country, often in groups, and then live in camps there. Tables 1.19 and 1.20 give data on the countries receiving refugees and the origins of refugees in 2007, while

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Table 1.21 offers data on internally displaced people. The biggest source of refugees and displaced people in 2007 was the wars in Iraq and Afghanistan. It is a human side of these conflicts which rarely receives much attention in the Western news media. It also confronts the receiving country with urgent problems of temporary resettlement, which, especially when these countries are themselves not rich, can strain their resources. The country with the largest number of refugees is Pakistan, most of whom have come from neighbouring Afghanistan. The war in Iraq has produced a large refugee crisis for Iran and Syria, not that there has been much sympathetic comment on this in the West. Combining these UNHCR figures with population size (Table 1.2), it suggests that just over 5% of Iraqis have become refugees, and around 8% have been internally displaced, so that altogether around one in eight Iraqis have had to flee their homes. At the same time in Afghanistan, the figure was approaching one in 10. Apart from the human toll of such displacement, it also has implications for prospects of future stability. The tables also show the impact of wars in Africa, especially in Sudan, in Somalia and in the central African countries. Some of these conflicts are not respecters of national boundaries, and Sudan and the Congo for example figure in all three tables, their own conflicts generating refugees and internally displaced persons, but other people escaping from conflicts in neighbouring countries and seeking refuge in them. While the Middle East and Africa dominate these three tables, the scale of people displaced by the fighting in Columbia is very considerable, and there are still large numbers in both Asia and Europe, especially in some parts of the former Soviet Union and Yugoslavia.

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Table 1.22 Asylum seekers since the 1980s Total in thousands per country per period (to nearest thousand) Country United Kingdom Germany United States Canada France Sweden Austria Belgium Netherlands Switzerland Italy Norway Ireland Australia Finland Denmark New Zealand Japan Total

Table 1.23 Asylum seekers in 2005 Country

1980–1989

1990–1999

2000–2007

45 705 396 174 285 139 128 47 55 100 43 24 .. 1 0 36 .. 1

374 1880 898 277 297 246 130 180 322 283 90 54 18 93 18 25 11 1

481 393 355 248 227 205 193 157 152 130 98 84 58 50 46 45 6 40

2178

5243

2933

2005 asylum seekers per million population

Index 2005 (2000 = 100)

2728 1941 1523 1349 1168 1047 817 757 681 674 512 417 351 164 158 85 82 3

123 108 37 57 50 40 128 28 113 61 31 19 37 61 25 22 59 178

803

65

Austria Sweden Belgium Switzerland Norway Ireland France Netherlands Finland Canada United Kingdom Denmark Germany Italy Australia New Zealand United States Japan Mean

Table 1.24 Acceptance of asylum seekers Proportion of asylum seekers accepted Country

18

1980s

1990s

2007

Canada Switzerland Norway Sweden Italy Netherlands Austria Finland New Zealand United Kingdom Australia Denmark Belgium France United States Japan Ireland Germany

36 25 63 87 34 20 52 33 .. 79 20 97 57 52 27 28 .. 15

62 39 43 50 16 39 13 51 18 43 13 74 25 20 44 9 18 10

47 42 40 39 36 33 30 27 22 21 20 19 18 17 17 13 10 6

Mean

45

33

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1.8 Asylum seekers ost of the time, the plight of refugees in the Middle East and Africa waiting in camps for their cases to be adjudicated and then perhaps acted upon receives only passing attention in Western societies. From the late 1980s onwards, two new developments made the issue of asylum seekers in their own countries a much more confronting and impatient presence for many of the selected countries. Firstly, the wars in the former Yugoslavia and other political convulsions following the fall of communism created the largest number of refugees in Europe for a generation. According to the UNHCR, ‘between 1983 and 2000, some 5.7 million foreigners applied for asylum in Europe, with peak numbers between 1989 and 1993. One half of all the cases were in Germany.’ Secondly, while the phrase ‘asylum seekers’ strictly refers to those whose refugee status has not yet been determined, and ‘refugee’ refers to those deemed to meet the requirements of the 1951 UN Convention, namely that they had left their country because of a realistic fear of persecution or danger, the asylum seekers of the past two decades also represented a new phenomenon. Rather than only going as far as the next country, they were prepared to travel a very considerable distance, maybe half a world, beyond the country they are fleeing. Often they arrive as individuals rather than part of a group. Sometimes they enlist the aid of ‘people smugglers’, and so their plight becomes confounded with the quantitatively much bigger issue of illegal immigration. (In 2000, there were an estimated 8.5 million illegal immigrants in the United States.) As Table 1.18 on the previous page indicates, asylum seekers have always been a very small proportion of the total refugee problem. Their number peaked at 6% in 2003, and was down to 2% by 2006. However, because of their immediacy, and especially when mixed with the considerable anti-immigrant sentiment already existing, and the growing trade

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in illegal immigration, they became a focus of political contention. In Australia, the issue reached a new urgency with the arrival by boat of asylum seekers in the early 1990s, and then in increasing numbers in the late 1990s. In 2001, the Howard Government acted very forcefully against the arrivals by boat on Australia’s northwest coast. Apart from the existing detention camps on shore, from then on asylum seekers attempting to arrive in Australia were relocated to offshore locations. In the six years after August 2001, Australian taxpayers spent more than $1 billion to process fewer than 1700 asylum seekers offshore, or an average cost of more than a half a million dollars per person. In the three years between mid-1999 and mid-2002, total unauthorised boat arrivals amounted to around 12 000 people. After this it dropped away to relatively negligible numbers. Tables 1.22 and 1.23 show that the number of asylum seekers also declined in most of the selected countries in this period, although the drop was sharper in Australia than most others. With some exceptions, the issue of asylum seekers receded considerably for most selected countries early in the 21st century. The tables also demonstrate that the problem was much more acute, both in total and proportionately, for some others than for Australia. Table 1.24 points to the political plasticity of the legal determination of who constitutes a refugee. Judgements varied greatly between countries – 97% of applicants in Denmark in the 1980s were accepted, compared with only 9% in Japan. They also became more stringent as numbers increased. The proportion of acceptances dropped between the 1980s and 1990s, while the figures for 2006 showed a further decrease. Some changes were quite dramatic, with the Danish acceptance rate down to 19%, and the British rate down from 79% to 21%.

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Table 1.25 Urbanisation Percentage of population living in urban areas and in large cities (i.e. larger than 750 000), 2005 % in urban areas

% in large cities

Number of large cities

Belgium United Kingdom Australia Denmark New Zealand Sweden United States Canada Netherlands France Norway Germany Switzerland Italy Austria Japan Finland Ireland

97 90 88 86 86 84 81 80 80 77 77 75 75 68 66 66 61 61

10 29 61 20 28 28 47 45 14 27 17 9 15 19 27 48 21 25

1 7 5 1 1 2 52 6 2 7 1 4 1 5 1 8 1 1

Mean

78

27

Country

Table 1.26 Biggest city Largest city’s population and share of national population, 2005

20

Country

Largest city


City’s share of national population %

Japan United States France United Kingdom Canada Australia Germany Italy Austria Sweden Denmark Finland Netherlands New Zealand Switzerland Belgium Ireland Norway

Tokyo New York Paris London Toronto Sydney Berlin Rome Vienna Stockholm Copenhagen Helsinki Amsterdam Auckland Zurich Brussels Dublin Oslo

35.2 18.7 9.8 8.5 5.3 4.3 3.4 3.3 2.3 1.7 1.1 1.1 1.1 1.1 1.1 1.0 1.0 0.8

28 6 16 14 16 21 4 6 27 19 20 21 7 28 15 10 25 17


1.9 Urbanisation ll the selected countries are overwhelmingly urban societies, and have been for generations. Table 1.25 shows that the mean proportion living in areas designated as urban represented 78% of the national populations in 2005, a figure which has been edging up only slowly for several decades. However, there is still a substantial difference between the countries at the top of the table (including Australia) and the more rural and provincial distributions of population among those at the bottom where around one in three people live outside urban areas. Moreover, the countries have very different proportions of people living in large cities (defined here as those with a population of more than three-quarters of a million). Almost half the countries have only one large city, while the most populous country, the United States, which also has a large area and dispersed population, has 52 such cities. One would think that it is a simple matter to determine how many people live in urban areas and to give the size of cities, but in fact it is fraught with methodological disputes. There is no agreed operational definition of what constitutes an urban area, and apparent changes in urbanisation sometimes actually reflect changes in methodology. There is even more difference in estimating the size of individual cities. The first source of difference concerns how to draw their boundaries, and there are two main variants. One is to follow the administrative borders, the city proper. This has the virtue of clarity, but is not valid in any sense to do with the workings of the social unit, and is normally much smaller than the ‘real’ city. The other measure is called the ‘urban agglomeration’. The United Nations defines an urban agglomeration as the city or town proper and also the suburban fringe or thickly settled territory lying outside, but adjacent to, its boundaries. This is more realistic, but more subject to variable

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estimates, as the functional limits of a city are more ambiguous than its legal boundaries. These tables use the UN World Urban Prospects data, based upon urban agglomerations, but readers should be aware that different sources often give substantially different city sizes. In particular, while Tokyo is certainly the largest city among the selected countries, other estimates put its population at less than half the 35 million given here. Australia has a very distinctive pattern of population distribution. In some ways, the sparseness of Australia’s total population density presents a curious contrast with its high degree of urbanisation and the proportion living in big cities. Australia ranks third in the proportion living in urban areas, and has by far the highest proportion living in large cities, the five mainland state capital cities, being more than double the 18-country mean. The obverse of this lop-sided concentration into a few major cities is that Australia has a lot more sparsely populated areas than most of the other countries. Despite Australia’s huge population increase over the last half century, there is little indication that its distribution is becoming less concentrated. According to Lane et al.’s figures, in 1950 Sydney had 18% of Australia’s population, while according to Table 1.26, the contemporary figure is even higher at 21%. Whatever else it might be doing, Australia’s population increase is not filling up the outback. Moreover Australia is unusual in having two premier cities of almost equal size, so that together Sydney and Melbourne probably occupy a larger share of Australia’s population than the largest two cities in any other of these countries. Many countries have only one dominating city, with the second largest much less significant in size and national importance. Although not close to the size of Tokyo or New York, Sydney and Melbourne are by international standards relatively large cities.

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Table 1.27 Religious tradition Self-described religious affiliation in the 1970s (%) Country Ireland Belgium Austria Italy France Switzerland Canada Germany Netherlands Australia United States New Zealand United Kingdom Sweden Denmark Finland Japan Norway

22


Roman Catholic

Protestant

Non-Christian

No religion

96 92 90 87 80 52 50 46 44 32 31 18 14 2 1 1 1 0

4 0 7 0 2 46 43 48 43 57 58 75 74 71 95 94 2 98

0 1 0 0 4 1 2 2 2 1 5 1 3 0 1 0 87 0

0 7 3 13 14 1 5 4 11 10 6 6 9 27 3 5 11 2

1.10 Religious tradition able 1.27, drawn from Barrett’s World Christian Encyclopaedia, documents religious practices in the 1970s, and is of historical rather than contemporary interest. While in some countries the number describing themselves as having no religion was already substantial, it would certainly have risen further since. The immediate political influence of religion has declined in most of the selected countries, but it has played an important role in shaping their histories. This table is thus a guide to religious heritage rather than contemporary belief. In terms of the broad historical influence of religious traditions, the 18 countries fall into five groups. First, and by itself, is Japan – the only country among our 18 with a predominantly non-Christian tradition. The major religions in Japan are Buddhism and Shinto with many Japanese professing both. The second group consists of countries where Catholicism is dominant, and where Protestantism never established itself very broadly in the population. It comprises the five countries at the top of the table – Ireland, Belgium, Austria, Italy and France. In each the Catholic Church has played an important role in the country’s politics, and religious conflict has figured less as Catholic versus Protestant and more as clerical versus anti-clerical. The four Scandinavian countries near the bottom of the table form a third group. Here Protestantism triumphed to become the dominant religion. Historically the eclipse of Catholicism was to some extent tied in with their development as nations and their national identity. Monarchs in Denmark, Norway and Sweden are obliged to be Protestant, for example. The final two groups comprise eight countries where Catholicism and Protestantism have had to learn to co-exist, sometimes after histories of sharp sectarian conflict. Four countries – Switzerland, Canada, Germany and the Netherlands – have close to numerical equality, or a slight Catholic majority. There are considerable differences in their religious histories, depending upon how politically mobilised

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the Catholic Church was, and upon the nature of religious conflicts. In the Netherlands, for example, the bitterness of the religious struggles and the prospect of eternal stalemate ushered in a political system based upon consensus and mutual compromise. In Switzerland and Canada, religious differences are overlaid by linguistic ones and there was also some degree of territorial segregation. The final group comprises the four Englishspeaking countries where there was a clear Protestant majority and a Catholic minority. It must be remembered that the Protestants in these countries were far from unified. In Australia, for example, there was always a clear divide between the Anglicans and other Protestant churches, which were also divided among themselves. The proportion of Catholics is larger in Australia and the United States, where its membership has been boosted by waves of immigrants, especially Irish and Italian. In Britain and New Zealand, Catholics form a smaller minority, and their political importance is consequently less. It is difficult to be definitive about how the different religious traditions have influenced contemporary national policies and outlooks. Certainly those countries with the most religious pluralism were the earliest and most emphatic in separating church and state. The four predominantly Protestant Scandinavian countries have been the most secular, with the apparent decline of religious belief and practice greatest in them. They have also been world leaders in the development of the welfare state and manifest the strongest social conscience, being for example among the most generous in their overseas aid contributions. Where there has been a Catholic nearmonopoly, that Church’s influence in areas like divorce, abortion and education has been more apparent. But again there has been considerable divergence among these countries in such matters. National traditions have many sources beyond religious denominations, and policies are rarely reducible simply to their country’s religious heritage.

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Chapter 2 GOVERNMENT AND POLITICS

Table 2.1 Constitutional history

Country United States Norway Belgium United Kingdom Netherlands Switzerland New Zealand Denmark Sweden Canada Australia Finland Ireland Austria France Italy Japan Germany

Table 2.2 Male suffrage Year when male suffrage was substantially achieved

24

Continuous national elections since

Date of independence

Date of current Constitution

1788 1814 1831 1832 1848 1848 1852 1855 1866 1867 1901 1906 1921 1945 1946 1946 1946 1949

1776 1905 1830 .. 1814 .. 1907 .. .. 1867 1901 1917 1921 1918 .. 1861 .. ..

1789 1814 1931 .. 1814 1874 1852 1953 1975 1982 1900 1919 1937 1920 1958 1948 1947 1949

Table 2.3 Female suffrage Year when female suffrage was substantially achieved

Country

Year

Country

Year

France Germany United States New Zealand Belgium Norway Australia Denmark Finland Austria Sweden Italy Netherlands Canada United Kingdom Ireland Switzerland Japan

1848 1869 1870 1879 1893 1897 1901 1901 1906 1907 1909 1912 1917 1917 1918 1918 1919 1925

New Zealand Australia Finland Norway Denmark Germany Austria Canada United Kingdom Ireland Sweden Netherlands United States France Italy Japan Belgium Switzerland

1893 1902 1906 1913 1915 1918 1918 1918 1918 1918 1919 1919 1920 1944 1946 1947 1948 1971


2.1 Constitutional history hese 18 countries were chosen because for more than the last half century they have continuously fulfilled minimal requirements for liberal democracies. This emphatically does not mean that they are ideal democracies, or that there is not scope for further improvement towards democratic ideals. It means that for this period their governments have always changed according to constitutional processes, and that they have had to face regularly scheduled, fairly conducted, competitive elections in which (close to) all the adult population could vote. They have thus met the criteria of inclusiveness, competitiveness and constitutionality. Australia is one of about half a dozen countries which had continuous elections throughout the 20th century. Another half dozen or so West European countries were always democratic except for periods of foreign occupation in wartime. Finally a third group achieved varying degrees of representative democracy but later relapsed into authoritarian rule, before again becoming liberal democracies after the end of World War II. This group includes the vanquished Axis powers, but also France (which had the most constitutionally problematic change during the contemporary period, namely the 1958 accession of de Gaulle to the presidency, and subsequent change from the Fourth to the Fifth Republic). The tables reveal that democracy rarely emerged fully blown, and did not come all at once to these countries. Rather there was often a series of struggles. In particular, many countries manifested degrees of competitiveness and pluralism before they became fully inclusive. One aspect hidden by the neat listing of dates in the tables on suffrage is the messiness of the process. Sometimes suffrage was achieved incrementally as increasing concessions were won. Some countries moved through a series of halfway houses, such as imposing property or literacy requirements. In some federations, such as the United States, different states had different regulations for permitting voter registration. Similarly before Federation the Australian colonies all had their own constitutional practices, and New South Wales has had continuous elections since 1855.

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In the dates for Tables 2.2 and 2.3, we have followed as far as possible the consensual scholarly judgements. Our criterion has been to assign the date when the nature of the country’s politics was substantially transformed in a democratic direction rather than when democratic principles were fully embraced. Sometimes, as in Australia, suffrage was achieved for the great majority of the population, but in crucial ways fell short of properly embracing democratic principles. With Federation in 1901, at the Commonwealth level, there was full adult suffrage for all whites, but Aboriginals did not gain those rights until 1962. As females gained the right to vote in some countries, they were still subjected to more restrictions than men, for example having a higher minimum age. Some countries maintained a prohibition on women standing for parliament even after they achieved the vote. The data suggest some recurring patterns. For several countries, the coming of independence also brought the coming of liberal democracy, whether independence was achieved through an evolutionary or revolutionary process. The oldest is the most famous. The American War of Independence produced the world’s oldest surviving democratic constitution, and began a process of democratic elections that has continued ever since. A second pattern is that extensions of the franchise often followed wars. After the sacrifices suffered by societies in both World Wars I and II, refusal of pressures towards greater democracy became unsustainable. The other variant of course was the imposition by the Allies after World War II of democratic institutions in the belief that bringing democracy would make the defeated countries less aggressive in future. Some scholars have suggested that Australia and New Zealand should be judged as the first liberal democracies to achieve substantially universal suffrage for both men and women. Lijphart argues convincingly that New Zealand has the stronger claim at national level because Maoris and women had full voting rights from 1893.

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25

Table 2.4 Heads of state and heads of government Head of state Title

Executive power

Belgium Denmark Japan Netherlands Norway Sweden United Kingdom

Monarch Monarch Monarch Monarch Monarch Monarch Monarch

Weak Weak Weak Weak Weak Weak Weak

Australia∗ Canada∗ New Zealand∗

Monarch Monarch Monarch

Weak Weak Weak

Government Government Government

Germany Italy

President President

Weak Weak

Legislature – Special Legislature

Austria Ireland

President President

Weak Weak

Public Public

Switzerland Finland France

President President President

Strong Strong Strong

Legislature Public Public

United States

President

Strong

Public

Country

Selected by

∗ Australia, Canada and New Zealand have the British monarch as head of state, represented nationally by a Governor-General, selected by the national government.

26


2.2 Heads of state and heads of government early all the liberal democracies in Table 2.4 maintain a distinction between the head of state and the executive head of government. The only outright exception is the United States, where both are embodied in the office of the presidency. In three other cases there is a mixing or sharing of roles. The Swiss system reflects that country’s peculiar traditions, with a rotating presidency (and prime ministership) investing less power in the individual leader and more in the collective, multiparty cabinet than any other country. France and Finland have what is sometimes called a semi-presidential system or dual executive. They have a popularly elected President holding the highest office in the land, elected for a longer period than parliament and with the power to dissolve it, but also needing to rule with parliament, which is the institution where governments must be formed. Both systems arose out of problems of parliamentary instability, which have now largely disappeared. In the other 14 cases, the head of state lacks substantial executive power. The most basic question then is why do these countries maintain the two separate roles – head of state and head of government? Typically there are three components of the head of state’s role. The first is symbolic – to preside at ceremonial events, embodying national unity above the fray of political conflict. This may include helping celebrate national festivals and leading national mourning. It also includes an international role, dealing with visiting dignitaries and representing the nation abroad. The second common role is to certify that proper procedures are being following in legislation and elections. The third is to have a ‘reserve power’ role in times of crisis. These latter two roles are infrequently exercised. They arise most often when the rules of the game – the national Constitution – do not unambiguously cover an eventuality that has arisen. In particular, they occur when the workability of the national parliament is in doubt.

N

When heads of state do intervene in political conflicts, it is likely to involve considerable conflict – potentially threatening their capacity to fulfil the consensual parts of the role. Perhaps the most surprising aspect of Table 2.4 is the persistence of monarchies. If the three former British colonies (whose head of state is the British monarch, represented nationally by a Governor-General) are included, then a majority of countries remain monarchies. These monarchs enjoy varying degrees of prestige in their respective countries. However, their current roles and the routes to them are essentially similar. They retain their privileges and ceremonial roles, often religious as well as national, in return for renouncing all attempts to influence politics. Sometimes this renunciation has been codified, such as in the post-World War II Japanese Constitution specifying that the Emperor must play no role in politics. More usually it is a matter of convention, and/or buried in constitutional double talk, which invests all power in the monarch while simultaneously withdrawing any opportunity to exercise it. The Danish Constitution, for example, proclaims that ‘the King shall have supreme authority in all the affairs of the Realm’, but also that the signature of the King is valid only when accompanied by the signatures of his ministers. In the four cases where there is a president with weak executive power, Ireland and Austria directly elect the president. In both cases, partisan competition is less fierce than in Australia. On occasion in Ireland there was only one candidate, and in Austria nearly all presidents have been former diplomats. In Italy, parliament elects the president, and both the role and selection of the president have been a matter of some dissatisfaction. In Germany, a specially convened assembly, nominated by both national and provincial parliaments, elects the president without debate. It is hard to know if any of these provides a clear model for a possible Australian republic.


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Table 2.5 Federal and unitary state structures

Country

System

Judicial review of government decisions

Australia Austria Belgium Canada Germany Switzerland United States

Federal Federal Federal Federal Federal Federal Federal

Y Y Y Y Y N Y

Referendum/veto Referendum/veto Referendum/veto Referendum/veto Referendum/veto Referendum/veto Referendum/veto

Denmark France Ireland Italy Japan Norway Sweden Finland Netherlands New Zealand United Kingdom

Unitary Unitary Unitary Unitary Unitary Unitary Unitary Unitary Unitary Unitary Unitary

Y Y Y Y Y Y Y N N N N

Referendum majority Referendum majority Referendum majority Referendum majority Referendum/veto Referendum/veto Parliamentary majority Referendum/veto Referendum/veto Parliamentary majority Parliamentary majority

Constitutional amendment

Regional governments 6 States 9 Land 10 Provinces 12 Provinces 16 Land 26 Kanton 50 States

Table 2.6 Taxation by level of government Proportion of all taxes raised by central government Country

Type

1985

2005

Australia Austria Germany Belgium United States Switzerland Canada

F F F F F F F

81.4 76.2 68.2 93.7 67.3 55.9 54.6

82.4 81.8 70.1 69.9 65.8 59.2 53.2

Ireland Netherlands New Zealand United Kingdom France Norway Italy Finland Japan Sweden Denmark

U U U U U U U U U U U

95.7 96.1 93.5 87.2 90.7 82.3 97.0 77.6 74.0 69.6 70.7

97.5 95.0 94.7 94.3 87.9 86.7 83.1 79.0 74.7 67.3 66.5

71.0 85.0

68.9 84.3

Mean F Mean U

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2.3 Federalism ll states of any size and complexity devolve some power to more local units of administration. What differentiates a federal system is that the powers of regional governments are constitutionally entrenched. The devolved powers cannot be reduced on the whim of the national government. So, a federal system consists of a division of power between a national government and regional governments, each guaranteed by the constitution to be independent within defined spheres. Federal systems tend to occur in countries which are larger in area, or where there are distinctive social interests (e.g. linguistic or ethnic) in different areas of the country. However, what best explains whether a particular country has a federal or unitary system is not geography but history. In almost all the federations in Table 2.5, the current nation state was formed by the coming together of existing more localised units of government, and in the formation of the new country, some federal guarantees were enshrined. In most cases there has been no change in the regional boundaries since the original constitutions were framed (although some like the United States have added new territories). Australia, for example, had six states in 1901 when its population was less than four million, and still has six states now that it has a population of more than 20 million. The exception to the above pattern is Belgium, which adopted a new fully federal constitution in 1993, following prolonged conflict between the Flemish and Walloon linguistic groups. The arguments for federation include that it encourages greater responsiveness to local needs and variations, and brings government closer to the people, that it allows diversity and experimentation in government, and that it provides a brake on the growth of centralised power. The arguments against involve issues of duplication and inefficiency, and of lack of accountability through buck-passing the responsibility for problems between different levels of government. Some institutional characteristics follow almost automatically from federalism. One is

A

judicial review of government decisions to ensure that one level of government is not abrogating the prerogatives of the other. (Switzerland with its unique mix of institutions is the only federation not to have such judicial review.) Of course countries have judicial review of parliamentary decisions for many reasons of constitutional protection, and, as Table 2.5 shows, most unitary systems also have this provision. In addition, a federal constitution places some rigidity on how that constitution can be changed. Again it is the nature of all constitutions to be relatively stable and difficult to change. Although three countries (Sweden, Britain and New Zealand) allow the possibility of change through a simple parliamentary majority, most others require a referendum. In addition, a change in federal countries typically requires not only a popular majority, but to meet ‘federal’ criteria as well. In Australia it needs a majority vote in a majority of states. Finally, federalism should not be confused with decentralisation. As Table 2.6 shows, central governments tend to raise a greater share of tax in unitary systems than in federal ones, but there is considerable overlap. This is one of federalism’s dilemmas. Either there is an administratively messy system with each state imposing its own taxes or there is ‘vertical fiscal imbalance’, where one layer of government is responsible for raising money that is spent on services provided by another, and so a potential recipe for mutual irresponsibility. Among federations Australia has the largest share raised by the central government. This figure is controversial because after the Howard Government pledged that moneys raised by the GST would go to the states, it tried to claim it was not a federal tax, even though it was collected federally and its level set federally. According to Tim Colebatch in the Age, of every $100 of tax, the Federal Government raises $82, the states raise $15 and local councils raise $3. But of every $100 of expenditure, the Federal Government spends $36, and the states and councils spend $64.


29

Table 2.7 Parliamentary structures

30

Country

Number of chambers

Strength of bi-cameralism

Method of election

Powers of second house

Australia Germany Switzerland United States

Bi-cameral Bi-cameral Bi-cameral Bi-cameral

Strong Strong Strong Strong

Incongruent Incongruent Incongruent Incongruent

Symmetrical Symmetrical Symmetrical Symmetrical

Belgium Italy Netherlands

Bi-cameral Bi-cameral Bi-cameral

Weak Weak Weak

Congruent Congruent Congruent

Symmetrical Symmetrical Symmetrical

Austria Canada France Ireland Japan United Kingdom

Bi-cameral Bi-cameral Bi-cameral Bi-cameral Bi-cameral Bi-cameral

Weak Weak Weak Weak Weak Weak

Congruent Incongruent Incongruent Congruent Congruent Incongruent

Asymmetrical Asymmetrical Asymmetrical Asymmetrical Asymmetrical Asymmetrical

Denmark Finland New Zealand Norway Sweden

Uni-cameral Uni-cameral Uni-cameral Uni-cameral Uni-cameral


2.4 Parliamentary structures able 2.7 reveals a paradox. While being bi-cameral (having two parliamentary chambers) is the norm among the selected countries, having a strongly bi-cameral system is very much the exception. Only five countries are uni-cameral. They include five of the six smallest countries in population and area. All are unitary rather than federal systems. At the other extreme only four, all federal countries, have strongly bicameral legislatures. The other nine countries have weakly bi-cameral systems. To meet the criterion of strong bicameralism, a country must have an upper house whose composition is distinctively different from the lower house (incongruent) and where both houses have substantially the same powers (symmetrical). Even in these systems, the houses nearly always differ in their prerogatives – often, the government must retain the confidence of the lower house to remain in government, the prime minister must be drawn from that house and money bills must originate there. The important criterion is that all legislation must obtain a majority in both houses. The weakly bi-cameral systems fall into two types. The first are those where the upper house lacks the powers of the lower house. They may have the power to criticise or delay legislation but not to block it. The capacity to alter the government’s timing varies: the British House of Lords can delay legislation for one year, the Austrian upper house for only eight weeks and the Japanese upper house for 60 days. The influence of these second chambers rests in moral suasion, their power to propose, disclose or embarrass. In the face of a patient and determined majority government, however, they are powerless. In the second group, legislation must pass both houses, but because of the method of selection, the upper house tends to be an echo of the lower one. Sometimes, as in Japan, the two houses operating on different schedules can produce chambers with contrasting compositions. In several of these, the upper house

T

is either appointed or indirectly elected, and so tends to reproduce the partisan complexion of the government. The source of the paradox – the prevalence of weak bi-cameralism – probably lies in the origins of parliamentary rule. Typically upper houses were based upon the suspicion and fear of popular majority rule. They were preserves of privilege to act as a check upon the popularly elected lower house (and hence the vertical imagery of upper and lower). Most evolved beyond these anti-democratic origins, either by changing their method of selection or by increasingly limiting their powers. Among the four countries with strong bicameralism, the situation derived from their federal origins. In each, the lower house directly reflects population size, while the upper house is based upon ensuring all the regions are equally represented. Although there is no genuine sense today in which these second chambers act as states’ houses, their distinctive composition can provide a check upon the lower house majority. The manner in which this happens is of course contingent upon election results. For most of its history, the Australian Senate was merely a ‘rubber stamp’ for the House of Representatives, but no government between 1981 and 2005 commanded a majority there. This has meant the government must negotiate either with the opposition or with minor parties to get legislation enacted. When the Howard Government effectively won control of both chambers in 2004, it greatly changed the political dynamics for that electoral term. In the United States and Switzerland, there is scope for conference committees where members from both houses seek to negotiate a solution, but in the absence of majority approval in both houses, the legislation lapses. In Australia there is scope to resolve such a deadlock by going to a double dissolution election, and for a joint sitting of both houses of parliament after the election to review the legislation. The first and only such joint sitting was after the 1974 election.


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Table 2.8 Governments, ministers and parliaments Does government depend on confidence of legislature?

Are ministers members of parliament?

Cohesion of governing parties

Government control over parliament

Australia Ireland Japan New Zealand United Kingdom

Y Y Y Y Y

Y Y Y Y Y

H H L H H

H H H H H

Austria Belgium Canada Denmark Germany

Y Y Y Y Y

Y+ Y+ Y+ Y+ Y+

H H H H H

M M H L M

Italy Netherlands Norway Sweden

Y Y Y Y

Y+ N N N

L H H H

L L M L

Finland France Switzerland United States

N N N N

Y+ N N N

H H L L

L H H L

Country

Y = Yes; Y+ = Yes, plus some others; N = No; H = High M = Medium; L = Low.

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2.5 Governments, ministers and parliaments arliament is the central institution of representative democracy. It is the forum where the elected representatives are meant to express the will of the people on a continuing basis, and through which executive government is responsible to the people. However, the institutional means by which different countries seek to achieve responsible, representative government differ enormously. Perhaps the most fundamental issue is whether the survival of the government depends on having the continuing confidence of the legislature. As Table 2.8 shows, the most common pattern among the selected countries is the British and Australian one, where governments must retain the support of parliament to stay in office. Different liberal democracies have devised two diametrically opposed institutional solutions to achieving responsible executive government. In the British-derived Australian system, ministers must be members of parliament, and answer to parliament on a continuing basis. In other systems, which emphasise the separation of powers, cabinet ministers must not be members of parliament. In the middle are a range of countries where nearly all ministers are members of parliament, but which occasionally go outside parliament for some appointments. The problem with ministers not being members of parliament is that the legislature runs the risk of lagging behind in knowing what executive government is doing. The problem with ministers being part of parliament is that in an age of tight party discipline, if the government has a secure majority, parliament simply ‘rubber stamps’ what executive government wants. These contrasts demonstrate that summary judgements about the relative power of different legislatures can be misleading. In one sense the US Congress has less power than parliaments in the British tradition, in that

P

except in extraordinary circumstances it cannot unseat the executive government and that government is not accountable to it in an ongoing manner. On the other hand it is a much less predictable institution – the executive government has less power to determine its legislative outcomes than in most parliamentary systems. In American scholar Bingham Powell’s terms (final column of table), government control over its agenda is low, and the party not in office has more scope to influence deliberations, for example through committee processes, especially given the lower level of cohesiveness and discipline in American political parties. To a considerable extent the differences in the flavour of national parliaments and relations between executive governments and their legislatures are determined by the logic of institutional structures and partisan competition. However, beyond this, countries have built their own traditions about how parliament should function. Institutionally the relationship between executive government and the parliament in Sweden is not so different from a British-style Westminster system, but their traditions are very different. The Swedish parliamentary system works much more through negotiation and deliberation in committees. Most legislation emerges in this way and then has a very high probability that parliament will approve it. The summary in the final column does not take sufficient account of Australia’s bicameral system. The government still has a high degree of control over the legislative agenda, and in this sense Australian parliamentary committee processes are not as developed or influential as in many other democracies, but when the government lacks control of the Senate, its importance as an avenue for scrutiny of government actions and social issues should not be underestimated.


33

Table 2.9 Electoral systems

Country

Plurality systems Canada United Kingdom United States Majority systems Australia France Mixed systems Italy Japan Germany New Zealand Proportional systems Austria Netherlands Denmark Sweden Belgium Finland Norway Switzerland Ireland

Single- or multi-member constituencies

Type of vote

Index of disproportionality 1971–1996

Single Single Single

Categorical Categorical Categorical

12.2 14.7 15.6

Single Single

Ordinal Categorical/Double Ballot

10.2 18.7

25:75 Single: Multi 63:37 Single: Multi 50:50 Single: Multi MMP 42:58 Single: Multi MMP

Categorical Categorical Categorical Categorical

3.8 5.3 1.5 14.6

Multi Multi Multi Multi Multi Multi Multi Multi Multi

Categorical Categorical Categorical Categorical Categorical Categorical Categorical Ordinal Ordinal

1.3 1.3 1.8 1.8 3.1 3.2 4.7 3.0 3.2

(In bi-cameral systems table gives electoral system of lower house only.) Index of Disproportionality: 1 = completely proportional; the higher the score, the more disproportional. MMP = Mixed Member Proportional.

Table 2.10 Number of national elections

Country Australia Denmark Japan New Zealand Canada Austria Belgium Netherlands Sweden Finland Ireland France Italy United Kingdom Germany Norway Switzerland United States

34


Number of national elections 1945–2008

Maximum interval between elections (years)

Average interval between elections (years)

25 25 24 22 21 20 20 19 19 18 18 17 17 17 16 16 16 16

3 4 5 3 5 4 4 4 4 4 5 5 4 5 4 4 4 4

2.2 2.2 2.3 2.5 2.6 2.7 2.7 2.8 2.8 3.0 3.0 3.2 3.2 3.2 3.4 3.4 3.4 3.4

2.6 Electoral systems hese countries are all representative democracies, so how they turn the wishes of the people into elected representatives is crucial. Electoral systems long fascinated scholars, who recognised that the formula by which people are elected has a large impact on who is elected. But in recent years, their importance has come into popular view as well. Among the variety of electoral systems, the first key variable is whether each constituency chooses one member or several. If there is only one winner, it means that those who voted for another candidate will not be represented. So one difference is that multi-member systems tend to produce more proportional outcomes – the representatives elected more closely match the votes cast – as Table 2.9 shows. In the 2005 UK election, in contrast, Tony Blair’s Labour Government won 55.2% of the seats with 35.5% of the vote, while the Liberal Democrats won 22% of the votes, but only 9% of the seats. Another, less commented upon aspect of electoral methods is whether voters must choose only one option (categorical) or whether they can express their preferences among candidates (ordinal). In single-member systems where there are more than two candidates, under a categorical system (as in the United Kingdom and the United States), the voter must make a strategic as well as preferential decision. Which candidate do I prefer? Do they have a chance of winning? Many voters who might prefer a minority candidate decide not to ‘waste’ their vote on someone who has no chance of winning. Apart from preferential voting, another solution to this problem is the one used in France. If no candidate obtains a majority in the first round, there is a run-off between the leading vote getters. This system drew wide criticism in the 2002 presidential election, where none of the 17 candidates got more than 20% of the vote in the first round, resulting in a second round between President Chirac and the extreme right party leader, Le Pen. Multi-member, proportional representation (PR) systems generate different problems.

T

People can be elected with a low percentage of the vote. In the Netherlands, where the whole country is one single electorate, which elects 150 members, a candidate can be elected with less than 1% of the vote. In some variants (now largely discarded) when voters could only choose one party list or another, they had no influence over which individuals were elected. This gave the party machines, which decided the list rankings, great power. Most list systems now give voters some choice among individual candidates. Some such as the Irish system (also used in the Australian Senate) allows voters to express preferences across parties. The most common criticism of PR systems is that they rarely produce clear parliamentary majorities, and that the result can therefore be weak and unstable government. Accidents of arithmetic can also give disproportionate power to small groups holding the balance of power. Perhaps because both systems have their drawbacks, when in the 1990s three countries changed their electoral system, they all adopted mixed systems, using both methods simultaneously. In the case of New Zealand, like Germany, there is also a provision to make the final composition of parliament proportionate to popular support. Malcolm Mackerras calculated that New Zealand thus improved its index of disproportionality to 1.8. Last but not least, only Australia and New Zealand have a maximum three-year interval between elections. The frequency of elections is also influenced by parliamentary stability and by whether the system allows governments to go to the polls early to maximise their electoral chances. Table 2.10 shows that Australia has had the equal most elections among these countries since 1945. In sum, Australia has a distinctive and home-grown electoral mix – frequent elections, preferential, single-member voting for the House, contrasting voting systems for its two houses of parliament, and compulsory voting.


35

Table 2.11 Party systems Effective number of parties 1971–1996

Capsule description of system

New Zealand Australia United Kingdom Canada United States

2.0 2.2 2.2 2.4 2.4

Essentially two-party Essentially two-party Essentially two-party Essentially two-party Essentially two-party

Austria Germany Ireland

2.7 2.8 2.8

Principally two-party with significant 3rd Principally two-party with significant 3rd Principally two-party with significant 3rd

France Sweden Norway Japan

3.5 3.5 3.6 4.1

Moderately multi-party Moderately multi-party Moderately multi-party Moderately multi-party

Netherlands Denmark Finland Italy Belgium Switzerland

4.7 5.1 5.2 5.2 5.5 5.6

Strongly multi-party Strongly multi-party Strongly multi-party Strongly multi-party Strongly multi-party Strongly multi-party

Country

Table 2.12 Electoral choice and government formation Identifiability of prospective governments in pre-election choice

Formation of government post-election

High High High High High High High High High

Usually clear result Usually clear result Usually clear result Usually clear result Usually clear result Usually clear result Usually clear result Usually clear result Variable

Norway Austria Ireland Denmark Netherlands

Variable Variable Variable Variable Variable

Usually clear result Variable Variable Negotiation after Negotiation after

Belgium Finland Italy Switzerland

Low Low Low Low

Negotiation after Negotiation after Negotiation after Negotiation after

Country Australia Canada France Germany Japan New Zealand United Kingdom United States Sweden

36


2.7 Party systems and electoral choice he most obvious difference when looking at political contests in these democracies is that some involve an essentially two-sided competition, while in others there is a larger number of competing parties. It would seem a simple matter to count the number of parties, but in fact it is a complicated exercise. To be relevant, some account has to be taken of the relative size of political parties and their role in forming government. Political scientists have used the concept of the ‘effective’ number of parties to count not just their existence but their importance and support. There are continuing disputes about the best way to calculate this, but Lijphart’s figures in Table 2.11 provide a good guide to the party competition in the selected countries. As can be seen from the descriptions in the right-hand column, they fall into four broad groups, from essentially two-party to strongly multi-party. In the period 1971–1996 the Englishspeaking countries all fell at the two-party end of the spectrum. All had single-member electoral systems. The association between electoral system and party system is strong. However, parties with a strong regional basis can lead to more than two parties, and this has become more pronounced in Canada. The New Zealand party system changed with its change of electoral system. Next is a grouping of three countries, where there was a third party whose support could influence the formation of governments. In each there has been principally a choice between two main parties for government, but some variability or uncertainty about who might join with whom in coalition. (The Italian scholar Giovanni Sartori famously classified the relationship between the Liberal and National parties in Australia as a coalescence rather than a coalition between two independent parties, given the high degree of cooperation between them.) As we move into the multi-party systems, the patterns become ever more various. Some revolve around one dominant party. For most of the contemporary era, two coun-

T

tries, Japan and Italy, had dominant party systems. The Christian Democrats in Italy and the Liberal Democratic Party in Japan were far bigger than their competitors and invariably, until the early 1990s, formed the basis of the government. After Italy’s anti-corruption and electoral reforms, the Christian Democrats disappeared, and party competition is increasingly based around two broad party groupings. In Sweden, most governments have either been based upon the Social Democrats (often able to form government in their own right) or a coalition of smaller conservative parties. As the number of parties increases, the nature of the electoral choice changes. G. Bingham Powell has analysed (Table 2.12) how in half these countries the nature of the government (either single-party or coalition) they are electing is usually clear to the public before the election. But in four strongly multi-party systems, there is not such a clearly identifiable choice between competing aspirants for government. Similarly, although no-one can predict all the permutations of party balances an election might throw up, in the two-party systems it is normally clear after the election who will form the government. In other countries, with many different groups represented, there can still be considerable uncertainty about what coalition will form government. A party’s own vote might go down, but because of the balance of competing powers its chance of being in government may increase. The lottery aspect of who forms government should not be exaggerated, but in some countries post-election negotiations can be protracted. We should conclude by noting the absence of one important type of comparative study: how similar or how different are election-night parties under the different systems? One might guess that there is drowning of sorrows and toasting of success everywhere. But in Denmark and the Netherlands, for example, unlike Australia, they rarely know for certain on election night the composition of the new government, and such uncertainty might be a sobering influence.


37

Table 2.13 Types of governments Parliamentary situation of governments 1945–1998 % of governments formed

Country

Table 2.14 Duration of governments

Single-party or minimal winning coalition

Minority government

Surplus coalition

100 95 93 90 81 77 65 60 55 44 42 34 23 16 14 12 6

0 5 0 5 0 9 35 22 45 0 58 67 29 14 86 0 38

0 0 7 5 19 15 0 18 0 56 0 0 48 70 0 89 56

New Zealand United Kingdom Australia Austria Germany Belgium Canada Japan Ireland Netherlands Norway Sweden Finland France Denmark Switzerland Italy

Number of governments 1945–1998

Mean duration (days)

France Italy Finland Japan Belgium Australia Denmark Germany New Zealand Norway Sweden Austria Canada Ireland Netherlands United Kingdom

56 55 45 40 36 28 28 25 24 24 24 20 20 20 20 19

336 331 404 461 511 661 638 660 794 775 752 917 947 900 879 995

Mean

30

685

Country

Switzerland not included because governments change after one year as a constitutional requirement. United States not included because of its presidential system.

United States not included.

Table 2.16 Outcomes of elections Proportion of national elections leading to changes in party composition of government 1945–2002

Table 2.15 Early Cabinet terminations Early Cabinet terminations 1950–1999 Country Australia New Zealand Switzerland United Kingdom Austria Canada Sweden Norway Japan Ireland Germany Netherlands Denmark Finland France Belgium Italy

Internal dissent

Lack of support

Total

0 0 0 0 3 0 3 1 2 2 7 6 2 14 8 14 16

0 0 0 0 0 3 1 3 4 5 2 3 10 3 9 5 16

0 0 0 0 3 3 4 4 6 7 9 9 12 17 17 19 32

United States not included.

Major change %

Slight change %

No change %

Ireland France United States United Kingdom New Zealand Norway Netherlands Canada Denmark Finland Belgium Australia Sweden Italy Austria Japan Germany

65 50 50 44 40 40 35 33 32 29 28 22 22 20 17 15 14

0 0 0 0 0 0 41 0 27 41 33 0 0 53 17 0 0

35 50 50 56 60 60 24 67 41 29 39 78 78 27 67 85 86

Mean

33

12

55

Country

Switzerland not included.

38


2.8 Types and duration of governments able 2.14 would seem to paint a picture of instability and vulnerability, with the selected countries having had an average of 30 governments in the 53 years from 1945, each lasting less than two years. However, this exaggerates the degree of discontinuity. Many end for routine reasons. Governments are considered to have ended when their leader retires or dies and when they face an election (whether or not they are re-elected). Even when they are terminated early because of political problems (as shown in Table 2.15), often a government dissolves only to be replaced by a somewhat different arrangement of essentially the same parties. However, Table 2.15 does display a stark contrast. In the top half of the table, it is rare, even unheard of, for national governments to be prematurely terminated for political reasons. But in Italy, around 60% of governments ended early, either because the coalition collapsed through internal dissent, or because the government lost support in the wider parliament. Belgium, Finland and France have similarly manifested considerable instability because of lack of internal cohesion. The revolving door nature of Italian governments has long been a comic theme, so it may be surprising to see in Table 2.14 that France had even more governments. This is really testament to the brevity of governments during France’s Fourth Republic (1945–1958), and since then it has had much more stability. Denmark shares with these countries a high rate of early terminations. On 12 occasions, governments were forced to the polls because of loss of parliamentary support. Some of the explanation for the differences in Table 2.15 can be found in Table 2.13. The Danish experience highlights the parliamentary situation of governments. In the Australian and British systems, it is common for an election to result in a government with a parliamentary majority formed by a single party, or by the minimum number of parties needed to gain that majority. Often, however, governments are formed without a parliamen-

T

tary majority. Indeed more than half the governments in Denmark, Sweden and Norway have been minority governments. Sometimes, especially in relatively consensual political systems like those countries, such governments can be fairly stable. They are, by nature, however, politically vulnerable if their opponents ever unite and mobilise against them. A third type of government is when a more inclusive coalition is formed. The attractions of such a ‘surplus coalition’ include insurance, so that the government will have some cushioning against the threat of a future defection, or the government may be aiming to create as wide a consensus as possible. (The brief periods of surplus coalition in Australia have been when there was a Liberal–National Party coalition government, even though the Liberals could have governed alone.) Table 2.16 further qualifies the impression of government vulnerability that Table 2.14 might have suggested. In two-thirds of national elections between 1945 and 2002, the government was either re-elected without change, or re-elected with a somewhat differing coalition make-up. Only in Ireland were governments more commonly than not voted out of office. At the other extreme lie Germany, Japan and Austria, where a government was rarely evicted by the electorate (although in Germany there were two occasions where there had been a major change of government before the election, which the election then confirmed in office). Australian governments have been relatively secure with elections bringing a change on only five occasions since 1945. Moreover, those most vulnerable to falling due to internal discontent in Table 2.15 are not the most electorally vulnerable in Table 2.16. In the extreme case of Italy, despite the apparent instability there was a strong, even suffocating, degree of continuity. All Italian governments from the 1940s to the early 1990s were based on the Christian Democratic Party, and it was only with the reforms of the 1990s that a more electorally responsive form of politics emerged.


39

Table 2.17 Partisan colour of governments 1950–2000 Participation in office of party types, proportion of cabinet seats, 1950–2000 Country Sweden Norway Austria Denmark Australia United Kingdom Finland Belgium New Zealand Germany Switzerland Italy Netherlands France Ireland Japan United States Canada

40


Social Democratic

Centre

Liberal

Conservative

Other

77 72 57 55 31 30 30 30 26 25 24 22 21 19 11 2 0 0

10 12 37 4 0 0 33 50 1 53 30 63 54 13 20 0 45 69

7 4 1 26 0 0 12 17 0 17 32 7 23 18 0 0 0 0

4 12 0 14 69 68 10 0 73 0 15 0 0 27 67 97 55 31

3 0 5 2 0 2 15 3 0 4 0 8 2 23 2 1 0 0

2.9 Partisan colour of governments entral to an understanding of any country’s politics is the nature of the choices between parties, and while these countries share democratic institutions, they have had very contrasting experiences of partisan competition and of which parties have been most successful. The most common labels, ‘left’ and ‘right’, are too simplistic to apply with any precision. Parties change their positions over time. It is often asserted, for example, that contemporary labour parties in Australia, New Zealand, Britain and elsewhere have moved to the right. Likewise the British Conservative Party since Margaret Thatcher has had far more in common with the small government views of the US Republican Party than it did under her more paternalistic predecessors. Nor are political parties which adopt left or right views in one area compelled to be similar in all other areas. The New Zealand Labour government of David Lange was more leftwing in its foreign policy – at least in its relations with America – but far more economic rationalist in orientation than the preceding conservative government of Piggy Muldoon. It is the nature of political parties to be broad coalitions, to reach beyond their core base to win elections, to aggregate and balance competing interests. A successful party is thus by nature prone to flexibility, compromise and inconsistency. Nor is it easy to summarise the living and changing nature of political ideologies, or how they relate to the peculiarities of different nations’ unique conflicts and challenges. No grouping of parties can then be completely satisfactory, but Manfred Schmidt’s summary, shown in Table 2.17, is one of the most comprehensive and sophisticated. The most common categorisation was built around left and right. The right (conservative) category includes the Australian Liberal Party, the British Conservatives, and the US Republicans. The left was based upon social democratic, labour and socialist parties, and was often defined by membership of the Socialist International. This included the Australian, British and New Zealand labour parties, the German and Swedish Social Democrats and so on. There were two major problems with this binary grouping. First Canada and the United

C

States were not considered to have any leftwing parties. The left-of-centre alternatives within their political spectrum – the Democrats and the Liberals – were not social democratic, and so all their governments were labelled ‘conservative’. The other problem was that there were clear differences in orientation between for example the more welfare-oriented and ‘big government’ Christian Democratic parties of Germany and Italy and the Austrian Conservative Party with the secular, more small government Anglo-Saxon conservative parties. So Schmidt developed a Centre category to include the US Democrats, Canadian Liberals and these Christian Democratic Parties. Two smaller categories complete the table – an emerging European tradition of small government, secular ‘liberal’ parties, and a residual category, a miscellany of parties which thus far have played only small roles in government (far right, green, regionalist etc. parties). No categorising can capture all the pertinent individualities but Table 2.17 reveals contrasting patterns. At the top are four small European countries, where social democratic parties have participated in government a majority of the time, and the political spectrum runs from left to centre. At the bottom are some countries where the pertinent political spectrum runs from centre to right. The middle group covers wide differences in political history. Australia, Britain and New Zealand form one group which has had social democratic governments for much less than half the period alternating with conservative governments, which have been in power more often. There is another group, including the Netherlands and Germany, and perhaps Switzerland and Italy, where the social democratic presence in government runs at only around a quarter, but the main alternative has been centre rather than conservative parties. To at least some extent, the very different national policy traditions, which we will see in subsequent sections, can be traced back to these patterns in the partisan composition of governments. GOVERNMENT AND POLITICS

41

Table 2.18 Women in parliament Women members of lower houses of parliament as a % of total Country Sweden Finland Norway Denmark Belgium Netherlands New Zealand Austria Germany Australia Switzerland Canada United Kingdom Italy United States France Ireland Japan Mean

Table 2.19 Female Cabinet ministers Women Cabinet ministers as a % of total Country

1975

1987

1995

2003

2008

21 23 16 16 7 9 5 8 6 0 8 3 4 4 4 2 3 1

29 32 34 29 8 20 14 12 15 6 14 10 6 13 5 6 8 1

40 34 39 33 12 31 21 23 26 10 18 18 10 15 11 6 13 3

45 38 36 38 23 37 28 34 32 25 23 21 18 12 14 12 13 7

47 42 38 37 36 36 32 31 31 28 25 24 19 16 16 14 14 11

8

15

20

25

28

1994

2000

2005

Sweden Finland Germany Norway Netherlands Austria Denmark United Kingdom Canada New Zealand Belgium Ireland Australia France Switzerland United States Japan Italy

30 39 16 35 31 16 29 9 14 8 11 16 13 7 17 14 6 12

55 44 36 42 31 31 45 33 24 44 19 19 20 38 29 32 6 18

52 47 46 44 36 35 33 29 23 23 21 21 20 18 14 14 13 8

Mean

18

31

28

Table 2.20 Female heads of government Country

Number

Type

Name

Total time (years and months)

Starting date (month/year)

Canada Finland

1 2

France Germany New Zealand

1 1 2

Norway Switzerland

1 2

United Kingdom

1

PM Pres PM PM PM PM PM PM Pres Pres PM

Kim Campbell Tarja Halonen Anneli Jaatteenmaki Edith Cresson Angela Merkel Jenny Shipley Helen Clark Gro Harlem Brundtland Ruth Dreifuss Micheline Calmy-Rey Margaret Thatcher

0.4 8.5 0.2 0.11 3.0 2.0 9.0 10.0 (3 periods) 1.0 1.0 11.7

6/1993 3/2000 4/2003 5/1991 11/2005 12/1997 12/1999 2/1981 1/1999 1/2007 5/1979

Never had a female head of government: Australia, Austria, Belgium, Denmark, Ireland, Italy, Japan, Netherlands, Sweden, United States. PM = Prime Minister Pres = President

42


2.10 Women in public life able 2.18 shows both how women were marginalised in politics in previous decades and how rapidly their representation in parliament has grown. In 1975, less than one in 12 members of parliament was a woman; by 2003 it was up to one-quarter, although by 2008 in no country had the split reached 50–50. As on many feminist issues, the leaders are the Scandinavian countries plus the Netherlands. The four Scandinavian countries each had a higher representation of women in parliament in 1975 than Australia had reached by 1995 or Japan by 2008. The most common comparative indicators only give lower house figures as most countries are either uni-cameral or not strongly bicameral (Table 2.7). Australia is probably the only one of the selected countries where this can be misleading. Traditionally, there were more women in the Australian Senate than the House, although more recently the proportions are about equal. It was widely accepted among electoral scholars that women (and other disadvantaged groups) were more likely to become members of parliament under a multi-member than single-member electoral system (Table 2.9). It can be seen from the table that the Englishspeaking single-member electorate countries tend to rank in the bottom half. These countries were all very low on women’s representation in the 1970s, although all have increased greatly since then. The highest is New Zealand, which changed its electoral system in the 1990s. However, multi-member electorates have not been sufficient to have Irish, Italian and Japanese women elected in larger numbers, so clearly cultural factors are still important, and the north-western European democracies have distinctive profiles in several aspects of political life, making any simple equations difficult to sustain.

T

Moreover women are not just becoming backbench members of parliament. Table 2.19 shows that on average their ministerial representation is around the same as their parliamentary proportions. Although we lack as long a run of data here, even between 1994 and 2000, women’s ministerial representation increased substantially, although it then plateaued. Sweden is the only country with a majority of female ministers, although three others have more than 40%. Australia ranks in the bottom third, and is one of the few countries which has a lower proportion of women ministers than of MPs. Italy and Japan rank last, with the United States again near the bottom. In only eight of the 18 countries (see Table 2.21) has a woman become head of government, and that includes France (where a woman has been prime minister but not president). In the other semi-presidential, dual executive system, Finland has had a woman in both leadership roles. In only three countries has more than one woman ascended to the peak of political success. Moreover only six of these women leaders have lasted more than a year in the leadership, and, as of late 2008, Britain’s Margaret Thatcher is still the woman with the longest leadership tenure. She was also the first woman leader in the selected countries, and only she and Norway’s Gro Harlem Brundtland (who has been Prime Minister during three separate periods) became leaders before the 1990s. So it is no longer a novelty to have women politicians in prominent positions in most of the selected countries, but they still fall a long way short of gender equity, with around a third of the countries still having women occupying fewer than one in five elected and ministerial positions.


43

Table 2.21 Electoral participation Voting turnout as a proportion of registered voters in each period Country

1945–1970

1971–1990

1991–2007

Australia Belgium Denmark Italy Sweden New Zealand Austria Germany Netherlands Norway United States Finland United Kingdom Ireland Canada France Japan Switzerland

94 92 84 92 83 91 95 86 95 81 93 79 77 74 76 79 73 68

95 93 87 91 90 88 91 87 84 82 76 76 75 74 74 74 70 51

95 92 86 84 84 83 81 80 78 77 69 67 67 66 65 64 57 45

Mean

84

81

74

Table 2.22 Membership of political parties Percentage of electorate belonging to political parties 1970s

1980s

1990s

Change (1970s–1990s)

Austria Finland Switzerland Norway Belgium Sweden Japan Ireland Germany Italy Denmark Netherlands New Zealand United Kingdom Australia France

25.9 17.2 10.4 12.8 10.0 19.6 1.1 4.6 3.7 12.8 14.0 4.4 14.6 6.2 3.7 1.9

24.2 14.4 9.1 13.4 9.1 23.7 2.7 4.5 4.5 7.1 7.5 4.1 7.8 3.8 2.6 3.1

17.1 10.5 8.7 7.9 7.6 7.1 4.2 3.4 3.2 3.2 3.1 2.2 2.1 1.9 1.5 1.5

−8.8 −6.7 −1.7 −4.9 −2.4 −12.5 +3.1 −1.2 −0.5 −9.6 −10.9 −2.2 −12.5 −4.3 −2.2 −0.4

Mean

10.2

8.9

5.3

−4.9

Country

Canada and the United States do not have formal party memberships as occur in the other countries.

44


2.11 Political participation n nearly every advanced liberal democracy there is concern about increasing public alienation from politics. Considerable survey evidence suggests increasing cynicism. The figures in Table 2.21 on voting turnout offer limited support for this concern. The trend in the most recent decades is for turnout to be on average 10 percentage points lower than in the post-World War II decades, a decline but not necessarily one suggesting a crisis. The figures on party membership in Table 2.22 show a more precipitate decline, essentially halving as a proportion of the population between the 1970s and 1990s. There are large differences between the countries. The Swiss have the lowest turnout at elections, perhaps because with their unique emphasis on quarterly referendums, they feel overly blessed with opportunities to participate. The fall in electoral participation has been greatest in Japan. Here it correlates with the nation’s increasing economic problems, and seems to suggest a lack of public optimism about any political solutions to them. Not surprisingly the figures show that the best way to achieve high turnout for voting is by making it compulsory. The four countries at the top of the list – including Australia – all have some degree of compulsion about voting, although in Austria and Italy it is only weakly enforced. Countries have different traditions about whether elections are held on a holiday or work day, whether there are two voting days or only one, and if the voter cannot vote in person in their own constituency how easy it is to cast an absentee or postal ballot. While modifying some procedures would probably increase participation in the more restrictive countries, logistical arrangements do not correlate strongly with overall levels of turnout. There can be marked variations in the same country at different elections. Apart from lack of enthusiasm for all politics, one variable affecting turnout is whether the outcome is predictable or uncertain. Thus Tony Blair’s predictable landslide re-election in Britain in 2001 was achieved with a very low turnout.

I

It can also vary with political strategies. The 2004 US presidential election had high turnout, partly because the strategy of Karl Rove, George Bush’s campaign architect, was to mobilise the Republican base, and they achieved an unusually high turnout among groups that support the Republicans, but don’t always participate actively. There are two ways of measuring voter turnout, and neither is universally satisfactory. The better option, which is used here, is as a proportion of registered voters, and the other is as a proportion of the voting age population. In many countries (including Australia) registration is compulsory and so all-but-identical with citizenship. In other countries, most especially the United States, registering to vote is voluntary, and sometimes – especially for minority groups – has proved difficult to achieve. So in earlier decades it was one country where the proportion of all adults voting was substantially lower than that of registered voters only. In the late 1990s, however, there was a great improvement there in the proportion of adults registered. A low proportion of voters compared with the total adult population is also characteristic of countries with high immigrant populations where newcomers have not or cannot become citizens. Measuring party membership is much more problematic. Parties often inflate membership figures for their own motives. Some organisations demand participation from their members; others are happy to have passive membership. Sometimes party membership comes from belonging to another organisation, for example a trade union. Whatever the reservations about the precision of the figures in Table 2.22, the broad story they tell is clear. Party membership declined sharply over two decades in nearly all countries, both where it was relatively high in the 1970s (e.g. Denmark, Sweden) and others where membership was already very low. Australia’s share of the population belonging to a political party began in the lowest quarter of countries, and had fallen to equal last by the 1990s.


45

Chapter 3 ECONOMICS

Table 3.1 Income per capita GDP per capita ($US 000 PPP) 2006 Country

$US 000

Norway United States Ireland Switzerland Canada Netherlands Austria Australia Denmark Sweden Belgium United Kingdom Finland Germany Japan France Italy New Zealand

52.1 43.8 40.7 37.7 36.8 36.5 35.7 35.5 35.2 34.9 33.5 33.0 32.7 32.0 32.0 31.0 29.0 25.9

Mean

35.4

Table 3.2 Income per capita 1870–1998 Per capita income in thousands of 1990 international dollars Country

46

1870

1913

1950

1973

1998

United States Norway Denmark Switzerland Canada Japan Australia Netherlands France Belgium Austria United Kingdom Sweden Finland Ireland Germany Italy New Zealand

2.4 1.4 2.0 2.2 1.7 0.7 3.6 2.8 1.9 2.7 1.9 3.2 1.7 1.1 .. 1.8 1.5 2.7

5.3 2.5 3.9 4.3 4.4 1.4 5.7 4.0 3.5 4.2 3.5 4.9 3.1 2.1 .. 3.6 2.6 5.2

9.6 5.4 6.9 9.1 7.4 1.9 7.5 6.0 5.3 5.6 3.7 6.9 6.7 4.3 3.4 3.9 3.5 8.5

16.7 11.2 14.0 18.2 13.8 11.4 12.8 13.1 13.1 12.2 11.2 12.0 13.5 11.1 6.9 12.0 10.6 12.5

27.3 23.7 22.1 21.4 20.6 20.4 20.4 20.2 19.6 19.4 18.9 18.7 18.7 18.3 18.2 17.8 17.8 14.8

Mean

2.1

3.8

5.9

12.6

19.9


3.1 National prosperity ncome per person, or GDP per capita, is the standard way of measuring the average material standard of living of a country’s population, although of course it tells us nothing about how evenly or unevenly income is distributed. Comparisons of the living standards of different countries are sometimes made by simply converting each country’s GDP per capita to a common currency, such as US dollars. However, this fails to allow for the fact that the amount of goods or services one US dollar buys differs greatly from one country to another. For this reason, international comparisons of living standards are more accurate when the common currency used has been adjusted to ensure it has similar purchasing power in each country. Table 3.1 uses US dollar annual amounts after they have been painstakingly adjusted by the OECD to achieve purchasing power parity (PPP) between countries. Leaving aside the special case of Norway – a small country with the good fortune to have discovered oil and the even greater good fortune of having a government with the foresight to carefully invest much of the proceeds – the table shows the United States is the most prosperous of the major economies. More surprising is the new-found affluence of Ireland, the Celtic Tiger. What stands out from the table is the way living standards in the developed world have converged. The incomes of two-thirds of the selected countries lie within a range of about $3000 above or below the mean per capita income of $35 400 a year. So Australians’ standard of living is pretty much par for the course in the developed world. All the selected countries have experienced a huge increase in living standards over the last century. Table 3.2 shows how, overall, real living standards in these developed economies rose by a factor of more than nine over almost 130 years. It is based upon the heroic efforts of the veteran scholar Angus Maddison, who has devoted his career to estimating

I

the world’s economic growth over past centuries. No doubt many of his estimates and assumptions could be argued with, but they are the best available over such a long period. Maddison has achieved comparable purchasing power by using ‘international dollars’. And because those dollars are all of the 1990 vintage, there is no need to allow for inflation when comparing amounts between years. Their increase over the periods reflects a real growth in income. Unfortunately, Maddison’s estimates have not been updated after 1998. The table well demonstrates the joint phenomena of ‘catch-up and convergence’ between the economies of the developed world. Over the period, the gap between the richest and poorest of the selected countries narrowed from a factor of more than five to less than two. At one extreme, Japan’s standard of living is estimated to have risen by a factor of 29; at the other, New Zealand’s rose 5.5 times. This is the right context in which to view Australia’s decline from being the world’s richest country on a per-capita basis in the second half of the 19th century to being in the middle of this league of high-income nations today. Initially, Australia was a New World country with a small population, a high proportion of which was engaged in the relatively easy exploitation of its considerable agricultural and mineral wealth. But this unusual and privileged position could not be sustained as Australia’s population grew and commodity prices fell, while other countries steadily caught up. New Zealand has had a similar experience, though more recent problems have taken it to the bottom of the league. The United States’ early rise to its position as the biggest and richest economy can be seen, as can the United Kingdom’s steady decline from near the top of the league to the bottom half. Japan’s post-World War II ascent is evident, as is the more recent rise of oil-rich Norway.

ECONOMICS

47

Table 3.3 Economic growth 1820–1998 Average per capita annual growth rates, 1820–1998, % Country

1820–1870

1870–1913

1913–1950

1950–1973

1973–1998

Ireland Norway Japan Austria Italy Finland United States Belgium Australia Denmark United Kingdom Netherlands France Germany Canada Sweden New Zealand Switzerland

.. 0.52 0.19 0.85 0.59 0.76 1.34 1.44 3.99 0.91 1.26 0.83 0.85 1.09 1.29 0.66 3.90 1.09

.. 1.30 1.48 1.45 1.26 1.44 1.82 1.05 1.05 1.57 1.01 0.90 1.45 1.63 2.27 1.46 1.51 1.55

.. 2.13 0.89 0.18 0.85 1.91 1.61 0.70 0.73 1.56 0.92 1.07 1.12 0.17 1.40 2.12 1.35 2.06

3.04 3.19 8.05 4.94 4.95 4.25 2.45 3.55 2.34 3.08 2.44 3.45 4.05 5.02 2.74 3.07 1.72 3.08

3.97 3.02 2.34 2.10 2.07 2.03 1.99 1.89 1.89 1.86 1.79 1.76 1.61 1.60 1.60 1.31 0.67 0.64

Mean

1.27

1.42

1.22

3.63

1.90

Table 3.4 Economic growth 1889–1939 Average per capita GDP growth rates 1889–1939, % Total 1889–1900 1900–1910 1910–1913 1913–1918 1918–1925 1925–1929 1929–1932 1932–1939 1889–1939

Country Japan Denmark Finland Norway Sweden Germany Italy Canada France Switzerland United States Austria New Zealand Belgium Netherlands United Kingdom Ireland Australia Mean

48

1.5 1.8 1.9 0.9 2.1 2.1 0.7 2.0 1.9 .. 1.9 1.7 1.4 0.9 1.3 1.1 1.1 −1.0

1.0 2.1 1.4 1.5 1.5 1.2 2.7 3.4 0.3 1.4 2.0 1.3 2.2 0.9 0.4 0.3 .. 2.6

2.1 1.8 3.4 3.5 1.3 2.8 3.2 3.0 5.5 1.1 2.2 1.7 −1.0 1.3 2.4 2.2 .. −0.5

3.8 −2.4 −8.3 −1.8 −3.9 −3.8 5.8 0.0 −7.2 −2.3 1.3 −5.9 −1.0 −7.5 −3.7 2.1 .. −1.7

1.8 3.4 7.9 3.7 3.6 2.6 −2.1 −0.3 8.2 5.1 1.5 4.0 1.1 7.2 6.0 −1.8 .. 1.8

1.8 3.8 3.9 4.2 4.6 3.5 1.5 3.9 3.1 4.1 2.4 2.4 −0.1 2.0 3.1 1.7 2.4 −2.8

−1.1 0.6 −2.1 1.3 −1.8 −9.0 −1.6 −10.2 −5.6 −3.4 −10.7 −7.4 −6.1 −3.0 −4.0 −2.2 1.7 −2.9

5.3 2.1 4.2 3.3 4.6 7.9 2.6 3.8 2.8 1.6 4.2 4.9 5.9 1.6 1.4 2.8 0.4 2.7

2.2 1.9 1.9 1.9 1.8 1.6 1.6 1.5 1.5 1.4 1.3 1.1 1.1 0.9 0.9 0.8 0.7 0.2

1.3

1.5

2.1

−2.1

3.2

2.5

−3.7

3.5

1.4


3.2 Long-term economic growth hile Table 3.2 charted the selected countries’ growing long-term income, Table 3.3 looks at this from the perspective of rates of economic growth. It does so by examining the annual growth rate of GDP per capita. The growth of economies is commonly measured simply by the increase in overall GDP but, because the population is growing also, the rise in income per capita (i.e. GDP per person) offers a better indication of whether the population is becoming more prosperous. Table 3.3 reveals that it is only since World War II that economic growth has been consistently achieved over time and across countries. Whereas, as Table 3.4 shows, there were two periods – World War I and the depression of 1929–1932 – when economic disaster was almost universal, there were few periods before World War II when economic growth was universal. The post-war improvement is commonly attributed to the advent of Keynesian demand management and the greater share of the economy accounted for by the relatively more stable government spending and the services sector generally. For all these countries, the period of nearly 30 years following World War II was the ‘golden age’ of rapid economic growth, unlike any period in world history before or since. The 18-nation average annual growth rate of 3.6% more than doubled any preceding period. Australia’s relative performance was not strong, but the same can be said of the other English-speaking countries, which together comprised the bottom third of countries. It was a period of catch-up for the non-Anglo economies, and the countries which enjoyed the fastest growth were those that lost the war and had most rebuilding to do. Moreover, despite Australia’s low ranking (17th of 18 countries), this was still easily Australia’s period of greatest growth in the 20th century. In the last quarter of the century, Australia’s rank improved to be in the middle of the field. So it needs to be stressed that, although Australia’s relative standing has declined since

W

World War II, it has done so while Australia enjoyed much more material enrichment than in any period since 1870. The golden age finished with the stagflation and oil price shock of 1973. The economic times since then have been more turbulent and the rate of growth has been lower. Even so, the latest period has been the second most dynamic. While there are spectacular changes in particular countries’ standing – most notably the dramatic post-war rise of Japan and the later relative decline of New Zealand – the most critical feature of the contemporary era is the shared and continuing growth in income. One stark fact leaps out from Table 3.4: the period from 1889 to 1939 was Australia’s horror half-century. However much commentators may bemoan Australia’s relatively mediocre performance after World War II, it was the previous 50 years in which it performed worst – both in absolute terms and relative to other countries. Australia followed an idiosyncratic path with multiple periods of negative growth. For many countries the 1890s were a time of expansion, but Australia’s standard of living in 1900 was less than it had been in 1889. Again in the period immediately before World War I, when most of the developed world was enjoying a boom, Australia was again in depression. From an economic perspective, World War I was much more devastating than World War II. Although afterwards Australia joined in the general economic recovery, the 1920s stopped roaring in Australia before they did elsewhere. Its economy began contracting in 1925 and was well into depression before the rest of the world joined it after 1929. So unlike the half century after World War II, the half century before it showed few sustained periods of shared economic growth, but rather severe boom-bust cycles and great variations between countries. Even amid this generally unimpressive picture, Australia lagged badly, its average per capita growth rate of 0.2% barely above stagnation.

ECONOMICS

49

Table 3.5 Contemporary economic growth Average per capita GDP growth rates, 1970–2006, % per annum Country

50

1979–1989

1989–1999

2000–2006

Ireland Finland Sweden New Zealand Australia United Kingdom Norway Canada Denmark Japan United States Belgium Austria France Netherlands Germany Switzerland Italy

1971–1973 3.5 5.0 2.0 3.7 2.3 3.9 3.9 4.1 2.9 5.3 3.6 4.7 4.8 4.0 3.0 3.5 2.5 3.2

3.3 1.9 1.5 −0.9 1.5 1.5 4.3 2.6 1.2 2.4 2.0 2.2 3.0 2.3 1.9 2.5 −0.1 3.0

2.7 3.2 1.8 1.4 1.9 2.2 2.3 1.7 1.4 3.1 2.0 2.1 2.0 1.8 1.3 1.9 1.7 2.3

6.1 1.2 1.1 1.0 2.2 1.6 2.7 1.1 1.7 1.4 2.0 1.7 1.8 1.3 2.2 1.3 0.2 1.2

3.6 2.6 2.4 2.2 2.0 2.0 1.6 1.5 1.4 1.4 1.4 1.3 1.2 1.1 1.1 0.9 0.8 0.4

Mean

3.7

2.0

2.0

1.8

1.6


1973–1979

3.3 Contemporary economic performance he most obvious conclusion from Table 3.5 is that the selected economies all became steadily richer between 1970 and 2006, even if they did so at differing rates. While some outstandingly strong and weak performances over the three and a half decades can be seen, 11 of the 18 economies – ranging from Australia and the United Kingdom on 2% to France and the Netherlands on 1.1% – had average growth rates within 0.5 percentage points of the overall average of 1.6% during the 2000s. This is strong evidence of the ‘convergence’ between the developed economies since World War II. The high and growing amount of trade and investment between the developed economies give them a tendency to move through the business cycle together. Even so, the timing of entry and exit from downturns can differ and particular countries are affected by idiosyncratic developments. Examining the figures for the growth in real GDP per capita over a period as long as 35 years should, however, give a good guide to medium-term trends in economic performance. Ireland’s outstanding performance – winning it the title of the Celtic Tiger – was concentrated particularly in the 1990s and early 2000s, but has been above average since 1973. Its possession of a well-educated, Englishspeaking but relatively low-paid workforce has made it an ideal base for non-European corporations seeking a foothold inside the borders of the European Union. Norway’s consistently strong performance is explained by its wealth from North Sea oil and prudent husbanding of that windfall. Japan offers another notable case. It would have ranked top on its performance to the

T

end of the 1980s, but suffered a disastrous decade in the 1990s. The plethora of books saying how the West had to become more like Japan have been replaced by an equally certain set of authors writing of Japan’s peculiar pathologies. The United States’ performance was very close to the mean for the period as a whole and for each sub-period. It is the largest and richest economy, with the highest level of productivity (output per unit of input). This is because it is at the frontier of technological advance. For this very reason, however, it had difficulty maintaining a high rate of productivity improvement throughout most of the period. Other countries, being back from the frontier, find it easier to achieve higher rates of productivity growth and thereby catch up somewhat. The high-taxing welfare states of Sweden and Denmark performed well below average for most of the period, but have done better in the 2000s. New Zealand performed particularly poorly in the 1970s and 1980s but, after extensive deregulation, did better in the 2000s. Switzerland is still a prosperous country, with the fourth highest GDP per capita in Table 3.1. Its low growth rate has been much less traumatic than New Zealand’s, not being accompanied by alarmingly high inflation, unemployment, and trade and budget deficits. During the 1970s, Australia was considerably below the 18-nation mean, during the 1980s just below, but during the 1990s and 2000s considerably above, ranking fifth among the 18. This underlying improved rate of growth in productivity – its best since the 1960s – gave Australia a late burst of speed, which meant that it performed close to the mean for the 30-year period as a whole.

ECONOMICS

51

Table 3.6 Inflation Average annual rise in consumer price index, % Country

1960–1973

1973–1979

1979–1989

1989–1999

Japan Switzerland Sweden Finland United Kingdom Germany Norway Austria France Denmark Belgium Canada Italy Netherlands New Zealand United States Australia Ireland

6.2 4.2 4.7 5.7 5.1 3.3 5.1 4.2 4.6 6.2 3.6 3.3 3.9 4.9 4.8 3.2 3.5 5.9

9.9 4.0 9.8 12.6 15.6 4.6 8.7 6.2 10.7 10.8 8.4 9.2 20.9 7.2 13.8 8.5 12.2 14.9

2.5 3.3 7.9 7.1 7.4 2.9 8.3 3.8 7.3 6.9 4.9 6.5 7.6 2.8 11.8 5.5 8.4 9.2

1.1 2.3 3.5 2.2 3.7 2.5 2.4 2.4 1.9 2.1 2.1 2.2 2.8 2.4 2.1 3.0 2.5 2.3

2000–2007 −0.4 0.9 1.4 1.6 1.6 1.7 1.8 1.9 1.9 2.0 2.1 2.3 2.4 2.5 2.6 2.8 3.2 3.5

Mean

4.6

10.4

6.3

2.4

2.0

Table 3.7 Long-term interest rates Average long-term interest rate % per annum in each period Country Japan Switzerland Germany Belgium Finland France Ireland Netherlands Austria Denmark Italy Sweden United States Canada United Kingdom Norway Australia New Zealand Mean

52


1985–1989

1990–1995

1996–2000

2001–2006

.. 4.4 6.6 8.9 .. 9.7 10.8 6.7 .. .. .. .. 8.8 9.8 10.1 12.6 13.2 15.2

5.1 5.5 7.5 8.4 10.6 8.2 8.8 7.6 7.7 8.7 11.8 10.4 7.2 8.7 9.1 8.7 9.8 8.9

2.1 3.5 5.2 5.4 5.6 5.3 5.7 5.3 5.4 5.8 6.3 6.0 5.9 6.0 6.2 6.0 6.6 6.9

1.4 2.8 4.1 4.2 4.2 4.2 4.2 4.2 4.3 4.3 4.4 4.4 4.5 4.7 4.7 5.0 5.6 6.1

9.7

8.5

5.5

4.3

3.4 Inflation and interest rates able 3.6 charts the chequered history of the developed countries’ experience with inflation over the past 47 years. In the post-war period to 1973, inflation in most countries was manageable, though not negligible. The remainder of the 1970s, however, saw a dramatic acceleration in the rate of price increase, with annual inflation rates reaching double figures in almost half these countries. Though the world prices of many rural and mineral commodities rose strongly in the early 1970s, the 1973 watershed is widely attributed to the first OPEC oil price shock. As well as a sharp jump in petrol prices, this brought about a sudden and massive transfer of wealth from the mainly oil-importing developed economies to the oil-exporting countries. For the developed economies, the shock was thus both inflationary for prices and contractionary for economic activity – a rare and difficult combination for the economic managers to respond to. It was the end of the post-war ‘golden age’ of troublefree economic growth and the commencement of the turbulent era of ‘stagflation’ – the previously unknown combination of a stagnant economy with rapidly rising prices. While the period 1960–1973 saw inflation within a fairly narrow band, the 1973–1979 period saw not only a much higher level of inflation overall but a far greater range. By the 1980s, the continuing struggle to return to low inflation and restore economic stability had achieved some success, though more in some countries than others. By the 1990s, inflation was back under control universally and this continued in the 2000s. Japan’s economy dipped in and out of recession throughout the 1990s, which explains why its average inflation rate was so low in the 1990s and the general level of prices actually fell during the 2000s. Such ‘deflation’ is not to be welcomed because it brings problems by discouraging spending, production and investment. Australia’s inflation rate was well contained during the 1960s, but it shifted to

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being among the worst performers after the advent of stagflation. In contrast to the United States, Japan and most of Europe, Australia’s inflation rate remained above the overall mean in the 1980s. Following the severe recession of the early 1990s, however, its rate fell back into line with the rest of the developed world. Its higher average inflation rate during the 2000s was exaggerated by the introduction of the goods and services tax, but also reflects a resources boom in the middle years of the decade. Interest rates are linked to the inflation rate because lenders require to be compensated for the expected loss in purchasing power of their money while it is in the hands of the borrower, as well as receive a ‘real’ interest rate as a reward for giving up the use of their money during the duration of the loan. According to one version of economic theory, in a world of highly integrated national financial markets, a country’s long-term interest rate should reflect its inflation rate and a uniform global real (after-inflation) interest rate, plus or minus a premium or discount reflecting the country’s peculiar circumstances, if any. For instance, countries with large current account deficits or high levels of foreign debt may have to pay a premium to encourage continued lending from abroad. Table 3.7 offers some rough support for this theory. Making the imperfect comparison of the latest column with the latest column in Table 3.6 shows 13 of the 18 countries’ average real interest rates falling in a narrow band from 1.7 to 2.6%. Ready explanations can be found for those countries – Ireland, Sweden, the United Kingdom, Norway and New Zealand – with real rates falling well outside this band. Note that the similarity of so many countries’ ‘nominal’ (before-inflation) interest rates evident in the latest column of Table 3.7 is explained by eight of the selected countries being members of the Euro currency and monetary union.

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Table 3.8 Exports Exports as a % of GDP, 1970–2005 Average for period is in first three columns and average for individual years is in last two columns 1970– 1973

1974– 1979

1980– 1989

1990

2005

Belgium Ireland Netherlands Austria Denmark Sweden Switzerland Norway Germany Canada Finland New Zealand France Italy United Kingdom Australia Japan United States

53 34 48 30 27 25 30 37 20 22 24 24 16 17 22 14 11 6

56 44 52 32 29 29 32 38 24 24 27 27 19 22 28 15 13 8

68 52 60 37 34 33 36 40 29 27 29 29 21 21 26 15 13 9

69 57 56 38 37 30 36 40 25 26 22 27 21 19 24 16 10 10

87 83 71 53 49 49 46 45 40 39 39 29 26 26 26 18 13 10

Mean

26

29

32

31

42

Country

Table 3.9 Imports Imports as a % of GDP, 1970–2005 First three columns indicate average level for the period; last two indicate for specified years 1970– 1973

1974– 1979

1980– 1989

1990

2005

Belgium Ireland Netherlands Austria Denmark Sweden Switzerland Finland Germany Canada New Zealand United Kingdom Norway France Italy Australia United States Japan

50 41 48 29 29 24 31 25 18 21 24 22 37 16 17 13 6 9

57 55 51 33 32 29 31 28 22 25 31 29 41 20 22 16 9 12

68 55 57 37 33 32 36 28 26 25 30 26 36 23 22 18 10 11

68 52 52 37 33 30 34 24 25 26 27 27 34 23 19 16 11 10

85 68 63 48 44 41 39 35 35 34 30 30 28 27 26 21 15 11

Mean

26

30

32

31

42

Country

Table 3.10 Inward foreign direct investment Foreign direct investment per capita, cumulated for each decade ($US)

Table 3.11 Outward foreign direct investment Per capita direct investment by countries abroad, cumulated for each decade ($US)

Country

Country

1971–1980 1981–1990 1991–2000 1997–2006

Belgium Ireland Sweden Netherlands Denmark Switzerland United Kingdom Finland Canada Norway France Germany Austria United States New Zealand Australia Italy Japan

936 488 108 765 305 .. 719 79 225 752 314 224 193 247 826 769 101 12

2763 531 1033 1860 690 2047 1963 410 1233 986 964 244 426 1474 955 2115 433 125

22135 13555 16947 11825 9503 7657 6958 6289 5136 7050 4055 3605 3637 4020 5359 3438 810 731

113911 21544 21373 18321 16064 13848 13286 10294 8831 8436 7885 5736 5587 5523 4635 4427 2219 415

Mean

415

1125

7373

15685

Periods for columns 3 and 4 overlap slightly. In final column, Belgium is combined with Luxembourg.

54


Belgium Switzerland Netherlands Sweden Italy United Kingdom Denmark Norway France Finland Canada Austria Germany United States Ireland Japan Australia New Zealand Mean

1971–1980 1981–1990 1991–2000 1997–2006 326 .. 1967 553 64 978 207 264 259 127 461 77 452 590 .. 155 171 119

2086 4882 3438 5659 487 3066 1302 1488 1788 2297 1564 522 1263 700 .. 2219 1482 1168

19412 23832 18043 14718 1371 13537 8358 7953 8369 12592 5181 2503 5484 3230 .. 3672 1549 892

113240 42888 31434 23256 21786 17420 14956 14493 14325 13725 10009 6316 6184 5330 3406 2591 2263 −244

423

2083

8865

19077

3.5 International trade and investment ables 3.8 and 3.9 are a powerful demonstration of globalisation. Their outstanding feature is the way both exports and imports have grown steadily and strongly over the past 35 years for virtually all the selected countries. This has been brought about partly by falling transport costs, but mainly by the successive reductions in tariff barriers to trade achieved by many rounds of multilateral negotiations under the GATT (the predecessor to the WTO). In these tables each country’s exports and imports are expressed as a proportion of that country’s national income (GDP) to facilitate comparisons between countries and also over time for a particular country (because this takes account of inflation and the real growth in the country’s income). It can be seen that the economies with the highest ratios of exports and imports to national income are the small European countries, many of them with contiguous borders and most of them members of the EU. The EU’s expansion and efforts to increase the economic integration of its members is another factor explaining the growth in trade over the period. The United States’ and Japan’s low ratios of exports and imports occur not because of high barriers to trade but because the sheer size of their economies causes them to be more selfsufficient. Even the United States, however, has become more open to trade over the period. Australia’s relatively low trade ratios are explained by its geographic isolation and, until the major tariff cuts of the late 1980s and early 1990s, its highly protected manufacturing sector. Tables 3.10 and 3.11 chart another important dimension of globalisation: the rise and rise of the transnational corporation – the company whose activities extend over a number of countries. The term ‘foreign direct investment’ (FDI) refers to foreigners’ investment in a country’s business corporations where the investment in the shares of particular

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companies is great enough to give the foreigners a significant influence over the company’s management. FDI may involve the foreigners establishing a new business, their purchase of an existing local business or the merger of their corporation with a local one. So FDI is to be distinguished from other, more volatile forms of foreign capital inflow to a country for the purchase of small parcels of shares or lending by foreign banks. Table 3.10 shows the total amounts of FDI flowing into the selected countries in each of the past four decades. Note, however, that these amounts have been given a human dimension by dividing them by each country’s population to show the value of FDI inflows per person. It can be seen that, judged in this way, inward FDI plays the largest role in relatively small European economies. It plays a smaller role in the bigger, more populous economies, and also in the small but far-flung economies of New Zealand and Australia. However, the point that leaps out from the table is the remarkable expansion in FDI inflows over the past four decades. But this is the right moment to turn to Table 3.11, which shows each country’s outflows of FDI to establish or buy businesses in other countries (again expressed on a per-person basis). It can be seen that the expansion in these outflows over the period has been even greater than that for inflows. So this table accounts for the former table – and vice versa. While almost all countries have been experiencing increased foreign ownership of their businesses, almost all countries’ businesses have been expanding their operations by buying businesses abroad. The result is that a growing proportion of the developed world’s big businesses now operate across a number of countries. It can be seen that, while Australia’s inflow of FDI more than quintupled over the period, its outflow grew by a factor of 13, so that, in the 2000s, every $2 of inflow was offset by $1 of outflow.

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Table 3.12 Exchange rates National currency units to $US Country

1970

1980

1990

1999

Australia Austria Belgium Canada Denmark Finland France Germany Ireland Italy Japan Netherlands New Zealand Norway Sweden Switzerland United Kingdom Euro

0.89 26.0 50.0 1.05 7.5 4.20 5.55 3.66 0.42 625 360 3.62 0.89 7.14 5.17 4.37 0.42 ..

0.88 12.9 29.2 1.17 5.6 3.73 4.23 1.82 0.49 856 227 1.99 1.03 4.94 4.23 1.68 0.43 ..

1.28 11.3 33.4 1.17 6.2 3.82 5.45 1.62 0.60 1198 145 1.82 1.68 6.26 5.92 1.39 0.56 ..

1.55 12.9 37.9 1.49 7.0 5.58 6.16 1.84 0.74 1817 114 2.07 1.89 7.80 8.26 1.50 0.62 1.08

2007 1.19 .. .. 1.07 5.4 .. .. .. .. 118 .. 1.36 5.85 6.75 1.20 0.50 0.73

Table 3.13 Big Mac Index Cost of buying a Big Mac hamburger in each country, converted to $US and compared to US price, July 2007, with comparison of results for 2002

Country Japan Australia United States Canada United Kingdom Euro Area Sweden Denmark Switzerland New Zealand

56


Price of Big Mac in $US

Implied relative valuation of currency July 2007

Implied relative value of currency April 2002

2.29 2.95 3.41 3.68 4.01 4.17 4.86 5.08 5.20 5.89

−33 −14 0 8 18 22 42 49 53 73

−19 −35 0 −15 16 −5 +1 +19 +53 −29

3.6 Exchange rates able 3.12 shows how each country’s currency changed in value relative to the US dollar over the past 37 years. So, for example, whereas one US dollar was worth 360 yen in 1970, by 2007 its value had fallen to 118 yen, meaning that the yen’s value had appreciated (risen) over the period by a factor of more than three. Similarly, whereas $US1 was worth only 89 Australian cents in 1970, by 2007 its value had risen to $A1.55, meaning that the Australian dollar had depreciated in relation to it. The missing values in the last column of the table occur because these eight countries adopted the Euro in 1999. It can be seen that, for the remaining nine currencies, four rose in value against the US dollar over the period, while four fell and one – the Canadian dollar – was little changed. The single factor that should do most to explain this realignment is the selected countries’ inflation rates relative to the United States’ inflation rate. Economic theory suggests that if a country’s inflation rate is consistently higher than another country’s, its exchange rate against the second country’s currency should fall over time so as to restore purchasing power parity between the two economies. In practice, of course, various other factors will also be at work. Table 3.12 has considerable potential to mislead (but it is not easy to report exchange rate movements in ways that do not). It should not be thought that the value of the US dollar stayed constant over the past 30 years while all other currencies changed around it. Clearly, the US dollar rose in value against some currencies, but fell against others. Nor is the table meant to imply that a country’s exchange rate with the US dollar is the only one that matters. A country has separate exchange rates with the currencies of all the countries with which it trades and the importance of those other exchange rates is determined by each trading partner’s share of the country’s trade.

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Finally, it should not be assumed that it is good to have an appreciating currency and bad to have one that’s depreciating. Depreciation and appreciation each have (opposing) sets of both advantages and disadvantages. Which direction happens to be desirable, on balance, is determined by a country’s circumstances at the time and, even then, will be a matter of debate. The Economist magazine’s famous Big Mac Index (Table 3.13) is a light-hearted but enlightening exercise. We live in an era of floating exchange rates in which relativities are changing continuously. Speculative trading plays a large part in currency markets to the point where, at any particular time, it is not uncommon for markets to have ‘overshot’ and caused currencies to be significantly over- or undervalued. But overvalued relative to what – and to what precise extent? Economists use varying models to attempt to answer these questions – but never with any certainty. The theory of purchasing power parity states that exchange rates should adjust to ensure that the prices of internationally traded commodities remain the same throughout the world. The Economist has applied this theory to just one commodity, the Big Mac hamburger, which, though not traded between countries, is produced by the McDonalds company in many countries to the same recipe. If the PPP theory held perfectly, the nationalcurrency retail price of each country’s Big Mac should, after conversion to US dollars, be identical to the hamburger’s price in the United States ($US3.41 in July 2007). Hence, the extent to which the hamburger’s actual price in other countries exceeds or falls short of the home US price is a quick but of course imperfect measure of the extent to which those countries’ currencies are over- or undervalued relative to the US dollar. The comparison with April 2002 suggests that whether a currency is over- or undervalued varies unpredictably over time.

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Table 3.14 Employment in agriculture Percentage of labour force employed in agriculture

Table 3.15 Agriculture’s share of the economy Agriculture’s % share of total value added (GDP)

1960– 1973

1975

1985

1995

2006

1996

2006

New Zealand Ireland Austria Finland Italy Japan Switzerland Australia France Norway Denmark Netherlands Canada United States Germany Belgium Sweden United Kingdom

12.7 30.8 17.1 27.0 24.6 21.7 10.3 9.2 16.7 16.5 13.8 7.4 12.5 5.9 10.4 6.1 10.7 3.8

10.7 22.4 12.5 14.9 16.7 12.7 7.6 6.8 10.3 9.4 9.8 5.7 6.1 4.1 6.8 3.8 6.4 2.8

11.1 16.0 9.0 11.5 11.2 8.8 6.1 6.2 7.5 7.4 6.7 4.9 5.0 3.1 4.6 3.1 4.8 2.3

9.7 11.7 7.5 8.1 6.7 5.7 4.4 5.0 4.6 5.2 4.4 3.7 4.1 2.9 3.1 2.4 3.1 2.1

7.1 5.7 5.5 4.7 4.3 4.3 3.7 3.5 3.4 3.3 3.0 3.0 2.6 2.5 2.3 2.0 2.0 1.3

New Zealand Finland Australia Canada Netherlands France Italy Austria Ireland Denmark Norway Japan Sweden Switzerland United States Belgium Germany United Kingdom

7.2 4.0 3.7 3.0 3.3 3.3 3.3 2.4 6.4 3.4 2.6 1.9 2.6 1.9 1.8 1.6 1.3 1.7

6.5 2.5 2.3 2.2 2.2 2.1 2.1 1.7 1.7 1.6 1.5 1.4 1.4 1.2 1.1 0.9 0.9 0.9

Mean

14.3

9.4

7.2

5.2

3.6

Mean

3.1

1.9

Country

Table 3.16 Trade in agriculture Agriculture’s % share of total exports or imports of goods and services Exports 1986–1988

Exports 2003

Imports 1986–1988

Imports 2003

New Zealand Australia Netherlands Denmark France Belgium United States Ireland Italy Austria Canada United Kingdom Germany Sweden Switzerland Finland Norway Japan

60 35 24 27 17 11 13 27 7 4 8 8 5 2 3 4 2 0

48 21 19 18 12 9 9 8 7 6 6 5 4 3 3 2 1 0

7 5 15 11 11 12 6 13 16 7 6 12 13 7 8 6 6 14

8 5 12 11 8 9 4 8 9 7 6 9 8 7 6 6 7 10

Mean

14

10

10

8

Country

58


Country

Table 3.17 Support for agriculture Public financial support for agricultural producers as a % of gross farm receipts Country

1986

2000

2005

New Zealand Australia United States Canada European Union Japan Norway Switzerland

20 12 24 38 43 65 72 78

1 5 24 20 34 60 67 72

3 5 16 21 32 56 64 68

Mean

44

35

33

3.7 Agriculture casual glance at Table 3.14 suggests employment in agriculture has fallen dramatically in all the selected economies. Similarly, Table 3.15 seems to say that agricultural production (‘value added’) has fallen significantly in all the countries in just the past decade. But casual glances can be misleading. Both tables show the rural sector’s share of the total economy – represented either by total employment, or total value added, otherwise known as GDP – and a decline in a sector’s absolute size is just one possible explanation for a decline in its share. By far the most significant reason for the decline in agriculture’s share is that it has not grown as fast as other sectors – notably, the services sector. There is a limit to how much any person wants to eat so that, while you would expect agricultural production to grow in line with the population, ever-rising material standards of living in the selected countries have not led to much growth in agricultural production compared with production of manufactures and, particularly, services. Were the figures for agriculture’s share of value added to go back a lot further it would be apparent that the sector’s share of total employment has fallen at a faster rate than its share of total production. This is explained by the sector’s longstanding pursuit of laboursaving technological advance, which has made a labour-intensive industry significantly less so over the decades – although its share of total employment remains higher than its share of total production. We are left with the likelihood that, while over the years employment in agriculture has declined in absolute terms in all the selected economies, absolute levels of production have not and, indeed, would have risen somewhat in most countries. The next factor is international trade in agriculture. Note that, again, Table 3.16 shows agricultural goods’ changing shares of total exports or imports, not their changing absolute levels. The marked declines in agriculture’s share of total exports in Ireland, Australia, New Zealand and Demark are more

A

likely to be explained by faster growth in the exports of other sectors than by dramatic falls in the quantity of rural exports – although, of course, this sector may be heavily affected by droughts and bumper harvests in particular years. Economic theory would lead you to expect that those countries with a comparative advantage in agricultural production would export a lot of that production, while not needing to import many farm products. Table 3.16 only partly confirms this expectation. New Zealand and Australia are the countries where farm products account for high proportions of total exports and only small proportions of total imports while, at the other end of the scale, Japan, Norway and Switzerland have negligible farm exports and, particularly in Japan’s case, high imports. But the reasonably economically efficient agricultureproducing countries of the United States and Canada do not seem to be as active in export as various countries of the European Union. The explanation for this lies in Table 3.17, which shows the degree of protection afforded to the agricultural sectors of the selected countries, measured as government financial support as a proportion of gross farm receipts. Financial support would include the value of protection against imports as well as direct government production subsidies. The table can be taken as showing the degree of economic efficiency of the countries’ rural sectors, with New Zealand and Australia being the most efficient (and thus requiring negligible levels of support) and Norway and Switzerland the least efficient. All countries of the European Union are covered by its highly protectionist Common Agricultural Policy. Table 3.17 shows a marked decline in public financial support, particularly between 1986 and 2000. This is explained by domestic reform in the cases of Australia and New Zealand, but mainly by the reduction in subsidies agreed to in the World Trade Organization’s Uruguay round of multilateral trade negotiations in 1993.

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Table 3.18 Employment in industry Percentage of the labour force employed in industry Country

1975

1985

1995

2006

Italy Germany Austria Japan Ireland Finland Belgium Denmark Switzerland Canada France New Zealand Sweden United Kingdom United States Australia Norway Netherlands

39 45 41 36 32 36 40 32 42 29 39 36 37 40 31 34 35 35

34 41 38 35 29 32 30 28 36 26 32 32 30 35 28 27 27 28

34 36 32 34 28 27 26 27 29 22 26 25 26 27 24 23 23 23

31 30 28 28 27 26 25 24 24 22 22 22 22 22 22 21 21 19

Mean

37

32

27

24

Table 3.19 Exports of high-technology manufacturing High-technology exports as a % of all manufactured exports Country

1990

2005

Ireland United States Netherlands United Kingdom Finland Japan Switzerland Denmark France Norway Sweden Germany Canada New Zealand Australia Austria Belgium Italy

41 34 16 24 8 24 12 15 16 12 13 11 14 10 12 8 5 8

48 32 30 28 25 23 22 22 20 17 17 17 14 14 13 13 9 8

Mean

15

22

Data on Ireland is for 2000.

Table 3.20 Industry and manufacturing’s share of the economy Percentage share of total value added (GDP) Country

60

Industry 1996

Industry 2006

Manufacturing 1996

Manufacturing 2006

Finland Ireland Germany Japan Austria Sweden Switzerland Italy Belgium Canada New Zealand Denmark Netherlands United Kingdom France United States Australia Norway

32.0 36.9 31.2 33.0 30.8 29.3 29.1 29.7 28.0 30.9 25.8 25.4 26.9 30.6 24.1 25.9 27.6 36.6

32.4 34.9 29.4 29.1 30.2 28.5 27.7 26.8 24.2 31.7 24.0 26.0 24.1 22.9 20.7 22.4 28.7 45.0

24.3 29.3 22.2 22.4 19.5 21.7 20.0 21.8 20.0 18.0 17.3 16.5 16.8 20.5 16.0 16.2 14.2 12.3

23.7 23.3 22.7 20.7 20.1 20.0 19.9 18.3 16.9 16.2 15.2 14.2 13.3 12.6 12.6 12.2 11.2 9.7

Mean

29.7

28.3

19.4

16.8


3.8 Industry and manufacturing he vaguely named ‘industry’ sector of the economy includes all those parts of the economy than cannot be categorised as either agriculture or services. Manufacturing lies at the heart of the industry sector – accounting for more than half of it – but it also includes mining, utilities (electricity, gas and water) and the construction sector. Table 3.18 shows a steady decline in the share of total employment accounted for in the industry sector in all the selected countries. As ever, this decline in share does not necessarily imply a decline in the absolute numbers of workers employed. The primary explanation for the sector’s declining share is the rapid growth in employment in the (much larger) services sector. However, Table 3.20, which switches from examining the sector’s share of total employment to looking at its share of total value added (GDP), sheds light on the story. It reveals that, whereas the industry sector’s share of total employment has declined over the past decade in all the selected countries, its share of total value added has declined in only 13 of the 18 countries. Furthermore, the mean decline in employment during the decade exceeded the mean decline in value added. This suggests that some part of the sector’s falling share of total employment is explained by greater use of labour-saving capital equipment. Table 3.20 also reveals that the manufacturing sub-sector’s share of total value added fell in all but two of the countries over the decade, with manufacturing’s mean share of total production falling by more than the whole industry sector’s mean share. This suggests that, for most countries, the lion’s share of the whole sector’s declining proportion of total employment is explained by manufacturing’s declining share. Indeed, over the past 30 years absolute levels of employment in manufacturing have fallen in many countries, including Australia. Thus in its own imperfect way, Table 3.18 charts the course of ‘deindustrialisation’ in the developed economies over the past 30 years. It is important to understand that the industrial structure of the developed economies – the relative shares of the agricultural,

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manufacturing and services sectors – changed continuously over the previous century and will continue changing in this century, driven primarily by technological advance and growing affluence. At the start of the last century, agriculture would have accounted for a large share of an economy’s total employment and valued added. But ever-more efficient laboursaving technology released workers from agriculture to seek employment elsewhere in the economy without any loss of rural production. Then we saw the expansion of employment and value added in manufacturing, fed by the continuous invention of mechanical, electric and electronic goods, starting with the motor car. But automation, computerisation and other labour-saving advances eventually released workers from manufacturing without any decline in production. This was deindustrialisation, with almost all the net growth in employment over the past 30 years occurring in the services sector in all the selected countries. Australia stands among the five countries experiencing a rise in the share of value added produced by the industry sector over the past decade, notwithstanding a decline in the share accounted for by the manufacturing subsector. This is explained by growth in the mining and construction sub-sectors. Table 3.19 shows the growing share of high-technology goods in the manufactured exports of almost all the selected economies. Note that the proportion can rise either because of the rapid growth of high-tech exports or because of the weak growth of lower tech exports. Australia’s proportion is relatively low and increased little over the period. Manufacturing – at whatever level of sophistication – is not part of Australia’s comparative advantage, with the result that it is a net importer of high-tech goods. It doesn’t always follow that high-tech manufactures are highly profitable. Note, too, that notwithstanding Ireland’s higher share of hightech manufactured exports, it is clearly not a more technologically advanced country than the United States.

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Table 3.21 Employment in services Percentage of labour force employed in services sector

Table 3.22 Services’ share of the economy Services’ % share of total value added (GDP)

1960– 1973

1975

1985

1995

2006

Country

1996

2006

Netherlands United Kingdom Norway Sweden United States Australia Canada France Belgium Denmark Switzerland New Zealand Finland Germany Japan Ireland Austria Italy

53 51 47 49 59 54 58 44 50 49 43 49 39 42 45 41 42 38

59 57 56 57 65 60 65 51 57 59 50 54 49 48 52 46 47 44

67 63 65 65 69 67 70 61 67 65 58 57 56 54 56 55 53 55

74 71 71 71 73 72 74 69 71 68 67 65 65 61 61 60 60 59

78 77 76 76 76 75 75 74 73 73 73 71 70 68 68 67 66 65

France United States United Kingdom Belgium Netherlands Denmark Switzerland Italy Sweden Germany Japan New Zealand Australia Austria Canada Finland Ireland Norway

73.1 72.2 67.7 70.4 69.8 71.2 69.1 67.0 68.1 67.4 65.2 67.0 68.8 66.8 66.1 64.0 56.7 60.7

77.3 76.5 76.2 74.9 73.7 72.5 71.2 71.1 70.1 69.8 69.5 69.5 69.0 68.2 66.1 65.1 63.4 53.5

Mean

47

54

61

67

72

Mean

67.3

69.8

Country

Table 3.23 Employment within the services sector Percentage of labour force working within each sub-sector, 2005 Retail and wholesale trade, restaurants and hotels

Transport, storage and communication

Finace and insurance

Property and business services

Public administration

Education health and personal services

Sweden Norway Denmark Japan New Zealand Finland United States United Kingdom France Belgium Netherlands Ireland Canada Australia Germany Austria Switzerland Italy

15 16 19 18 26 16 21 24 17 17 19 20 24 25 20 22 21 20

7 9 7 6 6 7 5 6 6 7 6 6 7 6 5 7 7 6

2 2 3 3 3 2 5 4 3 3 4 5 5 4 3 3 6 2

12 10 11 2 12 10 15 15 15 16 16 9 12 12 13 10 10 11

6 7 6 3 3 7 8 6 9 10 7 5 5 6 7 7 4 6

33 29 29 28 26 26 25 24 23 23 22 22 22 22 21 20 19 17

Mean Mean 1995

20 20

6 7

3 4

12 8

6 7

24 22

Country

Figures sum across to services sector’s share of the labour force, 2005.

62


3.9 Services or many decades as we have watched people moving from the country to the city and workers being shed from manufacturing as computerisation and tariff reform took their toll, people have wondered where all the new jobs would come from. Table 3.21 provides the answer: from the ever-expanding services sector. The services sector’s share of total employment has grown strongly over at least the past 40 years in all the selected economies, with its overall mean share rising from less than half to almost three-quarters of total employment. Employment in the services sector has grown strongly in absolute terms in all countries, accounting for virtually all the net growth in total employment. The table serves as a reminder that the changing industrial structure has followed remarkably similar patterns in all the developed countries. The main difference has been merely in the timing of the transitions in each country. It is noteworthy that, whereas in the mid-1960s the services sector’s share of total employment in the selected countries ranged from less than 40% to almost 60%, by today the range has narrowed from Italy’s 65% to the Netherlands’ 78%. Table 3.22 shows that the services sector’s share of total employment is reflected in its share of total value added (GDP), thus giving the lie to the old suspicion that, unlike industries that produce things that can be touched, the services sector is somehow ‘unproductive’. The purpose of economic production is to satisfy the needs of consumers and thereby generate income for those people supplying labour and capital to the production process. Clearly, the production of services fulfils that requirement just as readily as does the production of tins of baked beans. Comparison of Tables 3.21 and 3.22 shows that the services sector’s contribution to total employment is a little greater than its contribution to total value added. This is the sign that the services sector is, unsurprisingly, labourintensive – which should be a comfort to those who wonder ‘where the jobs will come from’.

F

There is a limit to how much we wish to eat and, pending the invention of ever-more enticing electronic gadgets, even a limit to how many physical goods we wish to buy, but no limit to the myriad services others could perform for us. Another old fear about the inexorable growth of the services sector is that service jobs must surely involve servility. While it is true that service jobs include serving behind counters, waiting on tables and cleaning floors, such a fear reflects a lack of imagination. Table 3.23, which reveals the main component industries of the services sector, serves as an antidote. Apply a little imagination to the table and you see that service jobs start with the prime minister, professors, surgeons, chief executives of telecom companies, money market traders, pop stars and professional athletes, and move on through doctors, nurses and teachers. Retail and wholesale trade constitutes the largest part of the services sector. Other large parts are the hospitality industry, education, health, transport and communications, and the public service. The fastest growing segment, however – which now exceeds the size of the manufacturing sector in Australia and some other countries – is ‘property and business services’, including ever-rising numbers of lawyers, accountants and consultants. Advances in technology have increasingly made services tradeable across national borders. By greatly reducing the cost of travel, the advent of the jumbo jet not only precipitated an explosion in international travel, but also made it possible for foreign students and patients to travel abroad for education or health care, as well as for engineers, architects and many other professions to go overseas to sell their services as consultants. Advances in telecommunications have also opened up opportunities. Nevertheless while trade in services is growing substantially, it is still small compared with trade in goods, but now approaching 10% of GDP in the selected countries.

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Table 3.24 External trade balance External trade balance as a % of GDP, average for each period Country

1970–1973

1974–1979

1980–1989

1990–1999

2000–2007

0.6 −7.4 −1.1 1.4 0.2 −1.2 −1.5 0.6 1.6 2.3 1.9 1.6 −0.1 0.1 0.2 0.9 −0.1 0.1

−2.7 −11.3 −0.9 −0.5 1.0 1.4 −2.8 −0.8 −0.3 −0.8 2.2 0.4 −0.2 −0.7 −4.0 −0.5 −0.9 −0.4

4.1 −2.5 0.4 1.5 3.0 −0.2 1.0 0.2 1.8 0.3 2.6 1.9 −0.5 −1.4 −1.0 −2.2 −0.2 −1.8

6.3 9.9 5.0 4.6 5.1 3.6 4.8 −0.2 1.3 3.5 0.9 1.6 2.5 1.3 1.6 −0.9 −1.0 −1.2

15.7 12.6 8.1 7.2 6.8 6.7 4.9 4.1 4.1 3.8 3.8 1.4 0.5 0.1 0.0 −1.4 −3.0 −4.8

0.0

−1.2

0.4

2.7

3.9

Norway Ireland Finland Sweden Netherlands Switzerland Denmark Austria Canada Belgium Germany Japan Italy France New Zealand Australia United Kingdom United States Mean

Table 3.25 Current account balance Current account balance as a % of GDP, average for each period Country

1970–1973

1974–1979

1980–1989

1990–1999

2000–2007

−1.2 0.1 −1.9 1.3 1.5 1.4 2.4 5.5 −2.5 0.1 0.2 −0.3 0.4 6.1 0.3 0.0 −0.6 1.2

−4.8 0.4 −2.9 −1.6 1.5 0.3 −0.8 8.0 −4.0 −1.9 −1.3 −0.2 −0.2 12.4 −1.2 −2.6 −0.8 −5.9

0.6 4.0 −2.0 −2.0 3.0 2.1 −1.1 15.6 −3.6 −1.0 −0.3 −2.3 −1.0 9.6 −0.3 −4.9 −2.0 −5.1

3.3 7.2 1.1 0.3 5.1 2.3 3.3 2.1 1.1 −1.2 −1.4 0.5 0.8 2.6 −0.9 −4.2 −1.7 −3.0

14.5 12.3 7.3 5.9 5.5 3.4 3.3 2.7 2.5 2.0 1.0 0.3 −1.3 −1.8 −2.2 −4.8 −5.1 −6.0

0.8

−0.3

0.5

1.0

2.2

Norway Switzerland Finland Sweden Netherlands Japan Belgium Germany Denmark Canada Austria France Italy Ireland United Kingdom Australia United States New Zealand Mean

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3.10 Trade and current account balances ables 3.8 and 3.9 in an earlier section showed how markedly exports and imports have been growing in virtually all the selected countries and over many years. In a simple world, a country’s exports and imports would be equal, thus paying for each other. In reality, this has never been the case, although it was a lot closer to being true in the 1960s and 1970s, when the global regime of fixed exchange rates and barriers to the transfer of funds between countries greatly limited the ability of countries to sustain large trade deficits or surpluses. It is thus a feature of the present world of floating exchange rates and integrated national financial markets that it has become possible for countries to run large surpluses or deficits for protracted periods. Many people find these imbalances worrying – though they tend to worry more about big deficits than big surpluses – but, in principle, imbalances need not be of concern provided they reflect saving and investment opportunities. When some countries perpetually save more than they can profitably invest at home, while others have more profitable investment opportunities at home than they can finance with their own saving, it benefits both sides for the former countries to run sustained surpluses and the latter to run sustained deficits. The counterpart to these imbalances will be large flows of financial capital from the surplus countries to the deficit countries. This greater flexibility – which permits capital to seek its most profitable use on a global rather than national scale – is portrayed as one of the benefits of globalisation. Only where countries are effectively borrowing to finance consumption rather than investment should there be cause for concern. Table 3.24 shows trade deficits and surpluses for the selected countries, expressed as proportions of each country’s GDP to facilitate comparisons between countries and over time. Ignoring the extreme case of Ireland in

T

the earlier periods, it can be seen how the size of deficits and surpluses was at first very small, but became progressively larger as globalisation continued. Note that, as a matter of arithmetic, the amount of all the trade deficits in the world must be exactly offset by trade surpluses. Note, too, that the 18 selected countries constitute only some of those engaged in international trade. And whereas in the early part of the period most of their trade was with each other, their trade with the developing countries of Asia and elsewhere grew as globalisation progressed. Finally, note that, the US economy being so much bigger than the other countries’, its average deficit of 4.8% of its GDP in the 2000s would have been big enough in absolute terms to account for many of the surpluses being run by so many of the other, much smaller selected countries. Table 3.25 shows each country’s current account balance, which is its balance of trade plus its net payments or receipts of interest on borrowings and dividends on equity investments. Thus a country that has borrowed heavily from the rest of the world and hosted much foreign investment in its businesses is likely to run a current account deficit, whereas a country that has lent to the rest of the world and invested in other countries’ businesses is likely to run a current account surplus. This explains why, looking across the columns for each country, trends in one direction or the other tend to be self-reinforcing. It is interesting though puzzling to note the English-speaking economies concentrated at the bottom, large-deficit end of the table. Despite the aberration in the early 1970s, Australia, being a ‘capital-importing country’, has almost always run a current account deficit, although since the early 1980s this has been roughly double its average in the post-war period. Australia’s deficit is heavily influenced by its business cycle, tending to blow out during booms and fall during downturns.

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Table 3.26 Household saving As % of household disposable income Country

Table 3.27 Household debt As % of household disposable income

1990–1995

1996–2000

2001–2007

France Belgium Germany Italy Sweden Switzerland Austria Netherlands Norway United Kingdom Japan Canada Denmark United States Finland Australia

11.4 15.5 12.3 21.8 8.3 10.7 11.1 15.4 4.7 10.0 13.6 11.7 1.3 6.2 5.5 6.2

12.2 16.2 9.9 13.6 5.3 10.9 8.3 10.8 4.1 7.3 10.2 5.1 −1.2 3.3 0.4 3.5

12.7 12.1 10.3 9.7 9.6 9.5 8.9 7.5 5.5 4.8 3.9 2.9 2.0 1.4 −0.5 −0.9

Mean

10.3

7.5

6.2

Country

1982

1992

2002

2007

Italy France Germany Canada Japan Sweden United States Australia United Kingdom New Zealand Norway Netherlands Denmark

8 61 – 55 84 – 69 38 66 – 101 82 –

31 78 86 83 127 86 90 53 99 69 133 93 –

54 80 112 102 134 94 118 119 121 116 144 188 240

69 92 105 131 131 135 147 159 161 162 183 261 288

63

86

125

156

Mean

No data on Austria, Denmark, Finland, Switzerland.

No data on Ireland or New Zealand.

Table 3.28 Gross national saving Percentage of GDP

66

Country

1995

2000

2005

Norway Switzerland Japan Netherlands Finland Denmark Belgium Austria Canada Sweden Ireland Germany Australia Italy France New Zealand United Kingdom United States

25.9 29.9 29.5 27.2 21.7 20.4 25.4 20.8 18.3 20.9 20.4 21.0 18.7 22.0 19.1 17.9 16.2 15.5

35.4 35.0 27.5 28.4 28.5 22.6 26.0 22.4 23.6 22.8 24.4 20.2 19.7 20.6 21.6 17.1 15.4 17.7

37.4 36.1 26.4 26.1 25.5 24.4 23.9 23.8 23.6 23.4 22.7 21.8 21.0 19.4 18.6 15.1 15.1 13.5

Mean

21.7

23.8

23.2


3.11 Saving and borrowing conomists define saving as that part of an entity’s income which is not spent on consumption. So, from the viewpoint of the individual, saving is necessary to permit additional consumption in the future. From an economywide viewpoint, however, saving is necessary to provide the funds needed for investment spending on new housing, business plant and public infrastructure. Table 3.26 shows the average amounts households saved in particular periods, expressed as a proportion of their household disposable income. A general picture of declining rates of saving can be observed over the past decade and a half. The decline is not easily explained, although some have speculated that the protections of the welfare state have reduced people’s inclination to make precautionary savings to cover possible future adverse events. Although the secular decline is clear, it is not even. Australia’s saving rate fell heavily over the period, although four countries ended the period with slightly higher saving rates. Historically, economists expected that fluctuations over time could partly be explained by the saving rate’s tendency to move with the business cycle. Because households prefer to smooth their consumption spending over time, the expected pattern was for saving rates to rise during booms, but fall during recessions. However, in more recent times a different pattern has been observed. During booms, when the prices of assets such as shares and housing are rising sharply, people tend to borrow to buy them, as well as viewing the gains in the capital value of their assets as a reason for reducing their saving from current income. In downturns this pattern is reversed, with people responding to the asset-price bust – and thus, their sudden loss of wealth – by tightening their belts and increasing their saving. Table 3.28 shows the saving rate from an economy-wide perspective, adding to the saving of the household sector the saving by the two other parts of the domestic economy: the corporate sector and the public sector. Here, saving is shown as a proportion of GDP rather

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than household disposable income. ‘Gross’ saving means no allowance has been made for the year’s depreciation of physical assets. Corporations save when they retain part of their after-tax income rather than paying it all out in dividends. Governments save when they spend less than all their revenue on recurrent purposes. It can be seen that, overall, rates of national saving have been reasonably stable over the past decade. The English-speaking countries are mainly in the bottom half of the league. Australia’s saving has always been below average; although it is the United States’ persistently low saving that is most noteworthy from a global perspective. It should not surprise that the ranking of countries in Table 3.28 correlates reasonably well with the ranking in Table 3.25, showing current account balances. Countries with high rates of national saving are more likely to run current account surpluses, whereas those with low rates of national saving are more likely to run deficits. Borrowing that permits households’ consumption to exceed their income is negative saving (dissaving), whereas any repayment of principal constitutes saving. Table 3.27 shows the often quoted figures for the growth in households’ outstanding debt, expressed as a proportion of annual household disposable income. This almost universally strong growth helps account for the decline in household saving. Note, however, that the great majority of household debt has been incurred to purchase homes rather than finance consumption. Much of the alarm over household debt levels results from an inappropriate comparison. It is not unusual for home buyers to borrow sums well in excess of their annual income. It makes more sense to compare households’ debt levels with the value of their assets (including their homes) and to compare their interest and principal repayments with their disposable incomes. The results from such comparisons are less dramatic. High levels of household indebtedness do indicate a vulnerability to higher interest rates or higher unemployment, however.

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Table 3.29 Labour productivity Average annual % increase in output per worker in each period Country

1980–1990

1991–1995

1996–2000

2001–2007

Ireland Finland Sweden United States United Kingdom Austria Japan Norway Denmark Australia Belgium France Germany Netherlands Switzerland Canada New Zealand Italy

3.6 2.5 1.5 1.4 1.9 2.0 2.7 1.9 1.6 0.9 1.8 2.2 1.3 1.1 0.3 1.0 1.5 1.8

2.6 3.1 2.9 1.2 2.5 2.0 0.8 3.2 2.5 1.8 1.6 1.4 2.2 1.0 0.1 1.4 0.9 2.0

3.8 2.5 2.5 2.0 1.9 1.9 1.0 1.9 1.8 2.5 1.6 1.4 1.2 1.5 1.4 2.0 1.5 0.9

2.2 1.9 1.9 1.8 1.7 1.6 1.6 1.5 1.1 1.0 1.0 1.0 1.0 1.0 0.8 0.7 0.7 −0.3

Mean

1.7

1.8

1.9

1.2

Table 3.30 Multi-factor productivity Average annual % increase in multi-factor productivity in each period Country

68

1980–1990

1991–1995

1996–2000

2001–2004

Ireland Sweden United States Finland Japan United Kingdom Australia Belgium France New Zealand Germany Netherlands Austria Canada Denmark Switzerland Italy Norway

4.2 1.0 1.1 2.4 2.1 2.3 0.4 1.8 1.9 0.1 1.5 2.3 2.1 0.8 1.3 .. 1.3 0.8

3.0 0.9 0.7 1.4 1.0 1.4 1.5 1.6 1.1 0.8 1.4 1.7 .. 0.6 1.8 −0.1 1.2 ..

5.4 1.5 1.3 2.6 0.8 1.3 1.8 1.3 1.5 0.8 1.3 0.8 1.6 1.5 0.4 0.8 0.3 1.0

2.8 2.0 1.8 1.7 1.5 1.4 1.3 0.8 0.8 0.7 0.6 0.4 0.3 0.2 0.1 0.1 −0.7 ..

Mean

1.6

1.3

1.5

0.9


3.12 Productivity f you want to summarise in two words the reason the developed countries got steadily richer over the past quarter century (and, indeed, for the past two centuries), they are ‘productivity improvement’. Here we take a country’s wealth to be its annual production of goods and services. It can increase its output of goods and services by applying more labour and physical capital (machines and buildings etc). But what if it were to increase its output by more than the increase in its inputs of labour or capital? This seemingly magical result is called an increase in productivity (productiveness), measured as output divided by input to give output per unit of input. The most commonly quoted productivity measure is the productivity of labour – output per worker or, better, output per hour of work. As can be seen from Table 3.30, almost all countries achieve an improvement in the productivity of their labour almost every year. Overall, labour productivity has been increasing at a rate averaging almost 2% a year for the past quarter century, although individual countries’ rates of increase vary between zero and 4%. The easiest and most obvious way to make workers more productive is to give them more or better machines to work with (that is, to increase inputs of capital). This explains firms’ unending pursuit of ‘laboursaving equipment’. But productivity is affected by various additional factors: by advances in technological know-how that are not ‘embodied’ in newly developed machines (such as improvements in the way firms are managed), by economies of scale, by the removal of government-imposed policy constraints on efficiency, and by changes (for better or worse) in the composition of a country’s industries and output. All these additional causes of productivity improvement (additional to improvements caused by the use of more capital or more labour inputs) are known as ‘multi-factor productivity’. MFP is the closest economists come to being able to measure the essence of

I

technological advance. Because labour productivity includes MFP (just as the productivity of capital also includes it), it can be seen that the rates in Table 3.29 generally exceed those in Table 3.30 and that the rankings in the two tables are strongly correlated. Dividing a country’s output of goods and services by its inputs gives its level of productivity at a point in time. The United States is the richest economy mainly because it has the highest productivity levels in most industries. This puts it at the ‘technological frontier’ and means it can achieve an increase in productivity only by coming up with inventions that push out the frontier. In consequence, it had quite low rates of annual improvement in labour productivity and MFP until just the last half of the 1990s. All other countries, by contrast, are back from the frontier and so can improve their productivity at a faster rate than the United States simply by appropriating American technology. The further back from the frontier a country is, the faster the rate at which it can catch up. This goes a fair way towards explaining Ireland’s remarkably rapid productivity growth. Another part of the explanation is its greatly expanded production of IT equipment. When the computer you produce this year has twice the capacity of the one you produced last year, but sells for the same price, this is equivalent to a doubling in output. The amazing productivity improvements achieved by IT production industries – and by one firm in particular, Nokia – explain tiny Finland’s outstanding performance. But America has led the way in IT production and use and this explains much of its notably improved, so-called New Economy, performance in the second half of the 1990s. Among the larger economies, however, it was Australia that turned in the best productivity performance during the 1990s. Economists commonly attribute this to the efficiencyenhancing effects of many years of microeconomic reform, but the improvement has not been sustained in the 2000s.

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Table 3.31 Global income per capita GDP per capita $US PPP 2005 (thousands) Region

Mean

World D18 East Europe Latin America Arab States East Asia South Asia Africa

9.5 31.8 9.5 8.4 6.7 6.6 3.4 1.9

Poorest New Zealand Tajikistan Bolivia Yemen Myanmar Nepal Malawi

Richest 24.9 1.3 2.8 0.9 1.0 1.6 0.6

United States Slovenia Bahamas Qatar Hong Kong Sri Lanka Seychelles

Other 41.8 22.2 18.4 27.7 34.8 4.6 16.1

Russia Brazil Egypt China India South Africa

10.8 8.4 4.3 6.8 3.5 11.1

Note: East Europe includes Central Europe; Latin America includes the Caribbean; Africa is sub-Saharan Africa.

Table 3.32 Global economic growth Annual growth rate, GDP per capita %, 1975–2005 Region

Mean

World D18 East Europe Latin America Arab States East Asia South Asia Africa

1.4 2.0 1.4 0.7 0.7 6.1 2.6 −0.5

Slowest Switzerland Tajikistan Haiti United Arab Emirates Brunei Nepal Congo

Fastest 1.0 −6.3 −2.2 −2.6 −1.9 2.0 −4.9

Ireland Poland Chile Lebanon China Bhutan Equatorial Guinea

4.5 4.3 3.9 3.2 8.4 5.4 11.7

Note: East Europe includes Central Europe; Latin America includes the Caribbean; Africa is sub-Saharan Africa.

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3.13 Global perspectives on income and growth he tables on this page serve as a stark reminder of how privileged the handful of rich countries are relative to the rest of the world. Table 3.31 focuses on average levels of income, at a point of time, 2005, and shows that the mean income for the whole world was $US9.5 thousand, after adjusting for purchasing power. The groupings of countries are then ordered according to their mean income. The average income in our selected countries (D18) – which are highly representative of all the world’s developed economies – exceeds the global average by a factor of 3.3. Eastern and Central Europe’s average income is close to the global average (as is its long-term rate of economic growth per capita, shown in Table 3.32), but all the other regional groupings are well below the global average. In round figures, Latin America’s average income is just 90% of the global average, the Arab States and East Asia are around 70% and South Asia is a little under 40%, leaving sub-Saharan Africa on just 20%. There are poor people around the world, with many more in Asia than Africa. But, clearly, if you seek the poorest of the poor, or the part of the world where economic development is most problematic, it is Africa. The table also shows the richest and poorest countries within each grouping, and one other important or interesting country in the ‘other’ column. Apart from the special cases of Qatar and Hong Kong, none of the countries listed comes close to matching the material affluence of the selected countries. Table 3.32 switches the focus from countries’ latest level of income per capita to their long-term rate of growth in income per capita, with the long term being the 30 years to 2005. At first blush, many of the differences revealed by Table 3.32 may seem small. But even the smallest difference will have a big effect when continued year by year for 30 years.

T

When comparing the rates of growth in different groupings, it is important to remember it is easier for developing countries to sustain high rates of growth than it is for developed countries. Arithmetically, the developing countries are growing from a low base and the same amount of income will constitute a higher percentage the lower the starting point with which it is compared. Economically, it is easier to catch up with the leaders – by accumulating capital, including human capital, and by appropriating existing technology – than it is for the leading countries to grow by achieving further technological advance. This explains why the United States, considered to be at the ‘technological frontier’, has long been able to grow only relatively slowly. Even so, it can be seen that the selected countries’ rate of growth over the past 30 years of 2% was hardly stratospheric when compared with the global average growth rate of 1.4%. It was exceeded by countries in the South Asia region (dominated by India) and far exceeded by East Asia (dominated by China). Because India and China account for almost 40% of the globe’s population, and because over long periods differences in rates of growth matter more than differences in starting-point levels, the table provides powerful evidence of the long-term convergence of living standards in a large part of the developing world with those in the rich world, raising questions about the natural environment’s ability to cope with so much more economic activity. By contrast, but equally important, is the table’s evidence of protracted economic contraction – and hence continuous decline in material standards of living – in sub-Saharan Africa as a whole. Moreover Latin America and the Arab states have only mediocre growth and Eastern Europe only slightly better. The mixed picture provides ammunition for both optimists and pessimists.

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Chapter 4 WORK AND LABOUR

Table 4.1 Labour force participation Labour force as % of total population Country

1960–1973

1974–1979

1980–1989

1990–1999

2000–2006

Switzerland Belgium Denmark Japan Norway Netherlands New Zealand Australia United States Sweden Finland United Kingdom Canada Germany Ireland France Austria Italy

51.2 39.1 47.6 49.1 40.7 37.3 37.8 41.9 40.3 48.7 48.1 46.3 38.4 45.5 38.5 42.3 43.6 40.0

48.8 40.5 49.9 47.9 45.7 36.7 40.4 44.8 45.4 50.6 50.2 46.5 45.3 44.2 36.7 43.0 40.2 38.8

52.1 41.7 54.0 49.4 49.8 41.3 44.7 46.7 49.1 52.6 52.5 48.3 50.4 46.7 37.4 43.8 44.0 41.1

56.6 42.4 54.7 53.1 50.7 47.8 48.5 49.4 50.9 49.9 49.8 49.1 51.0 48.7 40.7 43.9 47.5 41.4

59.0 53.2 53.2 52.4 52.2 51.8 51.6 51.1 50.8 50.5 50.4 49.0 48.7 48.7 47.4 45.3 42.9 41.9

Mean

43.1

44.2

47.0

48.7

50.0

Table 4.2 Aged dependency ratio People aged 65 and over as a % of those aged 15–64 Country

1980

2000

2030

Switzerland Japan Italy Austria Germany Sweden Finland Belgium United Kingdom Denmark France Netherlands Norway Canada New Zealand United States Australia Ireland

20.8 13.4 20.4 24.0 23.7 25.4 17.7 21.9 23.5 22.3 21.9 17.4 23.4 13.9 15.7 16.9 14.7 18.3

23.8 25.2 26.7 22.9 24.1 27.1 22.3 25.9 24.1 22.5 24.5 20.1 23.7 18.5 17.9 18.6 18.2 16.9

53.0 51.7 47.3 46.4 46.3 46.0 45.7 43.4 40.4 40.0 39.8 39.6 39.1 37.5 33.7 32.9 32.3 26.3

Mean

19.7

22.4

41.2

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Table 4.3 Life expectancy at retirement Life expectancy (in years) at effective retirement age Country

Males 1970 Males 2004 Females 1970 Females 2004

France Austria Italy Belgium Finland Netherlands Germany Australia Sweden Canada United Kingdom Norway New Zealand United States Switzerland Denmark Ireland Japan

10.8 12.4 13.1 12.6 10.8 12.5 10.5 10.9 11.9 13.1 10.5 12.2 10.7 11.0 9.0 11.7 8.1 8.5

21.4 20.8 20.6 20.2 19.6 19.5 18.9 18.9 17.8 17.8 17.6 17.4 17.3 17.1 16.8 16.2 15.1 14.8

13.4 17.6 18.4 16.7 16.4 15.0 13.9 12.4 14.9 16.2 15.3 13.9 14.4 14.7 10.8 15.5 8.6 13.1

26.2 25.5 23.9 26.6 23.8 24.2 23.8 21.2 22.9 21.3 21.9 21.9 21.4 21.0 21.7 21.0 18.9 22.0

Mean

11.1

18.2

14.5

22.7

4.1 Labour force participation he labour force ‘participation rate’ shown in Table 4.1 is the proportion of the total population that chooses to take part in the labour force. The labour force, however, includes not only those people with jobs (the workforce) but also those actively seeking work (the unemployed). The participation rate tends to move in line with the business cycle. It falls during recessions as jobseekers become discouraged and abandon the active search for jobs, thus ceasing to meet the tight definition of ‘unemployed’. Then, as the cycle turns up, formerly discouraged jobseekers resume the search for work, thus returning to participation in the labour force. However, the generally decadelong average rates shown in Table 4.1 should iron out most of the cyclical effect, exposing the longer term trend. The participation rate has been increasing steadily since the 1960s almost universally throughout the developed world. The latest rates are at or near the historical peak for most of the selected countries. Those countries show contrasting trends. Several that started the period with high participation have not had it rise much – Japan, Sweden, Finland and the United Kingdom – whereas several that started low have seen it rise considerably – the Netherlands, New Zealand, Belgium, Norway, Canada and Ireland. In other words, the period has seen a process of convergence on a higher average. Australia’s participation rate has gone from somewhat below average to a little above. As will be seen in Tables 4.4 and 4.6, the single most important reason for the rising participation rate is the increasing participation of women. Indeed, this has outweighed a decline in men’s participation. There seems to be little correlation between economic performance and labour force participation. Three of the four countries with the lowest participation rates were among the five fastest growing economies between 1973 and 1998 (Table 3.3), while four of the countries in the top half of the participation table are in the bottom half of the economic growth table.

T

Much of the furore about the ageing population concerns whether societies will be able to support such a large number of people retired from the labour force. Table 4.2 reveals the demographics of this concern. It takes the number of people aged 65 and over and expresses it as a proportion of the working-age population (those aged 15 to 64). This ‘aged dependency ratio’ rose on average across the selected countries by 2.7 percentage points in the last 20 years of the 20th century, increasing by far the most in Japan. The urgency of the concern over the ageing society, however, can be seen in the last column. According to the OECD’s projections, in the first 30 years of the 21st century, the 18-country mean of the aged dependency ratio will jump from 22% to 41%. Like all projections, this rests on many debatable and changing assumptions, but the dramatic rate of change cannot be doubted. Australia, along with the other New World English-speaking countries and Ireland, will remain among the ‘youngest’ of the developed countries, although even these countries will experience dramatically changing age ratios. At the other extreme, the aged dependency ratio in Switzerland and Japan will exceed 50%. The popular concern about population ageing has been heightened by consciousness of the looming progress of the bulge of ‘baby boomers’ (people born in the 15 years from the end of World War II) into their retirement years. Moreover, people live a lot longer in retirement than they used to. Table 4.3 shows that, on average for the selected countries, life expectancy at ‘effective’ retirement age (the average age at which people left the labour force at a given period) has risen since 1970 by seven years for men and eight for women. For Australia the increase has been even greater: eight years for men and almost nine for women. Remember, more people living longer lives is a good problem to have.

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73

Table 4.4 Male labour force participation Male labour force as a % of male population aged 15–64 Country

Table 4.5 Female labour force participation Female labour force as a % of female population aged 15–64

1960–1973 1974–1979 1980–1989 1990–1999 2007

Switzerland Japan New Zealand Denmark United Kingdom Australia Sweden Netherlands Canada Norway Germany United States Austria Ireland Finland France Italy Belgium Mean

Country

1960–1973 1974–1979 1980–1989 1990–1999 2007

104.7 89.9 91.8 94.8 96.0 93.5 91.4 92.7 87.7 89.6 93.2 87.0 88.7 97.9 86.1 88.5 87.8 84.8

96.4 89.5 88.0 90.3 91.6 89.4 88.4 81.4 84.9 88.6 86.3 84.9 82.1 90.6 81.7 84.0 82.7 80.9

95.2 87.9 85.6 88.3 87.5 86.1 85.5 78.4 85.2 87.3 82.2 84.5 81.3 85.4 82.0 78.0 79.2 75.3

98.4 90.6 83.5 86.3 84.3 84.6 80.7 80.9 82.3 83.8 80.9 85.2 80.7 79.1 77.9 74.6 76.5 72.4

88.2 85.2 85.0 84.0 83.1 83.0 82.9 82.7 82.4 81.8 81.7 81.7 81.6 81.4 77.4 74.8 74.4 73.1

Sweden Denmark Norway Switzerland Canada Finland New Zealand Netherlands United Kingdom Australia Germany United States Austria France Ireland Japan Belgium Italy

56.2 52.7 39.3 52.3 40.0 62.5 35.2 27.3 49.3 46.1 48.8 46.1 51.4 47.4 34.8 56.4 38.8 34.4

69.2 65.1 56.8 52.4 51.6 67.3 42.5 31.7 56.0 49.9 51.3 55.4 48.9 52.6 34.5 52.9 44.2 36.0

77.6 74.6 67.8 57.3 62.2 72.7 52.5 42.6 60.8 55.0 53.2 63.7 51.3 56.0 39.1 56.9 49.3 41.0

76.4 76.2 72.9 68.6 68.0 70.8 64.9 58.4 66.6 63.2 61.4 70.1 60.0 59.4 48.1 62.4 55.7 44.5

78.2 76.4 75.9 75.0 74.3 74.0 71.8 71.1 69.8 69.4 69.3 69.1 67.8 65.5 63.0 61.9 60.2 50.7

91.5

86.8

84.2

82.4

81.0

Mean

45.5

51.0

57.4

63.8

69.0

Table 4.6 Labour force participation among males aged 55–64 Percentage of males aged 55–64 in the labour force

Table 4.7 Labour force participation among females aged 55–64 Proportion of females aged 55–64 in the labour force

Country

1980

1990

2000

2007

Country

1980

1990

2000

2007

Japan New Zealand Switzerland Sweden Norway Ireland United States United Kingdom Australia Canada Denmark Germany Netherlands Finland Austria Italy France Belgium

85.4 70.2 88.8 78.7 79.5 81.8 72.1 84.2 68.8 74.6 76.2 67.3 63.2 56.9 56.8 52.7 68.6 64.7

83.3 56.8 87.9 75.3 72.8 65.0 67.8 68.1 63.2 64.3 69.2 53.4 45.7 47.1 38.7 59.6 45.8 35.4

84.1 72.2 79.3 72.8 74.4 64.7 67.3 63.3 61.5 61.0 64.5 52.5 51.4 48.1 44.5 42.7 41.7 36.3

84.9 82.2 78.4 76.4 74.7 70.0 69.6 68.9 67.8 67.1 66.9 66.5 63.3 59.2 51.3 46.3 42.6 42.2

Sweden Norway New Zealand Switzerland Finland United States Denmark Canada Japan United Kingdom Germany Australia Netherlands Ireland France Austria Belgium Italy

55.3 49.8 21.8 34.3 43.8 41.3 41.4 32.6 45.3 41.4 28.9 22.0 14.4 19.2 40.1 23.5 14.1 13.9

65.8 53.9 30.7 37.5 40.8 45.2 45.8 34.9 47.2 38.7 25.1 24.9 16.7 19.9 31.1 14.6 9.9 15.2

65.9 61.6 48.0 51.3 45.2 51.9 48.2 41.6 49.7 42.6 33.5 36.3 26.3 27.8 33.0 18.9 15.8 16.1

69.6 64.6 64.1 60.3 58.3 58.3 55.7 53.3 52.5 50.1 49.8 48.8 41.1 40.8 38.0 28.9 28.3 23.5

Mean

71.7

61.1

60.1

65.0

Mean

32.4

33.2

39.7

49.0

74


4.2 Males and females in the labour force he labour force participation rate in Tables 4.4 and 4.5 is the proportion of the population of working age (15 to 64 years) that participates in the labour force either by working or by actively seeking work. It makes no distinction between full-time and part-time employment. There are many reasons why the rate is likely to be well below 100%: young people still in full-time education, older people in early retirement, people who don’t have paid employment because they are looking after children or other dependents, people who are disabled, and people who would like to work, but have become discouraged from actively seeking it (and so no longer meet the tight definition of ‘unemployed’). As was seen from Table 4.1, the overall participation rate among the selected countries has been increasing steadily since the 1960s almost universally. However, Tables 4.4 and 4.5 reveal that this overall increase is more than fully explained by the rising participation of women and so conceals a universal decline in participation by men. Table 4.4 shows the mean male participation rate fell by more than 10 percentage points during the period, with most of that fall coming in the 1970s. Australia’s fall was about average. It began and finished a little above average. The decline in male participation is explained partly by the lower participation of teenagers as young people stayed longer in full-time education and partly by a trend to early retirement. One factor contributing to this has been the changing structure of the labour force. Manufacturing’s relative share of employment has been falling, while the services sector has been increasing. Labour-saving technological advances and increased international competition meant declining job opportunities in manufacturing. Many of the displaced older male blue-collar workers were not suited to take advantage of emerging opportunities elsewhere, and some would have become discouraged and left the labour force, entering early retirement involuntarily. The same structural changes help explain the remarkable rise in female participation

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evident from Table 4.5. Women occupy many of the white-collar, indoor, services sector jobs created in the past 50 years. The table shows that female participation has risen at a rapid but steady rate throughout the period and in all the selected economies. Overall, women’s participation has risen by more than 23 percentage points. In all countries a clear majority of working-age women are now in the paid labour force. Australia’s experience is about average. The changing structure of industry accounts for an increase in employers’ demand for female labour, but even more fundamental have been changes in women’s willingness to supply their labour. Changing parental attitudes towards girls’ entitlement to an education, rising educational attainment, stronger career aspirations and the financial pressures of family life have all led to increasing female participation in paid employment. Turning to men and women of preretirement age – 55 to 64 – Tables 4.6 and 4.7 again tell markedly different stories. Table 4.7 shows universally rising participation by preretirement age women contributing to the general rise in female participation. For Australia, the period saw participation by this group go from well below average to almost average. Superficially, Table 4.6 confirms the general story of declining male participation. Looking at the overall means, that was true over the 20 years to 2000. However, by 2007 participation by pre-retirement age men had actually risen in all but two of the selected economies, restoring the overall average participation rate for this group to where it was sometime during the 1980s. In seven countries the recovery began during the 1990s. This is a highly significant development: reversal of the longstanding trend to earlier retirement (which no doubt provides an additional explanation for the recent exceptionally strong increase in participation by preretirement age women). It represents both a response to and a (partial) solution to the problem of population ageing. It probably has further to run.

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Table 4.8 Unemployment Unemployed as a % of the labour force Country

1970–1973

1974–1979

1980–1989

1990–1999

2000–2006

Netherlands Switzerland New Zealand Norway Ireland Austria Denmark Japan United Kingdom United States Australia Sweden Canada Italy Belgium Finland France Germany

1.7 0.4 0.2 1.2 6.1 1.2 0.9 1.3 2.6 5.2 2.0 2.3 5.8 5.8 2.1 2.2 2.7 0.8

4.9 0.4 0.8 1.8 7.9 1.8 6.1 1.9 4.2 6.7 4.8 1.9 7.1 6.6 5.7 4.4 4.6 3.4

9.8 0.6 4.5 2.8 14.0 3.3 8.1 2.5 9.7 7.2 7.2 2.5 9.3 9.9 11.1 4.8 9.1 6.1

6.1 3.1 7.9 4.8 12.1 3.8 7.6 3.0 8.1 5.7 8.6 6.5 9.5 11.2 11.4 11.7 11.2 7.8

3.9 4.1 4.2 4.2 4.5 4.6 4.8 4.8 5.0 5.4 5.5 6.2 7.1 7.9 8.1 8.6 9.4 9.6

Mean

2.5

4.2

6.8

7.8

6.0

Table 4.9 Long-term unemployment Those unemployed one year or more as a % of all unemployed

76

Country

1990

2000

2007

New Zealand Canada Norway United States Sweden Australia Denmark Finland United Kingdom Austria Ireland Japan Switzerland Netherlands France Belgium Italy Germany

20.9 7.2 20.4 5.5 12.1 21.6 29.9 9.2 34.4 .. 66.0 19.1 16.4 49.3 38.0 68.7 69.8 46.8

19.2 11.2 5.0 6.0 26.4 27.9 20.0 29.0 28.0 28.4 55.3 25.5 29.1 32.7 42.5 56.3 60.8 51.5

5.7 7.5 8.5 10.0 13.0 15.5 18.2 23.0 24.7 26.8 30.3 32.0 40.8 41.7 42.0 50.0 50.0 56.6

Mean

31.5

30.8

28.0


4.3 Unemployment here could be little argument that the greatest economic and social problem plaguing the developed countries in the past 35 years has been unemployment. It is not by chance, however, that the other dominant economic problem through much of that period was the Great Inflation of the 1970s and 1980s. In short, in the early 1970s the developed countries entered a period of economic instability and dysfunction that did not begin to lift until some time in the 1990s. Table 4.8 shows a pattern of generally worsening unemployment over the last quarter of the 20th century, with each period worse than the preceding one. The unemployment rate is the proportion of the total labour force that is out of work, but available for, and seeking, work. Note that someone who is seeking a full-time job, but nonetheless accepts a few hours of casual employment to earn a little cash, will not be classed as unemployed. Similarly, someone who would like to have a job, but is not actively seeking one, will not be classed as unemployed. Thus the tight definition of ‘unemployment’ means that the official estimates often understate the full extent of joblessness and underemployment. Unemployment is heavily influenced by the economy’s progress through the business cycle, with the rate likely to rise sharply when the economy drops into recession, but then decline slowly as the economy enters the upswing of the cycle. However, the generally decadelong average rates of unemployment shown in Table 4.8 smooth away most of the cyclical effect, making longer term trends more evident. The rise in the average rates shown in the table up to the end of the 1990s reveals a steady worsening in ‘structural’ unemployment – the more serious and lasting form of unemployment in which the skills, location and other characteristics of the unemployed make them unsuited to the job vacancies that arise. Countries varied over time in the severity of their unemployment. Over the period to the end of the century, Switzerland had the best record. Until 1990, it was broadly

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matched by Japan, but that country’s problems have steadily worsened since. Up until the 1990s, Ireland had the worst record, but with its strong growth in that decade and since its unemployment situation has improved dramatically. Australia began below the mean, but was above it until the end of the 1990s, although never near the worst extremes. The good news that leaps from Table 4.8, however, is the fall in unemployment in all but three of the selected countries during the first half of the 2000s. The unemployment rate fell by more than three percentage points in seven countries, including Australia. This serves as a reminder that ever-worsening unemployment is not inevitable, particularly in an era of population ageing. The greater a country’s problem with structural unemployment, the more unemployed people are likely to have been without work for a year or more – to be the ‘long-term unemployed’. Table 4.9 shows the proportion of all unemployed people who have been without a job for a year or more. The table should be interpreted with caution, however, because this proportion will shift with a country’s movement through the business cycle. Even so, in the broad the figures show enduring differences between countries, which probably owe a lot to policy differences. The English-speaking and Scandinavian countries share an unaccustomed clustering at the bottom of the table, both relatively successful in avoiding the unemployed becoming longterm unemployed. They may take different approaches. Scandinavia has low rates of unemployment and has also invested most in active labour programs. America also has a relatively low rate, and its more stringent approach to welfare benefits seems to provide an incentive for people to find employment quickly. In contrast Belgium, Italy and Germany have a very large problem. Fortunately, however, the decline in overall unemployment during the 2000s saw the proportion of long-term unemployed falling in 13 of the 18 countries.

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Table 4.10 Youth unemployment Unemployment rates of 15- to 24-year-olds Country

1980

1990

2000

2006

Denmark Netherlands Switzerland Japan Ireland Norway Austria New Zealand Australia United States Canada Germany United Kingdom Finland Belgium Sweden Italy France

.. 9.3 0.2 3.6 14.7 4.7 .. .. 12.2 13.8 12.8 .. .. 8.8 .. 6.2 25.2 15.1

11.5 11.1 0.4 4.3 17.7 11.8 .. 14.1 13.2 11.2 12.4 5.4 10.1 9.4 14.5 4.5 28.9 19.1

6.7 6.6 4.8 9.2 6.4 10.2 6.3 13.2 12.3 9.3 12.6 8.4 11.8 21.5 15.2 11.9 29.7 20.7

7.6 7.6 7.7 8.0 8.4 8.6 9.1 9.6 10.4 10.5 11.6 13.5 13.9 18.8 18.9 21.3 21.6 23.9

Mean

10.6

11.7

12.0

13.0

Table 4.11 Youths not in education or employment Percentage of youths not in education or employment Country

Males 2000 Males 2005 Females 2000 Females 2005

Sweden New Zealand Italy Finland Germany Denmark France Canada Austria United States Belgium Switzerland Australia Norway United Kingdom Netherlands Ireland Japan Mean

4.7 3.8 4.5 .. 5.2 1.9 3.4 7.8 .. 6.8 6.7 7.3 6.4 .. 8.2 7.3 6.9 12.2

6.0 3.8 4.8 5.6 3.8 3.5 6.8 6.5 7.6 5.9 5.9 7.6 7.1 8.4 9.7 7.6 9.5 10.9

2.4 3.6 4.3 .. 6.3 3.6 3.2 6.6 .. 7.3 6.3 8.5 7.3 .. 7.9 10.3 11.2 14.1

3.3 3.8 4.0 4.9 5.0 5.2 5.5 5.8 6.2 6.3 6.6 6.8 7.7 8.6 9.0 9.9 10.0 11.4

6.2

6.7

6.9

6.7

Table 4.12 Education and unemployment Percentage at each educational level unemployed in 2006 Country Norway United Kingdom Ireland Switzerland Australia Netherlands New Zealand Austria United States Japan Denmark Finland Belgium Canada Sweden Germany Italy France Mean

78


Less than upper secondary

Completed upper secondary

Tertiary

4.7 5.7 5.7 7.6 5.6 4.8 3.1 7.8 8.3 .. 5.5 10.1 12.2 9.3 7.3 19.9 6.9 11.0

2.1 4.0 3.2 3.2 3.8 3.5 2.2 3.7 4.6 4.6 2.7 7.0 6.7 5.6 5.1 10.0 4.6 7.0

1.8 2.2 2.2 2.2 2.3 2.3 2.4 2.5 2.5 3.0 3.2 3.7 3.7 4.1 4.2 4.8 4.8 5.1

8.0

4.6

3.2

4.4 Youth, education and unemployment he risk and burden of unemployment are borne far from equally among all those in the labour force. The tables on this page reveal that the risk of joblessness is greatest among the less skilled and less educated. As can be seen from Table 4.12, it is universally true that the higher one’s level of educational attainment, the less one’s chance of becoming or remaining unemployed. Indeed, the mean degree of unemployment among those who failed to complete secondary schooling is more than twice that for those with a tertiary education. This is the right point to turn to the vexed question of youth unemployment, as reported in Table 4.10. Note that ‘youth’ is defined widely to include not just teenagers but all those aged between 15 and 24. It can be seen that, though the rate of youth unemployment has fallen in half the selected countries since 1990, in the other half it continued rising – to particularly high levels in countries in the bottom half of the league table – such that the overall mean has continued to worsen over the past 26 years. Australia has gone from above the mean to below it, although its rate of more than 10% in 2006 hardly seems something to boast about. But Table 4.10 needs to be interpreted with care. It shows the proportion of 15- to 24year-olds who are in the labour force and also unemployed. However, many people of such an age are not in the labour force, but rather in full-time education. So it should not be supposed that these figures tell us what proportion of all youth is unemployed. Rather, they tell us the unemployment rate among those youths who have chosen to join the labour force. And, with the exception of those in their mid-20s who had completed their tertiary education, one would expect most of these youths to be those who had not gone on to full-time tertiary study or who had quit secondary school

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prematurely. In other words, we see in these apparently high rates of youth unemployment a demonstration of the truth that unemployment is highest among the least skilled and least educated – a truth whose application is particularly harsh in the case of the young. Turning specifically to teenagers, the last part of the 20th century was a period of significant change in their relationship to the labour force. One change was that more teenagers stayed on to complete their high school education – a rise in the school ‘retention rate’ – and more went on to university. The second was a decline in employers’ willingness to offer full-time jobs to school-leavers, particularly early school-leavers. Employers became more inclined to hire university graduates for fulltime jobs. At the same time, however, many employers – particularly those in retailing and hospitality – became more inclined to offer part-time jobs. It is likely that many formerly full-time jobs in retailing and elsewhere were divided into several part-time jobs, with the advantage to employers of more closely matching their staffing levels with their busiest times of the week. It is also likely that the decline in young people’s supply of full-time labour and the decline in employers’ demand for young people’s full-time labour were inter-related. It follows from all this that the young people about whom we should be most concerned are those who have fallen between the two stools of education and employment and are engaged in neither. Table 4.11 shows that smaller but significant proportions of all people in the age group fall into this category. The table shows no clear change in the position during the first half of the 2000s, with Australia’s position being a little worse that the overall average. It is likely that most of these youths would have been early school leavers – and reducing early withdrawal from education is the key to dealing with this problem.

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Table 4.13 Part-time employment Persons working part-time as a % of total employment, 1985–2007 Country

1985

1990

2000

2007

Netherlands Switzerland Australia United Kingdom Germany New Zealand Ireland Norway Japan Belgium Canada Denmark Austria Italy Sweden France United States Finland

20 .. 20 20 11 17 8 .. 17 12 17 20 .. 8 .. 11 14 ..

28 22 23 20 13 20 10 22 19 14 17 19 .. 9 15 12 14 8

32 24 26 23 18 22 18 20 23 19 18 16 12 12 14 14 13 10

36 25 24 23 22 22 20 20 19 18 18 18 17 15 14 13 13 12

Mean

15

17

19

20

Table 4.14 Female share of part-time employment Country

1990

2000

2007

Austria Belgium Germany Switzerland France Ireland Italy United Kingdom Netherlands New Zealand Norway Australia Japan Canada United States Sweden Finland Denmark

.. 80 90 82 80 72 71 85 70 77 83 71 71 70 68 81 67 72

88 79 85 81 80 76 71 80 76 73 77 68 70 69 68 73 64 70

84 81 81 81 80 80 79 77 75 73 73 72 72 68 68 65 64 63

Mean

76

75

74

Table 4.15 Involuntary part-time work Percentage of part-time workers who want to be working full-time, 2007 Country

1.0 4.0 5.0 5.0 8.0 10.0 10.0 15.0 17.0 18.0 18.0 21.0 22.0 27.0 27.7 29.0

Mean

14.9

No data on Finland or the United States.

80


%

Ireland Netherlands Norway Switzerland United Kingdom Austria Denmark Belgium Japan Germany New Zealand Sweden Canada France Australia Italy

4.5 Part-time work n many of the selected countries, part-time work has become an increasingly important component of total employment. The term ‘total employment’ simply adds full-time and part-time jobs together. Similarly, the conventional figures for unemployment count those seeking part-time jobs along with those seeking full-time jobs. Table 4.13 reveals marked differences between these countries in both the importance of part-time employment and the extent to which its share of total employment grew over the past 20 years or so. It is not a particularly important feature of employment in the United States, but in Australia its share rose from a fifth to a quarter in just 15 years. And in the Netherlands in 2007, it accounted for more than a third of total employment. Other countries exhibiting strong growth were Ireland and Germany. Table 4.14 reveals that, regardless of the relative importance of part-time employment – whether in the United States or Australia – it is a form of employment dominated by women. The table also reveals, however, that women’s domination has slipped in half the selected countries, while increasing in three. What the table doesn’t reveal is that part-time jobs are predominantly in the services sector, and in many countries the rapid growth in parttime employment has accompanied the rapid growth in the services sector’s share of total employment. The growth in part-time employment has also been associated with the decline in full-time job opportunities for early leavers from the education system. Thus part-time employment is dominated by two kinds of worker: students in full-time education and married women. This table is a reminder, however, that some mature-age men are now accepting part-time jobs rather than going without. It is often assumed that part-time employment is, almost by definition, inferior to fulltime employment. Such a conclusion is too

I

sweeping and may betray a breadwinnerfocused view of the labour market. The growth in part-time employment is partly a function of increased demand from employers – it suits many firms in retailing and hospitality, for instance, to have a lot of extra hands during peak periods in the week, but a lot fewer hands during slow periods. But the growth is also a product of increased willingness to supply such labour on the part of some workers. Many mothers with young families would prefer to work less than the full 35 to 40 hours a week, as would most full-time students. So, though it is undoubtedly true that many people obliged to accept part-time employment would prefer to work more hours, it is equally true that many part-time employees are perfectly happy with the amount of hours they work. Table 4.15 shows those working part-time who would prefer to be working full-time and expresses this as a proportion of the entire labour force. Observe the size of the gap between the lowest and highest proportions. Table 4.15 is actually a measure of ‘underemployment’ and it can be seen that the rates of underemployment are particularly high in such English-speaking countries as New Zealand, Canada and Australia. The big rise in so many countries of the proportion of workers working part-time, when combined with the long standing convention that those working even just an hour or two a week be counted as employed, has prompted many to the view that official measures of unemployment significantly understate the true extent of the problem. Hence the new interest in the extent of underemployment and the desire to add it to official unemployment to give a broader and more accurate measure of labour ‘underutilisation’. It cannot be assumed, however, that all those who would prefer to work more hours would prefer a fulltime job. Some would be happy with just a few more hours a week.

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Table 4.16 Annual hours worked Mean hours worked per person in employment per year Country

1980

1990

2000

2007

Italy United States Japan New Zealand Canada Australia Finland United Kingdom Switzerland Austria Ireland Denmark Belgium Sweden France Germany Norway Netherlands

1950 1810 2121 .. 1802 1798 1849 1773 1805 .. .. 1646 .. 1517 1842 .. 1580 ..

1902 1827 2031 1810 1788 1781 1769 1771 1700 .. 1988 1518 1754 1561 1702 .. 1503 1504

1861 1832 1821 1830 1768 1785 1750 1711 1685 1632 1719 1581 1554 1574 1591 1473 1455 1372

1824 1794 1785 1771 1736 1722 1698 1670 1657 1652 1630 1574 1566 1562 1561 1433 1411 1392

Mean

1791

1744

1666

1635

Table 4.18 Weekly hours of full-time workers Average weekly hours of work of full-time workers 2007 Country

Country

1–19

20–29

30–34

35–39

40+

United States Japan Switzerland New Zealand Italy Austria Sweden Canada Germany Australia United Kingdom Finland Ireland France Netherlands Belgium Denmark Norway

5 6 15 13 5 7 6 9 13 14 13 6 8 5 21 8 11 13

8 13 11 9 10 10 8 9 9 10 11 6 12 8 15 11 7 8

5 8 5 6 4 5 11 7 5 6 6 6 5 6 11 8 10 7

6 7 4 7 17 18 17 22 23 21 24 41 41 48 21 43 42 57

77 66 65 64 63 59 58 53 50 49 47 41 34 33 32 31 30 16

Mean

10

10

6

22

48

Table 4.19 Weeks worked per year Average weeks worked 2005

Weeks worked per year

Public holidays each year (days)

Statutory minimum annual leave entitlement (days)

United States Australia New Zealand Japan Ireland Switzerland Italy United Kingdom France Germany Belgium Netherlands Austria Denmark Finland Norway Sweden Canada

46.2 46.0 45.8 45.4 43.9 42.6 41.3 40.8 40.7 40.6 40.3 39.6 39.5 39.4 38.9 37.0 36.0 ..

10 10 11 15 9 8 12 8 11 11 10 8 13 9.5 12 8 9 10

0 20 20 10–20 20 20–25 20 20 25 20 20 20 25 25 20 21 25 10–20

Mean

41.4

Hours

Australia New Zealand Austria United Kingdom Italy Switzerland Belgium France Germany Ireland Denmark Finland Sweden Netherlands Norway

44 44 43 43 42 42 41 41 41 41 40 40 40 39 39

Mean

41

No data on Canada, Japan or the United States.

82

Table 4.17 Weekly working hours Percentage of employees working different periods per week 2007


Country

Average annual leave entitlement (days) 17 .. .. .. .. .. 28 25 25 30 .. 26 25 30 25 25 33 ..

4.6 Working hours here may be few matters of economic statistical fact more prone to confidently held prejudices than the question of how hard people of different nationalities work. It is widely held, for instance, that the Japanese work the longest hours, rarely taking holidays – ‘economic ants’ was the cultured description made by a French prime minister, Edith Cresson. The Americans wouldn’t be far behind them, whereas the Europeans are notorious for short hours and long holidays – probably with the Brits leading the way. As for the Australians, they are wonderful people in many ways, but hardly renowned for their devotion to hard work. In the land of the long weekend, the workers are so laid back the economy is down for the count. If any of those views strike a chord, you may be in for some shocks from Table 4.16, which shows the average number of hours worked in a year by the country’s workers. The first surprise is that average hours have been falling since 1980 (and probably before) in almost all the selected countries. The next surprise is that Australia’s very small fall was sufficient to lift it up to sixth place. The gap between top and bottom is somewhat over 400 hours a year. Clearly the matter warrants investigation. There is a range of factors that influence the number of hours the typical worker works in a week. First would come the length of the country’s standard working week – 35, 38 or 40 hours – then the extent of overtime worked, then the length of annual leave taken and the number of public holidays. Another easily forgotten factor is where a particular national economy happened to be in the business cycle. One would expect average hours to be higher when the economy was booming and lower when it was in the doldrums. However, total annual hours worked is a crude measure that most importantly takes

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no account of the relative mix of full-time and part-time workers. The reminder that 24% of Australia’s workers are part-time (Table 4.13) makes its position towards the top of the league of hard workers more remarkable. This also helps to explain the bottom position of the Netherlands. At first blush Table 4.17 appears to offer an indicator of the degree of workaholism in the selected countries. But 40 hours is close to the standard working week in many countries, so it is nearer to being an imperfect measure of the proportion of full-time employees in the workforce. Certainly, the high proportion of part-time workers in countries such as Australia and the Netherlands does most to explain their low places in the table. But Table 4.18 reveals that, while many may be working 40 hours a week or more, most are not working a lot more. Even in Australia, full-time workers are averaging just 44 hours a week. The gap between the countries with the longest and shortest weekly hours is not wide. Table 4.19 further shatters many illusions by revealing that, in the main, there is not a great deal of difference between countries in the number of public holidays per year – but with Japan, of all countries, taking the prize for the most. And while the length of annual leave differs more widely, Australia’s four weeks is by no means excessive. It is noteworthy that, while the United States has no statutory leave entitlement, in practice people take an average of more than three weeks. Note how common it is for employers to grant more annual leave than required by the statutory minimum. In all, the perception that Aussies are too laid back to take work seriously is no longer true – if it ever was.

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Table 4.20 Gender wage gap Women’s median earnings as a % of men’s median earnings Country

Table 4.21 Gender and hourly pay Women’s hourly pay as a % of men’s, 2001 Country

%

90 89 88 86 85 83 83 81 81 81 79 79 78 77 67

Italy Belgium Australia Denmark France Ireland Finland New Zealand Sweden Austria Canada United States Germany Netherlands Switzerland United Kingdom

95 90 87 87 85 85 84 83 83 82 81 81 80 80 79 78

82

Mean

84

1996

2006

New Zealand Denmark France Ireland Sweden Australia Netherlands Finland Switzerland United States Canada United Kingdom Austria Germany Japan

78 86 90 78 84 85 78 79 75 76 75 74 77 76 63

Mean

78

No data on Belgium, Italy or Norway.

No data on Japan or Norway.

Table 4.22 Women doctors Female physicians as a % of total

Table 4.23 Division of housework Hours per week spent by husband and wife on housework, 2002

Country

1980

1990

2006

Finland Sweden Denmark United Kingdom Netherlands Germany France Ireland Norway Austria New Zealand Belgium Canada Italy Switzerland Australia United States Japan

33.3 22.0 20.3 19.5 20.4 21.6 21.0 .. 17.2 20.8 16.4 14.7 15.0 17.1 16.5 18.9 10.8 9.7

43.0 34.0 28.3 24.4 24.3 32.5 29.6 .. 23.7 25.9 23.9 21.4 23.8 24.5 21.9 21.4 19.6 11.3

50.4 42.3 41.4 39.4 39.2 39.0 38.4 38.1 38.1 37.8 37.3 35.8 35.6 35.3 33.6 32.9 29.5 17.1

Mean

18.5

25.5

36.7

Country

Wife

Husband

Total

Woman’s share %

Denmark Sweden United States Finland Australia Germany United Kingdom New Zealand Norway Belgium Netherlands France Austria Switzerland Ireland Japan

12.9 14.6 13.6 12.1 21.3 21.3 13.9 14.5 11.7 22.3 17.7 12.2 22.1 22.1 31.7 26.9

7.0 7.6 6.4 5.8 8.5 8.5 5.6 5.7 4.3 7.8 5.7 3.7 6.3 6.1 8.5 2.5

19.9 22.2 20.0 17.9 29.8 29.8 19.5 20.2 16.0 30.1 23.4 15.9 28.4 28.2 40.2 29.4

65 66 68 68 71 71 71 72 73 74 76 77 78 78 79 91

Mean

18.2

6.3

24.4

74

No data on Canada or Italy. Belgium is Flanders only.

84


4.7 Women, work and gender equity ontinuously rising levels of educational attainment among girls – which stem from a long-ago change of view among parents throughout the developed world that girls are just as entitled to an education as their brothers – are a major cause of women’s increasing participation in the paid labour force. However, their degree of participation still falls short of men’s, and their treatment is less than equal. Table 4.20 shows that in all the selected countries the earned income of women is significantly less than for men, averaging 82%. But there is a wide range, with New Zealand on 90% and Japan on 67%. These scores are not a simple measure of occupational discrimination, but rather a much broader measure of access to a society’s economic resources. They do not mean for example that men and women employed in the same job and working the same hours receive different amounts of pay. Rather they reflect a combination of factors: the relative labour force participation of women; the relative numbers working in full- and part-time positions; as well as their relative access to better paying jobs. A more precise measure is found in Table 4.21, which compares the relative hourly earnings. (The most basic measure of income discrimination would be to compare the incomes of males and females in the same occupations with the same qualifications etc.) The table shows less difference between the sexes than Table 4.20, although it still paints a picture considerably less than equality, where the ratio would equal 100. Italy and Belgium rank at the top, while the United Kingdom shows the greatest disparity. As an indication of the rate of feminisation of the workforce, including the profes-

C

sions, Table 4.22 shows a considerable rise in the proportion of female doctors between 1990 and 2006. In the selected countries in 1990, one in four doctors was a woman, but by 2006 the figure had risen to more than one in three. The data for earlier decades is too partial to tabulate, but the mean percentage for 10 countries in 1960 was only 12% (just less than one doctor in eight). This overall increase is far from uniform among the 18 countries. Only in Finland has the proportion of female doctors tipped 50%, almost three times the rate for the lowest country, Japan. In is notable that three of the four Nordic countries occupy the top three places, whereas four of the six Englishspeaking countries fall in the bottom half. Australia and the United States were close to the bottom, though not as low as Japan. And whereas Japan’s female proportion rose by less than six percentage points over the 16-year period, the proportions for Australia and the United States rose by at least 10 percentage points. Women’s increasing participation in the formal – paid – labour force has made more acute the difficulties of balancing work and home. Issues of equity arise also in the distribution of domestic labour tasks. Table 4.23 shows the division of housework between husbands and wives. Like Table 4.21 it makes no allowances for different labour force participation, part-time jobs etc. Three of the four Nordic countries were closest to gender equality, although four of the five English-speaking countries ranked in the top half of the distribution. At the other end, Japanese men did almost no domestic work.

WORK AND LABOUR

85

Table 4.24 Trade union membership Union members as a % of all employees Country

1970

1980

1995

2003

Sweden Finland Denmark Belgium Norway Austria Ireland Italy United Kingdom Canada Australia Germany Netherlands New Zealand Japan Switzerland United States France

68 51 60 42 53 55 59 36 46 30 45 32 32 52 35 30 27 22

80 69 76 53 57 49 64 49 52 35 50 35 31 60 31 27 22 19

83 80 77 56 57 41 46 38 33 33 32 29 26 28 24 23 14 9

78 74 70 55 53 35 35 34 29 28 23 23 22 22 20 18 12 8

Mean

43

48

33

29

Table 4.25 Industrial disputes Days lost per annum per 1000 employees in industrial disputes, average for each period Country Japan Switzerland Germany Netherlands France United States Belgium New Zealand Ireland United Kingdom Sweden Australia Denmark Norway Austria Finland Italy Canada Mean

1970–1975

1976–1980

1981–1985

1986–1990

1991–1995

1996–2000

2001–2006

117 1 41 38 161 417 228 164 386 512 59 547 307 37 12 488 1027 719

30 2 40 25 148 226 182 325 669 509 220 476 77 36 2 487 932 737

8 0 44 18 68 108 35 339 358 384 36 313 258 48 2 267 491 447

3 0 4 11 31 72 38 349 170 113 120 176 36 126 1 336 1 374

2 1 9 28 24 38 26 41 83 20 46 104 40 53 5 176 131 141

1 2 1 4 20 54 18 15 64 18 8 68 262 52 1 45 52 180

0 4 5 10 12 14 .. 18 26 26 29 32 35 36 67 80 105 134

292

285

179

109

54

48

37

No data on Belgium, which is placed as if constant from earlier period.

86


4.8 Trade unions ables 4.24 and 4.25 document a dramatic change in the position of trade unions in the selected countries. Membership of trade unions as a proportion of all employees (trade union density) fell by two-fifths between 1980 and 2003, from an 18-nation mean of 48% to 29%. The movement has not been universal. The top four countries in Table 4.24 (three Nordic countries plus Belgium) showed an increase in trade union density over the past 33 years, with Norway recording no net change. But the remaining 13 countries all showed a decline. The range from smallest to largest widened from 46 percentage points in 1970 to 70 in 2003. Most dramatically, in a range of countries where trade union membership was considerable (Ireland, Austria, the United Kingdom, Australia and New Zealand) density declined by a large amount. The declines were biggest in Australia (22 percentage points) and New Zealand (30). The decline in the number of days lost through industrial disputes per 1000 employees (Table 4.25) is even more spectacular. The 18-nation mean dropped from 292 in the early 1970s to 37 in the first half of the 2000s, down to about an eighth of the earlier level. The 1970s involved a peak of union militancy because of the destabilising effects of high inflation. The change since then has been so great and so universal that Australia was ranked 16th in the early 1970s with a figure of 547, and even though that number had dropped to 32 in the early 2000s, it rose only to 12th. The top three countries in the table all had an annual average of five or fewer days lost per 1000 employees in the early 2000s. Japan, Switzerland and Germany have long been almost free of industrial stoppages. Austria used to be among this group, but something went wrong in the first half of the 2000s. Figures on industrial disputes are very volatile. The five-year average largely obliterates such blips, although Denmark’s centralised system and large union membership produce large swings.

T

Although the substantial trends are not in doubt, there are problems of measurement in both tables. The figures on trade union density are based on both surveys and administrative data, the latter sometimes giving a higher estimate by a couple of percentage points, due to the reporting organisation inflating figures, or members (or their spouses) forgetting their memberships when polled in surveys. On the whole, these discrepancies are relatively small. Occasionally there are larger discrepancies. Normally this is because one source is using gross figures and the other net. Net membership only includes those employed, while gross union density also counts members when they are retired or unemployed. The discrepancy tends to be greatest in those countries (Denmark, Finland, Belgium and Sweden) where unions play a publicly subsidised role in welfare schemes. The problems of gaining harmonised and consistent data for industrial disputes are much greater. In calculating the rates for time lost, there are divergences in how both the numerator and the denominator are counted. Countries have different minima for number of days of labour lost before strikes are counted in their statistics. (Australia is more inclusive than many others.) Some types of strike (political and unofficial – ‘wildcat’) or stoppages among some groups (public sector, armed forces) are excluded in some countries. Governments also change their own methods of counting (see Italy during the 1980s for the most extreme example!). Proportions are sometimes given of all employed (as here), sometimes of civilian employees, and sometimes of some ill-defined group called ‘workers’. So these figures cannot be used to explore nice distinctions and small differences. However, the overwhelming trends over time and the extreme differences between countries still stand, even allowing for the severe measurement problems. Tables 4.24 and 4.25 represent a significant shift in social power in many of the selected countries.

WORK AND LABOUR

87

Chapter 5 GOVERNMENT TAXES AND SPENDING

Table 5.1 Government spending Total government outlays as a % of GDP Country

1960–1973

1974–1979

1980–1989

1990–1999

2000–2006

Sweden Denmark France Austria Belgium Finland Italy Germany Netherlands Norway United Kingdom Canada New Zealand Japan United States Australia Switzerland Ireland

38.9 33.8 38.0 38.7 39.1 30.3 33.7 37.5 40.8 36.7 36.7 31.6 .. 19.5 29.1 24.4 20.3 34.4

54.4 46.7 43.1 45.8 52.0 38.3 42.9 47.5 53.6 47.0 44.9 40.9 .. 28.4 32.2 34.4 29.2 45.1

62.9 56.5 49.8 50.7 59.8 43.1 49.2 47.8 61.2 46.6 45.0 46.3 .. 32.7 35.3 36.9 30.3 51.5

65.3 57.9 52.9 54.0 52.2 57.8 52.5 47.5 51.6 51.5 43.0 48.3 44.9 35.1 36.6 36.6 33.8 40.7

57.0 54.0 52.8 50.5 49.5 49.2 48.0 47.0 45.8 44.4 42.0 40.5 39.4 38.1 36.1 35.0 34.9 33.4

Mean

33.1

42.7

47.4

47.9

44.3

Table 5.2 Tax revenues Total taxation as a % of GDP Country

88

1970–1979

1980–1989

1990–1999

2000–2006

Sweden Denmark Belgium Finland France Norway Austria Italy Netherlands United Kingdom Germany New Zealand Canada Australia Ireland Switzerland United States Japan

42.8 40.4 38.3 35.5 35.5 39.2 36.3 25.9 40.0 34.2 34.6 28.6 31.0 24.2 29.1 23.2 25.8 21.9

49.2 45.7 43.2 38.9 41.8 42.5 39.9 33.9 43.6 37.2 35.9 32.7 33.1 28.0 34.3 26.7 26.1 27.6

49.7 48.1 43.5 45.6 43.2 41.1 41.9 40.8 42.3 34.9 36.5 35.5 36.0 28.5 32.8 27.4 28.0 27.2

50.3 48.9 44.9 44.5 43.9 43.1 43.0 41.8 38.3 36.4 35.6 35.0 34.0 30.7 30.1 29.9 27.5 26.8

Mean

32.6

36.7

37.9

38.0


5.1 Government spending and taxation he tables on this page show one method of measuring the size of government: government spending and taxation, by all levels of government, compared with the size of the economy (GDP). By this measure the size of the selected countries’ governments varies considerably, with the largest approaching twice the smallest. The single factor likely to do most to explain differences in size is the comprehensiveness and generosity of countries’ social welfare systems. So Sweden is at the top and Ireland near the bottom. Despite the widespread belief to the contrary, Australians are not heavily taxed. The tables reveal the quite dramatic growth in the size of government throughout the developed world over the 1970s and 1980s, but with little further growth or even some decline since then. Note that for government spending or revenue to rise as a proportion of GDP it must grow at a faster real rate than the economy overall. It can be seen from Table 5.1 that government spending (outlays) grew particularly strongly in the 1970s in all the selected countries and continued growing in the 1980s, though at a somewhat slower rate. In the 1990s, however, the rise in the overall mean was minor and in the 2000s spending declined relative to GDP in almost all countries. This is explained partly by strong growth in GDP (because strong growth leads to declining spending on unemployment and other welfare payments) but more particularly by greater and more effective efforts to restrain government spending. Relative positions changed little, however. The countries that began the period at the bottom of the spending league table – Australia, Switzerland, the United States and Japan – also ended it at the bottom. Australia’s government spending share was particularly low before 1973, but jumped in the 1970s, mainly during the three-year term of the Whitlam Government. Spending continued expanding during the 1980s – though at a rate significantly slower than for most of the

T

other countries – and fell during the strong economic growth of the 2000s, after many years of government concern about the size of budget deficits. Table 5.2 shows that the same story of marked growth in the size of government throughout the developed world can be seen on the revenue side of government budgets. The revenue expansion was greatest in the 1960s and 1970s, the momentum slowing in the 1980s and the 1990s. In the first half of the 2000s further growth was negligible, with almost half the selected countries achieving often significantly slower growth in taxation than in GDP. It is interesting to ponder the relationship between the growth of outlays and that of taxation. Did governments permit their spending to expand because their revenue was growing strongly, or did the public’s demand for greater government spending oblige governments to augment their revenue? The causation is likely to have run in opposite directions at different times. Up to 1973, the steady and uneventful growth in the public’s real incomes, accompanied by moderate but persistent inflation, permitted governments to expand their activities – and both sides of their budgets – with minimal complaint from voters. The high inflation of the 1970s caused rapid growth in income-tax collections as wage earners were pushed into higher tax brackets. This permitted further expansion in government spending, but seems eventually to have provoked widespread resistance to further tax increases as many people became convinced they were now ‘overtaxed’. Governments became increasingly reluctant to risk proposing overt tax increases and were under continuing pressure to limit the effects of ‘bracket creep’ by announcing regular (but short-lasting) ‘tax cuts’. Since then, almost all countries have succeeded in holding down the expansion of taxation as a proportion of GDP, with many managing to achieve slower growth in tax collections than in the economy in the first half of the 2000s.

GOVERNMENT TAXES AND SPENDING

89

Table 5.3 Components of taxation Types of tax revenues as proportion of total tax 2005 Personal income

Corporate income

Social security employees

Social security employers

Payroll

Property

Goods and services

Denmark New Zealand Australia Canada Switzerland United States Sweden Belgium Finland United Kingdom Ireland Italy Austria Germany Norway Japan Netherlands France

53 44 40 37 36 35 32 31 31 29 27 26 23 23 22 18 18 17

8 18 19 11 9 11 8 8 8 9 11 7 6 5 27 16 10 6

2 0 0 6 12 12 6 10 6 8 5 6 16 19 7 18 20 10

0 0 0 8 12 13 21 20 21 10 10 24 19 21 13 19 14 27

0 0 5 2 0 0 5 0 0 0 1 0 6 0 0 0 0 3

4 5 9 10 8 11 3 5 3 12 8 5 1 3 3 10 5 8

32 32 28 25 24 17 26 25 31 30 38 26 28 29 28 19 32 25

Mean

30

11

9

14

1

6

28

Country

The percentages in each row sum to less than 100 because miscellaneous ‘other’ taxes (highest for France and Italy) are omitted.

Table 5.4 Broad components of taxation Direct taxes on individuals

Business and property taxes

Goods and services taxes

Denmark Switzerland United States New Zealand Canada Germany Belgium Australia Austria Netherlands Finland Sweden Japan United Kingdom Ireland Italy Norway France

55 48 47 44 43 42 41 40 39 38 37 37 36 36 32 32 30 27

13 29 36 23 31 28 33 33 32 29 32 36 44 32 30 36 43 44

32 24 17 32 25 29 25 28 28 32 31 26 19 30 38 26 28 25

1970 Mean 2005 Mean

37 39

27 32

31 28

Country

Direct taxes include income tax and employees social security taxes; consumption taxes are the same as Table 5.3; the other four columns are combined under ‘Business and property taxes’. Most percentages do not sum to 100, because miscellaneous ‘other’ taxes are not included, and because of rounding.

90


5.2 Tax methods hereas Table 5.2 showed the levels of total taxation (as a proportion of GDP) in the selected countries, Table 5.3 shows the extent of each country’s reliance on particular types of taxation. It can be seen that, overall, personal income tax – the tax of which people are most conscious – accounts for less than a third of all the tax revenue raised by all levels of government. Taxes on the purchase of goods and services account for less than a third, meaning that a host of less prominent taxes accounts for roughly the remaining third. Table 5.4 reveals that, overall, the broad mix of the main tax types has not changed greatly since 1970 (even though the total amount of taxes raised grew by more than eight percentage points of GDP). Even so, they were years of almost continuous debate about the merits and demerits of particular taxes and endless adjustments and bouts of tax ‘reform’. Taxes can be criticised or supported on grounds of economic efficiency (the extent to which they distort people’s choices about work, consumption, saving or investment), fairness (progressive taxes take a larger proportion of high incomes than of low incomes, whereas regressive taxes do the reverse) and administrative simplicity. Some taxes are more susceptible to evasion (illegal) or avoidance (the exploitation of legal loopholes) than others. The categories in Table 5.4 are too broad to reveal some more subtle trends. One was the tendency for taxes on specific goods and services (including ‘sin’ taxes on alcohol, tobacco and petrol) to be outweighed by general consumption taxes. While the mean for the former fell from 18% to 10% of total tax revenue over the period, the mean for the latter rose from less than 14% to more than 16%. Most European countries have long had general consumption taxes in the form of value-added taxes, and various other countries – New Zealand, Japan, Canada and Australia – have

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joined them more recently with the renamed ‘goods and services tax’ (GST). Australia’s reliance on the taxation of goods and services was about average even before its introduction of the GST, and has not been greatly increased by that introduction. Only the United States now has no national-level general consumption tax, which would do much to explain why it has the lowest reliance – 17% – on the taxing of goods and services. Overall, about 23% of tax revenue is raised via compulsory social security ‘contributions’ from employers and employees, with the less-visible employer contributions exceeding employee contributions by roughly 5:3. While its states’ payroll taxes seemingly give Australia a heavy reliance on ‘payroll and workforce taxes’, in truth employers’ social security contributions are very similar to a payroll tax. Australia and New Zealand are exceptional in not having taxes tied directly to social security. This means that, as a matter of arithmetic, their remaining taxes account for higher proportions of total collections. But the funding of social security payments through general taxation also explains why they are among the countries most dependent on income tax. The high proportion of revenue raised though income tax, the most visible of taxes, may explain why many Australians consider themselves to be heavily taxed, whereas Table 5.2 revealed that they are among the most lightly taxed. It is noteworthy that, when personal income tax and employees’ social security contributions are combined, Australia drops back to the middle of the pack. Table 5.3 reveals that, after Norway, Australia is the country most heavily reliant on corporate income tax. It should be noted, however, that it also has one of the fullest dividend imputation systems, meaning that local shareholders receive an income-tax credit for the full extent of the company tax already paid on their share of company profits.


91

Table 5.5 Government deficits and surpluses Government net lending as a % of GDP Country

1990

1995

2001

2006

Norway Denmark New Zealand Finland Ireland Sweden Australia Switzerland Canada Netherlands Belgium Austria Germany France United States United Kingdom Japan Italy

2.2 −1.3 −4.6 5.4 −2.8 3.4 −2.2 0.6 −5.8 −5.3 −6.7 −2.5 −1.9 −2.4 −4.2 −1.8 2.1 −11.4

3.2 −2.9 2.9 −6.2 −2.1 −7.4 −3.7 −1.2 −5.3 −4.3 −4.4 −5.7 −3.2 −5.5 −3.1 −5.8 −5.1 −7.4

13.3 1.2 2.1 5.0 1.0 1.7 0.1 0.9 0.7 −0.3 0.5 −0.1 −2.8 −1.6 −0.4 0.9 −6.3 −3.1

18.0 4.7 3.8 3.7 2.9 2.3 1.2 1.1 1.0 0.5 0.2 −1.5 −1.6 −2.6 −2.6 −2.8 −2.9 −4.5

−2.2

−3.7

0.7

1.2

Mean

Table 5.6 Government debt General government financial liabilities as a % of GDP Country

1990

1995

2000

2006

Australia New Zealand Ireland Denmark Finland United Kingdom Sweden Netherlands Switzerland Norway United States Austria Canada Germany France Belgium Italy Japan

21.9 .. .. 66.4 16.3 32.9 46.7 87.8 31.1 29.4 63.0 57.2 75.2 40.4 38.6 125.8 97.3 68.6

41.9 51.3 .. 79.3 65.3 52.2 82.0 89.6 47.7 40.9 70.7 69.2 101.6 55.7 62.6 135.3 122.2 87.6

25.0 37.4 40.2 57.1 52.3 45.6 65.7 63.9 52.5 34.1 55.2 69.4 82.1 60.4 65.2 113.4 121.6 136.7

16.1 27.2 29.1 36.0 44.9 46.6 53.9 54.7 56.0 59.6 61.9 65.5 68.1 69.3 70.9 90.1 118.7 179.7

56.2

73.8

65.4

63.8

Mean

92


5.3 Government debt and budget balances hen governments’ revenue exceeds their spending they have a budget surplus, which is available to be lent to the private sector. More commonly over the past 40 years, however, spending exceeded revenue and so governments incurred budget deficits that needed to be covered by borrowing from the private sector. Unlike the pursuit of growth and lower unemployment, the budget balance is not an end in itself, but a means to those ends. Nor can it be assumed that a balanced budget is better than a budget deficit and a budget surplus better still. Because budgets are an instrument of economic management rather than an objective of that management, the desirable size and sign on the budget balance will be a function of where the economy happens to be in the business cycle at the time. The judgement will be influenced also by the degree of investment (as opposed to recurrent) spending included in the budget. Operating (or recurrent) deficits are appropriate – and, indeed, helpful – when economies are entering or leaving recessions, whereas operating surpluses are desirable when economies are growing strongly. Following such a rule will limit the build up of government debt over the medium term, thus ‘reloading the fiscal cannon’ ready for use during the next downturn. However, none of this implies any objection to borrowing to help cover the cost of public works that will deliver benefits over many years. Modest budget balances were typical before the post-war ‘golden age’ ended in the early 1970s, but then the ever-deeper cyclical troughs reached in the world recessions of the mid-1970s, early 1980s and early 1990s led to large deficits, which were reduced only somewhat in the cyclical peaks reached soon before the onset of the next recession. However, Table 5.5 shows how many countries managed to achieve budget surpluses by 2000. They did so partly by the diligence of their ‘fiscal consolidation’ (cuts in spending), but mainly because of the length of the 1990s boom in the United States and world economies.

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It can be seen that, notwithstanding their very high levels of government spending (Table 5.1), the Scandinavian countries have generally managed to avoid running budget deficits – though Norway’s remarkable story of almost continuous surpluses is explained by its prudence in salting away for the future part of the proceeds from its exploitation of North Sea oil deposits. At the other end of the spectrum, several of the core countries of the European Union have been running large budget deficits almost continuously despite their mature economies and relatively old populations. Japan’s budgetary performance deteriorated markedly during the 1990s as it repeatedly sought to use fiscal stimulus to lift itself from its post-bubble deflation. Australia’s performance was worse than average until the mid-1980s, but better than the mean since then as first the Hawke Government and then the Howard Government emphasised fiscal consolidation. Clearly, when governments run budget deficits their borrowing to cover those deficits adds to the stock of their debt, whereas budget surpluses are used to repay debt. Thus the ranking of budget balances shown in Table 5.5 correlates well with the ranking of government debt shown in Table 5.6. It can be seen from the latter table that, overall, debt levels grew significantly as a result of the big budget deficits incurred during the recession of the early 1990s, but then fell back significantly as a result of the widespread budget surpluses achieved in the second half of the 1990s and the first half of the 2000s. Debt levels continued growing in both Germany and France, however, and – despite some retrenchment – remained worryingly high in Italy and Belgium. The recent explosive growth in Japan’s debt is apparent. The United States’ low level of taxation (Table 5.2) is partly explained by its generally above-average budget deficits. Finally, Table 5.6 shows that despite Australia’s preoccupation with reducing budget deficits, government debt has been particularly low.


93

Chapter 6 HEALTH

Table 6.1 Health spending Total spending on health as a % of GDP Country

1960

1970

1980

1990

2000

2006

United States Switzerland France Germany Belgium Austria Canada Netherlands Sweden Italy Denmark Australia Norway United Kingdom Finland Japan New Zealand Ireland

5.1 4.9 4.2 4.8 3.4 4.3 5.4 3.9 4.7 3.6 3.6 3.8 2.9 3.9 3.9 3.0 4.3 3.8

6.9 5.6 5.8 6.3 4.1 5.3 7.0 7.5 6.7 5.2 6.5 5.0 4.4 4.5 5.7 4.5 5.1 5.1

8.7 7.6 7.4 8.8 6.4 7.5 7.2 7.5 9.1 7.0 6.8 6.3 7.0 5.7 6.4 6.5 6.0 8.7

11.9 8.5 8.8 8.7 7.4 8.4 9.0 8.0 8.5 8.1 8.4 6.9 7.8 6.0 7.9 6.1 7.0 7.0

13.1 10.7 9.3 10.6 8.7 9.9 9.2 8.6 8.4 8.2 8.3 8.3 7.7 7.3 6.7 7.6 8.0 6.4

15.3 11.3 11.0 10.6 10.3 10.1 10.0 9.5 9.2 9.0 8.8 8.7 8.7 8.4 8.2 8.1 8.0 7.5

Mean

4.1

5.7

7.4

8.0

8.7

9.6

Table 6.2 Increases in health expenditure Average real per person annual compound growth rate in expenditure, 1970–2005 Country

1970–1980 1980–1990 1990–2000 2000–2005

Ireland Finland Belgium Netherlands Sweden United Kingdom United States New Zealand Canada Denmark Australia Norway France Switzerland Italy Japan Austria Germany

8.5 4.5 8.1 .. 4.4 4.1 4.4 2.0 3.0 .. .. 9.1 5.4 4.2 6.3 7.0 7.4 6.1

1.1 4.8 3.4 2.2 1.0 3.1 5.5 2.7 4.0 0.8 2.7 3.1 3.6 2.8 3.6 2.7 1.4 2.1

6.6 0.1 3.5 2.4 0.0 3.8 3.2 2.9 1.8 1.7 3.1 2.8 2.3 2.5 1.4 3.9 3.1 2.1

9.3 5.8 5.3 5.1 4.5 4.5 4.2 3.9 3.8 3.8 3.3 3.2 3.0 2.6 2.5 2.4 1.8 1.2

Mean

5.6

2.8

2.6

3.9

Figure 6.1 Per capita funding of health $US PPP 2005 New Zealand Japan Italy Finland Denmark United Kingdom Ireland Australia Netherlands Sweden Mean Germany France Belgium Austria Canada Switzerland Norway United States

0

94


1000

2000

3000

4000

5000

6000

7000

6.1 Total health spending f you wonder why arguments about the funding of health care are rarely out of the news, Table 6.1 offers a big clue. Spending on health – by governments, private organisations and individuals – has grown rapidly and relentlessly in recent decades. Table 6.1 shows how, expressed as a proportion of national income (GDP), health spending more than doubled in the selected countries over the last 40 years of the 20th century, and kept on climbing in the first years of the 21st century. It should be remembered that when spending on any item rises over time as a proportion of GDP, this means it is growing at a faster real rate than the overall economy. Thus the increases revealed by Table 6.1 are even more notable than they may at first seem. It is undoubtedly true that health spending has increased because of general inflation and because of growing populations. But those two factors do not explain the rise in health spending’s share of GDP because the comparison with GDP effectively takes account of inflation and population growth. So the growth rate shown in Table 6.2, which again controls for inflation and population growth, shows that real spending per person grew rapidly in each of the periods. On average, the rate of growth was fastest in the 1970s, rather more constrained in the next two decades, and has accelerated again in recent years. Many factors are driving the rise in health spending. One is the good news on greater life expectancy, reported in Chapter 1 and explored further later in this chapter. Although there is no correlation between amounts spent on health and the age profile of these societies, other OECD data suggests that on average health expenditure for those over 65 is considerably greater than for those under 65. So future increases in demand are likely as the proportion in older age groups increases. A central driver of increased expenditure is the introduction of new goods and services – new drugs and surgical procedures,

I

for example. New technologies allow medicine to expand into areas where effective treatments were not previously possible. These typically produce better outcomes, but often also increase costs. The tables also show how much faster the growth has been in some countries than others. In every country, health spending has been commanding a bigger share of the national income, but the spread has become ever greater. By 2006 the biggest spending country, the United States, spent double the proportion of GDP that bottom-spending Ireland did. Remembering that the United States has the largest economy in the world, a greater share of its GDP translates into an even greater contrast in spending per person. Figure 6.1 shows that in spending per person, with exchange rates adjusted for spending power, the United States spends more than double the average of the selected countries, one-third more than the second-ranking country, Norway, and threeand-a-half times the bottom-ranking spender, New Zealand. The huge increase in expenditures on health means it has become an increasing concern for governments and individuals. It poses the question of whether it is unconstrained costs that are driving up health spending or whether it comes from increasing demands – more comprehensive and better services provided to more of the population. In the following pages, it will be interesting to trace whether countries’ relative spending on health is reflected in resources, services and outcomes. One group of American health economists observing America’s higher spending but its sometimes lower availability of health services concluded: ‘It’s the prices, stupid.’ By itself an increase in health spending is neither a good nor a bad thing. Rather, that spending must be related to needs and outcomes. Balancing the many demands for increased health funding against optimal health outcomes will continue to be a vexed policy issue in all the selected countries.

HEALTH

95

Table 6.3 Public expenditure on health Public health expenditure as a % of GDP Country

1960

1970

1980

1990

2000

2006

France Germany Denmark Austria Sweden United Kingdom Norway United States Canada Italy Switzerland Japan New Zealand Finland Ireland Australia Netherlands

2.4 .. .. 3.0 .. 3.3 2.2 1.2 2.3 .. .. 1.8 .. 2.1 2.8 1.9 ..

4.1 4.4 6.6 3.3 5.8 3.9 4.0 2.5 4.8 .. .. 3.2 4.2 4.1 4.1 2.8 4.1

5.6 6.6 7.9 5.1 8.2 5.0 5.9 3.6 5.3 .. .. 4.7 5.2 5.0 6.8 3.9 5.1

6.4 6.3 6.9 6.1 7.4 5.0 6.3 4.7 6.6 6.1 4.3 4.6 5.7 6.2 4.4 4.6 5.4

8.0 8.2 6.8 7.5 7.0 5.8 6.9 5.8 6.2 5.8 5.7 6.2 6.0 5.1 4.6 5.5 5.0

8.8 8.1 8.0 7.7 7.5 7.3 7.3 7.0 7.0 6.9 6.8 6.5 6.3 6.2 5.9 5.9 5.5

Mean

2.3

4.1

5.6

5.7

6.2

7.0

No data on Belgium.

Table 6.4 Private share of health funding Percentage of health funding from private sources Country

1970

1980

1990

2000

2006

United States Switzerland Netherlands Australia Canada Belgium Austria Finland Germany Italy Ireland New Zealand France Japan Sweden Denmark Norway United Kingdom

64 .. .. 40 30 .. 37 26 27 .. 18 20 .. 30 14 16 8 13

59 .. 31 37 24 .. 31 21 21 .. 18 12 .. 29 8 12 15 11

60 48 33 33 26 .. 27 19 24 21 28 18 23 22 10 17 17 16

56 44 37 31 29 29 30 25 25 27 27 22 24 22 15 18 15 19

54 40 38 32 30 25 24 24 23 23 22 22 20 19 18 17 16 12

Mean

26

23

26

27

25

Table 6.5 Out-of-pocket payments for health Out-of-pocket payments as a % of total health expenditure 2006 Country Switzerland Belgium Italy Finland Australia Austria Norway New Zealand Japan Canada Denmark Germany United States Ireland United Kingdom Netherlands France

30.3 20.9 20.2 18.7 18.2 16.5 15.6 15.4 15.1 14.5 14.3 13.2 12.8 12.4 10.9 9.0 6.7

Mean

15.6

No data on Sweden.

96


%

6.2 Public and private health spending he inexorable rise in health spending puts pressure on funding sources. It has become an increasingly important part of the government budget in all the selected countries. Table 6.3 shows that public sector health expenditure as a percentage of GDP all but trebled in the selected countries between 1960 and 2006. The countries are rather more closely grouped in public spending than in the wide spread of total health spending displayed in Table 6.1 on the previous page. In 2006, all the selected countries are within plus or minus two percentage points of the mean. All the countries have some mix of public and private funding. To a large extent, this reflects their more general approaches to the public provision of services, so that it is not surprising in Table 6.4 to find the United States has the largest share of private funding and the Scandinavian countries near the bottom of the table. It is perhaps more surprising to see Britain having the smallest share of private funding, but this shows the strength and popularity of their national health service. Table 6.4 shows that a high degree of public funding – not to mention actual public provision of services and government regulation of the whole sector – is the norm for health care systems in the selected countries. In all the selected countries, except the United States, the majority of health funding is from the public purse, and indeed in most of them private funding provides less than a quarter of total funding. Over recent decades, the average proportion of funding coming from the private sector has barely changed. In contrast to education, for example, Australia’s share of private funding fell during the period. However, while Australia falls just under the mean in total health funding in Table 6.1, it is towards the bottom of Table 6.3 in the commitment of public funds to health, and is still in the top quarter of countries in terms of the proportion of private spending.

T

Health care can be catastrophically expensive for an individual, and much of the need for it is unpredictable. Both public funding and private insurance schemes are designed to protect people from having to choose between financial ruin and loss of health. Public funding can allow for treatment to be matched to need rather than ability to pay. However, governments are often not willing to pay for all health care. Some critics argue that government provision of health care leads to over-servicing and abuse, while others argue that for budgetary reasons governments too often refuse to fund health at the needed levels. The commitment of private funds to health care does not seem to slow the growth of public funds going to health, however. No matter to what extent they rely on public funding or on private insurance arrangements, all funding systems call on individuals to supplement this with direct payments. Outof-pocket payments annoy the public but are beloved by economists, who believe they discourage overuse of services that otherwise appear to be ‘free’. It can be seen from Table 6.5 that, for the most part, such payments account for only a small proportion of total spending. Interestingly, the rankings in Tables 6.4 and 6.5 show only a modest correlation. Partly because of the potentially catastrophic nature, in many countries the private funding of health is carried out more through private insurance contributions, where the individual or his/her employer pays a premium, and particular payments are made by the insurer, rather than in direct out-of-pocket payments by the recipient. This is especially true of the United States, while in other countries, nearly all private payments are made directly by the recipient. Private insurance as a major means of funding has its own dynamics, rather different from the universalism of public funding and from the direct market disciplines and constraints of out-of-pocket payments.

HEALTH

97

Table 6.6 Doctors Number of doctors per 1000 population Country

1960

1970

1980

1990

2000

2006

Belgium Netherlands Switzerland Italy Norway Austria Germany Sweden France Denmark Ireland Australia Finland United Kingdom United States New Zealand Canada Japan

1.3 1.1 1.4 0.7 1.2 1.4 1.4 1.0 1.0 1.2 1.0 1.1 0.6 0.8 1.4 1.1 1.2 1.0

1.5 1.2 1.5 1.1 1.4 1.4 1.6 1.3 1.3 1.4 1.2 1.2 0.9 0.9 1.6 1.1 1.5 1.1

2.3 1.9 2.4 2.7 2.0 1.6 2.3 2.2 2.0 2.2 1.3 1.8 1.7 1.3 2.0 1.6 1.8 1.3

3.3 2.5 3.0 .. 2.6 2.2 2.8 2.9 3.1 3.1 1.6 2.2 2.4 1.5 2.4 1.9 2.1 1.7

3.9 3.2 3.5 4.1 2.9 3.1 3.3 3.0 3.3 3.4 2.2 2.4 3.1 2.0 2.7 2.2 2.1 1.9

4.0 3.8 3.8 3.7 3.7 3.6 3.5 3.5 3.4 3.3 2.9 2.8 2.7 2.5 2.4 2.3 2.1 2.1

Mean

1.1

1.3

1.9

2.4

2.9

3.1

Table 6.8 Expenditure on pharmaceuticals Expenditure on pharmaceuticals as a % of GDP Country

1980

1990

2000

2006

13.6 6.0 .. 10.9 6.3 5.2 3.1 3.1 4.3 4.2 5.0 2.4 4.6 .. .. 1.9

14.4 7.1 5.0 11.4 8.0 5.4 4.2 4.0 5.6 4.9 5.2 3.2 4.8 .. 3.7 2.6

13.8 7.7 5.7 5.3 6.8 5.9 5.9 6.1 6.7 5.5 6.1 3.9 5.5 .. .. 2.8

14.4 7.9 6.9 7.2 6.1 6.7 6.9 6.4 6.3 5.9 5.3 4.3 3.7 .. 4.4 2.9

13.7 7.5 7.5 7.0 7.0 6.7 6.4 6.1 5.9 5.6 5.1 4.3 4.0 3.4 3.2 2.8

5.0

6.0

6.2

6.3

6.0

Mean

No recent data on Ireland or Norway.

1980

1990

2000

2006

1.9 1.8 1.8 1.7 1.7 1.6 1.6 1.3 1.2 1.2 1.2 1.2 1.2 1.0 0.8 0.7 ..

Norway Ireland Belgium Denmark Switzerland United Kingdom Sweden United States New Zealand Germany Australia Japan Canada Netherlands Finland France Austria Italy

.. .. .. .. .. 10.3 7.0 .. 6.1 .. 10.3 4.1 9.6 .. .. 4.6 .. ..

.. 11.3 .. .. .. 7.9 9.2 .. 9.3 .. 11.6 5.8 11.1 .. 4.4 5.4 .. ..

.. 14.0 .. 12.4 12.9 11.3 9.9 10.2 9.6 9.4 10.0 7.6 10.1 .. 6.1 6.5 7.1 5.2

31.6 15.4 14.8 14.3 14.1 11.9 10.7 10.5 10.0 9.8 9.7 9.3 8.8 8.6 8.3 7.6 7.3 7.1

1.4

Mean

6.6

9.2

9.9

11.7

2000

2006

United States France Italy Belgium Canada Germany Japan Austria Australia Finland New Zealand Sweden Switzerland Netherlands Denmark Norway United Kingdom

0.8 .. .. 1.1 0.6 1.2 1.4 .. 0.6 0.7 0.7 0.6 .. 0.6 0.6 0.6 0.7

1.1 1.4 1.7 1.2 1.0 1.2 1.3 .. 0.7 0.7 1.0 0.7 0.9 0.8 0.6 0.6 0.8

1.6 1.9 1.8 1.4 1.4 1.4 1.2 1.2 1.1 1.0 1.1 1.2 1.1 0.9 0.7 0.8 1.1

Mean

0.8

1.0

1.2


1970

Japan Belgium Denmark Germany Italy Austria France Australia Canada Netherlands United Kingdom Finland United States Switzerland New Zealand Sweden

Country

1990

98

Country

Table 6.9 Nurses Practising nurses per 1000 population

1980

No data on Ireland.

Table 6.7 Public consultations with doctors Average number of visits per person per year

6.3 Doctors, nurses and drugs he tables on the accompanying page show one strong reason for the growth in health spending and the selected societies’ improved health status. As Table 6.6 shows, in the selected countries overall, the number of doctors in relation to population almost trebled between 1960 and 2006. While the countries seem fairly closely grouped, within plus or minus one percentage point around the mean of 3.1 doctors per 1000 people, the gap between the top half with 3.5 or more and the bottom quarter with 2.4 or fewer would still have substantial implications for the availability and cost of health care. In general the mainland European countries have relatively more doctors and the English-speaking countries and Japan relatively fewer. OECD research found that, after controlling for risk factors in the population, higher doctor numbers were significantly associated with lower premature mortality. But, also according to the OECD, there is no simple relationship between the number of doctors in a country and its total spending on health. Doctor numbers aren’t high in the United States, for instance. Of course, the number of visits to doctors per person will be a factor affecting costs, but methods of doctor remuneration – government salary versus private fee-forservice – are a more significant influence on total spending. Although the data may be less reliable, Table 6.7 suggests that visits to the doctor have not risen by as much as the number of doctors. Australia presents something of an exception, because the number of consultations with a doctor there broadly doubled between 1970 and 2006, although the number has been fairly constant since 1990. It only puts Australia in the mid-range of countries, however. The outlier is Japan. The average Japanese has twice as many consultations with a doctor each year as the average from the other countries, even though Japan has a lower density

T

of doctors than any of the countries, meaning that either Japanese doctors work long hours or their consultations are very efficient. Moreover, as we saw in chapter 1, the Japanese top the longevity league tables, perhaps partly due to their relative lack of obesity (see section 6.11 below), and despite the fact that Japanese males have the highest smoking rates among the selected countries (section 6.12). The high rate of consultations is also consistent with a Japanese propensity to hypochondria. According to other OECD health data, when surveyed about their health, around 80% of the people in the other selected countries report it is good or very good, but only 42% of Japanese put themselves in those categories. The largest group in the health labour force is nurses. On average the countries have threeand-a-half times as many nurses as doctors, but the somewhat incomplete data in Table 6.9 shows their number has been growing at a much slower rate than for doctors, edging rather than shooting up. By far the largest density of nurses is in Norway, more than double the next highest country, but there is no data for years before 2006, so there may be issues of comparability. The rankings in Tables 6.6 and 6.9 show little association, and the relative positions may indicate different priorities and practices in health spending between the selected countries. Within the fast-growing health sector, the quickest growing area of spending is on pharmaceuticals. Table 6.8 charts its steady rise both generally and in Australia. Australians now spend double the proportion of GDP on drugs that they did in 1980. The rise has been universal, although fastest in the leading nation, the United States. However, it is not a distant outlier here, with France and Italy just behind. The data do not allow us to distinguish whether their higher expenditure is because they take more medicines, or because the ones they take cost more.

HEALTH

99

Table 6.10 Acute care hospital beds Acute care hospital beds per 1000 population Country

1980

1990

2000

2006

Japan Germany Austria Belgium France Australia Switzerland Italy Finland Denmark Netherlands Norway Canada Ireland United States Sweden United Kingdom New Zealand

.. 7.7 .. 5.5 6.2 6.4 7.1 7.9 4.9 5.3 5.2 5.2 4.6 4.3 4.4 5.1 3.6 ..

12.3 7.5 7.1 4.9 5.2 4.4 6.5 6.2 4.3 4.1 4.3 3.8 4.0 3.2 3.8 4.1 2.9 8.3

.. 6.4 6.2 4.6 6.7 3.8 4.1 4.3 2.4 3.3 3.5 3.1 3.2 3.0 2.9 2.4 3.9 ..

8.2 6.2 6.1 4.3 3.7 3.5 3.5 3.3 3.1 3.0 3.0 3.0 2.8 2.8 2.7 2.2 2.2 ..

Mean

5.6

5.4

4.0

3.7

Table 6.11 Average length of stay in hospital Mean days per patient admitted to acute care Country

1980

1990

2000

2006

Japan Germany Switzerland Belgium United Kingdom Canada Italy Ireland Netherlands Australia Austria United States France Norway New Zealand Finland Sweden Denmark

.. 14.5 15.5 10.0 8.5 10.2 .. 8.5 14.0 7.7 14.5 7.6 15.9 10.9 .. 8.8 8.5 8.5

.. 14.1 13.4 8.7 5.7 8.6 9.5 6.7 11.2 6.5 9.3 7.3 10.6 7.8 .. 7.0 6.5 6.4

.. 9.6 9.3 8.0 6.9 7.2 7.0 6.4 9.0 6.1 6.3 5.8 8.5 6.0 4.9 4.4 5.0 3.8

19.2 8.5 8.2 7.7 7.5 7.2 6.7 6.6 6.6 6.0 5.8 5.6 5.4 5.0 .. 4.8 4.6 3.5

Mean

10.9

8.7

6.7

6.9

Table 6.12 Hospital bed days Days per person per year spent in an acute care hospital

Table 6.13 All hospital beds Hospital beds of all types per 1000 population

Country

Country

1980

1990

2000

2005

.. .. .. 11.1 .. .. 9.1 9.7 7.8 8.1 .. .. 7.2 6.8 6.0

.. 10.1 10.2 9.7 7.7 .. 8.0 5.9 7.2 4.9 5.6 .. 4.6 6.5 6.0 4.9

14.7 9.1 8.6 8.1 7.8 7.5 6.3 5.2 4.7 4.0 4.3 4.1 3.8 4.1 3.8 3.5

14.1 8.5 7.7 7.5 7.4 7.0 5.6 4.5 4.0 3.9 3.7 3.7 3.6 3.6 3.4 3.2

8.2

7.0

6.2

5.7

1980

1990

2000

2005

Netherlands United States Canada Finland Ireland Italy Norway United Kingdom Denmark Australia France Switzerland Belgium Austria Germany Japan

1.6 1.2 1.6 .. 1.3 1.9 1.6 0.9 1.5 1.6 1.8 2.0 1.7 2.6 .. ..

1.2 0.9 1.4 1.1 1.0 1.6 1.1 0.9 1.2 1.2 1.5 1.9 1.5 2.3 2.6 ..

0.8 0.7 1.0 0.9 0.9 1.1 0.9 0.9 1.0 1.0 1.1 1.3 1.4 1.9 2.0 2.4

0.7 0.7 0.9 0.9 0.9 0.9 0.9 0.9 1.0 1.0 1.0 1.1 1.2 1.8 1.8 2.1

Japan Germany Austria France Belgium Finland Ireland Netherlands Italy Australia Denmark United Kingdom Norway Switzerland Canada United States

Mean

1.6

1.4

1.2

1.1

Mean

No data on New Zealand; no recent data on Sweden; Denmark 2005 figure is for 2000.

100


No data on New Zealand or Sweden.

6.4 Hospitals aken in isolation, the tables opposite about hospitals would not lead one to think there had been a great increase in health expenditure, rather the opposite. The number of acute care beds relative to population (Table 6.10) and of all hospital beds (Table 6.13) has declined; the average length of stay in hospital has decreased substantially (Table 6.11); and the average number of bed days each person spends in hospital has declined (Table 6.12). In sum, the tables on hospital resources and hospital care suggest reductions rather than increases. The possible reasons for this relative decline are several. One is the vigorous efforts by governments and health authorities to limit ever-spiralling health costs. The rather limited OECD data on the percentage of health expenditure devoted to in-patient care suggest that until 1980 hospital spending was rising more rapidly than general health spending but since then has been growing less rapidly. A central reason has been the considerable reduction in average length of stay in hospital, and this has been an important factor in the other reductions. Average length of stay in hospital is often used as an indicator of efficiency. Like all such indicators, however, it is far from foolproof and is open to abuse. If hospital stays are too short, the comfort or recovery of patients may be compromised, and shorter stays may transfer costs to other parts of the health system or onto the patients and their families. On the other hand, the reasons for shorter stays in hospital also include technological advances in anaesthetics, the development of less-invasive surgical techniques, and improved pre- and post-operative treatment regimes. One reason for the reduction in Table 6.14 is that there is a growing category not figuring in these figures. An increasing number of procedures, including surgical procedures, are conducted on a same-day, out-patient basis. The Australian Institute of Health and Welfare reported that in 1996, there were 159 acute care admissions per 1000 people in Australia,

T

but that number would have jumped to 288 if same-day admissions were included. While eight countries, including Australia, have between three and four acute care hospital beds per 1000 people, Table 6.10 shows both three countries with more than six – Japan, Germany and Austria – and five others with fewer than three. Australia is similarly close to the mean for average length of stay in hospital, with the Nordic countries having the shortest stays, and by a very long distance the Japanese having the longest. Japan and the German-speaking countries also have more of their population spending time in hospital in Table 6.12. Some at least of the apparent national differences are probably due to definitional differences. In theory, acute care beds should only include those intended for curative care. This covers the reasons for which most patients are admitted to hospital – childbirth, performing surgery, curing illness or providing definitive treatment of injuries, and performing diagnostic or therapeutic procedures. It generally does not include long-term care, or those residing in nursing homes. There are, however, counting issues of when acute care becomes long-term care. Table 6.13 gives data on hospital beds of all types (not including nursing homes, but including for example psychiatric care and some types of more chronic care). These also show the decline in beds in relation to population. The rankings here are somewhat similar to Table 6.10, with Japan, Germany and Austria at the top, and this time the North Americans in the rear. In contrast to the other tables, Australia is here clearly below the mean. Probably, in all these tables, although there are substantial national contrasts, the more fundamental fact is the shared downward trend. The reductions derive from improved procedures but there are many complaints of inadequate resources. For all the selected countries, balancing financial pressures against the accessibility and quality of hospital care will continue to be a critical issue.

HEALTH

101

Table 6.14 Magnetic resonance imaging units Number of units per million population Country

Table 6.15 Dialysis Patients undergoing dialysis per 100 000 population Country

1990

1995

2000

2006

Japan United States Austria Finland Italy Switzerland Denmark Ireland Germany Belgium Netherlands Canada United Kingdom France Australia New Zealand Norway Sweden

6.1 3.7 .. 1.8 1.3 3.9 2.5 0.3 1.9 2.0 1.3 0.7 1.0 0.8 0.6 .. 0.7 1.5

18.8 6.8 .. 4.3 3.0 9.8 .. .. 4.8 3.2 3.9 1.3 2.9 2.1 2.9 .. .. 6.8

23.2 8.1 10.8 9.9 7.5 12.9 6.6 .. 6.2 3.2 .. 2.5 4.6 2.6 4.7 2.6 .. 7.9

40.1 26.5 16.8 15.2 15.0 14.0 10.2 9.7 7.7 7.1 6.6 6.2 5.6 5.3 4.9 3.7 .. ..

Mean

1.9

5.4

7.6

12.2

1970

1980

1990

2000

2006

United States Austria Norway France Finland Sweden Netherlands Belgium Canada Ireland Germany Switzerland United Kingdom Denmark Australia Italy New Zealand Japan

.. 0.2 0.5 0.3 0.2 1.8 0.5 0.7 .. 0.2 0.1 0.8 0.4 2.5 1.5 0.0 .. ..

2.1 1.2 2.0 0.9 2.8 2.9 1.6 1.5 .. 1.2 0.9 2.5 1.6 2.0 2.4 0.4 1.6 0.2

3.8 5.5 4.8 3.4 2.5 3.9 2.9 3.9 3.0 3.9 2.5 3.3 3.2 3.6 2.6 0.6 3.0 0.6

4.8 4.9 4.3 3.3 3.7 3.2 3.5 4.0 3.8 3.4 2.7 3.5 2.9 2.9 2.8 2.3 2.8 0.6

5.7 5.2 5.0 4.5 4.0 4.0 3.8 3.7 3.7 3.5 3.4 3.4 3.4 3.2 3.1 2.9 2.3 0.9

Mean

0.7

1.6

3.1

3.3

3.7

102


1980

1990

2000

2006

0.9 .. 1.6 0.6 .. 2.0 2.2 3.5 1.0 2.1 1.8 1.7 1.6 3.2 1.5 0.4 2.7 3.3

31.3 21.4 17.6 16.8 13.2 15.7 18.4 14.5 10.4 10.1 10.0 6.8 5.2 11.9 4.4 3.9 9.0 16.2

83.6 51.7 29.7 25.6 21.9 26.1 23.6 .. 25.1 19.4 17.3 15.5 9.0 21.0 12.4 5.8 14.1 24.4

162.4 86.5 64.0 31.6 47.3 32.9 37.0 16.8 37.1 38.7 33.4 27.4 9.9 28.2 22.9 6.1 25.4 26.5

207.0 114.7 80.1 71.3 62.8 60.0 59.1 47.6 46.9 46.8 44.6 38.9 35.4 32.2 28.8 .. .. ..

Mean

1.9

13.2

25.1

40.7

65.1

Table 6.17 Births by caesarean section Number per 1000 live births

Table 6.16 Kidney transplants Kidney transplants per 100 000 population Country

1970

Japan United States Germany Italy Canada Belgium France New Zealand Austria Denmark Australia United Kingdom Ireland Netherlands Finland Norway Sweden Switzerland

Country

1985

1990

1995

2000

2006

Italy Australia United States Switzerland Germany Canada Ireland Austria New Zealand United Kingdom Denmark Belgium France Sweden Finland Norway Netherlands

158 150 .. 198 .. .. 77 .. .. 106 133 94 .. 121 148 120 65

208 175 227 186 157 .. 105 .. 121 124 .. 105 139 108 142 128 74

261 192 208 .. 172 175 .. 124 151 158 .. 135 150 120 155 126 97

333 217 211 .. 209 205 204 172 202 170 145 159 171 144 157 137 129

394 300 291 288 278 262 251 244 239 233 194 178 178 172 160 152 136

Mean

125

143

159

185

232

No data on Japan.

6.5 Medical technology ealth care is a very technologically dynamic area, subject to continuous research and improvements in treatment. While the advances in medical procedures rightly produce widespread appreciation, there is also an ongoing debate about whether sometimes they are prolonging the quantity of life, but it is spent without quality. Are such technologies increasing the cost of health care more than the benefits they deliver? The tables on this page cannot resolve such issues, but they do offer some prime examples of the rapid take-up of life-saving and life-enhancing (but expensive) technological advances in recent decades. End stage renal failure is a condition where a person’s kidneys are permanently impaired, often associated with diabetes and hypertension, and so on the increase in the selected countries. The major way of treating it is through dialysis. More rarely – largely because of a shortage of donors – it is treated with a kidney transplant, but then successful patients are able to live normally again. Table 6.15 shows a marked and continuing growth in the use of kidney dialysis machines in the selected countries since 1970. The takeup varies widely between countries, with the Japanese and then the Americans the clear leaders. Australia, the United Kingdom and several European countries are well below the mean. To some extent, the rankings correlate with total health spending and with the countries which have most emphasis on technological innovation. Table 6.16 shows the strong and widespread growth in kidney transplant operations since 1970. Again the United States is the leader, but this time Japan is at the bottom of the table. To an extent, Japan’s pre-eminence in dialysis is a result of its citizens’ distaste for transplant operations. Australia got an early start, but its growth has not kept up with other countries and is now below the overall mean. The number of kidney transplants per 100 000 population fell in almost half the selected countries during the 1990s. The growth

H

of transplant operations has not been as rapid or continuous as some of the other procedures, perhaps due to a lack of donors. Heart transplants – perhaps the epitome of the modern medical miracle – have never become a widespread procedure, and OECD data shows that rates fell in the 1990s, probably because of doubts about its cost effectiveness. Diagnostic technologies have also been improving and diffusing rapidly. Table 6.14 traces the rise of one important example, the rapid spread of magnetic resonance imaging (MRI) machines during the 1990s. MRI machines produce anatomical images in 3-D. Unlike conventional radiography or computer assisted tomography (CAT) scans, they do not expose patients to ionising radiation, and at the same time they offer more functionality. Australia ranks substantially below the mean here, but part of the reason (only part) is that for some reason the statistics only cover those eligible for Medicare reimbursement. In 1999 this comprised about 60% of the total MRI units. So again doubts about comparability inhibit precise comparisons, but the general trend is clear and dramatic. Table 6.17 reports yet another remarkable change: the large growth in rates of birth by caesarean section since 1985. Across the selected countries the growth has been almost universal and continuous, but again with noteworthy divergences. Italy has a rate double that of the bottom-ranking countries. Australia has had the second-sharpest rise. What drives this remarkable growth? Has it resulted in significantly reduced risks for babies and their mothers? It is good if countries’ higher incomes have allowed them to afford to satisfy a genuine need that formerly went unsatisfied. On the other hand, has the rapid growth occurred because of overservicing by doctors, or to suit the convenience of hospitals? Considering the speed of change and the range of differences, it is hard to believe that all the increase is explained solely by a need to improve the safety of mothers and babies.

HEALTH

103

Table 6.18 Infant mortality Deaths per 1000 live births

Table 6.19 Maternal mortality Deaths per 100 000 live births

Country

1900

1925

1950

1975

2000

2006

Country

1960

1970

1980

1990

2000

2006

Japan Finland Sweden Norway Austria Belgium Ireland Denmark France Germany Italy Netherlands Switzerland Australia United Kingdom New Zealand Canada United States

155 153 99 91 231 172 109 128 162 229 174 155 150 83 148 62 .. 142

142 85 56 50 119 100 68 80 89 105 119 58 58 53 79 40 102 72

60 44 21 28 66 53 45 31 52 60 64 25 31 25 31 28 41 29

10 10 9 11 21 15 17 10 14 19 21 11 11 14 16 16 16 16

3.2 3.8 3.4 3.8 4.8 4.8 6.2 5.3 4.6 4.4 4.5 5.1 4.9 5.2 5.6 5.8 5.3 6.9

2.6 2.8 2.8 3.2 3.6 3.7 3.7 3.8 3.8 3.8 3.9 4.4 4.4 4.7 5.0 5.2 5.4 6.9

Ireland Belgium Austria Italy Australia Norway Japan Canada Sweden Germany Finland New Zealand France United Kingdom Denmark Netherlands Switzerland United States

.. .. 87.3 .. 52.5 .. 130.6 45.0 .. 106.3 71.8 .. .. 47.0 .. 38.9 .. 37.1

31.1 20.4 25.8 54.5 25.6 10.8 52.1 20.0 10.0 51.8 12.4 .. 28.2 24.0 8.5 13.4 25.2 21.5

6.8 5.6 7.7 12.8 9.8 11.8 20.5 8.0 8.2 20.6 1.6 13.8 12.9 11.0 1.8 8.8 5.4 9.2

3.8 3.2 6.6 8.6 6.1 3.3 8.6 2.5 3.2 9.1 6.1 6.6 10.4 8.0 1.6 7.6 6.0 8.2

1.8 5.6 2.6 2.7 6.0 3.4 6.6 3.4 4.4 5.6 5.3 7.0 7.4 7.0 7.4 8.7 3.8 9.8

0.0 2.5 2.6 3.4 3.5 3.5 4.9 5.9 5.9 6.1 6.8 6.8 7.0 7.2 7.7 8.1 8.2 15.1

Mean

144

82

41

14

4.8

4.1

Mean

63.7

25.6

9.8

6.1

5.6

5.8

Table 6.21 Healthy life expectancy Healthy life expectancy in years 2001

Table 6.20 Life expectancy at 60 Average further years of life expectancy of males and females at age 60 Females 1970

Females 2006

Males 1970

Males 2006

Japan France Switzerland Italy Australia Finland Canada Norway Sweden New Zealand Belgium Austria Germany Ireland Netherlands United States United Kingdom Denmark

19.3 20.8 20.4 20.2 19.4 18.3 21.4 21.0 20.9 19.8 19.3 18.8 18.8 18.7 20.1 20.7 19.8 20.6

27.9 27.0 26.5 25.9 25.8 25.5 25.3 25.1 25.0 24.9 24.9 24.9 24.8 24.5 24.4 24.0 23.7 23.3

15.9 16.2 16.7 .. 15.0 15.0 .. 17.3 17.8 15.7 15.3 14.9 15.2 15.6 16.5 16.1 15.2 17.1

22.4 22.0 22.5 .. 22.3 20.6 21.8 21.7 21.7 22.1 20.8 21.0 21.1 20.8 20.8 20.8 20.9 20.0

Mean

19.9

25.2

16.0

21.1

Country

104


Country

Males

Females

Japan Switzerland France Australia Sweden Austria Italy Finland Germany Norway Belgium Canada New Zealand Netherlands United Kingdom Denmark Ireland United States

71.4 71.1 69.0 70.1 70.5 68.9 69.2 67.7 68.3 69.3 67.7 68.2 69.1 68.7 68.4 69.3 67.6 66.4

75.8 74.4 73.5 73.2 73.2 73.0 72.9 72.5 72.2 72.2 71.8 71.6 71.5 71.1 70.9 70.8 70.4 68.8

Mean

68.9

72.2

6.6 Improved life expectancy ne central reason that life expectancy has increased so dramatically is that childbirth has become much safer for both mothers and babies. Table 6.18 records – at 25-year intervals – the remarkable fall in infant mortality over the course of the 20th century. In round figures, in 1900 one in seven babies from the selected countries died before their first birthday. By 2000 the ratio was one in 200. The infant mortality rate is the number of babies who die aged less than one year per 1000 live births during the same year. A notable feature is the process of convergence over the century. Whereas in 1900 mortality rates ranged from New Zealand’s 62 to Austria’s 231, by 2000 the range from best to worst was a tiny 3.2 to 6.9. Between 2000 and 2006, many countries kept on improving. Whereas only four countries had a rate of less than four per 1000 in 2000, 11 did by 2006. The United States and Canada did not share in the improvement, and Australia is now somewhat above the mean. The maternal mortality rates reported in Table 6.19 are the number of maternal deaths from all causes per 100 000 live births. Note the shift from per 1000 to per 100 000. It is as though we are looking at the figures under a microscope to make minute differences easier to see. That is, death of mothers in childbirth is now very rare in all developed countries. A further implication of the numbers being so small – and the amplification so great – is that minor year-to-year variations may be mistaken for genuine improvement or deterioration. The 2006 figure for the United States is a blip, but in every recent year it has been the worst performed on maternal mortality. The continuing improvement in infant and maternal mortality rates – albeit now much smaller than in the past – is a reminder that

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a major reason for increased life expectancy is that a smaller percentage of people die at younger ages. But a characteristic of the constantly improving longevity in the selected countries is that life expectancy is improving at every stage of life. A major reason for increasing life expectancy in the first part of the 20th century was the reduction of premature deaths due to infectious diseases. In recent decades, the more important contributor has been older people living to greater ages. Even in the 36 years between 1970 and 2006, the life expectancy for people when they are 60 has increased by five years for both sexes. The countries at the top of the table, especially Japan and France, have improved the most. Australia has also achieved considerable success in its older people living to a greater age, and the data on the following pages will indicate some of the reasons. While increasing life expectancy is desirable, if it is prolonging an existence spent in pain or with a serious disability, it is less desirable. So in recent years, health analysts have supplemented the conventional measure of life expectancy to take account of the quality of life as well. Table 6.21 thus gives not just the life expectancy but the years of expected good health in each country. While expected healthy lives are obviously shorter than total expected lives, allowing for ill-health does not greatly change the ranking of the selected countries. Japan still leads the way; Australia ranks highly and the United States comes 18th. Females still enjoy a greater healthy life expectancy than males – for males at birth on average, healthy life expectancy is just under 70 years, and for women 72, a smaller margin than in total life expectancy.

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Table 6.22 Deaths from external causes Standardised death rates per 100 000 population Country

1960

1970

1980

1990

2000

2005

Netherlands United Kingdom Germany Ireland Italy Switzerland Australia Canada Austria Japan New Zealand Norway Sweden Denmark France United States Belgium Finland

49 50 .. 36 51 83 72 70 93 75 64 52 63 69 75 74 69 87

62 45 .. 49 54 83 77 73 100 67 76 58 64 70 87 82 82 92

42 40 63 53 53 71 58 65 83 48 70 59 59 68 83 69 78 75

31 33 42 43 42 65 44 47 61 41 58 52 47 58 69 58 57 85

27 28 34 40 33 41 39 38 47 44 41 41 35 47 53 50 55 66

25 27 29 29 31 34 35 37 39 40 40 40 42 .. 45 54 .. 65

Mean

67

72

63

52

41

39

Belgium and Denmark ranked according to 2000 figure.

Figure 6.2 Potential Years of Life Lost (PYLL) – external causes males Number of years of life lost per 100 000 population 3500 3000 2500 2000 1500 1000 500 0 1960

1970

1980 Australia

1990

2000

2005

D18 Mean

Figure 6.3 Potential Years of Life Lost (PYLL) – external causes females Number of years of life lost per 100 000 population 3500 3000 2500 2000 1500 1000 500 0 1960

1970

1980 Australia

1990

2000

2005

D18 Mean

∗ D18 refers to the 18 selected democracies, which are the primary comparators in this book.

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6.7 Deaths from external causes he three most important causes of death in the selected countries, in order of their prevalence, are circulatory diseases (heart disease and stroke), cancer, and death from external causes. Deaths in general, and deaths from particular causes, are conventionally measured as age standardised death rates per 100 000, which takes into account the differences in age structure of populations. This allows comparisons over time and between countries. Death rates can also be measured from a different perspective, one that takes account not just of death itself but also of the number of years of life the death costs. Everyone dies from something, but a cause of death that cuts life short earlier in the life span is much more of a problem than one that strikes at the end of a natural life cycle. So analysts constructed the measure Potential Years of Life Lost (PYLL), which weights a particular death by subtracting the person’s age at death from 70 years. The total number of years lost by all those dying from a particular cause in a given year is then expressed as the number of years of life lost per 100 000 of population. Deaths from external causes – external to the body – include a variety of causes, including deaths from suicide, homicide and traffic accidents, all of which are further explored in Chapter 16. The category further includes deaths from other accidents, such as falls, accidental poisoning, drowning etc. As a cause of death, the external category is much smaller than cancer or heart disease, and is comparable with relatively lesser causes, such as deaths from diseases of the respiratory and digestive systems. However, whereas most deaths from illness are more prevalent among older people, death from external causes is no respecter of age. External causes of death are so important because they are strongly associated

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with premature or untimely death, and so in terms of total potential years of life lost they rank with cancer and heart disease as a major cause of mortality. Table 6.22 shows the death rate from external causes rising between 1960 and 1970, but then falling almost universally and continually in the following 35 years. It is also apparent that the dispersion in death rates between the selected countries has narrowed over the period. However, the safest country, the Netherlands, has a death rate less than half the countries with the highest rate, Finland, Belgium and the United States. Australia’s performance, however, has gone from worse than the overall mean to slightly better. There is a very strong difference between the sexes in rates of death from external causes, and this is shown in Figures 6.2 and 6.3. As would be expected in PYLL, both males and females manifest the same general trend as the population trend in the death rate. They both peaked in 1970 and have shown a very considerable decline since, by 2005 down to just over half the 1970 figure. These figures compare the Australian rate with the mean for the 18 democracies (D18). Whereas in total death rates Australia fares slightly better than the mean, in these PYLL figures Australia fares slightly worse, suggesting a younger profile in this country of people dying from external causes. Apart from the shared trend downwards towards a lower death toll, the most striking aspect of Figures 6.2 and 6.3 is the difference between males and females. In every single country, males manifest a higher PYLL due to external causes than females, and by 2005, on average in the selected countries, and also in Australia, the figure for males was almost three times higher than that for females.

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Table 6.23 Deaths from circulatory diseases Standardised death rates per 100 000 population Country

1960

1970

1980

1990

2000

2005

Japan France Switzerland Canada Netherlands Australia Norway Ireland United Kingdom Italy United States Sweden New Zealand Austria Finland Denmark Belgium Germany

473 372 517 584 429 624 448 586 583 520 632 516 564 537 662 512 474 ..

468 332 435 488 426 637 446 584 533 465 557 443 555 540 658 457 478 ..

339 283 366 379 345 444 373 544 461 409 414 416 487 497 488 402 399 450

215 195 274 261 279 310 332 403 350 289 311 326 338 371 397 347 274 350

139 157 196 192 224 198 234 302 265 224 251 242 233 303 277 237 234 276

118 133 160 161 166 172 172 197 201 205 205 206 213 214 220 229 .. 241

Mean

531

500

416

312

232

189

Figure 6.4 Potential Years of Life Lost (PYLL) – circulatory diseases males Number of years of life lost per 100 000 population 3500 3000 2500 2000 1500 1000 500 0 1960

1970

1980 Australia

1990

2000

2005

D18 Mean

Figure 6.5 Potential Years of Life Lost (PYLL) – circulatory diseases females Number of years of life lost per 100 000 population 3500 3000 2500 2000 1500 1000 500 0 1960

1970

1980 Australia

108


1990 D18 Mean

2000

2005

6.8 Deaths from circulatory diseases n terms of their toll measured by standardised death rates, circulatory diseases – including heart attack and stroke – are by far the greatest single cause of death among all the categories determined by the World Health Organization. But the tables on this page tell the remarkable story of the marked decline in death from these diseases over the last 45 years. Circulatory or cardiovascular disease covers all diseases and conditions involving the heart and blood vessels. The main problem is the clogging of blood vessels with fat, cholesterol and other substances which may affect the blood flow to the heart or brain. Table 6.23 shows that, for the selected countries overall, the death rate from circulatory disease has more than halved since 1960. At the same time, the dispersion between the countries with the highest and lowest death rates has narrowed. The most remarkable story is that of Japan, where the death rate in 2006 is only one-quarter of what it was in 1960, and it now heads the table with Japan and France considerably ahead of others. Australia started as one of the worst performing countries in 1960 and 1970, but especially between 1970 and 2000 it showed one of the best improvements among the selected countries, although in the early 2000s, its continuing rate of improvement was not as great as for some others. The reasons for national differences can only be speculated upon. Many analysts have focussed on diet, but it is hard to think of two diets more different than the Japanese and French, although both perform near the top. Nevertheless the main feature of the table is the strength and commonality of the trend. As late as 1980, no country had a death rate lower than 250 and by 2005 no country had a death rate higher than 250. Figures 6.4 and 6.5 give the more penetrating measure of the mortality impact of circulatory diseases by examining the trends

I

among males and females in Potential Years of Life Lost (PYLL). The PYLL rate weights each person’s death by subtracting their age at death from 70 years. The total number of years lost by all those dying from circulatory diseases in a given year is then expressed as the number of years of life lost per 100 000 of population. Focusing on PYLL shows even more starkly the improvement in reducing the premature death toll from circulatory diseases. Among females, in Figure 6.5, the 2005 figure for the selected countries overall is one-quarter what it was in 1960, showing a rapid improvement in all the periods summarised. Moreover the improvement is still continuing into the 21st century. The improvement among Australian females has been even greater, being above the mean until 1980 and below it ever since. In Figure 6.4, in contrast to the improvement in the female trend, the male situation worsened slightly between 1960 and 1970, but after that improves almost as rapidly as for women. The 2005 mean is less than one-third the 1970 figure. Again the Australian improvement is greater than the mean, with its figure being above the mean until 1980 and below it ever since. The figures for the PYLL are even more impressive than for the standardised death rate in Table 6.23, implying that, on average, people are now dying from cardiovascular problems at a later age. Comparing Figures 6.4 and 6.5 shows that the mean for males is almost two-and-a-half times that for females, illustrating that this is still a much bigger health problem for men than women. Cardiovascular disease remains Australia’s largest health problem, accounting for 39% of all deaths. Nevertheless its reduction – and the success in delaying its onset until later ages – has been the single biggest reason for increasing life expectancy since 1970.

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Table 6.24 Deaths from cancer Standardised death rates per 100 000 population Country

1960

1970

1980

1990

2000

2005

Finland Switzerland Japan Sweden Austria Australia Germany United States Norway France Italy Canada New Zealand United Kingdom Ireland Netherlands Belgium Denmark

202 194 154 171 220 159 203 169 160 182 161 177 167 193 166 198 204 213

192 194 157 168 217 176 206 176 164 181 178 183 194 204 189 210 210 202

180 186 157 176 203 178 200 181 166 192 187 186 199 208 199 211 220 220

164 184 154 158 189 179 189 188 171 188 194 192 202 210 206 204 204 220

145 154 152 150 167 162 173 172 167 175 172 176 181 184 196 189 203 213

135 139 140 150 153 155 158 158 159 166 166 169 173 173 175 178 .. ..

Mean

183

189

192

189

174

159

Figure 6.6 Potential Years of Life Lost (PYLL) – cancer males Number of years of life lost per 100 000 population 3500 3000 2500 2000 1500 1000 500 0 1960

1970

1980 Australia

1990

2000

2005

D18 Mean

Figure 6.7 Potential Years of Life Lost (PYLL) – cancer females Number of years of life lost per 100 000 population 3500 3000 2500 2000 1500 1000 500 0 1960

1970

1980 Australia

110


1990 D18 Mean

2000

2005

6.9 Deaths from cancer ancer shows a different pattern from the previous two causes of death. The decline has been less, and the gap between the sexes is less pronounced. Cancers are a diverse group of diseases that all involve the growth and spread of abnormal cells which invade and destroy surrounding tissue. In Australia, the main types of cancer causing death among males are lung, colorectal and prostate cancers and among females are breast, colorectal and lung cancers. A comparison of Table 6.24 with Table 6.23 on the previous page shows that in every year circulatory diseases caused more deaths than cancer, and also that the death rate from both was decreasing over the decades. It also shows that the gap has narrowed. Whereas Table 6.23 shows a steady decline since 1960, so that the 2005 mean for the selected countries is around 35% of the 1960 one (531:189), Table 6.24 shows the overall mean continuing to rise until 1980 and then falling by a much lesser amount. Some of the increase probably reflected better diagnosis as well as increased incidence. In 1980, the difference in the selected countries overall was more than 2:1 (circulatory diseases 416: cancer 192); by 2005 it was very much closer (189: 159). So while Table 6.23 shows dramatic improvement almost universally, the story from Table 6.24 on deaths from cancer is more mixed. Some of the top-ranking countries in the table, such as Finland, Switzerland and Austria, have had substantial falls in the death rate. Others such as Japan, and to a lesser extent Sweden and Australia, started with relatively low rates but have not improved as greatly. Australia dropped from second best in 1960 to fifth best in 2005. Several countries have shown virtually no improvement or even a deterioration. These include Italy, New Zealand and Ireland. Although there is no data for 2005, the two worst performing countries in 2000, Belgium and

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Denmark, were still essentially at their 1960 levels. But the news on death from cancer is not all disappointing. Figures 6.6 and 6.7 shift the focus from the conventional death rate to the more penetrating measure of Potential Years of Life Lost (PYLL). The PYLL rate weights each person’s death by subtracting their age at death from 70 years, and then expressing the total number of years lost by all those dying from that cause in that year as years of life lost per 100 000 population. Here we see a fall from a 1970 peak of 1366 for males down to 854 by 2005, and for females from their 1960 peak of 1220 to 767. Australia’s PYLL has always been better than the mean, although less so in more recent years, where some other countries have improved more. The encouraging story then is that although most countries have had limited success in reducing the actual death rate from cancer, they have had more success in ensuring that, on average, it strikes at a later age. This probably reflects success in prevention, but in addition early detection and better treatment regimes now mean there is a much higher survival rate in many forms of cancer. Nevertheless while cancer shows considerable improvement in PYLL rates, this is not nearly as dramatic as the improvement for circulatory diseases. The result is that whereas circulatory diseases were a bigger premature source of death in the earlier decades, cancer now takes a bigger early toll for both men and women. For women, cancer is the greatest of the three leading causes of premature death. Its dominance has been strengthened by the greater decline in premature death from heart disease. For men, external causes – mainly accidents of all kinds – remain the greatest cause of premature death. But cancer has moved from third place to second because of the greater success in curbing the loss of years of life from heart disease.

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Table 6.25 Deaths from HIV/AIDS Deaths per 100 000 population Country

Table 6.26 Incidence of AIDS AIDS cases per 100 000 population

1990

2000

2005

Ireland Japan Finland Sweden New Zealand Netherlands Norway United Kingdom Australia Germany Austria Switzerland Canada France Italy United States

0.0 0.0 0.0 0.7 1.5 1.6 0.8 0.0 1.9 1.5 0.8 .. 3.2 4.6 3.2 9.1

0.0 0.0 0.2 0.3 0.5 0.7 0.3 0.3 0.6 0.6 0.6 1.6 1.4 1.5 1.5 4.5

0.0 0.1 0.2 0.2 0.3 0.4 0.4 0.4 0.5 0.5 0.7 0.8 1.1 1.1 1.8 3.6

Mean

1.9

0.9

0.8

No recent data on Belgium or Denmark.

Country

1985

1995

2006

Japan Germany New Zealand Norway Ireland Sweden Austria Canada Finland Australia Denmark Belgium Netherlands United Kingdom France Italy Switzerland United States

0.0 0.4 .. 0.3 0.1 0.3 0.3 1.5 0.1 0.8 0.8 0.7 0.5 0.4 1.0 0.3 1.3 3.4

0.1 2.3 1.7 1.5 1.5 2.2 2.6 6.1 0.8 4.5 4.1 2.4 3.5 3.0 8.9 9.9 8.5 27.0

0.3 0.4 0.5 0.5 0.6 0.6 0.7 0.8 0.8 0.9 0.9 1.0 1.2 1.4 1.7 1.9 2.1 13.7

Mean

0.7

5.0

1.7

Table 6.27 Global deaths from HIV/AIDS Deaths per 100 000 population, worst 10 countries, 2005 Country Swaziland Zimbabwe Lesotho Botswana Zambia Namibia Mozambique South Africa Malawi Central African Republic

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Number 1550 1384 1282 1020 840 837 707 675 605 594

6.10 HIV and AIDS n the early 1980s the most dramatic public health threat for decades confronted Western authorities. A mystery disease that struck and quickly killed apparently healthy people spread frighteningly in the United States, especially among high-risk groups such as male homosexuals, haemophiliacs and intravenous drug users. Eventually it was diagnosed as AIDS (Acquired Immunodeficiency Syndrome) and later it was discovered that it resulted from HIV (Human Immunodeficiency Virus). It was also discovered that HIV is not spread by casual contact, but can be contracted through exposure to blood and blood products (e.g. used hypodermic needles), semen and female genital secretions or breast milk. HIV attacks and eventually destroys the immune system. During AIDS, the last stage of HIV infection, the victim is vulnerable to being killed by a wide range of infections. Despite the scale and drama of the tragedy, Tables 6.25 and 6.26 also document the measure of success achieved by governments and community groups in responding to the threat. Urgent effort was put into the development of (still expensive) drugs to prevent HIV progressing into AIDS, but the most important measures were in prevention, combating the spread of HIV through the promotion of safe sex, free needle-exchange programs, and better procedures when handling blood. Table 6.26 shows how the disease escalated between the mid-1980s and mid-1990s, but then that the number suffering from AIDS was substantially reduced between 1995 and 2006. The scourge has not been eliminated, but its spread was contained and then very much reduced. Table 6.25 shows how the proportion of people dying from HIV/AIDS halved between 1990 and 2000, but had only reduced slightly since then. Among the selected countries, the disease struck first and struck most severely in the United States. In 1990, the American fatality rate of 9.1 was double the next worst country, France. Partly this was an accident of

I

timing. Because AIDS hit first in the United States, it spread very rapidly there before effective strategies for prevention were known. Despite America’s success in reducing the mortality rate by 2006 to around 40% of its 1990 total, it remained the worst hit of the selected countries. The severity of the AIDS epidemic varied considerably. Japan, Ireland and some of the Nordic countries remained relatively untouched. Australia is among a group of countries where the initial impact was considerable, but which responded relatively successfully. Overall the mortality rate by 2005 was less than half what it had been in 1990, and the incidence of AIDS in 2006 was one-fifth its 1995 level. In terms of total numbers HIV never became one of the major causes of death in the selected countries. But this takes no account of its tendency to strike most severely among younger age groups, nor the early mystery and fears around its rapid spread and the then impotence of doctors to save its victims. Nevertheless, despite the early manifestations of prejudice and fear, the public health response in these countries must be judged a relative success. But this stands in stark contrast to the global pandemic that developed. By 1996, the year that UNAIDS was formed to coordinate the global struggle, more than 4.6 million people had died, and 20 million were living with the HIV virus. By 2005, 25 million had been killed, and perhaps 60 million were living with the virus. The number of new infections has finally started to drop, but in 2007 there were still 2.7 million new HIV infections and 2 million HIV-related deaths. The toll has been worst in sub-Saharan Africa. In 2005, the death toll from HIV/AIDS in the United States, the worst of the selected countries, was 3.6 per 100 000, but in Table 6.27 the 10 countries where it was worst in proportion to population, the impact was more than 100 times greater, a toll far, far worse than any war.

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Table 6.28 Obese males Percentage of male population with a body mass index > 30

Table 6.29 Obese females Percentage of female population with a body mass index > 30

Country

Country

Japan Switzerland Austria Norway France Italy Netherlands Denmark Sweden Belgium Germany Ireland Finland Canada New Zealand Australia United Kingdom United States Mean

1990

2000

2005

1990

2000

2005

2 6 8 .. 6 .. 5 8 5 .. .. .. 8 .. 10 10 13 21

2 7 9 7 9 9 9 10 9 11 12 12 11 16 15 19 21 28

3 8 9 9 10 10 10 11 11 12 14 14 15 17 20 22 22 31

Japan Norway Switzerland Austria France Italy Sweden Netherlands Denmark Ireland Belgium Germany Finland Canada Australia New Zealand United Kingdom United States

3 .. 5 9 6 .. 6 7 .. .. .. .. 9 .. 12 13 16 26

3 6 7 9 9 8 9 10 9 9 12 11 11 14 22 19 21 34

3 8 8 9 9 10 10 11 12 12 13 13 14 19 21 22 24 33

9

12

14

Mean

10

12

14

Table 6.30 Overweight males Percentage of males with a body mass index of 25–30 Country

Table 6.31 Overweight females Percentage of females with a body mass index of 25–30

1990

2000

2005

1990

2000

2005

Japan France Switzerland Belgium Canada United States Denmark Ireland Netherlands Sweden New Zealand Norway United Kingdom Germany Italy Australia Finland Austria

21 29 .. .. .. 40 .. .. 34 .. 40 .. 40 .. .. 42 .. ..

25 34 .. .. .. 40 40 .. 39 40 40 .. 45 .. 40 48 .. 54

25 31 38 39 39 40 41 41 41 41 42 43 43 44 44 45 45 54

Japan France Austria Switzerland Belgium Canada Ireland Denmark Italy Norway Sweden Finland Australia Netherlands New Zealand Germany United States United Kingdom

19 19 .. .. .. .. .. .. .. .. .. .. 24 24 25 .. 25 29

18 20 21 .. .. .. .. 25 25 .. 27 .. 31 30 30 .. 28 34

17 20 21 22 24 25 25 26 26 26 26 27 28 28 28 29 29 32

Mean

35

41

41

Mean

24

26

26

114


Country

6.11 Obesity peaking English must be a health hazard or tend to be fattening. That would seem to be the implication of Tables 6.28 and 6.29, where the English-speaking countries are clustered at the bottom of each table. Excluding Ireland, the other five English-speaking countries’ mean for male obesity in 2005 was 22% and for the other 13 countries 10%. For female obesity, the equivalent figures are 24% compared with 10%. While all the English-speaking countries are facing this epidemic of obesity, the United States is the clear leader, nine percentage points ahead of the second country in each table. At the other end of the tables, all by itself, is Japan. Whereas three in 10 American males are obese, only one in 30 Japanese males is. Whereas one in three American females is obese, one in 30 Japanese females is. The data going back is annoyingly incomplete, but for the English-speaking countries on which we have 1980 data, the increases since are dramatic. Obesity among Australian males increased from 9% in 1980 to 22% in 2005; British from 6% to 22%; and Americans from 12% to 31%. Among females, the equivalents were from 8% to 21% in Australia; 8% to 24% in Britain; and 17% to 33% in America. Obesity is defined as a body mass index (BMI) of 30 or more. The BMI is the ratio of a person’s weight (in kilograms) to the square of their height (in metres). A person six feet tall (1.83 metres) becomes defined as obese when they weigh 100 kg or more. The term ‘overweight’ is defined as having a BMI from 25 to less than 30. Tables 6.29 and 6.30 give data on the extent of overweight. It is only for 2005 that we have data on all the selected countries. The biggest difference between the tables on overweight compared with obesity is that sex differences were minor on obesity, but quite substantial

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on percentages of people overweight. In several cases, the sex differences are pronounced, for example in Austria, with the same proportion of obesity in both sexes, 54% of males are overweight and only 21% of females are. These two tables are best read in conjunction with the previous two, however. The combined number of obese and overweight people in each country is the more meaningful measure than just overweight people alone. So while the United States is in the lower half of Table 6.30, if the 40% overweight males are added to the 31% obese males, it gives a total figure of 71%. On such combined percentages, the English-language countries would again cluster together as the most overweight. There has been much speculation about the causes of this rapid change. Overweight and obesity result when energy intake from diet continuously exceeds energy output through activity. While individual differences are due to a mix of genetic and environmental factors, the trend towards greater proportions of the population becoming obese must be found in behavioural changes, and they must be found by looking at patterns of both activity and diet. The figures on food intake in section 15.2 on mean calorie intake can give limited help here, although issues of distribution of intake are more important than averages in understanding the growth of obesity. While there is doubt about all the causes of increasing obesity, there is none about the dramatic extent of the increase, and unfortunately neither is there any doubt about the negative health consequences which it brings. Excess body weight is associated with many health problems including coronary heart disease, Type 2 diabetes, respiratory disease and some cancers. The deleterious health consequences of these changes will become increasingly important in coming decades.

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Table 6.32 Male daily smokers Percentage of males who smoke daily Country

Table 6.33 Female daily smokers Percentage of females who smoke daily

1970

1980

1990

2000

2006

1970

1980

1990

2000

2006

Sweden Australia Canada United States Belgium New Zealand United Kingdom Finland Norway Austria France Ireland Denmark Italy Germany Switzerland Netherlands Japan

.. 45 49 44 45 .. 55 .. 51 45 53 .. 68 .. .. .. 75 78

35 41 37 38 41 40 42 35 42 41 46 39 57 54 48 45 52 70

26 30 30 28 38 27 31 32 36 36 38 31 47 38 38 39 43 61

17 25 21 21 34 25 29 27 31 36 33 28 32 32 31 38 36 52

14 19 19 19 23 23 25 26 26 27 28 28 29 29 30 31 35 46

Country Japan United States Belgium Canada Italy Australia Finland Sweden Austria France Germany Denmark New Zealand Switzerland United Kingdom Norway Ireland Netherlands

16 31 .. 30 .. 28 .. .. 13 .. .. 47 .. .. 44 32 43 42

14 29 28 29 17 31 17 29 17 16 21 44 29 28 37 30 34 34

14 23 26 27 18 27 20 26 20 19 22 42 27 29 29 33 29 32

15 17 22 18 17 20 20 21 23 21 19 29 25 27 25 32 27 29

14 15 16 16 16 17 18 18 19 19 19 23 23 23 23 24 26 26

Mean

56

45

36

30

26

Mean

33

27

26

23

20

Table 6.34 Tobacco consumption Grams of tobacco consumed per person (aged 15 or more) per year Country

1960

1970

1980

1990

2000

2004

New Zealand Finland Canada United Kingdom France Norway Australia United States Denmark Sweden Ireland Germany Italy Austria Belgium Switzerland Netherlands Japan

3293 1526 4640 3080 2233 1735 3576 4373 .. 2040 2653 1790 1658 1969 3217 1900 2647 2350

3114 1660 3267 2680 2411 2104 3309 3524 2227 2180 3015 2676 2093 2509 3555 2640 2963 2442

2856 1492 2964 2954 2416 2169 2843 3075 2022 1990 3381 2631 2643 2691 3077 3025 3588 2528

1971 1376 1927 2298 2118 1956 1972 2218 1854 1850 1770 2473 .. 2329 2462 2869 3043 3220

1352 957 1510 1259 1684 1509 1353 1542 1639 1631 1834 2311 .. 2157 2243 2456 2472 3176

999 1007 1108 1178 1208 1241 1277 1406 1567 1654 .. 2046 .. .. .. 2300 .. ..

Mean

2694

2732

2688

2150

1815

1416

Countries without 2004 data ranked according to their 2000 figure.

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6.12 Tobacco he first scientific articles drawing a link between smoking and health problems appeared around 1950. In the following decades an overwhelming array of evidence linked smoking to cancer and heart disease, and to a range of lesser medical problems, and this information gradually penetrated into the public consciousness. The Australian Institute of Health and Welfare (AIHW) reports that smoking is the largest single preventable cause of premature death. Given the strength of the evidence and the magnitude of the problems, perhaps the amazing thing is how tobacco consumption has persisted. However, its downward trend is clear from these tables. Even so there are great variations between countries both in current consumption levels and in the timing of changes in habits. In 1960, the English-speaking New World countries contained the heaviest smokers. Table 6.34, which looks at volume of tobacco consumption in relation to the adult population, shows that in that year America and Canada led the way with over 4500 grams each year, while Australia and New Zealand were third and fourth. But it is also in these countries that the decline started first, and where it has been greatest. According to the table, all began to decline in the 1960s, and each now has a per capita tobacco consumption around one-third or less of their 1960 levels. All the other countries started with lower initial rates of tobacco consumption, but many started reducing their consumption much later. Japan was the last of the selected countries to start changing habits, with reductions only beginning (and then very slight ones) in the 1990s. But several European countries were also slow to adjust to the dangers of tobacco. The Netherlands, Belgium, Austria, Germany and France not only had rising consumption into the 1980s, but have reduced much less than the English-speaking countries. (The United Kingdom shows broadly similar trends to the New World countries, while Ireland’s sharp drop in the 1980s may be due to a measurement problem.)

T

Tables 6.32 and 6.33 look at tobacco consumption by seeing the trend in the proportion of the population who are daily smokers. The tables do not look at how many cigarettes people smoke, nor at the numbers who may be more occasional smokers. However, both tables tell the same story, a steady and substantial decline between 1970 and 2006. Australia has generally been just under the mean for the proportion of female daily smokers, but the fall among male daily smokers in Australia has been particularly sharp, so that it is substantially less than the overall mean, and indeed ranks equal second lowest with Canada and the United States, behind Sweden. It is sometimes claimed that men are smoking less but women are smoking more in recent years. The tables show that smoking among both sexes has been declining. The fall among males, starting from a much higher percentage, has been sharper, but the number of male daily smokers has always been greater than female ones in the selected countries overall. Only in Sweden did the percentage of female daily smokers outnumber males. A special note of sympathy should be sounded for Japanese women, who have the smallest proportion of smokers among these countries, while Japanese men rate highest – 14% to 46%. Moreover, given the figures on tobacco consumption in Table 6.34, Japanese men must be very heavy smokers. Both the OECD in comparing countries and the AIHW within Australia have noted how differences in tobacco smoking were matched by trends in deaths from lung cancer. In Australia, mortality among men peaked almost a quarter of a century after the peak of tobacco consumption in 1960, but was still rising among women. It is desirable to further reduce the prevalence of this very damaging habit, but the tables do provide an interesting study in behaviour change, especially the much more rapid reduction in English-speaking countries than Japan and some European ones.

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Table 6.35 Global life expectancy Countries where average life expectancy at birth was 50 years or less, 2007 Country

Table 6.36 Global infant mortality Number dying before one year of age per 1000 live births Countries where infant mortality rate > 100, 2007

1970

1990

2007

Swaziland Angola Mozambique Sierra Leone Zambia Zimbabwe Afghanistan Central African Republic Congo Rwanda Nigeria Ivory Coast Somalia Burundi Botswana Cameroon South Africa These countries’ mean

48 37 39 35 49 55 35 42 45 44 42 49 40 44 55 46 53 45

59 40 43 39 49 63 41 50 47 33 47 54 42 46 64 55 62 49

40 42 42 42 42 43 44 44 46 46 47 48 48 49 50 50 50 45

Global mean

59

65

68

Table 6.37 Access to improved drinking water Percentage of population with access to improved water, countries with least access 2006 Country

%

Afghanistan Somalia Papua New Guinea Niger Mozambique Ethiopia Equatorial Guinea Congo Nigeria Madagascar Fiji Chad

22 29 40 42 42 42 43 46 47 47 47 48

World Of 163 countries number with 100% access 95–99%+ access

87

118


36 30

Afghanistan Sierra Leone Chad Equatorial Guinea Guinea-Bissau Mali Angola Mozambique Central African Republic Rwanda Burundi Congo Burkina Faso Zambia World Countries where rate = 0–9 100+

1990

2007

168 169 120 103 142 148 150 135 113 117 113 127 112 99

165 155 124 124 118 117 116 115 113 109 108 108 104 103

51 29 31

36 53 14

Table 6.38 Doctors – a global perspective Number of physicians per 100 000 population, 2004 Countries with 1–20 doctors/100 000 21–50 51–100 101–200 201–300 301–400 401+ Total

Number

%

42 22 17 36 22 25 10

24 13 10 21 13 14 6

174

100

6.13 Global perspectives on life expectancy hen one sees the stark contrast between patterns of life expectancy and health conditions in the rich democracies that are our selected countries and the poorest countries in the world, one of two responses, both too simplistic, is common. One is to believe that improvement is inevitable and that progress will just come automatically. The other is to assume that it is hopeless and that nothing will ever change. Table 6.35 gives data on life expectancy at birth in the 17 countries where it was 50 years or below in 2007. This is in contrast to the mean in the selected rich democracies of around 80 years. As we saw in chapter 1, the increase in life expectancy in those countries has been sustained with dramatic improvements over the decades. Taking the globe as a whole, as the bottom row in Table 6.35 shows, there was some improvement between 1970 and 2007, from 59 to 68, but it was less spectacular than in the developed democracies. In contrast most of the countries listed in the table showed no improvement. As can be seen from their mean, there was some improvement between 1970 and 1990, from 45 to 49, but a falling back since then to 45. In Afghanistan, the explanation for its poor life expectancy must be at least partly sought in the decades of war that have ravaged that country. Apart from Afghanistan, all the countries with the worst life expectancy were in Africa. Many of these poor countries always had low life expectancy, which has continued to be the case, such as Angola, Mozambique and Sierra Leone. Others however had reasonable life expectancies, but have gone backwards since 1990. This is especially the case with countries in southern Africa, such as South Africa (down from 62 to 50), Zimbabwe (59 to 40), Zambia (49 to 42), Botswana (64 to 50) and Swaziland (59 to 40). These are the countries

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where HIV/AIDS has taken a particularly heavy toll, producing a radical reduction in life expectancy. In the poorest countries, the problems of reduced life expectancy begin with the safety of the process of being born. Table 6.36 shows the infant mortality rate for the 14 countries where more than 100 babies in every 1000 die before they reach the age of one. In Table 6.18 we saw that the mean rate of infant mortality for the selected countries was 4.1 per 1000. Again, apart from Afghanistan, the countries with the worst rates are all in Africa. Many of these countries have shown little improvement between 1990 and 2007. However, in the world as a whole the rate fell by around one-quarter, and the number of countries where the rate was less than 10 rose from 29 to 53, so many countries saw a substantial improvement. While Table 6.36 shows infant mortality, it should also be remembered that maternal mortality is also starkly higher. In Niger, which has the worst risk of maternal mortality, one in seven women die in childbirth, while in the developed world the figure is one in 8000. Life expectancy is affected also by the risk of infectious diseases. One indicator of this is the proportion of people with access to safe drinking water. In nearly all countries, except those listed in Table 6.37, the figure is now more than 50%, and in a third it is over 95%. The country with the least number of doctors relative to population among the selected countries (see Table 6.6) is Japan with its figure of 210, while Australia’s is 280. In contrast 66 countries, or just over one-quarter of those for which we have data, have fewer than 50 doctors per 100 000 population. When we look at life expectancy and health issues globally, especially in those with the lowest life expectancy, we see multiple disadvantages compounding one another.

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Chapter 7 EDUCATION

Table 7.1 Educational attainments of adult population Percentage of adult population (aged 25–64) with specified levels of educational qualifications 2006

Primary/lower secondary

Upper secondary (including post-secondary, non-tertiary qualifications)

Tertiary

Canada Japan New Zealand United States Denmark Finland Australia Norway Belgium Sweden Ireland United Kingdom Netherlands Switzerland France Germany Austria Italy

14 .. 22 12 17 20 33 21 33 16 34 14 28 13 33 17 18 48

39 60 31 48 47 44 34 46 35 54 35 38 42 55 41 59 63 38

47 40 38 38 34 34 33 32 31 31 30 30 29 27 26 23 18 13

Mean

23

45

31

Country

Figure 7.1 Male and female adults with upper secondary education % of male and female adult population (25–64 years old) and selected age groups with at least upper secondary qualifications, 2004

Table 7.2 Labour market entrants with tertiary qualifications Percentage of those entering the labour market with tertiary qualifications Country

1965–1969

1975–1979

1985–1989

1995–1999

Canada Finland Sweden United States Belgium Norway Denmark Ireland Australia France Netherlands Switzerland United Kingdom New Zealand Germany Austria Italy

31 24 25 33 18 22 25 14 21 13 22 20 21 18 22 14 6

41 30 33 41 24 28 32 19 29 18 28 27 27 26 26 17 11

44 36 34 39 32 31 32 27 31 21 29 30 30 26 27 20 11

54 43 42 41 40 39 39 39 36 36 33 33 33 28 27 21 15

Mean

20

26

29

35

No data on Japan.

90 80 70 60 50 40 30 20 10 0

Figure 7.2 Male and female adults with tertiary education % of male and female adult population (25–64 years old) and selected age groups with tertiary qualifications, 2004

% 25–34 year olds Males Australia

% 35–44 year olds Males D18 Mean

% 45–54 year olds Females Australia

% 55–64 year olds

Females D18 Mean

90 80 70 60 50 40 30 20 10 0 % 25–34 year olds Males Australia

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% 35–44 year olds Males D18 Mean

% 45–54 year olds Females Australia

% 55–64 year olds Females D18 Mean

7.1 Educational attainment n a complex sophisticated economy, education is a key both to individual prospects and to national economic performance. Before World War II, in most countries, most people finished their schooling at junior secondary level or below. Now, as Table 7.1 shows, more than three-quarters of the adult population in these countries have completed at least upper secondary education, and many go on to complete other post-secondary and tertiary qualifications. Table 7.1 shows that Canada, Japan and the United States have the most qualified adult populations, while Austria and Italy are the only countries where fewer than one in five has tertiary qualifications. While Australia is close to the average on tertiary qualifications, it is below average on completion of upper secondary schooling. Each educational system grew up with its own assumptions and methods. However, international bodies have devoted considerable attention to standardising the types of institutions and qualifications in different countries. While they are broadly comparable, one should not assume that someone graduating from secondary school in one country has exactly the same skills as a graduate from another country, or equally that a high school graduate from 1959 has the same skills as one in 2009. Because Table 7.1 shows the whole adult population, it is a slow-moving indicator, reflecting the legacy of past educational practice more than recent performance. The other data on the page capture the generational changes in education more revealingly. Table 7.2 shows averages for four five-year periods of the proportions of those entering the labour force who had tertiary qualifications. It shows how in these countries, in the 35 years from the mid-1960s to the end of the 1990s, the proportion of tertiary qualified labour market entrants rose one-and-three-quarter times. There are also substantial national differences. As in most tables on educational attainment, Italy is a distant laggard. It also shows

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how North America and Scandinavian countries have been leaders in giving their citizens opportunities for tertiary education. It is one of several indicators that suggests how the United States democratised access to tertiary education earliest, but in recent decades has not kept up the pace of improvement shown by others. In the late 1960s, the United States was first on this measure, just leading Canada, but by the late 1990s, it ranked only fourth, not having increased its proportion since the late 1970s. The German-speaking countries – Germany, Austria and Switzerland – rank relatively low on this table, partly because they tend to have longer (and possibly more demanding) university degrees than others. Germany also stands out as a country that has changed least, ranking equal sixth in the 1960s, but having dropped to 16th by the late 1990s. Australia ranked in the middle in the 1990s as it had in the 1960s. Its sharpest rise was from the sixties to seventies reflecting the big Whitlam-era investment in tertiary education. Figures 7.1 and 7.2 show generational changes in educational attainments for males and females, and compare Australia with the mean for the selected countries. For the 25– 34-year-old cohort, over four in five of both sexes have completed upper secondary education. Australia falls below the mean for both sexes in each age group, although less so for the youngest group, showing that its expansion of education at secondary level was somewhat later than others. The changes in tertiary qualifications, as shown in Figure 7.2 show sharper contrasts. Comparing 25–34 year olds with 55–64 year olds shows that in this 30-year span, the proportion of male tertiary graduates on average rose by one-third, from 25% to 33%, while the proportion of females with tertiary qualifications doubled, from 20% to 40%. Among the older cohort, male graduates outnumbered females, but among the younger cohort, female graduates outnumbered males. Australia’s pattern for each sex is also almost exactly average.

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Table 7.3 Total education spending Education expenditure as a % of GDP Country Denmark United States New Zealand Sweden Canada United Kingdom Switzerland Belgium Finland France Australia Norway Austria Germany Netherlands Japan Italy Ireland Mean

Total 1995

Total 2005

6.2 6.6 4.8 6.2 7.0 5.5 6.0 5.8 6.3 6.2 5.5 6.3 6.1 5.4 4.8 4.7 4.7 5.2

7.4 7.1 6.7 6.4 6.2 6.2 6.1 6.0 6.0 6.0 5.8 5.7 5.5 5.1 5.0 4.9 4.7 4.6

5.7

5.9

Table 7.4 Changes in real expenditure per student Change in real spending per student 1995–2004 1995 level = 100 Country

Per secondary student

Per tertiary student

Switzerland United States Italy Ireland Denmark Austria Finland Germany Norway Australia Netherlands Japan Sweden United Kingdom

105 130 105 181 121 .. 122 105 109 138 136 127 117 120

134 132 130 126 123 122 110 107 103 101 101 101 99 93

Mean

124

113

No data on Belgium, Canada, France or New Zealand.

Table 7.5 Student-staff ratios Number of students per staff member 2005

Table 7.6 Teachers’ salaries Teachers’ salaries in relation to per capita GDP, 2006

Country

Country

Primary

Secondary

Primary

Upper secondary

Belgium Norway Austria Italy France Switzerland Australia Sweden Finland Japan United Kingdom Ireland New Zealand Germany United States Netherlands Canada

12.6 10.9 14.0 10.7 19.3 15.1 16.0 12.1 15.0 19.2 19.8 19.4 17.7 18.7 14.6 15.3 ..

9.9 9.9 10.7 10.7 11.9 11.9 12.2 12.7 12.9 13.7 13.7 14.6 14.6 15.1 15.2 15.8 15.9

Switzerland Germany Netherlands Belgium Japan Denmark New Zealand Finland United Kingdom Australia Ireland Austria France Italy Sweden United States Norway

1.4 1.6 1.2 1.2 1.5 1.1 1.4 1.1 1.3 1.2 1.2 1.0 1.0 1.0 0.9 1.0 0.7

1.9 1.7 1.7 1.5 1.5 1.4 1.4 1.3 1.3 1.2 1.2 1.1 1.1 1.1 1.0 1.0 0.7

Mean

15.7

13.0

Mean

1.2

1.3

No data on Denmark.

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No data on Canada.

7.2 Expenditure on education areless commentaries sometimes lump education and health together as two areas inexorably consuming relatively more social resources as demand for them goes ever upward. While it is true that each generation has higher educational attainment than the one before, the trends in spending on education present a contrast to health. On average in the selected countries, education receives only two-thirds as much of GDP as health, and while the upward trend of relative resources devoted to health is clear and consistent, education shows no such direction. As Table 7.3 shows, on average for the selected countries between 1995 and 2004, total education spending as a proportion of GDP barely moved. Australia is close to the mean at both the beginning and the end of the period, although it is one of the countries to show an increase. Recent OECD publications do not offer long-term trend tables on education expenditure, presumably because changes in definition over the years detract from precise comparability. Earlier figures, which we used in the first edition, but perhaps should be viewed with caution, suggest that in 1987 the average for these countries was 6.2%. So unlike health there is no sign of an increasing share of GDP going to education. Simon Marginson’s research, however, gives us systematic longer term Australian data. Fuelled by the baby boom and greater school retention rates, Australian expenditure on education grew faster than the economy as a whole in the two-and-a-half decades from 1950. From 1.6% of GDP to education in 1950, the percentage devoted to education doubled to 3.2% in 1960, and rose again to 4.6% in 1970. Then under the Whitlam Government, there was a spurt to 6.2% in 1975. But the relative growth has not been sustained, and has fluctuated just below that figure ever since. One reason why educational expenditure as a share of GDP has not been increasing more is that the school age cohort as a

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proportion of the total population is decreasing with the ageing of society. This is more relevant to some other countries than to Australia. Moreover, it should be remembered that this table offers education spending as a share of national income. The income of all these countries increased substantially during the nine years, so a declining figure does not normally mean decreased expenditure but rather that education spending has not kept pace with the increased income. This is especially pertinent to Ireland, whose economy grew the fastest in the period. Table 7.4 thus offers a more generous picture than the first table. It shows that in real terms expenditure per secondary school student increased in every country for which there is data. Indeed here Ireland leads the way, while Australia showed the second-largest increase. The increase in real spending per tertiary student is only half as great, and here there is a group of countries of which Australia is one which have barely increased, or indeed have reduced, spending. The most crucial resource in education, and the area where the great bulk of spending is directed, is the teaching staff. Teachers’ salaries are everywhere the major component of spending at school level, and increasing their salaries or reducing student-staff ratios has major budgetary implications. Intuitively it would seem that both measures might improve educational outcomes, but there has long been contention about both. Table 7.5 shows that, perhaps counterintuitively, there is more of a spread in studentstaff ratios in primary schools than in secondary. Thirteen of 16 countries are within plus or minus two of the mean for secondary schools, while only seven fall inside that range for primary schools. In both cases Australia is close to the mean, as it is in the rather crude gauge of teachers’ salaries in Table 7.6. Some countries which have higher studentstaff ratios have more generous salaries, with several European countries and Japan leading the way.

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Table 7.7 Public expenditure on education Public expenditure on education as a % of GDP Country

1995

2005

Denmark Sweden Finland Belgium Norway France Switzerland Austria New Zealand United Kingdom United States Canada Netherlands Australia Ireland Italy Germany Japan

7.3 7.2 6.8 .. 8.0 5.9 5.4 6.0 5.6 5.3 5.0 6.5 5.0 5.0 5.0 4.8 4.6 3.6

6.8 6.2 5.9 5.8 5.7 5.6 5.6 5.2 5.2 5.0 4.8 4.7 4.6 4.3 4.3 4.3 4.2 3.4

Mean

5.7

5.1

Table 7.8 Public and private shares of education expenditure Public expenditure as a % of total education expenditure Country

1995

2005

Finland Norway Sweden Belgium Ireland Denmark Austria France Italy Netherlands Germany United Kingdom New Zealand Canada Australia Japan United States

98 94 98 92 90 97 93 92 91 90 82 87 .. 81 79 76 71

98 98 97 94 94 92 91 91 91 91 82 80 78 76 73 69 67

Mean

88

85

No data on Switzerland.

Table 7.9 Public share of tertiary education expenditure Percentage of tertiary education spending provided by government Country

1995

2005

Denmark Finland Norway Austria Belgium Sweden Germany France Ireland Netherlands Italy United Kingdom New Zealand Canada Australia United States Japan

99 98 94 96 92 94 89 .. 70 81 83 80 .. 57 65 37 40

97 96 96 93 91 88 85 84 84 78 70 67 60 55 48 35 34

Mean

78

74


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Table 7.10 Public expenditure on public and private education institutions Percentages of public spending 2004 Country

Public institutions

Private institutions

United States Austria Italy Japan Ireland Finland Switzerland New Zealand Sweden Norway France Germany Denmark United Kingdom Australia Belgium

99.8 98.0 97.0 96.3 90.8 90.5 90.5 89.5 87.1 86.1 84.0 84.0 80.9 78.9 75.9 44.5

0.2 0.5 1.3 3.5 .. 6.4 7.3 3.7 6.9 6.2 12.6 11.1 6.0 19.1 20.3 52.9

Mean

85.9

10.5

No data on Canada or the Netherlands.

7.3 Public and private spending on education he previous section examined total education spending, while these tables examine the relative contributions of public and private spending. This has been a contentious issue in Australian politics, both about state support for private schools and the way tertiary students are required to pay the Higher Education Contribution Scheme (HECS). A rather different picture emerges from Table 7.7 than from Table 7.3. Australia’s total spending was right on the mean, and it ranked in the middle in the first table, it ranks only 13th and is almost a full percentage point below the mean in this table. Whereas in the first table Australia’s total education spending as a share of GDP had increased, in this table its public expenditure on education, in the same period by the same measure, has slightly decreased. In all the selected countries, education is primarily a public responsibility, and in most of the countries overwhelmingly so. Table 7.8 shows that in 11 countries, public expenditure accounts for more than 90% of education spending. Moreover these shares remained stable in the decade under review. It was only in the countries where the public share was already lower that it decreased still further between 1995 and 2005. Australia with Japan falls very much at the private end of the spectrum, with only the United States relying more on private funding. Moreover, Australia’s share of public funding fell by the greatest amount, showing how private funding increased much more than public funding in these 10 years. The table shows that such a trend was uncommon. In most countries (although Germany and Switzerland move substantially in the opposite direction) tertiary education requires a greater private contribution than secondary education. So while in 2005, in the selected countries, the public share in total education spending averaged 87%, when tertiary education is taken alone, in Table 7.9, the average drops to 74%. Again Australia was an outlier in trends on public and private spending. It is one of

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just three countries where the public share of spending on tertiary education is less than half. The other two – Japan and the United States – have long traditions of private universities, where the overwhelming bulk of funding comes from private purses rather than the public one. According to the OECD, three-quarters of university students in Japan and one-third in America attend private universities. Moreover, in this, the most recent decade for which there is comparative data, Australia’s share of public funding of tertiary education fell far more dramatically than in any other country. Britain showed the second most radical shift with a drop of 13 percentage points, while Australia’s dropped 17. Table 7.10 also shows a distinctive Australian pattern. Overall in these countries, the great bulk of public expenditure is directed at public institutions. Australia has the secondhighest share of public funds going to private educational institutions. If there was an up-to-date figure available for the Netherlands, Australia would drop to third-highest. Belgium and the Netherlands share a long tradition of state support for church-based educational institutions. In Britain, Belgium and the Netherlands, according to the OECD, universities are state-supported private institutions. The other countries with the largest amounts of private funding – the United States and Japan – do not share this tendency for public subsidy of private institutions. Australia is thus unique in having a system where almost all university students attend state institutions, but where private expenditure plays such a large role. Moreover, if we could further disaggregate the Belgian and Dutch figures, it may be that Australia’s public subsidy of private schools is higher than the other selected countries. So, in both shares of public and private educational expenditure, and in the trends in both, for better or worse, Australia has a distinctive pattern.

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Table 7.11 Total spending on tertiary education Total expenditure on tertiary education as a % of GDP Country

Table 7.12 Public expenditure on tertiary education Public spending on tertiary education as % of GDP 2005, and change 1995–2004

1995

2005

United States Canada Denmark Finland Australia Sweden Switzerland New Zealand Japan Norway Austria France Netherlands United Kingdom Belgium Ireland Germany Italy

2.4 2.3 1.6 1.9 1.7 1.6 0.9 .. 1.1 1.7 1.2 .. 1.4 1.2 .. 1.3 1.1 0.7

2.9 2.6 1.7 1.7 1.6 1.6 1.6 1.5 1.4 1.4 1.3 1.3 1.3 1.3 1.2 1.2 1.1 0.9

Mean

1.5

1.5

Table 7.13 Education levels and earnings inequality Percentage earning more than 1.5 times median income, 2006, by education level Below upper secondary

Tertiary

Belgium Denmark Norway Sweden Finland Netherlands Switzerland Australia France Germany New Zealand Italy Austria Ireland United Kingdom United States Canada

11 15 16 16 19 19 20 21 21 22 22 23 24 26 27 27 29

2 7 7 7 10 6 2 8 9 11 9 14 6 13 6 5 14

35 27 25 31 45 41 46 37 47 47 38 46 54 54 55 45 48

Mean

21

8

42

No data on Japan.

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%

Finland Denmark Sweden Canada Switzerland Norway Austria Belgium France Ireland Netherlands United States Germany New Zealand United Kingdom Australia Italy Japan

1.7 1.6 1.5 1.4 1.4 1.3 1.2 1.2 1.1 1.0 1.0 1.0 0.9 0.9 0.9 0.8 0.6 0.5

126 129 134 .. 176 117 123 .. .. .. 111 154 109 109 106 96 208 128

Mean

1.1

130

Table 7.14 International students in tertiary institutions International students as a % of all tertiary students 2006

All levels

Country

Country

Index of change 1995–2004 (1995 = 100)

Country

%

New Zealand Australia Switzerland United Kingdom Austria Canada Belgium France Germany Sweden Denmark Norway Netherlands Finland Japan United States Italy

28 21 19 18 16 15 12 11 11 10 8 7 6 3 3 3 2

Mean

11

No data on Ireland.

7.4 Universities s was shown earlier by Table 7.1 and Figure 7.2, Australia’s participation rate in universities is just on or very slightly above the norm for the selected countries. It is not surprising then that Table 7.11 shows its spending on tertiary education, expressed as a share of GDP, is similarly just above the average. The largest spenders on universities are the North American and Scandinavian countries, while some of the European countries are at the bottom. Moreover total spending on tertiary education kept pace with rising incomes in all these countries. The average share of GDP in 2005 was the same as it had been in 1995, which was also broadly true for Australia. The picture from public funding of tertiary education is rather different. Australia ranked equal third bottom among the countries in Table 7.12, well below average, and spending only half or less than the leaders – Denmark, Finland, Sweden and Switzerland – do. Moreover while other countries increased their public spending by roughly one-third between 1995 and 2004, Australia was the only one to spend less, as the final column of the table demonstrates. Systematic, harmonised long-term comparative data on tertiary education spending is not available. However, Considine et al. have charted the trends within Australia. From the early 1970s until the late 1980s, Australian universities were almost 90% funded by government. Government outlays as a percentage of GDP devoted to tertiary education peaked in 1975 at 1.5%. In constant prices, government final consumption expenditure (this does not include capital outlays and personal benefits for students) peaked in 1977. By 1998, total government spending per student had fallen in real terms to around half the level it had been in 1975. Kniest provides more recent data. In 2005 dollar values, the government grant per student in 1996 was $11 128. By 2005 it had dropped to $8494. The average HECS contribution rose from 20% to 37% of the

A

funding per government-supported university student. The policy rationale for HECS is that a university education benefits not only the society as a whole, but enhances the individual graduate’s earning power. Table 7.13 makes clear that this is true. It looks at those earning more than one-and-a-half times the median annual income, according to their educational level. The societies vary considerably in their degree of inequality. Belgium has the lowest proportion earning more than this amount, and the United States and Canada the highest. But in all the countries those with tertiary qualifications are much more likely to be in this relatively affluent group than the less educated. Apart from the increasing importance of HECS contributions and the decreasing public commitment of funds, one other big change in Australian universities is the way that tertiary education has become a major export earner. Table 7.14 shows that one-fifth of students now enrolled at Australian universities are foreign. The only country with a higher proportion is New Zealand, whose foreign students include a considerable number of Australians. The OECD data does not distinguish between those who have crossed borders specifically in order to study and long-term foreign-born residents, who are studying where they live. Their data reveals however that the number of foreign tertiary students rose from 0.9 million in 1985 to 1.9 million in 2000 and 2.7 million in 2004. Although foreign students form only a small proportion of the US student body, it is the biggest destination for international students (22%), with Australia ranking fifth globally (6%). According to the ABS, education services to international students comprised Australia’s third-highest export, over $9 billion, in 2004–2005, twice as much as beef, and four times as much as wool, for example. Moreover in 2005, they had become crucial to the financial health of Australian universities, providing 15% of revenue.

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Table 7.15 Students’ reading literacy Reading literacy mean scores (scaled so OECD average = 500)

Country

2000

2006

Difference from 2000

Finland Canada New Zealand Ireland Australia Netherlands Sweden United States Belgium Switzerland Japan Germany United Kingdom Denmark Austria France Norway Italy

546 534 529 527 528 .. 516 504 507 494 522 484 523 497 492 505 505 487

547 527 521 517 513 507 507 .. 501 499 498 495 495 494 490 488 484 469

0 −7 −8 −9 −15 .. −9 .. −6 5 −24 11 −28 −2 −2 −17 −21 −19

Mean

512

503

−9

Discrepancies in final column are due to rounding.

Figure 7.3 Reading proficiency levels Reading literacy proficiency levels 2006 Mean Australia Finland 0

10

20

30 High

Medium

Low = below level 1 and level 1; medium = levels 2 to 3; high = levels 4 to 5

128


40

50 Low

60

7.5 Students’ reading literacy omparative studies in education for a long time had a vacuum at their heart. Over the years, scholars had carefully built up data on comparative educational expenditures, and levels of attainment and participation in educational institutions. But there was nothing directly on the end product of the educational process – the skills that students took into their adult working and social life. In recent years some major projects have addressed this gap. The Programme for International Student Assessment (PISA) is by far the most important and ambitious attempt to comparatively chart students’ literacy skills. Originally it was an initiative of the OECD, and the Australian Council for Educational Research is the body charged with co-ordinating this mammoth project. This collaborative effort surveys 15-year-old students. So far there have been three assessments, in 2000, 2003 and 2006, with the next to occur in 2009, and at threeyear intervals into the future. At age 15, students are approaching the end of compulsory schooling, but have not yet specialised too much in particular disciplines. In 2006, 57 countries participated, including all the OECD members. In each country there was a representative sample of at least 4000 students, and in some countries (including Australia) much larger samples. All students underwent pencil and paper assessments, and completed large questionnaires about their personal circumstances and attitudes, while school principals also completed questionnaires on the characteristics of their schools and the policy environment in which they worked. ‘PISA uses the term “literacy” to encompass (a) broad range of competencies relevant to coping with adult life in today’s rapidly changing societies.’ This emphasis on acquisition and application of skills underlines the approach to the three main domains they test – reading, mathematical and scientific

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literacy. In the first wave of surveys, the emphasis was on reading literacy with more minor attention to the other two; in 2003 on maths; in 2006 on science; and in 2009 the cycle will start again on reading literacy. In each domain the answers are scaled so that the mean for the OECD countries is 500. For our selected countries, the mean is normally somewhat higher. Table 7.15 ranks the countries according to their reading literacy performance in 2006. Because the survey has now been carried out three times, we can also chart trends. In both years, the same three countries – Finland, Canada and New Zealand – ranked at the top, and the same country, Italy, ranked at the bottom, indeed dropped even further behind. Australia ranked fifth in 2006, roughly the same as it did in 2000, although in the sixyear period, it showed a statistically significant decline, as did several other countries in the table. Japan and Norway also showed substantial declines, while only Germany showed a strong upward trend. In addition to the scaled scores, the PISA study divides each sample into performance bands, or levels of proficiency, where the cutoff points are designated as having skills to perform designated tasks and problems. On all the tests, level 2 is designated as the minimum acceptable level. For students in the two lowest levels, 1 and an unbounded region below that, their lack of literacy skills inhibit their capacity to learn and understand other subjects. Figure 7.3 simplifies PISA’s levels of reading literacy (1 to 5 as well as a group below level 1) into three broad categories. As is to be expected, it shows a broadly similar ranking to Table 7.15, but with some important wrinkles. Finland’s performance appears even more impressive, while it suggests (see web table) that fully one-quarter of Italy’s students lack adequate reading literacy skills, and some other countries – Austria, Germany and France – have particularly long tails.

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Table 7.16 Students’ maths literacy Students’ scores in maths PISA 2006, scaled so that OECD mean = 500 Mean 2006

Change from 2003

Change in 75th percentile scores

Finland Netherlands Switzerland Canada Japan New Zealand Australia Belgium Denmark Austria Germany Sweden Ireland France United Kingdom Norway United States Italy

548 531 530 527 523 522 520 520 513 505 504 502 501 496 495 490 474 462

4 −7 3 −5 −11 −1 −4 −9 −1 0 1 −7 −1 −15 .. −5 .. −4

3 −12 5 −7 −18 −6 −11 −13 −7 5 −5 −11 −3 −10 .. −8 −12 −3

Mean

509

−4

−7

Country

Table 7.17 Students’ science literacy 2006 PISA results, scaled so OECD mean = 500 Country

Mean

Finland Canada Japan New Zealand Australia Netherlands Germany United Kingdom Switzerland Austria Belgium Ireland Sweden Denmark France United States Norway Italy

563 534 531 530 527 525 516 515 512 511 510 508 503 496 495 489 487 475

Mean

513

Figure 7.4 Science proficiency levels Science proficiency levels 2006

Mean Australia Finland 0

10

20

30 High

40 Medium

Low = below level 1 and level 1; medium = levels 2 to 4; high = levels 5 to 6

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50 Low

60

70

80

7.6 Students’ mathematical and scientific literacy able 7.17 shows the mean scores for each country on mathematical literacy for 2006. The major concern of the second PISA survey in 2003 was in mathematical literacy, and it is only back to then that we can make absolute comparisons, because the foundations for future assessment were laid then. Australia is within the top half of these countries, and is still considerably above the mean. Again Finland and Canada are significantly stronger than Australia, while the Netherlands, Switzerland and Japan did better in maths than in reading literacy. Italy lags behind by a considerable margin, while the others scoring less than the OECD mean of 500 may be more surprising – the United States, Norway, the United Kingdom and France. Australia was one of several countries whose mean maths score declined between 2003 and 2006. The overall decline was relatively small, four points, but this masked two contrary trends. As the final column shows, the decline was greatest at the top end. The fall at the 75th percentile (the top quarter of students) was much greater than for the overall mean, because the lower end showed some improvement. In 2006, science was for the first time the major literacy domain studied by PISA, and so absolute comparisons with 2000 and 2003 are not possible. Australia ranked in the top third of countries, the four countries higher also being higher on maths, and again Finland was substantially ahead. Five countries scored below the OECD mean of 500. Denmark and France were just below 500, while the United States and Norway were below 490, and again Italy was well behind the others on 475. As with the other domains, students were assigned to proficiency levels in scientific literacy, with level 2 as the minimum needed for basic tasks. Level 1 and those below level 1 are not yet at this stage. In contrast, in the top proficiency level (level 6) ‘students can consistently identify, explain and apply scientific knowledge and knowledge about science in a

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variety of complex life situations. They can link different information sources and explanations and use evidence from those sources to justify decisions.’ They use scientific reasoning and their scientific understanding to seek solutions to unfamiliar scientific and technological situations. Figure 7.4 (and web table) simplifies the PISA categorisation into three groups. Again Finland stands out with a distinctive distribution, with by far the largest percentage in the top levels and the smallest proportion in the lowest. While New Zealand’s mean score is slightly higher than Australia’s, this figure shows that Australia’s students are more grouped in the middle proficiency levels, while New Zealand has both more in the low and high groups. While Finland has only 4% of students in the low levels, four countries – Italy, the United States, Norway and France – have 20% or more. So PISA, the most rigorous and sophisticated attempt to so far measure students’ literacy levels across countries, has dispelled various myths and confirmed some expectations about national performance. Finland is clearly the leader in all three areas, but its Scandinavian neighbours do not perform so well, and Norway in particular lags on these measures. Canada and New Zealand clearly outperform the largest English-speaking countries of the United States and United Kingdom. Japan still performs well, especially in science and maths, but shows worrying downward trends. Australia’s solid performance belies some of the alarmist claims about its educational standards, and it is in the top third of the selected countries in each of the three literacy domains. On the other hand, Australia is trending down rather than up in reading literacy and slightly so in maths. Among countries not included in our 18, Korea consistently performs near the top, often only behind Finland, and these two countries have also done relatively well economically in recent periods.

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Table 7.18 Range of literacy performance Difference in points between 5th and 95th percentiles on each of the 2006 scales Country

Reading

Maths

Science

Finland Denmark Sweden Canada Ireland Italy Netherlands Norway Austria Belgium Switzerland Australia Germany Japan France United Kingdom United States New Zealand

265 294 323 317 303 351 317 342 353 360 311 307 358 337 341 335 .. 344

267 278 295 281 268 311 290 299 319 341 320 288 325 298 312 297 292 306

281 305 307 309 309 312 313 313 322 324 325 327 327 329 333 344 348 352

Mean

327

299

321

Table 7.19 Gender differences Difference in mean scores ( − = females superior; + = males superior) Country

Reading

Maths

Science

Sweden Norway France Belgium United States Denmark New Zealand Ireland Finland Switzerland Netherlands Australia Canada Italy United Kingdom Germany Japan Austria

−40 −46 −35 −40 .. −30 −37 −34 −51 −31 −24 −37 −32 −41 −29 −42 −31 −45

5 6 6 7 9 10 11 11 12 13 13 14 14 17 17 20 20 23

1 −4 3 1 1 9 −4 0 −3 6 7 0 4 3 10 7 3 8

Mean

−37

13

3

Table 7.20 Socio-cultural inequalities and literacy standards Mean scores on scientific literacy scale by PISA index of economic, social and cultural status Lowest quartile score

Highest quartile score

Difference

Finland Canada Japan Australia New Zealand Netherlands United Kingdom Ireland Sweden Austria Germany Switzerland Belgium Denmark Norway France United States Italy

535 501 493 484 480 478 467 467 466 462 460 458 456 453 453 437 435 435

598 569 562 572 589 578 570 555 543 559 572 563 566 543 523 559 552 511

63 68 69 88 109 100 103 88 77 97 111 105 110 90 69 122 117 76

Mean

468

560

92

Country

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7.7 Excellence and equity ublic expectations of education systems have two broad demands which are sometimes thought to be in conflict. On the one hand, it is important that education be inclusive, that it maximise the life chances of all. On the other, the keys to a dynamic future are seen as lying in cultivating the highest levels of excellence. While the differences in the mean literacy scores between the selected countries are substantial and interesting, it should be remembered that the variations within each country are far greater than the differences between them. Table 7.18 offers a measure of the ranges of scores in each domain. It gives the difference between the scores at the fifth percentile and the 95th percentile, in other words the range once the very top and bottom extremes have been eliminated. Emphatically, the top-performing country, Finland, is also the one with the narrowest spread. It combines excellence and equity better than any of the others. Canada and Ireland also combine high performance with a relatively narrow spread of scores. Denmark and Sweden, as is characteristic of Scandinavian countries, achieve a high degree of equality but with only average educational performance. Australia, and much more so New Zealand, have relatively high scores, but also a wider spread. The table is ordered according to the range of scores in science, and the rankings are broadly the same in all three literacy domains, but some European countries, such as Austria, Belgium and Italy, show a much greater spread in reading literacy than the other two domains. The first concern with educational equity is with the range of outcomes, that ‘no child be left behind’ as President Bush’s policy slogan put it. In an information age, literacy skills are crucial to many social opportunities both in work and leisure, and in an increasingly technological world, all adults need to be literate in all three domains – reading, mathematics and science. The second concern relates to how education reinforces or qualifies existing inequalities.

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Gender, the denial of social opportunities to women, has been one important traditional dimension of social inequality. Concern about gender equality traditionally centred on the underachievement of females. Their lower educational attainment in the past probably always owed more to different attitudes about their right to advanced education rather than to any difference in ability, but, as figures 7.1 and 7.2 showed, inequalities in attainment have disappeared. Table 7.19 shows differences between males and females in each of the tests. In science, the mean difference is close to zero – exactly zero in Australia – although in most of the countries males were slightly ahead. The traditional stereotype was that girls perform worse at maths, and this is still true, especially in Austria, Germany and Japan – where there is a 20 point difference between girls and boys. However, by far the largest gender difference is in reading literacy, and here girls are ahead in all the countries, and the mean difference is almost three times as great as in the reverse direction on maths. In all countries, the socio-economic situation of their families has some relationship with students’ literacy skills. Table 7.20 is based upon the PISA’s primary measure of a student’s family and home background, the Index of Economic, Social and Cultural Status (ESCS). It is a composite measure based on the occupation of parents, their highest educational level, an index of family wealth, and indices of the students’ homes’ educational resources and cultural possessions. The table, which is based on scientific literacy scores, shows that disadvantaged social groups perform best in the high-achieving countries of Finland and Canada, with Japan also doing well on this measure. The size of the differences between the top and bottom quartiles varies substantially between the countries, with France, the United States, Germany and Belgium having the greatest gap. Australia is among the more equitable of countries by this measure.

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Table 7.21 Student time studying subjects at school Percentage of students in 2006 saying they spend more than four hours weekly in classes in each subject

Table 7.22 Student time studying lessons outside school Percentage of students in 2006 saying they have weekly classes outside school in each subject

Country

Country

Science

Maths

English

Italy Canada France Sweden Netherlands Australia Germany United Kingdom Switzerland Norway Finland Belgium United States Ireland New Zealand Japan Denmark Austria

25 59 26 11 18 36 33 58 16 7 27 23 49 16 65 12 27 21

66 68 68 47 52 52 52 55 55 46 49 49 57 49 40 31 27 27

86 66 66 65 59 51 51 50 50 49 46 46 43 43 36 20 15 15

Mean

29

50

48

Table 7.23 Student time spent studying subjects by self Percentage of students in 2006 saying they study each subject at least two hours a week by themselves Country

Science

Maths

English

Sweden Italy Ireland New Zealand Canada France Germany Australia Norway Netherlands Austria Denmark United States Switzerland Belgium Finland United Kingdom Japan

14 39 20 22 28 22 32 19 19 21 22 13 27 14 21 12 32 6

48 35 49 35 37 37 33 33 29 34 44 44 32 32 37 37 27 16

57 47 37 33 31 31 31 31 30 28 26 26 23 23 21 21 13 13

Mean

21

35

29

Science

Maths

English

Italy Netherlands France Canada Germany Australia Norway New Zealand Sweden Ireland United States Switzerland United Kingdom Japan Finland Belgium Denmark Austria

28 34 38 36 29 23 61 25 36 21 31 24 44 18 23 18 53 12

70 54 47 47 38 38 40 39 40 41 40 40 37 25 29 29 27 27

72 45 41 41 34 34 33 31 30 30 29 29 26 25 23 23 12 12

Mean

31

39

32

Table 7.24 Variance in performance Variance in science performance PISA 2006, column one shows national variance as a % of OECD average variance, column two shows amount of variance explained by differences between schools (cf within schools) National variance in performance

Between school variance

Finland Norway Sweden Denmark New Zealand Ireland Australia Canada United Kingdom United States Switzerland Japan Belgium Italy Austria Netherlands Germany

81 99 96 96 125 99 111 98 124 125 110 109 109 101 107 101 110

6 10 12 15 16 17 18 18 19 23 34 49 52 52 57 59 60

Mean

106

30

Country

No data on France.

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7.8 Schools and learning environments he value of PISA lies not only in its unprecedented international benchmarking, but in providing insights into how educational policies and practices improve learning outcomes. A commonsense belief is that more study time will result in better performance, and Tables 7.21 through 7.23 are devoted to charting students’ study times in each of the three domains. National stereotypes of how hard students study are confounded by these tables. They show Italian students near the top while the allegedly hard-working Japanese are near the bottom. But it should immediately be added that the data are based on students’ self reports rather than outside measurement of their behaviour. So as much as actual differences in time spent studying, they may also reflect national differences in how students respond to such questions. The Italians may disproportionately feel they are working hard, or disproportionately want to impress others that they are. Conversely Japanese students may feel guilty that they are not working harder, or underestimate just how much work they are doing. Within these constraints, the data do offer some interesting comparisons. In all three tables, students overall say they spend most time on maths than on the other two domains. Table 7.21 has the five English-speaking countries topping the list in terms of time spent studying science in class, and suggests that even by the age of 15 a large proportion of students in European countries has already opted out of studying science. Overall in these countries between 30% and 40% say they attend classes outside school, and the data suggests coaching colleges in Italy must be a very lucrative industry. At least on the results of Table 7.23, the students do not appear to be overburdened by homework. In all three tables of time spent, the topperforming country, Finland, is in the bottom half. Limiting time comparisons to the English-speaking countries does provide some correlation between time spent and national student performance, with the top-performing

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countries, Canada, New Zealand and Ireland, all saying they do more homework, with Australia next, and the United States and United Kingdom doing less. PISA also gives insights into how official policies affect the environments in which students learn. Table 7.24 examines two aspects of unequal performance. The first column examines the spread of scores (their variance), and then expresses the amount of variance in each country as a percentage of the OECD average. In other words countries with a figure less than 100 have lower than average variance and those more than 100 greater than average variance. Finland has by far the lowest spread, while, at the other extreme, the United States, New Zealand and Britain have the largest. The second column then examines how much of the variation in each country’s performance is explained by differences within schools and how much by differences between schools. In the Scandinavian countries, and especially Finland, most of the variance occurs within schools rather than between them. In other words, the schools themselves are less stratified by the factors affecting performance, whether socio-economic or academic streaming. Australia, despite its overall relatively high inequality of outcomes, falls in the top half of countries by this measure. In contrast, in the bottom five countries more than half the variance is explained by differences between schools. The schools are more internally homogeneous but there are greater differences between them. Tellingly, some of these countries fall toward the bottom on overall performance. Indeed the greatest improver in the PISA studies between 2000 and 2006 was not one of our selected countries, but Poland. Its mean for reading literacy rose from 479 to 508. Scholars attribute at least some of its improvement to its change, moving from early streaming into academic and vocational schools to comprehensive schools. As the the Economist commented, the PISA findings suggest that rising educational tides lift all boats.

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Chapter 8 INEQUALITY AND SOCIAL WELFARE

Table 8.1 Income inequality Gini coefficient (0 = most equal; 1 = most unequal) at each period Country

Mid-1980s

Mid-1990s

Early 2000s

Denmark Sweden Austria Finland France Belgium Netherlands Norway Switzerland Germany Australia Canada Japan Ireland New Zealand United Kingdom Italy United States

.221 .198 .236 .207 .300 .274 .259 .234 .. .257 .. .287 .304 .331 .271 .325 .309 .338

.215 .211 .238 .228 .270 .287 .282 .256 .. .272 .309 .283 .323 .324 .335 .354 .348 .361

.232 .234 .265 .269 .270 .271 .271 .276 .276 .298 .301 .317 .321 .328 .335 .335 .352 .381

Mean

.273

.288

.296

Table 8.2 Trends in real household income Average annual change, %, for income groups, mid-1990s to mid-2000s Country Ireland Norway Australia United Kingdom Italy Netherlands Finland Belgium Sweden New Zealand France Denmark Canada United States Germany Japan Austria Mean No data on Switzerland.

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Bottom quintile

Middle three quintiles

Top quintile

5.2 4.4 2.4 2.4 2.2 1.8 1.6 1.4 1.4 1.1 0.9 0.6 0.2 −0.2 −0.3 −1.4 −2.1

7.7 3.9 2.0 2.1 1.0 2.0 2.5 1.3 2.2 2.2 0.7 0.9 1.2 0.5 0.5 −1.0 −0.5

5.4 5.1 1.9 1.5 1.6 1.4 4.6 1.7 2.8 1.6 1.0 1.5 2.1 1.1 1.3 −1.3 −0.4

1.3

1.7

1.9

8.1 Income inequality ational summary measures of economic growth or income take no account of its distribution. They measure the size of the cake, but not how it is divided up. However, distribution is central to people’s sense of their wellbeing, and to their capacity to use the national wealth for their own personal goals. Table 8.1 uses the most common measure, the Gini coefficient, which takes a value of 0 if every household has identical income and a value of 1 if one household has all the income. Thus an increase in the coefficient represents an increase in inequality. The Gini coefficient is a ratio measure, which includes all members of a population, and allows comparisons over time and between countries. Generally richer countries such as the selected countries have a lower Gini coefficient than poorer countries. Most Third World countries have coefficients of between .40 and .65, compared with the mean of the selected countries here of just under .30. This table and Table 8.2 are both taken from the OECD’s landmark study published in 2008, Growing Unequal? Income Distribution and Poverty in OECD Countries. This book is the most comprehensive and systematic statistical study of social inequality, and a major advance in scope and methodology. Table 8.1 shows that Denmark and Sweden are the most equal countries, and the United States the most unequal. The countries fall into two broad groups: nine countries, all European, which in the middle of the 2000s scored between .232 and .276. Nearly all these countries consistently ranked in the most egalitarian half of the countries. All the English-speaking countries fall in the less egalitarian half of the table. Despite its egalitarian self-image, Australia scores slightly

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worse than the mean. The most extensive and long-running attempt to generate comparative data on income and inequality has come from the Luxembourg Income Study (LIS), which pioneered the comparative statistical study of social inequality. Its principal research tool has been household survey data, and so the availability of data varies with the years in which surveys were conducted in different countries. It had tended to assign Australia somewhat higher Gini coefficients than the OECD does, although only slightly so. The overall mean in Table 8.1 shows an upward movement over the two decades in the table. However, there is considerable movement in both directions. Australian inequality reduced slightly between 1995 and 2005. France had the biggest reduction over the two decades. New Zealand’s movement was the greatest toward more inequality, while relatively unequal societies such as the United States, Italy and Canada became more so. Table 8.2 takes another perspective on changes in income distribution. It divides each country into five income groups, quintiles. It looks at the bottom fifth, the middle three and the top fifth, and sees how their income changed in the decade roughly between 1995 and 2005. It shows considerable variety. All the income groups in Austria and Japan shrank slightly. In fast-growing Ireland and Norway, all groups grew considerably. In the United States and Germany the bottom fifth declined slightly, while the top quintile increased the most. In other countries as well, the top quintile grew most, including Canada, Finland and Sweden. Australia and the United Kingdom had the most egalitarian growth with the bottom quintile growing fastest.

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Table 8.3 Income levels and structure Incomes in $US PPP ’000, at 10th percentile, median and 90th percentile income level, 2005 Country

P10

Median

P90

Rank P10

Rank median

Rank P90

Norway Netherlands Austria Denmark Sweden United Kingdom Switzerland Belgium Finland France Australia Canada Ireland Germany New Zealand Japan United States Italy

10.9 10.8 10.5 10.4 9.4 9.3 9.2 9.1 9.1 8.7 8.2 8.0 7.7 7.4 6.2 6.0 5.8 5.3

26.6 28.0 25.1 22.9 20.7 24.7 27.5 22.3 21.0 20.7 23.0 25.3 22.4 22.0 19.3 22.8 27.0 16.8

56.4 67.8 62.9 47.9 44.1 80.4 65.3 53.1 51.7 54.2 58.8 70.7 64.5 57.3 72.3 60.3 93.1 56.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

4 1 6 9 15 7 2 12 14 16 8 5 11 13 17 10 3 18

12 5 8 17 18 2 6 15 16 14 10 4 7 11 3 9 1 13

8.4

23.2

62.0

Mean

Table 8.4 Income shares Ratio of final incomes at 90th percentile to those at 10th percentile Early to mid-1980s

Mid- to late 1990s

Mid-2000s

Denmark Sweden Norway Finland Netherlands Austria Switzerland France Belgium Australia Germany Canada United Kingdom New Zealand Italy Ireland Japan United States

3.22 2.71 2.92 2.59 2.94 2.89 3.39 3.92 2.73 3.97 3.01 4.05 3.79 .. 4.05 4.23 .. 5.71

3.15 2.61 2.83 2.90 3.15 3.73 3.62 3.54 3.19 4.33 3.18 4.13 4.58 .. 4.77 .. 4.17 5.45

2.72 2.79 2.83 3.21 3.23 3.27 3.29 3.39 3.43 3.95 3.98 4.12 4.21 4.27 4.31 4.41 4.77 5.91

Mean

3.51

3.71

3.78

Country

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Table 8.5 The richest 1% Share of the richest 1% of income earners Country

1950

1970

1980

1990

2000

Netherlands Sweden France Switzerland Japan Australia New Zealand Ireland Germany United Kingdom Canada United States

12.1 7.6 9.0 10.0 7.7 12.7 11.1 .. 11.6 12.7 10.9 11.4

8.6 6.1 8.3 11.0 8.2 6.1 6.7 .. 11.3 8.1 9.0 7.8

5.9 4.0 7.6 8.4 7.2 4.8 5.7 7.0 10.8 7.0 8.1 8.2

5.6 3.8 8.2 9.2 8.1 6.4 7.8 6.6 10.9 9.8 9.4 13.0

5.4 6.0 7.7 7.8 8.2 8.9 9.6 10.1 11.1 12.6 13.6 16.5

No data on Austria, Belgium, Denmark, Finland, Italy or Norway. Latest year for Switzerland = 1996, and for some others 1998.

8.2 Rich and poor easures of inequality usually look at shares within the same country, while measures of GDP per head take no account of distribution or inequality. This leads into one of the eternal arguments in social analysis: is it better to be poor in a country such as America, which is very rich but also relatively unequal? Or to be poor in a country like Sweden, which distributes its lesser riches more equally? Table 8.3 addresses the income aspect of this question. In standardised $US adjusted to take account of purchasing power in each country, the first three columns give the annual income of those sitting at the 10th percentile of incomes, at the median or middle income amount, and then those at the 90th percentile. In both the P90 and P10 columns, the top countries’ values are more than double the bottom. In the top countries – Norway, the Netherlands, Austria and Denmark – this group has an income around double that of the bottom country, Italy. Australia is fractionally below the mean. The range among the richest group, the P90 band, is much wider in dollar terms, with the top nation, the United States, being almost $US50 000 higher than the lowest, Sweden – $US93 000 to $US44 000. The most interesting aspect is the different rankings in the final three columns, highlighted particularly by the two countries just mentioned, Sweden and the United States. The United States ranks richest at the P90 level, third at the median level and second bottom at the P10 level, starkly highlighting not only its high ranking in terms of GDP, but the greater degree of inequality it has compared with the other selected countries. The four Nordic countries are in the top half of countries for the P10 level, but all are in the bottom half of the table at the P90 level, highlighting the relative flatness of their income distribution. New Zealand and Canada show a similar but not as dramatic profile as the United States, ranking high at the richer level but low

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at the poorer level. Others such as the United Kingdom, the Netherlands and Switzerland are consistently fairly high in their rankings, while Australia is close to the middle at all levels. Table 8.4 also looks at the difference between rich and poor by comparing the 90th percentile and the 10th percentile. In this way it seeks a more representative measure of inequality, one that is unaffected by the minority of incomes that are either extremely high or extremely low. Table 8.4 produces smaller ratios than Table 8.3 because it takes more account of the compositions of households. It shows a small overall trend towards greater inequality in the 20 years between the mid-1980s and mid-2000s. The gap in Australia tended to widen somewhat in the first decade and then narrow slightly in the second. The United States showed the obverse trends. Denmark and France showed the greatest trend toward more equality, Germany the greatest trend towards more inequality, although this may be an artefact of German unification following the fall of the Berlin Wall. Again the four Nordic countries, followed by the Netherlands, Austria and Switzerland, have the smallest income differences, and the United States easily the biggest. Table 8.5 is derived from the work of ANU economist Andrew Leigh and shows a fascinating trend in the share of the richest 1%. In 1950 they claimed the greatest share of income in Australia and the United Kingdom, but then in both countries, and in most of the countries for which we have data, their share dropped substantially until 1980, but then increased again in the last two decades of the 20th century. This rise was particularly sharp in the United States and the United Kingdom, perhaps testimony to the reigns of Reagan and Thatcher, but also a more general trend among all the English-speaking countries.


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Table 8.6 Poverty Percentage of population with income below 50% of the country’s median income

Table 8.7 Persistent poverty Percentage of those still in relative poverty after three years

Country

Country

%

Netherlands Denmark Germany Austria France United Kingdom Belgium Finland Australia Canada Italy United States Ireland

41 44 46 48 50 50 52 54 56 61 62 63 69

Mean

53

Denmark Sweden Austria Norway France Finland Netherlands United Kingdom Switzerland Belgium New Zealand Germany Italy Canada Australia Ireland Japan United States Mean

Mid-1980s

Mid-1990s

Mid-2000s

10.1 5.3 6.7 7.2 7.3 5.4 3.9 9.2 7.6 4.5 .. 5.3 10.4 12.4 11.3 11.1 .. 15.8

9.2 6.6 10.6 6.4 8.0 5.4 8.1 12.5 9.3 8.0 .. 7.5 14.2 12.8 14.3 .. .. 17.0

5.3 5.3 6.6 6.8 7.1 7.3 7.7 8.3 8.7 8.8 10.8 11.0 11.4 12.0 12.4 14.8 14.9 17.1

8.3

10.0

9.9

No data on Japan, New Zealand, Norway, Sweden or Switzerland.

Table 8.8 Poverty and material deprivation Percentage saying they had suffered from the following, 2005 Poor Arrears in Arrears in Inability Average Inadequate Constrained environmental paying paying mortgage to make across heating food choices Over-crowding conditions utilities or rent ends meet all items

Country Sweden Denmark Norway Finland Austria Netherlands United Kingdom Germany Ireland France Belgium Australia United States Japan Italy Mean

1.4 8.9 1.3 2.6 3.1 3.1 5.6 4.4 4.0 5.3 14.0 2.4 5.1 0.5 10.6

3.2 1.9 3.6 2.9 8.7 2.6 6.1 10.1 2.9 6.4 3.8 3.0 16.4 10.5 6.3

8.4 7.7 5.9 5.9 15.1 3.7 8.5 6.5 6.8 6.4 5.1 9.0 14.1 15.0 26.3

5.0 6.7 7.7 12.8 9.1 14.9 13.9 21.1 7.6 17.2 16.8 11.1 25.4 29.8 22.1

5.0 2.8 7.9 7.4 1.7 3.2 0.1 2.7 6.9 7.2 5.7 16.7 10.0 4.3 10.5

5.1 3.1 5.9 4.4 1.3 3.8 4.9 2.4 5.0 6.2 3.0 8.0 6.3 6.0 3.4

8.5 6.8 8.7 8.5 8.8 16.9 12.9 11.3 24.8 16.2 17.1 34.6 14.2 26.7 34.6

5.2 5.4 5.9 6.3 6.8 6.9 7.4 8.3 8.3 9.3 9.4 12.1 13.0 13.3 16.3

4.8

5.9

9.6

14.7

6.1

4.6

16.7

8.9

No data on Canada, New Zealand or Switzerland.

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8.3 Poverty lthough everyone knows what poverty is, its measurement and conceptualisation are politically and intellectually contentious. In developing countries, to be poor is to have so little money as to be in danger of dying through malnutrition or exposure. This is sometimes called subsistence poverty – insufficient income to afford the most basic standards of food, clothing and shelter so that their very survival is at stake. Very few people in the developed countries face poverty this severe, and describing their poverty has led to two approaches. The first is an absolute material conception, using some notion of basic needs, and the second is based upon relative deprivation, where poverty is determined by reference to the general standard of living and social expectations. According to an originator of this approach, Peter Townsend, people are in relative poverty when their resources are so seriously below the average that they are excluded from commonly accepted living patterns and activities. The differences have political implications, with a purely absolutist approach tending to be associated with a minimalist definition and response to the problem, and a relativist approach associated with more activist and redistributive responses. The most common relative poverty line used in international comparisons is 50% of each country’s median (or dead-middle) income. This is an arbitrary figure, and sometimes either 40% or 60% are used. Having a constant measure means that, over time, a relative poverty line moves not according to the rise in the cost of living (inflation) but according to the rise in the standard of living (some measure of average income). This, in turn, means that a rise in the proportion of people falling below a relative poverty line does not necessarily mean the poor are having to get by on lower real incomes. It’s more likely to mean that the incomes of the poor have been rising in real terms, but not as quickly as the incomes

A

of all the other people in the community. In other words, there has been a shift in relativities. It follows that a fall in relative poverty is achieved only if the incomes of the poor grow faster than those of others, that is there is a change in the structure of the distribution of income. In Table 8.6 Denmark and Sweden have the lowest rates of relative poverty. Ten countries, all European, have proportions of less than 10%. The four New World English-speaking countries are in the half having a greater proportion of people living in poverty. At each of the three data periods, the United States had the highest proportion living below the poverty line. Tables such as this, giving what are called head counts of poverty, define it in terms of access to money. They thus fail to capture the qualitative experience of poverty, or how economic disadvantage compounds into other deprivation – lack of opportunity, security, status and access to health and social resources. Nor do they say anything about ‘mobility’ – the individual’s chances of leaving (or entering) poverty over time. The OECD had several countries participating in a three-year longitudinal study. This survey found that of those under the poverty line in the first year of the study, just over half were still under that line in the third year. Ireland had the fewest escaping from poverty while the United States, Italy and Canada had the next greatest amount of constancy. Table 8.8 is also based upon survey evidence, and studies the types of material deprivation people say they have had to endure. The Nordic countries, predictably, had the fewest saying they had to go without, and Italy had the greatest. The most common types of deprivation differed between countries. Australians joined Italians in being most likely to complain about a general inability to make ends meet, and topped the list in being in arrears in paying for their utilities.


141

Table 8.9 Social expenditure Public social expenditure as a % of GDP

Table 8.10 Net social expenditure Net social expenditure as % of GDP

Country

1980

1990

1995

2000

2003

Country

1997

2001

Sweden France Denmark Germany Belgium Austria Norway Italy Finland Netherlands Switzerland United Kingdom New Zealand Australia Japan Canada United States Ireland

28.6 20.8 25.2 23.0 23.5 22.6 16.9 18.0 18.4 24.1 13.9 16.6 17.1 10.9 10.3 14.1 13.3 16.8

30.5 25.3 25.5 22.5 25.0 23.7 22.6 19.9 24.5 24.4 13.5 17.2 21.8 14.1 11.2 18.4 13.4 15.5

32.5 28.3 28.9 26.6 26.4 26.6 23.5 19.8 27.4 22.8 17.5 20.4 19.0 17.1 13.9 19.2 15.4 16.3

28.8 27.6 25.8 26.6 25.3 25.3 22.2 23.2 21.3 19.3 18.0 19.1 19.1 17.9 16.1 16.7 14.6 13.6

31.3 28.7 27.6 27.6 26.5 26.1 25.1 24.2 22.5 20.7 20.5 20.1 18.0 17.9 17.7 17.3 16.2 15.9

Germany France Sweden United Kingdom Belgium United States Denmark Netherlands Italy Austria Australia Norway Canada Japan Finland New Zealand Ireland

28.8 .. 30.6 24.6 28.5 23.4 27.5 24.0 25.3 24.6 21.9 25.1 21.8 15.7 25.6 17.5 18.4

27.6 27.0 26.0 23.3 23.2 23.1 22.5 22.1 21.9 21.8 21.1 20.9 20.3 20.2 20.0 15.9 12.5

Mean

24.0

20.1

Mean

18.6

20.5

22.3

21.1

22.4

Table 8.11 Level of unemployment benefits Unemployment benefits as a % of GDP per capita, average 1980–1999 Country


Table 8.12 Redistributive effect of public policies Interquintile ratio (P80:P20) before and after effects of public policies, mid-2000s Market income

After transfers and public services

Denmark Sweden Norway Finland France Netherlands Austria Australia Germany Switzerland Canada Ireland New Zealand United Kingdom Italy Japan United States

3.1 3.4 3.7 3.7 4.0 3.6 3.9 4.9 4.3 3.9 4.8 5.0 5.4 5.2 6.2 5.7 6.9

1.9 2.0 2.2 2.5 2.6 2.6 2.7 2.8 2.8 2.8 3.2 3.2 3.3 3.4 3.7 3.7 4.0

Mean

4.6

2.9

%

Denmark Netherlands Austria Ireland Sweden Germany Belgium Norway New Zealand Canada Australia Finland France United Kingdom Japan Italy United States

86.8 84.1 57.3 55.1 52.6 52.2 52.0 43.2 42.7 35.6 33.1 33.1 31.6 31.4 30.5 21.8 16.6

Mean

44.7


Country

No data on Belgium.

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8.4 Social expenditure and redistribution ublic social expenditure is spending by governments to provide support to individuals and households during circumstances that adversely affect their welfare. It covers cash transfer payments, but also the direct ‘in-kind’ provision of goods and services and tax breaks for social purposes. The label ‘social expenditure’ can be used to cover different groupings of spending. The broadest is to include education, health and welfare spending. Most commonly just health and welfare are used, and sometimes only social welfare. Table 8.9 shows that the growth of social expenditure (welfare and health) in these countries significantly outpaced the general growth of economies between 1980 and 1995, but stabilised thereafter. In every year in the table, Sweden is the biggest spender, with Denmark consistently also near the top. The biggest increases are seen in France and Norway. The English-speaking countries and Japan are at the bottom. It is notable that welfare spending is not determined by any simple notion of need. The measures of poverty on the previous page show a negative correlation with levels of welfare spending. Increases in social welfare spending can result from any of three factors: an increase in the number of people who meet unchanged eligibility criteria, government decisions to widen eligibility criteria, and government decisions to increase the real value of benefits paid. All three factors would help to explain the strong growth in total spending over the period, although it’s likely that the last two were more common earlier in the period and less common more recently. As the bills for earlier generosity have grown, taxpayers have become more resistant to higher taxation and governments have begun worrying about the budgetary implications of an ageing population. Spending in some areas, particularly unemployment, varies with the business cycle, while in others – age pensions – it is growing with a demographic inevitability. Table 8.10 attempts to provide a more comprehensive picture than just concentrating on gross public expenditure. Net social expendi-

P

tures differ from gross public social expenditures for two reasons. One is the provision of private social expenditure. The other is government’s clawing back of cash transfers through direct taxation. Net social expenditure is more complicated to calculate and it is only relatively recently that analysts at the OECD have systematically begun to chart it. Some laggards in the first table, notably the United States, Japan and Australia, tend to rank more highly here. Often in Europe a popular shorthand measure for the generosity of welfare payments is the net replacement rate. Australia sometimes looks relatively stingy on such schemes, sometimes because it is, and sometimes because of its ‘lean’ system of flat-rate, tightly meanstested welfare benefits. Many European countries pay the unemployed a proportion of their previous salary, while in Australia an unemployed garbageman and unemployed doctor both receive the same dole payment. So a preferable measure of relative generosity to net replacement rate is given in Table 8.11, which expresses expenditure on unemployment benefits for each unemployed person in relation to that country’s GDP, and finds a range from Denmark’s 87% of GDP per capita down to America’s 17%. The data is dated, but unlikely to have changed radically. Most people earn the majority of their income from employment, while a minority earn it from the businesses, rental properties and financial investments they own. Income gained in all these ways is referred to as ‘market income’ and its distribution is highly unequal. Governments, however, use their budgets to redistribute income, thereby reducing the extent of inequality. The two columns in Table 8.12 show the interquintile ratio (P80:P20) for market income, and then after the effects of public interventions, showing a considerable reduction, although the rankings of countries still broadly follow the original market inequalities. Australia ranks near the middle, but its redistributive impact is greater than the European countries around it which finish with a similar value, after starting with a lower one.


143

Table 8.13 Old age poverty Percentage in poverty among retirement age population, mid-2000s (Defined as those with income less than half the median of the entire population)

Table 8.14 Cost of old age pensions Expenditure on old-age and survivors’ pensions as a % of GDP Country

Total

% of those living in single households

Netherlands New Zealand Canada Sweden Austria France Germany Norway Denmark United Kingdom Belgium Finland Italy Switzerland Japan United States Australia Ireland

2 2 6 6 7 9 9 9 10 10 13 13 13 18 22 24 27 31

3 3 16 13 16 16 15 20 17 17 17 28 25 24 48 41 50 65

Mean

13

24

Country

1980

1990

2003

Ireland Australia Canada New Zealand Netherlands United Kingdom United States Finland Denmark Switzerland Norway Belgium Japan Sweden Germany France Austria Italy

4.0 3.2 2.8 7.0 6.5 5.1 5.0 4.7 5.8 5.6 4.5 6.1 2.9 6.7 8.7 7.6 8.5 7.4

4.2 3.7 4.3 7.4 7.0 5.3 6.1 8.1 7.4 5.8 7.6 9.1 5.0 9.3 10.2 10.9 11.9 10.2

3.7 4.1 4.4 4.5 5.8 6.1 6.3 6.4 7.2 7.2 7.4 9.3 9.3 10.8 11.7 12.3 13.2 13.9

Mean

5.7

7.4

8.0

Table 8.15 Level of old age pensions Net old age pension replacement rates, % at different pre-retirement income levels, early 2000s Country Denmark Netherlands Canada Austria Finland Australia Sweden Switzerland New Zealand Belgium Norway France Italy United States Ireland United Kingdom Japan Germany Median

144


Half median

Median

Double median

104.4 97.0 91.7 90.4 83.3 82.5 82.4 82.3 81.0 80.2 79.5 78.4 77.6 66.8 65.8 65.7 52.5 48.4

59.6 96.8 58.6 90.9 67.1 55.8 64.3 59.2 41.4 66.5 63.0 61.8 79.8 51.8 38.5 41.1 39.3 58.0

40.7 94.8 31.4 66.4 67.8 40.7 74.3 31.9 23.0 43.0 43.3 50.2 80.1 42.9 23.5 24.0 32.5 44.4

78.3

60.1

47.5

8.5 Old age poverty and pensions ne of the first areas in the development of the welfare state was the desire to look after people too old to work. Growing old should not mean becoming poorer or, at least, not desperately poor. Table 8.13 shows the proportion of elderly people living below the poverty line (defined simply as 50% of each country’s median income for all people). The range is very considerable: 10 countries with 10% or less and four with more than 20%. While the United States is again in the top three of poverty shares, this time it is eclipsed by Australia and Ireland. On this measure, however, the English-speaking countries do not cluster, with New Zealand and Canada having very low rates of old age poverty. In every country, old people living alone have considerably higher poverty rates than elderly people as a whole. In most countries there is a higher rate of poverty among the elderly than among those of working age. The contrast is particularly great in Australia (27% compared with 10%) but it is normal for people’s incomes to go down after they retire from the paid labour force. It should be noted, however, that these figures are based entirely on income, and are not related to expenses or living conditions. So in some senses this figuring might give an exaggerated impression of the privation in which Australian old people actually live. Older Australians have had a relatively high rate of home ownership. Owning their own homes outright significantly reduces their day-to-day living expenses compared with those still paying rent to private landlords, as well as giving them a greater sense of security. Nevertheless, while there should be some caution about taking the figures on elderly poverty rates at face value, the fact that they show a quarter of Australia’s elderly below the poverty line, and by this measure a poverty rate more than double most of the selected countries, is a stark statistic.

O

Table 8.14 shows the fairly strong growth in governments’ spending on old age pensions between 1980 and 2003, a trend which projected into the future with the ageing society has induced alarm among some policy analysts. The table shows a wide disparity in this spending, with Italy spending almost four times the share of national income on age pensions as Ireland. (Remember that these figures refer to share of national income, and Ireland’s income was the fastest growing in the period after 1990.) Australia had the secondlowest spending, and so the two lowest spending countries on this table were the two with the highest poverty rates on the previous table. However, the correlation is far from perfect, because the next two lowest spenders, Canada and New Zealand, had very low poverty rates. However, the very high percentages already spent on old age pensions by the countries at the bottom of the table helps to explain the analysts’ alarm about future trends. Italy’s spending fully one-eighth of national income on old age pensions hardly seems like a formula for dynamic growth. Table 18.5 switches from the cost to the generosity of age pensions. It presents pension rates for three income groups: those earning half the median income before retirement, those at the median, and those at double the median. Australia’s changing position between the three columns – above the mean in the first column and below in the next two, is largely explained by the frugality of its flat-rate age pension and its relatively stringent means testing. The downward movement in the median of the three columns shows that most countries use the aged pension at least partly as a welfare and redistributive measure, but consider how generous the Netherlands and Italy are to their high earners. Others such as Belgium and Austria are relatively generous at least up to the median income.


145

Table 8.16 Child poverty Proportion of children living in relative poverty Country

Mid-1990s

Mid-2000s

Denmark Finland Sweden Norway Austria France Switzerland Belgium United Kingdom Australia Netherlands Japan Canada New Zealand Germany Ireland Italy United States

5 4 3 4 15 8 10 6 20 13 8 12 16 8 11 14 20 22

3 4 4 5 6 8 9 10 10 12 12 14 15 15 16 16 16 21

Mean

11

11

Table 8.17 Households, employment and child poverty Poverty (living in households with less than half median income) among children by family types, % in each group, mid-2000s Single not working

Single working

Couple not working

Couple one worker

Denmark Norway Australia Finland Sweden United Kingdom Belgium Austria France Italy Ireland Germany Netherlands New Zealand Canada United States Japan

20 31 68 46 18 39 43 51 46 .. 75 56 62 48 89 92 60

4 5 6 6 6 7 10 11 12 16 24 26 27 30 32 36 58

21 29 51 23 36 36 36 36 48 78 55 47 65 47 81 82 50

5 4 8 9 14 9 11 4 12 24 16 6 12 21 22 27 11

Mean

53

19

48

13

Country


Table 8.18 Poverty risk of jobless single parents Poverty risk of single parents not working relative to households where the single parent is working Country Japan Italy New Zealand Germany Netherlands United States Canada Sweden Ireland France Belgium Austria Denmark United Kingdom Norway Finland Australia Mean No data on Switzerland.

146


Increased risk (times greater)

% of households with children

1.0 1.0 1.6 2.1 2.3 2.5 2.8 2.9 3.1 3.9 4.3 4.9 5.1 5.8 6.5 8.3 11.1

0.3 0.5 4.7 5.0 4.8 1.8 2.0 2.2 3.1 2.5 1.6 1.0 0.7 7.3 4.4 1.8 6.2

4.1

2.9

8.6 Child poverty and single parents overty by its nature always involves deprivation and disadvantage, but poverty among different groups carries its own peculiar sadness. Among the old, it seems particularly sad that after people have spent a lifetime working they cannot find material security. Among the unemployed, there are the problems of loss of respect and of self-esteem compounding their material disadvantage. Poverty among children is particularly sad if it is likely to lead to a lifetime of disadvantage. Through no fault of their own, they are growing up in a situation that could severely affect their life chances. Childhood poverty thus strikes a blow against equality of opportunity, and deprivation in childhood can perpetuate a cycle of disadvantage. Table 8.16 reveals that the proportions of children living in poverty (defined as those living in households with disposable income less than 50% of median income) range widely between the selected countries. They are marginally lower than the rates of poverty among the elderly (Table 8.13: 13% compared with 11%), but are still unacceptably high. The rankings are very broadly similar in the two tables, with the usual suspects largely in their usual places. The Scandinavian countries have the lowest rates of child poverty, followed by various other European countries. The United States has the worst rate, while Ireland, Italy and Germany are on the next rung up. Italy seems rather better at taking care of its elderly than its children, while Australia is the reverse, its poverty rate being almost exactly average here while being second worst in Table 8.13. Table 8.16 documents also the success of the Blair Government’s announced intention to reduce child poverty in Britain. The rate halved from 20% to 10% in the decade covered by the table. The OECD argued that the most important factor affecting childhood poverty is the employment rate of parents. This becomes particularly acute when the parents are separated.

P

Table 8.17 gives the child poverty rates among four groups – those living with single parents, working or not working, and with couples, with neither working or with one working. (In situations with two parents and both working, child poverty rates are extremely low, almost non-existent.) While in both contrasts, the couple situation has fewer children living in poverty than when single parent households are involved, by far the more important factor is whether there is no employed parent living with the child. The figures are suggestive of larger social patterns. For example, it seems difficult for Japanese single parents to escape poverty, whether working or not. The prevalence of the working poor in the United States, and to a lesser extent Canada, is also apparent. The contrast in poverty rates between households with employed and unemployed adults is starkest in Australia. This is made explicit in the first column of Table 8.18. This gives the increased risk (the multiple by which the incidence increases) of child poverty in single parent families when the parent is not working compared with when they are. Except for Japan (where the risk is high in both) and Italy, it is higher in all countries, but for 10 of them, the factor of increased risk is less than four. Australia stands all alone at the bottom of the table, with the risk of child poverty increasing by 11 times for unemployed compared with employed single parents. It follows from this that a policy priority in reducing child poverty should be to facilitate the employment of single parents. And of all selected countries this is most the case in Australia. The importance of this is accentuated by the second column in the table shows that Australia has the second highest rate of children living in single parent jobless households. The Australian figure of 6.2% is only lower than Britain’s, and more than double the 18-nation mean.


147

Chapter 9 INTERNATIONAL RELATIONS

Table 9.1 Military spending Military spending as a % of GDP

Table 9.2 Size of armed forces Total size of armed forces (’000s)

1970

1980

1990

2000

2006

Country

1970

2000

2007

United States United Kingdom France Australia Italy Netherlands Norway Sweden Denmark Finland Germany Canada Belgium New Zealand Japan Austria Switzerland Ireland

7.9 4.8 4.2 3.5 2.7 3.5 3.5 3.7 2.7 1.4 3.3 2.4 2.9 2.2 0.8 1.1 2.2 1.3

5.4 4.9 4.0 2.6 2.1 3.1 2.9 2.9 2.4 1.9 3.3 1.8 3.3 1.9 0.9 1.2 1.9 1.9

5.5 4.0 3.6 2.2 2.1 2.6 3.2 2.6 2.1 1.6 2.8 2.0 2.4 1.8 1.0 1.0 1.9 1.3

3.1 2.5 2.6 1.7 2.1 1.6 1.8 2.1 1.5 1.3 1.5 1.2 1.4 1.0 1.0 0.8 1.1 0.7

4.0 2.6 2.4 1.9 1.8 1.5 1.5 1.5 1.4 1.4 1.3 1.2 1.1 1.1 1.0 0.8 0.8 0.5

United States France Germany Japan Italy United Kingdom Canada Netherlands Australia Austria Belgium Finland Sweden Norway Denmark Ireland New Zealand Switzerland

3188 577 499 .. 557 372 92 112 84 .. 95 41 .. 48 48 8 12 ..

1366 294 221 237 251 212 59 52 51 40 39 32 53 27 22 12 9 28

1506 255 246 240 191 191 63 53 52 40 40 29 28 23 22 10 9 4

Mean

3.0

2.7

2.4

1.6

1.5

Mean

410

167

167

Country

Table 9.3 Global arms spending and trade

Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

148

Country

Spending on arms 2007 ($US million)

World share %

Arms exports 2007 ($US million)

Share world arms exports %

Balance arms trade ($US million)

United States United Kingdom China France Japan Germany Russia Saudi Arabia Italy India South Korea Brazil Canada Australia Spain

547 60 58 54 44 37 35 34 33 24 23 15 15 15 15

45 5 5 4 4 3 3 3 3 2 2 1 1 1 1

7454 1151 355 2690 0 3395 4588 0 562 0 214 24 343 1 529

31 5 1 11 0 14 19 0 2 0 1 0 1 0 2

+6867 +453 −1069 +2627 −519 +3310 +4588 −72 +386 −1318 −1593 −151 −280 −684 +144

World

1339


24210

9.1 Military spending able 9.1 shows that on average among these established democracies the proportion of national income devoted to military spending has declined substantially over the last generation, and in 2006 was half what it was in 1970. Even in the last two decades of the Cold War, military spending did not keep pace with the growth in national incomes, but the end of the Cold War brought a substantial peace dividend. In the decades leading up to 2000, military spending as a proportion of GDP fell in all the selected countries. In some countries, this meant an absolute decline in military spending. More commonly it meant that military spending grew less quickly than the economy. The decline has not been as even as the decade intervals in the table might suggest. The United States increased its military spending greatly during the Reagan era, peaking at 6.6% of GDP in 1986. Similarly, according to figures from the Stockholm Institute for Peace Research (SIPRI), one of the two major world centres for compiling military data, world military expenditures reduced from 1987 to 1998, but then began climbing again. In terms of manpower, however, the decline was absolute, not just relative. The size of the armed forces in the selected countries in 2000 was less than half the 1970 totals (Table 9.2). The much greater drop in manpower than expenditure demonstrates that military strategies have become more technological, although equally, the plateau of the years following 2000 suggests that there is a lower limit to this trend. Many would have expected military spending to have jumped again following the terrorist attacks of 11 September 2001. Table 9.1 shows increasing divergence in the following years. For more than half the selected countries, military spending as a share of national income remained stable or fell. In only four countries, including Australia, Britain and the United States, did it increase.

T

These divergent trends have accentuated the already existing tendency towards American dominance. According to SIPRI data, in 2001 the United States’ military expenditure comprised 36% of the world total, and its spending equalled the next nine countries’ combined total. In 2007 (see Table 9.3), it comprised 45% of the world total, more than the world’s 14 next biggest spending countries combined. These 15 biggest spending countries account for three-quarters of the world’s total military spending. As Australia has increased its military expenditure since 2001, by 2007 it figured among these 15, one of seven countries on the list who are close American allies, making its dominance in spending even more emphatic. The United States is also dominant in arms exports, but its share is not as great, supplying 31% or almost one-third of the world’s conventional arms trade. Perhaps surprisingly, Russia has continued to be an important force here, ranking a clear second. It is a very concentrated trade: the top four arms exporters – the United States, Russia, Germany and France – provide two-thirds of the world’s total. And they are the four countries whose trading balance sheets show the biggest surpluses in armaments. Interestingly, three East Asian countries – China, Japan and South Korea – are major importers when it comes to armaments, all of them being among the major arms importers in the world, even though they generally tend to be big suppliers of the world’s manufactured goods. In Japan’s case this is a result of their peace constitution, which they interpret as limiting military expenditure to 1% of GDP, and refraining from dealing in arms exports. Australia also has a substantial deficit in its arms trade, and increases in military expenditure would be likely to increase that deficit.

INTERNATIONAL RELATIONS

149

Table 9.4 Foreign aid Official development assistance as % of gross national income Country

1990

1995

2003

2006

2006 ODA per capita $US

Sweden Norway Netherlands Denmark Ireland United Kingdom Belgium Austria France Finland Switzerland Germany Australia Canada New Zealand Japan Italy United States

.90 1.15 .90 .95 .17 .30 .43 .14 .61 .72 .34 .40 .36 .45 .24 .32 .30 .20

.80 .85 .81 1.00 .30 .28 .36 .25 .51 .32 .34 .31 .31 .35 .22 .24 .18 .11

.79 .92 .80 .84 .39 .34 .60 .20 .40 .35 .39 .28 .25 .24 .23 .20 .17 .15

1.02 .89 .81 .80 .54 .51 .50 .47 .47 .40 .39 .36 .30 .29 .27 .25 .20 .18

397 592 319 394 207 190 185 184 164 164 228 123 92 110 66 98 74 85

.49

.42

.42

.48

204

Mean

Table 9.5 Targeting of foreign aid Proportion of bilateral official development assistance going to the least developed countries (LDCs) 2006 Country

% to LDCs

Ireland Denmark Norway Belgium Finland Canada United Kingdom Japan New Zealand Sweden Switzerland United States Netherlands France Germany Italy Australia Austria

51 39 38 37 35 34 31 30 29 29 27 27 26 25 25 22 21 17

Mean

30

Table 9.6 Commitment to development aid Quantity and quality of foreign aid 2007 Higher score = more and better aid

Table 9.7 Comparative spending on arms and aid Aid spending as a % of military expenditure (100 means they are equal).

Country

Score

Country

%

Denmark Sweden Netherlands Norway Ireland Belgium Finland United Kingdom Switzerland Canada France New Zealand Australia Austria Italy Germany United States Japan

12.0 11.6 10.7 10.5 6.9 5.7 4.9 4.8 4.5 4.1 4.0 3.6 3.1 2.9 2.7 2.6 2.2 1.2

Ireland Sweden Austria Norway Denmark Netherlands Switzerland Belgium Finland Germany Japan New Zealand Canada France United Kingdom Australia Italy United States

108 68 59 59 57 54 49 45 29 28 25 25 24 20 20 16 11 5

Mean

150

5.4


Mean

39

9.2 Foreign aid n 1970, the United Nations adopted a target of rich nations giving 0.7% of their Gross National Product to aid poorer countries. Table 9.4 shows that four donor countries surpass that target and easily exceed all others in their generosity. Denmark, Norway, the Netherlands and Sweden all give more than 0.8% of their Gross National Income (GNI – the successor concept to GNP) in overseas aid, and then there is a considerable gap. Although the United States, being the largest national economy in the world, is the largest single donor of foreign aid in the world, as a share of national income it ranks at the bottom of these rich countries. The final column of the table offers another perspective on the countries’ relative generosity – how much they contribute per head of population. Although Sweden tops the list in terms of proportion of the economy, because Norway is a richer country, it comes top on a per capita basis. However, the rankings are broadly similar with some slight wrinkles. Switzerland moves up several places, while Italy drops into last place behind the United States. Australia remains firmly in the bottom third. Interestingly, and encouragingly, between 2003 and 2006, there was a increase in many of these countries’ commitment to foreign aid. There was publicity around international gatherings, with several leaders pledging further aid, especially to Africa, and indeed those pledges have been at least partially followed through. Ireland, Britain and Austria, in particular, increased their aid efforts in that threeyear period, and now all rank in the top half of the table. The New World English-speaking democracies also increased their aid, although not as dramatically. Ireland is particularly notable in that it has been increasing sharply its share going to foreign aid while decreasing the share going to military spending. As a result, it is the only one of the selected countries (Table 9.7) which

I

spends more on aid than on the military. The Scandinavian countries and the Dutch all spend at least half as much on aid as on the military, while at the other extreme, the United States spends 20 times as much on the military as on foreign aid, and Australia around six times as much. Although the public rationale for aid is to alleviate poverty, in practice its direction is shaped also by a variety of diplomatic, commercial and strategic factors. Table 9.5 examines what proportion goes to the poorest countries, the Least Developed Countries, as defined by the United Nations. Again Ireland tops the list. Australia comes near the bottom, largely because most of its aid is directed towards the Asia Pacific, and only a small proportion goes to Africa, where many of the poorest countries are concentrated. There have been several attempts to measure the quality as well as the quantity of aid. All necessarily suffer from some degree of arbitrariness, but sometimes can highlight important differences. The Center for Global Development created a Commitment to Development Index, part of which is their Aid score, reported here in Table 9.6. Their Index penalises ‘tied aid’ where recipients cannot seek the best deal but must take things from the donor country, which can raise project costs by up to 30%. It looks at how much aid is in the form of loans rather than grants. It also examines whether it goes to corrupt regimes. It penalises countries which overburden recipient countries by splitting their aid into too many small aid projects, carrying heavier implementation and reporting costs. On the other hand it rewards countries which make donations to private foreign aid charities tax deductible. Of course it puts all this in the context of the total amount given. By these criteria, Denmark, Sweden, the Netherlands and Norway remain very clearly at the top. Japan drops to last and the United States second last. Australia remains at 13th.

INTERNATIONAL RELATIONS

151

Chapter 10 ENVIRONMENT

Table 10.1 Mammals Number of mammal species found in each country; number of endemic and threatened species

Table 10.2 Birds Number of bird species breeding in country, number of endemic and threatened species

Country

Country

United States Australia Canada Japan France Italy Germany United Kingdom Austria Netherlands Switzerland Belgium Sweden Norway Denmark Finland New Zealand Ireland

All mammals

Endemic

Threatened

468 376 211 171 148 132 126 103 101 95 93 92 85 83 81 80 73 63

104 225 7 43 3 6 1 1 0 0 0 0 0 0 0 0 7 0

41 64 17 37 15 12 9 9 6 10 4 8 5 10 3 4 8 3

United States Australia Japan United Kingdom France Germany Italy Canada Sweden Netherlands Norway Belgium Denmark Finland Austria Ireland Switzerland New Zealand

All birds

Endemic

Threatened

888 851 592 557 517 487 478 472 457 444 442 427 427 421 412 408 382 351

122 387 55 11 5 5 3 6 3 6 5 3 4 4 3 5 0 128

74 50 39 3 5 4 7 18 3 1 2 1 3 3 5 1 2 70

Table 10.3 Reptiles Number of reptile species in each country, number of endemic and threatened species

Table 10.4 Protected areas Protected areas for wildlife

Country

Country

Australia United States Japan Italy New Zealand France Canada Switzerland Austria United Kingdom Germany Netherlands Belgium Denmark Norway Sweden Ireland Finland

152

All reptiles

Endemic

Threatened

880 360 92 55 54 46 39 17 16 16 15 13 12 8 7 7 6 5

760 106 34 3 49 0 0 0 0 0 0 0 0 0 0 0 0 0

38 32 11 5 12 5 3 0 1 0 0 0 0 0 0 0 0 0


Austria Switzerland New Zealand Germany United Kingdom United States Netherlands France Sweden Australia Japan Finland Italy Denmark Norway Canada Belgium Ireland

Area (’000 hectares)

Percentage of land area

2348 1180 6471 7575 4750 137923 430 5563 4237 73406 3454 2946 1936 247 1553 47315 97 78

28.3 28.2 24.2 21.3 20.0 14.6 12.4 10.2 9.6 9.5 9.3 8.9 6.4 6.0 5.1 4.8 3.2 1.2

10.1 Biodiversity nvironmental issues do not always lend themselves to a comparative, quantitative summary. Every country has its own natural endowments and problems bestowed by its geographical setting. Sometimes comparative measures are merely charting these different geographic-cum-economic inheritances rather than any meaningful difference in environmental performance. Similarly, many environmental problems are primarily local – the effluent produced by a neighbourhood factory; the problems of water flow and salinity in the Murray-Darling Basin; or the destruction of a particular urban heritage in the name of development. National summary measures cannot capture this local impact. Tables 10.1 to 10.3 give a crude measure of countries’ biodiversity simply by measuring the types of animals found in each. Counting species as if they are all of the same value, like a unit of currency, obviously fails to capture key dimensions of bio-diversity. However, the tables do show great differences among the selected countries. Australia is one of 17 ‘mega-diverse’ countries, whose ecosystems have exceptional variety and uniqueness. Of the selected countries, only the United States is also recognised in this way. The tables give testimony to this rich bio-diversity. The United States and Australia are the top two countries in all three tables, having far more mammals, birds and reptiles than any of the others. (The very large numbers are because zoologists distinguish many different types where most lay observers would see far fewer. Indeed, since the previous edition of this book, the numbers of species have increased, due to the industry of zoologists rather than natural evolution.) Australia and the United States both cover large areas, encompassing several climatic and geological zones, and allowing a range of flora and fauna. Australia, for example, has 15 900 native higher plants, which is more than the total for the whole of Europe (12 500). In addition, Australia’s geographic isolation has given it a vast array of species not found

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elsewhere. The second data column in the three tables gives the number of endemic species, i.e. species unique to that country. Here, America and Australia are still the leaders in all tables, but it is Australia which has by far the highest number. Indeed among the selected countries, Australia has more than half the endemic species in all three, largely because it does not share a land border with any other country. With economic development and population growth, wildlife has come under increasing stress. The three tables also summarise the numbers in each country under threat. The World Resources Institute distinguishes three levels of threatened species: critically endangered (an extremely high risk of extinction in the wild in the immediate future); endangered (a very high risk of extinction in the wild in the near future); and vulnerable (a very high risk of extinction in the wild in the medium-term future). Because of their larger total number of species, it is not surprising that Australia and the United States are again clear leaders. However, in Australia’s case, the threat has been greatly exacerbated by ongoing programs of land clearing, and by the introduction of invasive species. Foxes and cats prey on native species, while rabbits and goats compete for their land, and degrade it. The big gap between Australia, the United States, Japan and New Zealand compared with the numbers threatened in the other countries, though, is hard to explain, and may be at least partly due to methodological differences. A common response to the pressures on the natural habitat has been to set aside protected areas for wildlife. Although in absolute size, Australia has the second-greatest area set aside, in terms of proportion of land area it ranks well below the 18-nation mean. This is a crude measure which pays no attention to the quality of the areas, or their importance for native flora and fauna. Similarly more discriminating measures would be needed to know how well these wilderness areas redress the prospects of threatened species.

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Table 10.5 Global greenhouse gas emissions Tonnes of carbon dioxide equivalents (CO2 -e) per year Country

Total 2005

Tonnes per capita

Change since 1990

Rate of change (annual %)

7485.3 7424.3 2393.6 2200.7 1856.5 1432.0 990.8 859.4 745.8 696.0 666.9 634.1 593.9 570.4 557.8 543.2 220.1 145.4 94.3 93.4 68.8 68.1 63.0 62.9 57.0 55.6

5.7 25.0 2.2 15.4 9.9 11.2 12.0 3.9 23.1 6.7 11.1 30.9 8.6 9.7 11.6 8.6 13.5 13.8 23.0 11.4 13.2 7.6 11.7 15.3 12.4 7.4

3614.8 1115.5 810.0 −843.2 660.7 193.9 −186.5 242.2 154.4 180.6 −41.9 156.2 276.5 66.5 267.8 15.5 16.2 8.4 10.5 17.8 −1.5 −3.4 −4.6 6.9 8.7 3.2

4.5 1.1 2.8 −2.1 3.0 1.0 −1.1 2.2 1.6 2.0 −0.4 1.9 4.3 0.8 4.5 0.2 0.5 0.4 0.8 1.4 −0.1 −0.3 −0.5 0.8 1.1 0.4

China United States India Russia Brazil Japan Germany Indonesia Canada Mexico United Kingdom Australia Iran Italy Korea France Netherlands Belgium New Zealand Austria Finland Sweden Denmark Ireland Norway Switzerland World 1990 World 2005

154

34391.7 43475.9


10.2 Global warming ome environmental issues are purely local in scope, but others are global. The issue of global warming, if left unaddressed, is the greatest long-term threat to current patterns of social and economic life, not only in the selected countries but throughout the world. As the OECD and United Nations have observed, 11 of the 12 years between 1995 and 2006 ranked among the warmest 12 recorded since 1850. Global temperatures have risen by 0.74◦ C over the last century. If current trends continue, they are projected to rise by between 1.4◦ and 5.8◦ C in the 21st century. This would be a bigger climate change than any experienced over the last 10 000 years. Its consequences would be many-sided and radical. A central concern is rising sea levels because of the melting ice caps. The Arctic summertime ice is decreasing by just over 7% a decade. At regional levels there would be a variety of consequences – droughts in some areas, but more rain in others, more tropical cyclones, more bushfires. Global warming is attributed to the greenhouse effect, a short-hand description for the way carbon dioxide and other gases form a blanket, which stops some of the sun’s heat escaping from the earth, so making the planet warmer. Establishing that global warming is manmade is inherently difficult because the weather itself is so full of extreme natural variability that it is impossible to tie any particular occurrence to the long-term trend. Not only is there variability year to year but through human history there have been long cycles as well. Nevertheless the reasons for thinking recent changes are anthropogenic are compelling. Atmospheric carbon dioxide and methane concentrations are higher than at any time over the last 650 000 years, and the human race is now producing ‘greenhouse gases’ at a far greater rate than ever before. The 1997 Kyoto Protocol forcefully focused attention upon global warming, and it has continued to be an issue ever since. As the International Energy Agency commented, ‘the climate change problem is unique in at least

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three important ways: it is global in nature, it has an unusually long-term character, and both climate change itself and the effects of policies to mitigate it remain inadequately understood’. Most urgently, there is the danger of passing a point of no return in terms of environmental damage. While most policy issues involve reactions to already-manifest problems, global warming involves the anticipation of a problem, whose adverse consequences will damage future generations rather than the present one. Furthermore the measures needed to combat it have immediate costs, while their benefits are in the avoidance of future catastrophes – not the most promising scenario for decisive political action. Table 10.5, which gives the data for the selected countries plus all those countries globally whose annual emissions total more than 550 tonnes of CO2 -e, illustrates the complexities obstructing any international solution. The Kyoto Protocol bound the most developed nations to a series of reductions in greenhouse gases, with others to follow later. Critics rightly point out that some of these other countries, particularly China and India, need to be included in any agreement for it to effectively address the problem. China has now supplanted the United States as the leading greenhouse gas emitter – the two countries together produce around onethird of the planet’s total – while other large countries not included in the first phase of the Kyoto Protocol are also high on the table. The third and fourth columns show that these countries’ emissions are increasing at the fastest rate. Historically, however, the most affluent economies have contributed most to the problem developing, and the table’s second column shows that in terms of emissions of greenhouse gases per person the United States is four times higher than China. Indonesia ranks somewhat ahead of Australia in total emissions, but on a per capita basis, Australia produces more than eight times as much.

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Table 10.6 Changes in total greenhouse gas emissions Total anthropogenic emissions (Gigagrams [Gg]) of greenhouse gases, 2006 (LULUCF = land use, land-use change and forestry) Country

Total Gg of emissions including LULUCF

Percentage change since 1990 including LULUCF

Percentage change excluding LULUCF

968 654 28 136 477 210 51 70 1249 26 456 47 6171 73 752 69 55 550

−19.3 −15.6 110.6 −5.0 −9.4 −2.0 1.5 −1.1 5.8 −28.7 4.1 −10.8 14.0 12.5 54.8 24.3 33.0 6.6

−18.2 −15.1 −8.7 −5.2 −3.5 −2.0 0.8 2.2 5.3 7.7 9.9 13.2 14.4 15.1 21.7 25.6 25.7 28.8

6.5

9.7

Germany United Kingdom Sweden Belgium France Netherlands Switzerland Denmark Japan Norway Italy Finland United States Austria Canada Ireland New Zealand Australia Mean

..

Table 10.7 Greenhouse gas emissions Tonnes of carbon dioxide equivalents (CO2 -e) per head per year Country

156

1990

2005

Switzerland France Sweden Austria Italy Japan United Kingdom Germany Norway Belgium Denmark Netherlands Finland Ireland New Zealand United States Canada Australia

7 9 6 9 9 9 13 15 10 14 13 14 11 14 15 20 20 29

7 8 8 9 10 10 11 12 12 13 13 13 16 17 19 21 23 27

Mean

13

14


10.3 Greenhouse gas emissions he Kyoto Protocol identified six greenhouse gases. Carbon dioxide (CO2 ) is the most important, contributing around 74% of the total. Methane (CH4 ) contributes around 15%, and nitrous oxide (N2 O) about 9%. Three combined fluorinated gases (or F-gases) together comprise somewhat less than 2%. In order to look at the totality of their impact, the measure of carbon dioxide equivalents has been constructed. One tonne of methane, for example, has the same effect as 21 tonnes of CO2 , so one tonne of methane has the warming effect of 21 CO2 -e. Although the mixes differ for each country, world-wide, in 2005, the energy sector generated 69% of CO2 emissions, agriculture provided 44% of methane emissions and 83% of N2 O emissions. The major concern of the delegates at the 1997 Kyoto summit was to secure agreement between the United States, the European Union and Japan on targets. 1990 was the baseline year, so that in 2010 greenhouse gas emissions for the countries as a whole were to be reduced by 5.2% (a 29% cut in terms of what was projected otherwise to have been the case). Different countries signed on to different targets. Australia, being a relative minnow, was able to exploit the overriding wish of the major powers for a unanimous agreement, by becoming, with Iceland, one of two countries to be allowed an increase in total emissions as its Kyoto target, in Australia’s case an 8% increase. Australian delegates exploited another peculiarity of 1990 as the base year. In that year, abnormally heavy land clearing had occurred in Queensland. Such land clearing increases CO2 concentrations, but in what became known to other delegates as ‘the Australia clause’, Australia insisted strenuously late in the negotiations that it must be included. In environmental jargon this is referred to as land use, land-use change and forestry (LULUCF). Table 10.6 shows the total emissions per country in 2006, including LULUCF.

T

The next two columns show the amount of change between 1990 and 2006 if LULUCF is included and then if it is excluded. Including LULUCF makes those countries still undertaking land clearing, such as Canada and New Zealand, rate comparatively more poorly, and those with large forests and carbon sinks, such as Norway and Finland, rate comparatively better. If LULUCF is excluded, Australian emissions have increased the most among the selected countries, up by almost 29% in those 16 years, compared to an overall rise of just under 10%. In contrast if LULUCF is included, Australia’s rate of increase looks much better, less than one-quarter as much, and now rating almost exactly at the mean. (The Swedish figure is as published, but looks anomalous. As carbon trading becomes more widespread, there will be greater pressures for accuracy.) In 1990, an anomalous year, LULUCF comprised around 20% of Australia’s emissions; in 2006 it comprised just 3%. By 1995, it was already down to 4%. Thus Australia achieved its greatest progress in meeting its Kyoto target before the protocol was agreed, and before the Howard Government came to power. The last two columns of Table 10.6 show considerable variations in the changes since 1990. When LULUCF are included, eight countries have reduced their emissions, and when excluded, six have done so. That table gives total emissions irrespective of population size. Even so, Australia’s total is higher than France and Italy, which are three times more populous. Table 10.7 gives the figures on a per person basis. It can be seen that many European countries and Japan have lower readings, and the four New World English-speaking democracies have the highest. The distinctive aspects which contribute to Australian pre-eminence in greenhouse gas emissions are the reliance on coal-fired power stations for electricity, the heavy reliance on road transport, large-scale agriculture and some continuing land clearing.

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Table 10.8 Energy usage per person Total primary energy supply tonnes of oil equivalent (TOE) per person Country

1976

1986

1996

2006

Italy Denmark Switzerland United Kingdom Ireland Japan Austria Germany New Zealand France Netherlands Belgium Sweden Australia Norway Finland United States Canada

2.41 3.87 2.93 3.66 2.22 2.90 2.89 4.36 3.04 3.33 4.76 4.66 5.21 4.43 4.02 4.54 8.13 7.32

2.34 3.94 3.66 3.66 2.60 3.04 3.09 4.64 3.52 3.68 4.38 4.69 5.90 4.65 5.12 5.61 7.41 7.54

2.83 4.29 3.58 4.01 3.24 4.08 3.63 4.32 4.46 4.27 4.87 5.55 5.89 5.48 5.30 6.22 7.95 7.99

3.14 3.73 3.78 3.84 3.89 4.13 4.16 4.24 4.24 4.36 4.90 5.36 5.66 5.93 6.51 7.18 7.76 8.30

Mean

4.15

4.42

4.89

5.06

Table 10.9 Means of electricity generation Percentage of different fuels used in electricity generation, 2007 Fossil

Nuclear

Hydro

Other renewable

Australia Ireland Netherlands Italy Denmark United Kingdom United States Germany Japan Finland Belgium Norway Austria Canada France Sweden Switzerland New Zealand

91 90 87 81 78 75 71 61 61 44 39 35 33 25 10 3 2 1

0 0 3 0 0 19 19 26 28 28 54 0 0 15 78 47 43 0

7 4 0 14 0 2 7 4 9 14 2 54 57 58 11 43 51 98

2 6 10 5 22 4 3 8 2 13 5 11 10 2 1 7 4 1

2000 Mean 2007 Mean

50 49

20 20

27 24

4 7

Country

158


10.4 Energy nergy generation is itself a major part of the economy, but is also pivotal to other economic and social activities, and it can have huge impacts on the environment in air pollution, in the production of greenhouse gases, and in the depletion of non-renewable resources. Energy efficiency is important in making other parts of the economy more productive. The conventional measure of energy intensity – the amount of energy per unit of GDP – shows considerable improvement over the decades, but this stems more from changes in the patterns of the economy, especially the rise of the services sector and the relative decline of manufacturing in many of the selected countries. A strong incentive towards greater energy efficiency in the economy has also been rising prices, especially after the various oil shocks and spikes since 1973. Nevertheless while the energy intensity of the economy has improved, Table 10.8 instead tells a story of increasing energy usage per person. From 1976 to 2006, energy supply measured in the conventional way of tonnes of oil equivalent went up by about 20% for each person, reflecting continuing growth in domestic usage and motor transport. The rankings in the table have stayed broadly consistent over time, with North America, Australia and three of the Nordic countries having the highest energy usage. They show some contrasting trends however. Finland, perhaps because of its growing affluence, has increased more than any other. Australia has also shown a greater than average increase, growing from 0.28 to 0.87 tonnes above the mean, with each decade recording increases of broadly similar scale. Table 10.9 shows the shares of fuels used for electricity generation in 2000. The large differences between countries are explained by a country’s natural resource endowments. Hydro power, for example, is the major source of electricity in a few countries with the mountains and fast-flowing rivers that lend themselves to it. So it supplies almost all New

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Zealand’s electricity, and is the biggest source in Canada, Austria, Norway and Switzerland. Nor is it surprising that it is a negligible source in the low-lying relatively flat countries of Denmark, the Netherlands, Belgium and Britain. Similarly, dependence on fossil fuels – principally coal and to a lesser extent natural gas – correlates strongly with which countries have had plentiful supplies. Australia heads the list. It is not only dependent on coal for its own electricity generation, but is a major coal exporter as well. There is great divergence between the countries in the degree to which they have embraced nuclear energy. The countries which developed nuclear power did so for a variety of reasons, perhaps its relative cheapness among different possibilities, perhaps to match their great power ambitions, perhaps because they saw it as the way of the future. France heads the list, with its neighbours Belgium and Switzerland also relying on nuclear power as a major source. Seven countries, including Australia, have not developed nuclear power at all. Nevertheless, in the years between 2000 and 2007, nuclear power’s share in the selected countries overall did not grow. Indeed the shares of all sources of electricity remained largely constant over these seven years, with a slight gain by renewable sources, such as wind, and a slight fall in hydro. By 2007, renewable energy sources represented more than 10% of electricity in the Netherlands, Finland, Norway and Austria, and 20% in Denmark. It remained a small source in Australia. The Australian State of the Environment Report 2001 noted that cleaner renewable sources of electricity were growing at a much slower rate than the older, non-renewable sources, such as coal. Australia’s liberalisation of the energy market had lowered prices without internalising the full cost of its environmental effects, and had further increased the price differential to the detriment of renewable sources of energy. Nothing in this later data would change this judgement.

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Table 10.10 Spending on pollution control Expenditure on pollution measures as a % of GDP Country

Table 10.11 Generation of waste Kilograms of waste generated per person per year, 2003 Country

Municipal

Household

2.4 2.3 2.3 1.7 1.6 .. 1.5 1.4 1.1 1.1 0.8 0.8 0.8 0.8 0.7 0.6 0.3

Japan Belgium Finland Sweden Italy France New Zealand Austria Netherlands United Kingdom Canada Germany Switzerland Denmark Australia Norway United States Ireland

410 440 450 470 520 540 .. 560 600 610 640 640 660 670 690 700 740 760

270 370 190 .. .. 350 400 410 520 500 330 510 450 560 400 370 440 400

1.3

Mean

594

408

Late 1990s

Early 2000s

Austria Denmark Netherlands France Germany United States Belgium Japan Canada Sweden Australia Finland Italy Switzerland United Kingdom Ireland Norway

1.7 0.9 1.8 1.4 1.5 1.6 0.9 1.6 1.1 1.2 0.8 1.1 0.9 1.6 1.0 0.6 1.2

Mean

1.2

No data on New Zealand.

New Zealand placed roughly where figure on household waste would suggest.

Table 10.12 Glass recycling Quantity collected for recycling as a % of apparent total consumption

Table 10.13 Paper recycling Quantity collected for recycling as a % of apparent total consumption

Country

Country

1990

1995

2003

Switzerland Sweden Japan Belgium Germany Austria Norway Netherlands Finland Denmark Ireland Italy France New Zealand Australia United Kingdom United States

65 44 48 55 54 60 22 67 36 35 23 53 41 .. .. 21 20

85 61 61 67 75 76 75 80 50 63 39 53 50 30 42 26 24

96 92 90 88 88 86 86 81 73 71 67 59 58 48 40 36 19

Mean

43

56

69

No data on Canada.

160


1990

1995

2003

Japan Germany Finland Switzerland New Zealand Norway Netherlands Sweden Austria Belgium Denmark France United Kingdom United States Australia Italy Canada Ireland

50 44 43 49 .. 29 50 46 52 33 35 34 33 28 51 27 28 ..

51 67 56 61 47 46 59 70 66 37 44 39 35 40 .. 28 41 11

88 74 73 70 69 69 68 67 62 53 53 53 51 48 47 47 43 38

Mean

40

47

60

10.5 Waste, recycling and pollution control aste is a by-product of nearly all human activities. Even in ancient cities, the hygienic and efficient disposal of waste was a major problem. With the scale of contemporary metropolises, industrial production and affluent consumer lifestyles, waste disposal and pollution control have become expensive and contentious policy issues. Who should pay for combating pollution? How are the environmental costs of goods and services to be built into prices and taxes? Where should the sites for waste disposal be situated? (The answer is usually ‘Not in my back yard’ [NIMBY].) Are they safe? Pollution abatement and control (PAC) activities are defined as activities aimed at the prevention, reduction or elimination of pollution and other nuisances arising as a residual of production or consumption of goods and services. Table 10.10 shows that on average these activities cost 1.3% of GDP in the early 2000s, just above its late 1990s figure. Whether it is because its problems are less severe or its response has been slower, Australia is among a group of lower spenders in the bottom third of the table. Austria, Denmark and the Netherlands lead by a considerable margin, all having substantially increased in the short interval covered by the table. However, the table contains a lot of erratic and seemingly inexplicable movement, including sharp drops by Switzerland and Norway, which would seem to raise issues of measurement reliability at least for those countries. Municipal waste includes waste from households, offices, shops and other commercial enterprises, but excludes sewerage, construction, industrial and hazardous waste. According to the OECD disposal of municipal waste represents more than one-third of the public sector’s financial efforts to contain and control pollution. The importance of waste disposal is shown by Table 10.11. Each year in the selected

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countries, each person on average generates 594 kilograms of waste, which includes 408 kilograms of household waste. While Australian households are close to average in the waste they generate, Australia ranks above average in the amount of municipal waste. The large costs of waste disposal, plus the prospect of ever-increasing amounts that will not break down naturally extending endlessly into the future, contributed to a concern with waste minimisation. One approach has been the growth of recycling, defined as any re-use of material in a production process that diverts it from the waste stream. Table 10.12 shows that between 1990 and 2003 there was a substantial rise in the recycling of glass. Although all countries except the United States shared the general increase, by the 2000s there was a large range in the degree to which they had embraced the practice. Seven of the countries have rates of 86% or greater, while four English-speaking countries, including Australia, are still below half, and well below the mean. The OECD’s environmental data sources, from which this table is drawn, give no information on the practices (compulsory refundable deposits on bottles or taxes on plastic bags for example) which might account for such differences. Table 10.13 shows that while in 1990 there was only a small difference between glass and paper recycling, the rise of the latter was not as fast, with paper having a mean nine points lower in 2003. Only Japan had a rate above 80%, but for most the figure was greater than half. Apart from New Zealand, the Englishspeaking countries and Italy had the lowest rates. While some environmentalists argue it is more important to reduce consumption than to increase recycling, waste management, waste minimisation and pollution control and abatement are going to continue to be major concerns of all the selected governments.

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Table 10.14 Ecological footprint Global hectares per person Country

162

1999

2008

Germany Netherlands Italy France Japan Austria Switzerland Belgium Sweden Finland United Kingdom Ireland Norway Canada New Zealand Australia Denmark United States

4.7 4.8 3.8 5.3 4.8 4.7 4.1 6.7 6.7 8.4 5.3 5.3 7.9 8.8 8.7 7.6 6.6 9.7

4.2 4.4 4.8 4.9 4.9 5.0 5.0 5.1 5.1 5.2 5.3 6.3 6.9 7.1 7.7 7.8 8.0 9.4

Mean

6.3

6.0


10.6 Ecological footprint erhaps the most fundamental environmental issue is sustainability. Will a particular society be able to continue its practices indefinitely into the future, or are current practices exhausting resources, building up environmental problems or incurring economic and social costs so that they will have to be significantly curtailed, or, even, end in disaster? The concept of sustainability entered official policy discourse at a global level when governments embraced it at the United Nations Conference on the Environment and Development at Rio de Janeiro in 1992 (the first Earth Summit). A group called Redefining Progress has since sought to measure sustainability by constructing an Ecological Footprint. It has drawn up Ecological Footprint Accounts, which document humanity’s demands on nature, and assess our ecological ‘bottom line’. In Wikipedia’s summary, ‘The ecological footprint is a measure of human demand on the Earth’s ecosystem. It compares human demand with planet Earth’s ecological capacity to regenerate. It represents the amount of biologically productive land and sea area needed to regenerate the resources a human population consumes and to absorb and render harmless the corresponding waste.’ Redefining Progress says that ‘Ecological footprints measure how much of the biosphere’s annual regenerative capacity is required to renew the natural resources used by a defined population in a given year . . . When a population’s footprint is greater than biocapacity it is reported to be engaging in ecological overshoot.’ Redefining Progress expresses its measure in terms of global hectares: the biologically productive space required to provide the services using current technology. The idea of the Ecological Footprint is then a simple, comprehensible and useful indicator of sustainability. Its drawback is that the calculations needed to arrive at this bottom line are very complex, and it has been criticised at several points.

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Table 10.18 shows the countries fall into two broad groups. The first group which on average scored better on sustainability consists of 11 countries which scored between 4.2 and 5.3 global hectares, with Germany and the Netherlands scoring best. Then there is a second group of higher scoring countries. The top-scoring six countries include the Englishspeaking New World democracies, plus two Scandinavian countries. The American standard of living demands more global hectares per person than any other country by a large margin, while Australia ranks third top among the selected countries. The table shows data for 1999 and 2008. While they keep developing and improving their methodology, it may mean that the figures for the two years are not strictly comparable. They show a slight decline in the overall mean, with countries moving in both directions. Australia is one of seven countries to record a rise, although a slight one. Redefining Progress estimates that in 2005 – there is a three-year lag in its data because it has to await the UN figures on all its various components – humanity’s footprint exceeded Earth’s biocapacity by 23%. It estimates that the sustainable limit for each person should average 1.9 global hectares. The table shows that all the selected countries exceed this figure, and their mean is around three times greater than the maximum desirable. This is not surprising. It reflects the huge differences in development between the selected countries and the Third World. The OECD, a group which includes our 18 countries but several other advanced economies as well, has one-quarter of the world’s population, but accounts for 80% of GDP and 80% of world trade. In the late 1990s, OECD populations consumed 45% of all meat and fish, 58% of global energy, 84% of all paper, and 87% of all cars. This huge inequity in material standards of living bedevils many global negotiations on environmental issues.

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Chapter 11 SCIENCE AND TECHNOLOGY

Table 11.1 Investment in knowledge Investment in knowledge as a % of GDP

Table 11.2 Research and development Percentage of GDP devoted to research and development

Country

Country

1997

2004

United States Sweden Finland Japan Denmark Canada France Australia Germany Netherlands United Kingdom Austria Belgium Italy Ireland

5.7 5.6 5.2 4.4 3.8 3.9 3.8 3.6 3.5 3.5 3.3 3.1 2.6 2.0 2.6

6.6 6.4 5.9 5.3 5.1 4.5 4.3 3.9 3.9 3.8 3.5 3.4 3.4 2.4 2.3

Mean

3.8

4.3

No data on New Zealand, Norway or Switzerland.

1985

1995

2005

Sweden Finland Japan Switzerland United States Germany Denmark Austria France Canada Belgium Australia United Kingdom Netherlands Norway Ireland New Zealand Italy

2.8 1.5 2.6 2.6 2.8 2.6 1.2 1.2 2.2 1.4 1.6 1.1 2.2 2.0 1.5 0.8 .. 1.1

3.3 2.3 2.7 2.6 2.5 2.2 1.8 1.5 2.3 1.7 1.7 1.6 2.0 2.0 1.7 1.3 1.0 1.0

3.9 3.5 3.3 2.9 2.6 2.5 2.5 2.4 2.1 2.0 1.9 1.8 1.8 1.7 1.5 1.3 1.2 1.1

Mean

1.8

1.9

2.2

Table 11.3 Researchers Researchers per 1000 in employment Country

164

1985

1995

2005

Finland Sweden Japan Denmark New Zealand United States Norway Australia France Canada Belgium Germany Austria Switzerland Ireland United Kingdom Netherlands Italy

4.1 5.0 6.3 3.3 .. 7.3 4.8 4.3 4.7 4.4 4.1 5.3 2.1 4.2 2.5 4.9 4.3 2.9

8.2 8.2 8.3 6.1 4.7 8.1 7.5 7.1 6.7 6.4 6.0 6.2 3.9 5.5 4.5 5.2 4.8 3.5

16.5 12.5 11.0 10.2 10.2 9.7 9.3 8.5 8.0 7.7 7.6 7.0 6.8 6.1 5.9 5.5 4.5 2.9

Mean

4.4

6.2

8.3


11.1 Investment in knowledge here has been considerable talk in recent decades about the information society, and undoubtedly the ability to create, distribute and exploit knowledge is increasingly central to a country’s competitive advantage and rising standard of living. So investing in these areas is important for innovation, job creation and continuing economic growth. To investigate this, the OECD has constructed a new concept of ‘investment in knowledge’, defined as spending on higher education, research and development (R&D) and software. It covers spending by both the public and private sectors, but excludes consumer spending on software, and differs from the cumulative spending in the three areas by seeking to eliminate overlap, and also to isolate, for example, the research aspects of higher education. It can be seen in Table 11.1 that, by 2004, total annual spending on knowledge averaged 4.3% of GDP across the selected countries. Between 1997 and 2004, investment in knowledge had grown somewhat more quickly than the economy as a whole. The United States’ high level of total investment in knowledge is not surprising – it is, after all, the country at the world’s technological frontier. Similarly, Japan in fourth place is consistent with that country’s reputation for innovation. Perhaps more surprising may be the presence of three Nordic countries in the top five places. Ireland, Italy, Belgium and Austria often seem to lag behind on measures to do with technology and innovation. Australia was just below the mean in 1997 and had slipped a bit further below it by 2004. Table 11.2 narrows the focus to one of the three components of the investment in knowledge measure, namely the total public and private spending on R&D. Here we have a longer run of data, and it can be seen that over the two decades from 1985 to 2005, annual R&D spending rose fairly steadily as a percentage of GDP – meaning, of course, that R&D spending grew at a faster rate than economies did overall. Australia was below the mean in each

T

of the years, but still substantially above the three countries investing least in R&D – Italy, New Zealand and Ireland. As is conventional, Table 11.2 puts each country’s R&D spending into the context of that country’s relative size by expressing it as a percentage of national GDP. When countries’ spending is compared in absolute terms, however, a very different picture emerges. The United States accounted for 42% of the selected countries’ total spending on R&D, with Japan contributing 17% and the combined EU figure comprising 30% of the OECD total. Table 11.3 puts a more human face on the pursuit of knowledge by ranking the selected countries according to their number of researchers per 1000 in the labour force. Here researchers are defined broadly as professionals engaged in the conception and creation of new knowledge, products, processes, methods and systems. It can be seen that the proportion of researchers grew almost universally in these two decades – meaning not merely that their ranks kept increasing, but that their numbers grew at a lot faster rate than the labour force as a whole. The mean for the selected countries almost doubled between 1985 and 2005, with Australia’s increase being similar. Perhaps because of the breadth of the definition of ‘researchers’, this is the only table where Australia is above the mean, but still behind New Zealand. The leader in the table, Finland, had the sharpest increase, and by 2005 had double the mean of the other countries. Its Scandinavian neighbours, Sweden and Denmark, are notable for their commitment to research, and Japan ranks highly. Again, moving from expressing figures in share to absolute terms shows the dominance of the largest nation, the United States. Taking the OECD as a whole, the United States has 37% of all researchers, the EU 33% and Japan 18%.

SCIENCE AND TECHNOLOGY

165

Table 11.4 Business investment in R&D Business R&D as a % of value added in industry Country

Table 11.5 Researchers in business Researchers per 1000 in employment, 2005 Country

2005

Sweden Finland Japan Switzerland Denmark United States Germany Austria France Belgium United Kingdom Netherlands Canada Australia Ireland Norway Italy New Zealand

4.6 3.6 3.4 3.2 2.7 2.6 2.4 2.3 2.0 1.8 1.6 1.5 1.4 1.3 1.3 1.2 0.8 0.7

Mean

2.1

Table 11.6 Sectors of business R&D Share of business R&D in services and of manufacturing R&D in high- and low-tech areas, 2004 Services

High tech

Medium-low and low tech

Finland Canada United States Ireland United Kingdom Sweden Denmark France Netherlands Belgium Italy Japan Germany Norway Australia

14.9 39.4 36.3 38.9 21.6 10.6 33.7 9.8 19.2 18.5 24.6 9.3 8.3 41.7 47.4

66.4 64.3 63.6 62.7 62.5 58.5 57.9 51.8 50.9 49.5 46.5 42.8 33.5 31.6 26.5

14.0 19.4 10.1 15.0 9.2 7.4 15.5 13.5 12.2 20.5 12.5 13.4 7.8 36.0 34.2

Mean

24.9

51.3

16.1

Country

No data on Austria, New Zealand or Switzerland.

166


Business

Other

Finland Sweden United States Japan Denmark Canada Norway France Germany Austria Belgium Ireland United Kingdom Switzerland New Zealand Australia Netherlands Italy

9.2 8.5 7.7 7.5 6.4 4.7 4.6 4.3 4.3 4.3 3.9 3.5 3.2 3.0 2.6 2.4 2.3 1.1

7.3 4.0 2.0 3.5 3.8 3.0 4.7 3.7 2.7 2.5 3.7 2.4 2.3 3.1 7.6 6.1 2.2 1.8

Mean

4.6

3.7

Table 11.7 Big and small business R&D Percentage of business R&D by size of firm, 2005 Country

Small

Medium

Large

Japan Germany United States France Italy United Kingdom Sweden Finland Switzerland Netherlands Austria Denmark Canada Belgium Australia Ireland Norway New Zealand

0.0 1.9 6.6 6.5 5.1 5.8 8.3 9.0 8.0 8.1 9.6 15.0 16.6 16.7 22.8 20.1 21.5 46.2

7.9 6.4 7.7 9.9 11.9 12.8 11.6 11.3 12.4 18.7 17.5 15.4 18.4 23.5 18.3 27.1 30.3 27.2

92.1 91.7 85.7 83.6 83.0 81.4 80.1 79.7 79.6 73.2 72.9 69.6 65.0 59.8 58.9 52.8 48.2 26.6

Mean

12.7

16.1

71.3

11.2 Business research and development hile the tables on the previous page gave the countries’ total commitment to R&D, both public and private, here the focus is narrowed to concentrate on the private sector. The first two tables give the commitment of business to R&D in 2005. Table 11.4 gives the percentage of business spending on R&D in relation to the value added in industry. Sweden clearly leads the way, with a figure more than double the mean of the selected countries. Finland, Japan and Switzerland are on the next level down, still very substantially above the overall mean. Italy and New Zealand bring up the rear, and Australia also trails at around 60% of the mean for the selected countries. Table 11.5 also offers a snapshot of data from 2005, this time focusing upon the employment of researchers. If you add up the two columns in Table 11.5, they should sum to the figure in the final column of Table 11.3 on the previous page. Some countries have a major commitment to research in both public and private sector employment, especially Finland, but it is noteworthy that among the top 13 countries on the table, only Norway has more public sector than private sector researchers (and then by just 0.1%). But in the bottom five countries, four of the five have more in the public than private sector. In other words, Norway apart, government commitment to employing researchers is never sufficient by itself to give a country a high ranking in total research employment. The countries at the bottom of the table are there not so much because their governments do not employ researchers but because their businesses do not. This is especially marked in Australia and New Zealand. While these first two tables chart the total commitment to R&D in each country’s business sector, the other two give some insights into where and how the research effort is manifested. Table 11.6 does this in terms of the

W

sectors of the economy where R&D is carried out. The first column does this by looking at the share of the total being carried out within the services sector, and Australia has by far the highest proportion here. The last two columns looks within the R&D being done in manufacturing: how much is done in high-tech areas, and how much in low- and medium-low tech areas. Again this shows Australia having a distinctive pattern with the lowest share going to high tech and the second highest to low and medium-low tech. Table 11.7 shows the share of business R&D being done by large, medium and small businesses. Overwhelmingly most of it is done by big business. The six countries at the top of the table are the six largest economies. In other words, in big economies most R&D is done by big firms, whereas in the smaller economies most R&D is done by smaller firms. One reason for this may be differences in government incentives to research. For example, in big military spenders, such as the United States and France, military R&D is overwhelmingly contracted to large firms. Virtue and vice are not situated at any particular level of business enterprise, but R&D involves long lead times, uncertain timing, high risks, high upfront expenses, and so on the whole larger and richer organisations are often better able to absorb the costs and risks and see research through to fruition. There are debates about ‘first mover’ advantages compared with what Veblen called the advantages of being second. Australia has tended to be more of an adaptor of others’ technologies in many areas, agriculture and mining apart. No country can be a pioneer in all areas, but there are also dangers in having a branch office economy, lagging behind the international leaders. The increasingly important information economy poses questions for every country about support for research and innovation.


167

Table 11.8 Patents Triadic patents per million population

Table 11.9 Scientific articles Scientific articles per million population

Country

1995

2005

Country

1993

2003

Japan Switzerland Germany Netherlands Sweden United States Finland Denmark France Austria Belgium United Kingdom Canada Norway Australia New Zealand Ireland Italy

75.2 102.2 58.0 45.9 75.8 45.1 59.8 34.5 31.6 27.0 36.4 25.8 13.0 19.8 12.1 5.5 7.6 10.6

119.3 106.7 76.0 72.6 72.3 55.2 50.3 40.5 39.3 36.5 31.8 26.4 25.4 24.1 20.2 15.7 14.2 12.2

Switzerland Sweden Finland Denmark Netherlands United Kingdom Australia Canada New Zealand Norway United States Belgium Austria Germany France Japan Ireland Italy

983 980 711 784 743 736 672 831 627 612 758 447 386 420 445 347 281 269

1154 1143 998 982 831 811 792 783 751 731 726 637 604 537 516 470 441 429

38.1

46.6

Mean

613

741

Mean

Table 11.10 Product innovations Percentage of firms with new to market product innovations Small and medium enterprises (SMEs) and large firms, 2002–2004 Country

SMEs

Large

Austria Ireland Denmark Belgium Finland Sweden France Netherlands Canada Italy United Kingdom New Zealand Japan Norway Germany Australia

24.2 22.0 23.8 19.9 20.3 25.4 11.3 15.7 28.8 10.8 20.0 20.0 11.0 13.1 8.3 7.0

53.0 47.2 45.1 44.1 44.1 43.9 42.0 40.6 36.3 36.0 32.4 27.0 26.0 24.5 19.1 12.0

Mean

17.6

35.8

No data on Switzerland or the United States.

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11.3 Outputs – patents, publications, products hile the previous two pages focused on the inputs in science and technology – investments and labour – the tables on this page focus upon outputs, although as a measure of progress each has its drawbacks. Patents are one tangible measure of inventive activity that has potential commercial value, and as individuals and companies have become more conscious of the importance of intellectual property, and as in nearly all phases of economic and social life there is more emphasis on innovation, patent activity has increased. While countries have had national patent offices for well over a century, the registering of them internationally and international agreements to observe them have increased over recent generations. The OECD has developed the construct of triadic patent families which are defined as a set of patents taken at the European Patent Office, the Japan Patent Office and the US Patent and Trademark Office that protects the same invention. This improves the international comparability of patent activity by eliminating the influence of geographical advantage and national home office ‘advantage’. Patents included in the triadic family are typically of higher value, as patentees only expend the extra cost and effort of registering transnationally if they think it is worthwhile. Table 11.8 examines countries’ triadic patent activity in relation to population, showing that it increased by around 20% overall between 1995 and 2005. Japan and Switzerland, both above 100 per million population, were clearly the top two countries, well ahead of Germany, the Netherlands and Sweden in the 70s, with the United States and Finland in the 50s. Australia was in the bottom quarter keeping company with other regular technological followers, New Zealand, Ireland and Italy. While Table 11.8 compares the patent activity relative to population size, it should also be remembered that in absolute size in 2005 the United States accounted for 31% of all patent families in the OECD; Europe 28% and

W

Japan 29%. Japan’s share was slightly up and the others slightly down when compared with 1995. Table 11.10 examines commercial innovation from another perspective, by looking at the percentage of big firms and of small and medium enterprises which introduce newto-market innovations. In other words these products are new, and not adaptations of existing ones, or improvements in technique or marketing of existing ones, and where the innovation is for the market as a whole, not just a company’s new venture into an existing field. The table shows firstly that the introduction of new to market products is very much the province of big rather than small companies, by a factor of about 2:1. It also shows that smaller European countries dominate as having the highest intensity of innovation while Japanese companies are less innovative by this measure. The table shows Australian companies bringing up the rear in both categories, but Australian big firms are much lower than the norm, at only one-third of the overall mean. Australian large companies have put comparatively more effort into process innovation, and largely restricted themselves to being adaptors of existing products. This low ranking is consistent with their fairly low rankings on business R&D. The third table, 11.9, looks at publication counts, which have been long used as an indicator of scientific productivity, especially of universities, but also of research centres and public agencies. Like patents, publications in total showed an increase of around 20% in the decade being considered. Some rankings are similar to the patents table, and some different. Switzerland is near the top of both, as are the Nordic countries with the exception of Norway. Ireland and Italy are near the bottom of both. Japan goes from top to close to bottom. Unlike the commercial measures, where Australia is below the mean, here it is well within the top half, grouped with some other English-speaking countries.


169

Chapter 12 TELECOMMUNICATIONS AND COMPUTING

Table 12.1 Personal computers Personal computers per 1000 population

Table 12.2 Mobile telephones Mobile telephones per 1000 population

Country

1988

1990

1995

2000

2005

Country

Switzerland Canada Netherlands Sweden United States United Kingdom Denmark Austria Australia Germany Norway France Ireland New Zealand Finland Japan Belgium Italy

52 71 51 59 184 75 58 39 103 67 .. 55 54 .. .. 42 51 21

88 105 93 105 212 109 115 65 151 81 .. 71 85 .. 100 60 88 37

286 218 201 249 320 205 268 162 278 179 274 146 183 219 235 120 178 84

656 420 396 507 567 344 506 358 472 336 489 302 358 361 396 315 223 178

887 877 855 835 773 765 695 610 608 605 594 579 530 516 500 407 379 370

Italy Austria United Kingdom Germany Netherlands Ireland Finland Denmark Sweden Norway Switzerland Belgium Australia New Zealand France Japan United States Canada

65

98

211

399

632

Mean

Mean

1985

1990

1995

2000

2005

2007

0 1 1 .. 0 0 14 9 9 15 0 0 0 0 0 1 3 0

5 10 19 4 5 7 52 29 54 46 18 4 11 16 5 7 21 22

68 48 98 46 35 44 201 158 227 225 63 23 124 101 22 93 128 88

737 770 727 586 673 650 720 631 717 751 643 520 447 408 493 526 389 294

1231 1058 1097 959 971 1029 1004 1003 1007 1029 942 922 914 876 795 753 714 527

1531 1186 1185 1176 1175 1159 1152 1145 1137 1105 1097 1027 1025 1017 898 839 835 617

3

16

100

593

935

1072

For Australia and Japan, latest year = 2003.

Table 12.3 Internet users Internet users per 1000 population Country

1995

2000

2003

2005

2007

Norway Netherlands Denmark Sweden Finland Switzerland Canada United States Germany United Kingdom New Zealand Australia Japan Austria Belgium Ireland Italy France

64 65 38 51 139 36 42 93 18 19 49 28 16 19 10 11 5 16

267 440 391 456 372 480 423 436 301 269 480 470 299 333 291 179 229 143

750 640 710 770 660 650 640 626 540 610 620 600 483 410 496 310 395 363

800 790 770 810 730 700 680 690 650 660 640 630 666 550 580 370 482 432

849 840 810 800 790 770 730 725 720 720 700 690 689 670 667 570 543 512

39

348

571

646

711

Mean

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12.1 Personal computers, mobile phones and internet f we compare life in Australia and the other advanced democracies today with earlier decades, three technological innovations, which were barely envisaged in 1979, and still had very limited presence in 1989, have transformed people’s daily lives. The three tables on this page chart the very rapid and all but universal diffusion of these innovations. The first was the personal computer (PC), which changed the way most people work, increasing productivity and convenience by a huge amount. They have become so much a part of everyday life that it is almost impossible to imagine life without them. So it may be surprising to recall just how recent their invention and spread have been. They began in a small way in the early 1980s, but take-up was relatively slow. By 1988, the first year for which we have systematic data, they had established a firm foothold in offices and among some professionals, with around one in 15 people having one. However, as Table 12.1 shows, by 2005 there were almost two personal computers for every three people – including business and home computers. Even in the first five years of the 21st century, the number of personal computers in relation to population was growing as rapidly as it had been in the 1990s. The figures for Australia and Japan would have been higher but the latest year for which there was data was 2003. The overall average is depressed by two countries – Italy and Belgium – which lag a long way behind the others. When looking at the growth recorded in Table 12.1, it should be remembered that the capacity of a personal computer in 1988 was only a fraction of what it was by 2009. It is a remarkable story of decreasing price and increasing power. The range of tasks for which people use PCs has increased, and it is the means by which most people connect to the other great popular computing innovation of recent times – the internet.

I

There are few more rapid social changes than the spread of personal computers, but Table 12.2 tops it. The cellular mobile telephone went from novelty to ubiquity in 20 years. In 1985, mobile services were only commonly used in the Nordic countries, and in the selected countries overall there were only three mobile phones for every 1000 people. By 2007, mobile phones outnumbered people in 14 of the 18 selected countries. (These figures may be inflated by multiple subscriptions or simcards, or counting discarded phones, but they are still impressive.) Taking the 18 countries together, it was in the second half of the 1990s that more than half the population came to possess a mobile phone, but the growth continued into recent times, even increasing by more than 10% between 2005 and 2007. Mobile phone technology developed in Scandinavia, and for a long time those countries were the world leaders in their use. Then, in the early 1990s, the next phase of rapid adoption came in the English-speaking world. In the late 1990s, the most dramatic growth was in some European countries – Italy, Austria and Ireland – which were relatively late adopters of the technology, but which now rank among the leaders, surpassing the Scandinavians and North Americans. The growth of the most recent of the three innovations – the internet – is just as dramatic. The very idea of the internet was unimaginable for most people before the mid-1990s. At that time, according to Table 12.3, less than one person in 25 used the internet. Since then it has transformed the way in which people seek information and entertainment and communicate with each other. By 2007, seven people in 10 were users, the number having doubled between 2000 and 2007. In France and Italy, only just over one in two people use the internet.

TELECOMMUNICATIONS AND COMPUTING

171

Table 12.4 Telecommunications revenue Telecommunications revenue as a % of GDP Country

1985

1995

2005

New Zealand Belgium Australia Switzerland Japan Germany United States Sweden Finland Italy Denmark Ireland Austria Canada France Netherlands United Kingdom Norway

2.46 1.27 1.92 2.15 1.58 1.60 2.67 1.78 1.50 1.48 1.49 2.31 1.68 2.21 1.65 1.45 2.36 1.91

3.44 1.56 2.99 2.62 2.14 1.87 2.71 2.91 1.95 1.68 2.07 2.08 1.82 2.09 1.94 2.05 2.50 2.14

5.39 3.63 3.61 3.54 3.40 3.05 2.90 2.80 2.70 2.55 2.54 2.53 2.52 2.38 2.37 2.22 2.18 1.63

Mean

1.86

2.25

2.89

Table 12.5 Telecommunications revenue per person $US Country

2000

2005

Italy United Kingdom France Canada Netherlands Austria Finland Germany Norway Sweden Japan United States Denmark Ireland Belgium Australia New Zealand Switzerland

430 516 448 671 638 552 774 627 604 774 1287 1135 782 592 709 761 576 1144

771 805 807 835 862 939 1013 1035 1045 1109 1210 1212 1213 1228 1290 1300 1442 1722

723

1102

Mean

Table 12.6 Employment in Information and Communication Technology (ICT) Share of ICT-related occupations, broadly defined, % of total labour force Country

1995

2004

United Kingdom Netherlands Sweden Denmark Norway Finland Switzerland Ireland Germany Belgium Italy United States Australia Canada France Austria

27.8 23.0 20.4 20.4 .. 20.1 .. 17.3 20.4 18.7 20.9 21.2 21.0 20.7 18.6 15.1

28.7 24.5 24.4 24.1 24.1 23.8 23.4 22.2 21.5 20.6 20.4 20.3 20.1 19.9 19.8 17.2

Mean

20.4

22.2

No data on Japan or New Zealand.

Figure 12.1 Telephone charges $US, August 2006 1200 1000 800 600 400 200 0

Residential high usage

Residential low usage D18

Mobile data is for May 2007

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Mobile phone low usage

Australia

Small office/home office

12.2 The telecommunications market elecommunications and computing – with their mix of technological dynamism and very popular new services – have been growing far more rapidly than the economy as a whole. Table 12.4 shows that in the 20 years between 1985 and 2005, the share of national income taken up by telecommunications increased by more than 50%, from 1.86% to 2.89%. Even though prices for many services were declining, use and quantity were increasing to produce this growth in relation to GDP. Australia’s growth was particularly rapid, almost doubling its share from 1.92% to 3.61%, although not growing quite as rapidly as the two countries ahead of it on the table, New Zealand and Belgium. Not all countries exhibited such growth however and in a couple, the United Kingdom and Norway, the share of national income going to telecommunications declined. Because national income was also rising in this period in all the countries, Table 12.4 gives a somewhat muted picture of rising telecommunications expenditure. In Table 12.5, which gives data on how the telecommunications revenue per person changed in the five years between 2000 and 2005, all countries except Japan showed a substantial rise. Australian consumers are in the top three countries in terms of this measure, and, in dollar terms their spending grew the fourth most, with the other countries at the bottom of the table – Switzerland, New Zealand and Belgium – increasing even more. Growth in telecommunications and IT revenue has been much greater than growth in employment. Table 12.6 shows that broadly defined these occupations grew by just under 10% as a proportion of total employment in the selected countries between 1995 and 2004, fairly healthy growth overall but not consistently shared. Indeed, Australia is one of the four countries where we have data that employment fell by this measure between 1995 and 2004. So by 2004–2005, Australia was

T

in the top quarter of countries on telecommunications expenditure, but also in the bottom quarter in terms of ICT employment. Because of the changing nature of services provided, it is not always easy to chart changing prices. Many technological advances should have made services much cheaper, and there is controversy over whether charges to consumers have sufficiently matched the decline in underlying costs. Just to compare them at one point in time is also difficult. The OECD has gone to considerable lengths to compare equivalent costs in its member countries by constructing ‘baskets’ of services. Figure 12.1 offers a snapshot of prices in August 2006 for fixed line services. In each case Australia falls into the most expensive quarter of countries. Among the 18 countries, it ranks 15th in terms of costs for a high usage residential service; 17th on the residential low usage basket and 18th on the small office/home office basket. As can be seen in the graphs, in each case Australia is considerably more expensive than the mean for the selected countries. This is also the case in terms of the low usage mobile service basket which the OECD presents, where Australia ranked 15th. Sometimes Australia’s relatively high telecommunication charges are justified in terms of its large area and low population density. This overlooks Australia among the most urban of the selected countries, as we saw in chapter 1. Perhaps the country closest to Australia in terms of geography and demography is Canada, and in each of the four baskets its charges are considerably lower: $368 compared with $1008 for residential high usage; $298 compared with $460 for residential low usage; $560 compared with $933 for home office/small office; and $188 compared with $260 for the mobile phone low usage basket. For Australian telecommunications consumers who feel their bills are too high, a look at comparative countries is not likely to be soothing.


173

Table 12.7 Share of mobile phones in telecommunications revenue Percentage of total telecommunications revenue coming from mobile services Country

Table 12.8 Cellular mobile phone revenue per subscriber Annual revenue $US

1995

2000

2005

Austria Italy Japan Finland United Kingdom Ireland Norway Australia France Belgium Denmark Netherlands Germany Canada United States Switzerland New Zealand Sweden

33 15 22 20 9 20 15 16 7 10 8 10 15 14 9 7 10 12

48 38 46 42 32 47 33 25 26 22 24 34 31 18 19 23 28 23

61 54 54 50 49 47 44 44 40 38 37 37 34 31 30 30 23 22

Mean

14

31

40

Country

1995

2000

2002

2005

Sweden Netherlands New Zealand Italy Germany United Kingdom France Denmark Norway Finland United States Canada Belgium Austria Switzerland Ireland Australia Japan

422 1601 488 726 1829 465 1487 380 488 2952 593 642 1787 .. 1210 .. 792 2160

247 310 286 222 331 277 241 292 277 447 566 413 281 347 403 518 460 1122

216 376 260 271 318 275 288 285 348 473 552 387 385 410 471 361 233 921

246 315 330 343 371 374 421 442 448 496 506 507 533 559 562 570 634 860

Mean

1126

391

379

473

1995 figure for Austria and Ireland = 1998.

Table 12.9 Share of pre-paids in mobile phone subscriptions Shown as a %

Table 12.10 Competitive structure in mobile telephony Operators’ share of market, 2005

Country

Country

1999

2002

2005

Italy Ireland Netherlands New Zealand United Kingdom Belgium Sweden Germany Australia Austria Switzerland France Norway Canada Denmark United States Finland Japan

84 40 58 57 50 40 39 24 7 48 35 35 44 16 37 5 1 3

90 72 63 68 68 66 54 53 33 48 40 44 44 25 30 8 2 3

91 76 74 71 66 63 51 51 46 45 41 37 37 23 18 11 7 3

Mean

35

45

45

Number 1

Number 2

Number 3

Number 4

United States United Kingdom Canada Germany Austria Italy Denmark Australia France Belgium Ireland Netherlands Sweden New Zealand Japan Norway Switzerland Finland

25 26 36 37 40 40 41 45 47 48 49 51 52 53 53 60 63 66

24 23 27 37 24 33 24 33 36 33 38 23 28 47 24 24 19 4

21 23 37 14 21 19 21 17 17 18 13 11 17 0 16 8 18 19

10 23 0 12 12 8 5 5 0 0 0 15 3 0 3 6 1 12

Mean

46

28

17

6

Operator numbering is in order of when operators were established.

174


12.3 Mobile telephony s we saw in Section 12.1, mobile telephones now outnumber people in most of the selected countries, and their rapid growth has made them an increasingly important source of revenue for the telecommunications industry. Table 12.7 shows that in the 10 years between 1995 and 2005, mobile revenue rose from 14% to 40% of the total telecommunications revenue in the selected countries. In four countries it was over half, but in two it was still less than a quarter. Australia was at 44%, just above the mean. Table 12.8 shows the average revenue per subscriber to a mobile service. In stylised terms, it presents a U-shape. In 1995, charges for the consumer were very considerable, and in some countries, notably Finland and Japan, staggeringly so. Over the next five years, however, there was a dramatic drop, so that the mean in 2000 was only about one-quarter what it was five years earlier. As was seen in Table 12.2, this five years (when prices were dropping) was the period in which subscriptions rose sharply. The trough of this downward path in revenue per subscriber was reached in 2002, when the overall mean was $US379, and then revenue per subscriber rose fairly substantially, increasing by almost $100, up by a quarter, in the next three years, presumably due at least partly to increased usage. In all but three of the countries – Japan and the United States, the two biggest spending countries in 2002, and the Netherlands – revenue per subscriber increased, in most of them markedly. Even within this picture of general increases, Australia stands out. It had by far the biggest increase, with a rise of $US400 per subscriber. (Note that this OECD data does not seem to be adjusted for relative purchasing power or in constant dollars to take account of inflation. So the comparisons are somewhat susceptible to changes in exchange rates.) Australia ranks as the second-greatest generator of revenue per subscriber, 40%

A

higher than the mean, and behind only Japan. One reason for the surge in the popularity of mobile phones was the increasing prevalence of ‘pre-paid’ deals. Comparing Table 12.9 with Table 12.2 shows that mobile phones have achieved some of their highest penetration in countries where the proportion of pre-paids is greatest, most notably Italy. In eight of the 18 countries, pre-paids account for more than half of mobile subscriptions, but there is great variation and their popularity seems to have plateaued. The mean for 2005 was identical to that in 2002. Moreover in 2005, while in Italy 91% of mobile phone subscriptions were pre-paid, in Japan it was only 3%, and North America and the Nordic countries, apart from Sweden, also seem relatively immune to their appeal. The huge growth in telecommunications has coincided with substantial deregulation of the sector. Historically in all countries except the United States, telephone services were provided by a public monopoly. Many of these have now been at least partially privatised, while all countries have allowed some competition, although sometimes highly restricted. Some aspects of telecommunications lend themselves to competition more easily than others. The greatest obstacle has long been ‘the last mile’, the line connecting the customer’s premises to the network, which nearly always remained a monopoly of the incumbent carrier. The competition between incumbents and new entrants was also lop-sided because of the former’s existing infrastructure and established customer base. Mobile telephony is one of the areas which most lends itself to competition, but Table 12.10 shows that in half the countries the incumbent still enjoys more than half the revenue. Only in the United States and United Kingdom is its share down to around a quarter, and only in those two countries and Germany is there near parity between it and its closest competitor in market share.


175

Table 12.11 Internet hosts Registered internet hosts by domain name (’000) and number per 1000 population in 2006

Table 12.12 Secure servers Secure servers per 100 000 inhabitants, in July each year

Country

1998

2006

Hosts/ population

Finland Norway Netherlands Denmark Sweden Australia Switzerland Belgium Austria New Zealand Japan Italy Germany France United Kingdom Canada Ireland

450 286 381 159 319 665 115 88 109 169 1169 243 995 333 988 839 38

2506 2109 7258 2316 2817 6039 2125 2546 1957 972 24904 11223 9853 6863 5778 2817 241

476 453 444 426 310 293 284 243 237 235 195 191 120 112 95 86 58

US data not included because not comprehensive.

Table 12.13 Business use of the internet As a % of businesses with more than 10 employees, 2006 Have own website

Have broadband access

Sweden Japan Denmark Switzerland Finland Netherlands Austria United Kingdom Germany Norway Belgium Canada Ireland France New Zealand Italy Australia

86 86 83 82 80 79 78 75 73 72 67 68 64 61 59 57 53

89 .. 83 85 89 82 70 77 73 86 85 92 61 87 82 70 70

Mean

72

80

Country

No data on the United States.

176


Country

1998

2002

2006

United States Canada Denmark Australia New Zealand Switzerland United Kingdom Ireland Netherlands Sweden Finland Norway Germany Japan Austria Belgium France Italy

5 3 1 3 2 2 1 2 1 2 1 1 1 0 1 1 0 0

38 25 12 24 26 22 17 15 8 14 14 12 10 6 12 4 4 2

87 64 58 57 57 55 55 42 39 39 37 36 33 31 27 14 9 5

Mean

2

15

41

Table 12.14 Dial-up and broadband internet Percentage of internet connections using each, and number of subscribers per 100 inhabitants, December 2005 Country

Dial-up

Broadband

Subscribers

Belgium Canada Netherlands Denmark Finland Japan France Norway Austria Switzerland United Kingdom Italy Sweden United States Australia Germany New Zealand Ireland

13 19 25 26 27 27 29 30 34 34 39 40 43 48 60 61 67 69

87 81 75 74 73 73 71 70 66 66 61 60 57 52 40 39 33 31

21 26 34 34 31 24 21 31 22 36 27 20 35 31 34 33 25 21

Mean

38

62

28

12.4 The internet t is abundantly clear that the internet is transforming social life and behaviour. As with many social phenomena, it is easier to get valid statistics on revenue and infrastructure than usage, let alone attitudes. On many aspects of on-line activity, we have no reliable measures. We have no reliable data, for example, on the amount of email communication (let alone any figures distinguishing wanted from unwanted emails) or on the number of hours people in different countries spend on-line. However, the continuing dramatic growth of the internet is charted in Tables 12.11 and 12.12. The number of internet hosts registered in each country is shown in Table 12.11. All the countries showed a very large growth. In Australia, for example, there were nine times as many in 2006 as there had been in 1998. According to the OECD’s figures in 1998 there were just under 30 million domain names registered worldwide. By 2006, this had grown to 394 million. Websites in a sense represent the ‘front of shop’. While they have been growing, the ‘back of shop’ infrastructure to support them has been growing at a parallel rate. According to the OECD, in 2000 there were 2.21 million web servers in the world; by 2006 that number had leapt to 19.86 million. The coming age of e-commerce has been heralded frequently in recent years. Its growth, together with increasing concerns about security, underpins the rapid recent growth in the number of secure servers. Secure servers provide a protocol for encrypted transmissions, and so protect the security of credit card transactions, a crucial step for the growth of internet shopping. Table 12.12 shows the number of secure servers increased from two to 41 per 100 000 people in the eight years between 1998 and 2006. The English-speaking countries, and especially the United States, largely led the way. Italy, France and Belgium were again the

I

slowest adopters of this technology. Japan was slow to begin, but between 2002 and 2006 started to increase more rapidly. These figures are on a per capita basis. When put in absolute terms they show the pre-eminence of the United States. In 2006, America accounted for 59% of all the secure servers in the OECD. Nevertheless Table 12.13 suggests that Australian businesses have been somewhat slow to embrace the internet. Only just over half (53%) of Australian businesses with 10 employees or more had their own website in 2006, compared with an average of 72% in the selected countries overall. At that time, seven in 10 Australian businesses were also lagging in broadband access, with seven of 10 companies having broadband, so that Australia was keeping company with Italy and Austria, and was somewhat ahead of Ireland, which was bringing up the rear among the selected countries. This last figure may reflect lack of availability of broadband more than businesses not taking it up. As Table 12.14 shows, the rollout of broadband was slower in Australia than in most of the other selected countries. By December 2005, more than half the internet connections were broadband, rather than dial-up, in 14 of the selected countries. Australia was one of four still below that mark. Column three shows the number of internet subscribers. (This figure is naturally lower than the number of internet users in Table 12.3. Only one subscription per household or workplace would normally be taken out.) The countries fall into two groups, with nine countries having 31 or more subscribers per 100 people and the others 27 or less. Again, Italy is the laggard with just 20. Just above it, perhaps by coincidence, come several other predominantly Roman Catholic countries – Belgium, Ireland, France and Austria. Australia ranks equal third with several countries closely grouped around the same number of 33.


177

Table 12.15 Broadband penetration Total broadband subscribers per 100 population (in second quarter of each year) Country

2002

2004

2006

2008

Denmark Netherlands Norway Switzerland Sweden Finland Canada United Kingdom Belgium France Germany United States Australia Japan Austria New Zealand Ireland Italy

6.6 4.9 3.0 3.8 6.8 3.5 10.3 1.3 6.2 1.6 3.2 5.5 1.3 3.9 4.6 1.1 0.1 1.1

16.9 15.4 11.3 14.6 12.3 10.9 16.4 7.4 14.2 7.9 6.6 10.9 5.2 12.7 8.7 3.5 1.6 6.0

29.3 28.9 24.4 26.5 23.4 24.9 21.9 19.2 19.2 17.6 15.1 17.9 16.9 19.0 15.7 11.6 8.8 13.1

36.7 35.5 33.4 32.7 32.3 30.7 27.9 27.6 26.5 26.4 26.3 25.0 23.5 23.0 20.6 20.4 19.1 18.2

3.8

10.1

19.6

27.0

Mean

Table 12.16 Broadband speed Average speed of a representative broadband subscription 2007 (Kbit/s) and fastest download speed offered by incumbent telecommunications operator, October 2006 Country Japan Finland New Zealand Sweden Italy France United Kingdom Canada Germany Netherlands Norway Belgium Denmark Switzerland United States Austria Ireland Australia Mean

Table 12.17 Data caps on broadband subscribers Percentage among survey offers with no explicit bit/data caps, and price per additional megabyte, $US PPP, October 2007 Country

% no limit

United States Sweden Norway Netherlands Japan Italy Germany France Finland Switzerland Denmark United Kingdom Austria Ireland New Zealand Canada Belgium Australia

178

100 100 100 100 100 100 100 100 100 90 88 75 61 39 0 0 0 0

Additional price .. .. .. .. .. .. .. .. .. 0.11 0.12 0.002 0.08 0.02 0.01 0.001 0.01 0.11


Representative

Incumbent

102400 24576 24576 24576 20480 18432 8192 7168 6144 6144 6144 4096 4096 3500 3072 2048 2048 1536

100000 24000 3500 24000 20000 20000 8000 16000 16000 6000 16000 17000 20480 5000 30000 2048 3000 1500

14957

18474

Table 12.18 Broadband costs Average monthly broadband advertised prices in $US PPP, 2007 Country

Per month

Per Mb/s

Japan France Italy United Kingdom Switzerland Germany Norway United States Finland Ireland Netherlands New Zealand Austria Denmark Sweden Belgium Australia Canada

34.21 36.70 41.09 33.34 32.69 32.22 55.74 53.06 31.18 40.41 39.06 48.66 50.08 34.34 34.00 46.08 52.26 51.07

3.09 3.70 4.61 5.29 8.17 8.44 9.81 12.60 13.45 14.92 15.26 16.75 17.66 17.70 18.40 18.55 21.34 28.14

Mean

41.45

13.21

12.5 Broadband – access, speed, costs he internet revolution was less than a decade old when a sub-revolution in its delivery began. Broadband, with its greater bandwidth than the traditional dial-up telephone lines, was able to carry far more data more quickly and more cheaply. So the starting point of any contemporary consideration of accessing the internet is the availability of broadband. Table 12.15 shows the very rapid rise of broadband subscriptions. The average per 100 people in the selected countries rose from 3.8 in 2002 to 27.0 in 2008, a seven-fold rise in six years. Countries were already at quite different stages in 2002, but all have joined in the rapid growth since. Now the highest ranked country, Denmark, has double the rate of the lowest ranked, Italy. Australia began well below the mean and was considerably below the mean in each year of the table, in 2008 still falling in the bottom third of the countries. Apart from basic availability, there are large differences in the speed and costs of broadband across the selected countries. Table 12.16 offers data on download speeds. The OECD gives two measures, one the advertised rate offered in a typical subscription, the other the fastest speed advertised by the incumbent telecommunications carrier, which, in Australia’s case, is Telstra. In both cases, however, Australia comes a distant last among the selected countries, with an advertised speed less than one-eighth the mean. Japan is the fastest, and its rate is more than 50 times that of Australia. There is also a marked contrast between the countries in the volume a subscriber can download. In nine of the countries in Table 12.17, there is no limit on how much

T

can be downloaded. In another five, there is a variety of arrangements with the majority of subscriptions having no limits on downloads. Australia was one of four countries where no such unlimited subscriptions are possible, and among these four it had the highest price for going beyond the cap. The price per additional megabyte in Australia was 11 cents. For the other three at the bottom of the table it was one cent or less. Table 12.18 gives data on advertised broadband prices. Whether they are examined on the basis of monthly fees or on the price per downloaded megabyte, Australia ranks among the most expensive, in both cases well above the mean. Canada is more expensive on a volume basis, while American and Norwegian monthly subscriptions, which have unlimited volumes, cost more than Australia’s. The tables on this and other pages in this section paint a distinctive picture of Australian telecommunications compared with the other selected countries. Australian consumers have embraced the internet as least as eagerly as most others, but the provision of services has been slow to roll out, while those services have been relatively slow and expensive. In these senses, they offer a direct contrast to the Japanese, where infrastructure is fast and cheap, but whose embrace has been limited to a smaller number of consumers. Combined with the relatively high charges for fixed line and mobile telephones, the high costs of accessing the internet and the slower speeds and download caps placed on them, when viewed comparatively Australian telecommunication consumers have few blessings to count.


179

Chapter 13 MEDIA

Table 13.1 Newspaper circulation Paid circulation of daily newspapers per 1000 population

Table 13.2 Number of newspapers Paid daily newspaper titles 2007

Country

1980

2007

Country

Japan Norway Finland Sweden Switzerland Austria United Kingdom Germany Denmark Netherlands Ireland New Zealand United States Canada Australia Belgium France Italy

567 463 505 528 393 351 417 .. 366 326 229 334 270 221 323 232 192 101

624 580 503 449 355 345 308 291 280 268 236 216 213 173 166 161 154 112

Norway Switzerland Finland Sweden Denmark New Zealand United States Germany Canada Australia Belgium Ireland Austria Netherlands United Kingdom France Italy Japan

Mean

342

302

Mean

Number

Titles per 1000 adults

74 90 53 84 32 23 359 99 52 26 9 17 29 104 85 85 109

19.3 14.0 12.1 11.0 7.2 7.0 6.0 5.1 3.7 3.1 3.0 2.7 2.4 2.1 2.1 1.7 1.7 1.0

..

5.8

..

Table 13.3 Newspaper revenue Percentage of daily newspapers’ revenue from advertising, and % of this from classified advertising, 2007 % revenue from advertising

Of which % is classified

United States Canada Ireland Australia Belgium Finland Sweden Germany United Kingdom Italy Netherlands Denmark France Japan Switzerland

86 77 72 65 58 54 53 53 51 49 47 39 38 36 ..

31 35 27 58 42 25 38 .. 22 7 10 44 32 8 28

Mean

55

29

Country

No data on New Zealand, Austria or Norway.

180


13.1 Newspapers hile, after Gutenberg’s invention of the printing press, the book has the claim to be the first mass medium, it was the newspaper which from the 18th century on became central to political life and to the development of democracy. In the 21st century, at least in the English-speaking democracies, there is great pessimism about its future. This pessimism is only partly borne out by the circulation figures in Table 13.1. They show that, overall, the penetration of daily newspapers, measured by sales per 1000 population, declined in the 27 years between 1980 and 2007 by just over 10%, from 342 to 302 – a substantial decline but not necessarily catastrophic. Moreover, in four of the countries, the penetration of newspapers increased, including in the top two countries, Japan and Norway. While the rankings have remained broadly constant, the range in circulations has become even greater, with circulation holding up relatively well in the top countries, while in the traditionally low newspaper reading countries, such as Italy, France and Belgium, circulation has declined even further. By 2007, Japan had five times the relative newspaper circulation of Italy. The decline was greatest among the Englishspeaking countries, and sharpest of all in Australia. Australian newspaper penetration almost halved in these 27 years, down from 323 per 1000 to 166, putting Australia firmly in the bottom quarter of the selected countries. The primary reason for Australia having such a precipitate decline was the closing of titles. Between 1987 and 1992, all Australia’s afternoon newspapers, seven of them, closed. But in addition, the surviving newspapers have also been losing circulation, both relatively and absolutely. The closure of the afternoon newspapers also contributed to the fact that on a population basis Australia has fewer than average daily newspaper titles. The number of titles only correlates weakly with circulation. Japan, which has the highest circulation, also has by far the smallest number of newspapers relative to population, showing that its

W

major papers are very large organisations. On the other hand, the high-circulating Scandinavian countries also have a large number of newspapers, and low circulation countries, Italy and France, have relatively few papers. Australia’s relatively small number of newspapers in relation to population is a product of demography, history and commercial interest, which (although we lack systematic comparative data) has also made its press ownership uniquely concentrated. Two proprietors, Murdoch and Fairfax, account for more than 80% of daily circulation. Newspapers are supported by a mix of sales and advertising. Again, the table shows considerable variety. In Japan, newspapers earn almost two-thirds of their revenue from sales to the public, and only just over one-third, 36%, from advertising. In contrast, American newspapers earn fully 86% of their income from advertising and only 14% from the cover price. Although in more than half the countries for which there is data newspapers earn more than half their revenue from advertising, Australia is in the top quarter, with its newspapers earning almost two-thirds of their revenue from advertising, and only one-third directly from readers. In turn, there are two types of advertising, display and classified. It can be seen from the table that Australian newspapers are unusually dependent on classified advertising, the only country in which more than half of advertising revenue comes from that source. In a couple of countries, Italy and Japan, it is not important, while in most it represents just over one-quarter of advertising revenue. This dependence is unfortunate for Australian newspapers because it is classified advertising that disproportionately is migrating to the internet. While these varied figures offer little scope for generalising about the future of newspapers, it can be seen that the Australian press is not faring well in comparative terms. Its circulation is below average, and declining unusually rapidly, and it is particularly vulnerable to a decline in classified advertising revenue.

MEDIA

181

Table 13.4 Advertising Advertising as a % of GDP, averaged for each period Country

1987–2000

2003–2007

United States New Zealand Japan Australia Norway Netherlands Ireland United Kingdom Austria Belgium Switzerland Denmark Finland Germany Canada Sweden Italy France

1.31 1.33 0.80 1.22 0.74 0.86 0.88 1.20 0.77 0.65 0.99 0.81 0.86 0.92 0.80 0.77 0.50 0.71

1.35 1.31 1.28 1.12 1.05 0.98 0.94 0.94 0.87 0.85 0.78 0.76 0.74 0.73 0.71 0.69 0.59 0.56

Mean

0.90

0.91

Table 13.5 Advertising expenditure shares Proportion of advertising expenditure in each medium, 2007 Country

182

Newspapers

Magazines

Television

Radio

Cinema

Outdoor

Internet

United Kingdom Sweden Denmark Norway Australia Canada France Japan United States Finland New Zealand Germany Netherlands Belgium Italy Austria Ireland Switzerland

31.1 41.5 42.6 42.0 34.6 35.2 14.8 21.3 27.9 53.5 37.6 39.2 39.5 29.3 18.9 39.7 60.9 36.2

11.9 11.2 5.7 8.5 7.0 6.7 20.1 8.2 14.3 15.8 11.8 22.8 21.8 8.5 13.7 18.5 2.2 21.4

26.6 21.2 17.9 23.5 31.5 28.4 33.9 44.8 32.8 19.5 29.6 24.2 22.8 38.2 53.2 24.1 18.7 25.2

3.7 3.0 2.2 4.6 8.8 13.6 7.6 3.7 11.8 3.7 12.7 4.1 7.2 12.2 6.7 6.8 7.3 3.5

1.3 0.4 0.4 0.8 0.8 .. 0.8 .. 0.3 0.2 0.6 0.7 0.1 0.9 0.8 0.7 0.6 1.3

6.7 4.9 3.1 3.8 3.6 3.7 10.6 11.9 3.9 3.0 3.7 4.9 4.6 7.6 3.5 7.1 7.7 11.0

18.8 17.9 17.2 16.9 13.7 12.5 12.2 10.1 9.0 4.4 4.1 4.1 4.0 3.3 3.2 3.1 2.6 1.3

Mean 2003 Mean 2007

39.3 35.9

13.4 12.8

29.8 28.7

7.4 6.8

0.7 0.7

5.6 5.9

2.8 8.8


13.2 Advertising dvertising is credited with many social advantages and disadvantages, but whatever its larger social effects or its effectiveness in shaping consumer behaviour, it is crucial to sustaining many media activities. Overall, the proportion of the economy devoted to advertising has remained fairly stable in the last 20 years, at around 0.9% of GDP, according to Table 13.4. This conceals some fairly large variations, however. The American advertising sector compared to the American economy is two-and-a-half times as large as the French advertising sector in relation to its economy. Although there are several contrasting individual trajectories, there has been some convergence in the amount of GDP devoted to advertising. The factor which seemed to explain much of the variation decades ago was the amount of commercial television in a country, but the divergences have been somewhat reduced by the universal growth in the multi-channel environment. In both periods, New Zealand and Australia are near the top of the rankings in the amount of national income devoted to advertising. Table 13.5 shows what proportions of advertising are devoted to the different media in the selected countries. Perhaps its most interesting aspect is found in the bottom two lines comparing the means for each medium in 2003 and 2007. In just four years, the percentage of all advertising going to the internet more than trebled, from 2.8% to 8.8%. As a consequence, nearly all other media have declined somewhat.

A

The proportion of advertising going to the internet varies greatly between the countries. Britain leads the way and in eight countries the internet now attracts more than 10% of their advertising, while at the other end, there were still nine countries where it is less than 5%. Switzerland and Ireland bring up the rear. Indeed the whole of Table 13.5 shows marked variations. In 13 of the 18 countries, newspapers were still the biggest medium for advertising, and in Ireland and Finland they still account for more than 50%. In the other five countries, television is the major advertising medium. These countries included the newspaper laggards, France and Italy, but also the newspaper leader, Japan, where advertising in newspapers is relatively limited despite the high press penetration that Table 13.1 showed. Indeed the figures in Table 13.5 are testimony to how enduring are the differences in national traditions regarding advertising. In every medium, the gap between highest and lowest is considerable. The press ranges from a high of 60.9% (Ireland) to a low of 14.8% (France). Television ranges from a high of 53.2% (Italy) to a low of 17.9% (Denmark). Magazines peak at 22.8% (Germany) to trough at 2.2% (Ireland). Radio is highest in Canada (13.6%) and lowest in Denmark (2.2%). Outdoor advertising is highest in Japan (11.9%) and lowest in Finland (3.0%). Australia is quite a bit below average in the proportion devoted to magazines, and somewhat above average in television, radio and the internet.

MEDIA

183

Table 13.6 Television’s institutional basis Ownership of free-to-air (FTA) terrestrial television broadcasting and number of channels (public plus private) available in largest city Country

1970 system

Austria Denmark Netherlands Switzerland Belgium France Germany Ireland Italy New Zealand Norway Sweden Australia Canada Finland Japan United Kingdom United States

Public Public Public Public Public Public Public Public Public Public Public Public Mixed Mixed Mixed Mixed Mixed Private

Channels

1999 system

Channels

2 3 2 3 2 4 3 2 2 1 2 2 1+3 2+1 2+1 2+5 2+1 ..

Public Public Public Public Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed Mixed

2 2 3 3 2+2 2+3 3+3 3+1 3+8 2+2 2+1 2+1 2+3 2+2 3+2 2+5 3+2 ..

Table 13.7 Number of channels available Total available national channels 2005 Country Japan Italy New Zealand United States France Australia Germany United Kingdom Canada Denmark Finland Ireland Austria Netherlands Sweden Switzerland Belgium Norway

Table 13.8 Average television viewing time Average household viewing time, hours per day, 2005 or latest available year Country

Hours

United States Italy Belgium Japan Australia Canada Denmark United Kingdom Austria Finland New Zealand Ireland Switzerland Sweden

8.2 4.1 3.8 3.7 3.2 3.1 3.0 3.0 2.8 2.8 2.7 2.6 2.5 2.4

Mean

3.4

No data on France, Germany, Netherlands or Norway.

184


Terrestrial FTA national channels

Cable and satellite 100+ channels

128 13 10 9 8 5 5 5 4 4 4 4 3 3 3 3 2 ..

Y Y N Y Y Y Y Y Y N N N N Y N N N N

13.3 Television n none of the selected countries did broadcasting (first radio and later television) develop as just another industry where market forces could reign. Partly this was because of technological necessity, but even more centrally it was because of the cultural peculiarities and political power of broadcasting. There was an almost universal belief that a free market could not operate in television, that it would produce rubbish – with no standards, no local content, no quality drama, no children’s programs, no quality news or current affairs and last, but not least, no profits. Whereas in none of the countries is there any government-owned newspaper, only in America was there no publicly owned television channel. Indeed, as Table 13.6 shows, in nearly every mainland European democracy a government monopoly existed. In five countries, a mixed system of public and private prevailed. However, their mix and traditions differed considerably. In Britain, television began as a BBC monopoly, and then the private Independent Television Network (ITN) began in 1954. Later a second BBC channel was added, so that the public channels outnumbered the private 2:1. In addition, there was not one single owner for the private channel to be their fiefdom, but a complicated governance arrangement and stringent regulations about its operation and programming. In Australia, the private channels were able to be fully controlled by particular corporations, and initially outnumbered the public channels 2:1, which expanded to 3:1 less than a decade after television began in 1956. There are three possible means of financing television, and all have their disadvantages. The first, and most common in the English-speaking countries, is through advertising. The implicit equation is that viewers pay for the TV programming by buying the products advertised. It can occasionally produce subservience to advertisers, but the more fundamental objection is that, depending on market structure, it produces no institutional incentives towards excellence or catering to minority audiences.

I

The second means of financing is through the government, either by licence fee or from consolidated revenue. Especially when there is a government monopoly, this method carries the danger of political subservience. Its most basic problem is the lack of relationship between the funding mechanism and the audience. There are no performance-based incentives for ensuring responsiveness to public taste. The third means is by subscription. This is the most honest in the sense that there is a direct relationship between audience and product. For a long time, it was not technically possible. When it became so, its key disadvantage was that viewers had become accustomed to thinking of television viewing as free. Table 13.6 also records that despite the different beginnings, there was considerable convergence in the last decades of the 20th century, with nearly all countries moving towards a multi-channel environment and increased commercial participation. By 1999, terrestrial free-to-air television remained a public monopoly in only four countries. Table 13.7 shows just how much of a reality the multi-channel environment has become, both via terrestrial free-to-air services and other means of delivering services (including from across national borders). Indeed according to a 2008 Nielsen survey, the average American household now has 119 channels coming in. The early arguments about the scarcity of the spectrum are a long way in the past. The growth in the number of television channels has not been matched by a great increase in television viewing. While it is true that Americans watch TV more than the other selected countries, the discrepancy is not as great as Table 13.8 suggests. It was not possible to obtain systematic data about hours watched by individuals per week, and the figure for households in the table reflects partly that American households have more people in them, and perhaps also a custom of leaving the TV on whether or not anyone is watching. Australia’s figure of 3.2 hours per day (22 hours per week) is close to the average.

MEDIA

185

Table 13.9 Audience share of public service television Percentage of daily viewing going to public channels, 1999 and 2004 (or latest available year) Country

1999

2004

Denmark Austria United Kingdom Finland Germany Italy Norway France Sweden Ireland Netherlands Switzerland Belgium Australia Canada United States

67 59 50 43 43 48 40 42 47 50 35 35 26 18 13 3

72 51 46 45 44 44 44 41 40 38 37 36 29 20 11 2

Mean

39

38

No data on Japan or New Zealand.

Table 13.10 Public broadcasters’ funding Public broadcasters’ revenue 1999 Country Denmark Austria Norway United Kingdom Switzerland Finland New Zealand Ireland Germany Netherlands Sweden Belgium Italy Japan France Australia Canada Mean

186


Revenue per capita ($US)

Public funding per capita ($US)

117 96 86 83 83 73 66 66 64 58 51 47 47 44 43 29 25

76 47 80 57 56 69 6 28 49 39 48 31 22 44 23 23 16

63

42

13.4 Public broadcasting s we saw in Table 13.6, in all the selected countries except the United States, television began with a public broadcaster playing a central role, and indeed in a majority of the countries having a monopoly role. As the multi-channel environment has grown, public broadcasters have become a smaller proportion of available channels. However, as Table 13.9 shows, at least in the five years between 1999 and 2004, their audience shares remained fairly stable. There was some individual variation with the biggest drops (all from high levels) in the public broadcasters’ audience shares in Ireland (down 12 percentage points), Austria (down eight) and Sweden (down seven). Data published by the European Audio-Visual Observatory suggest that in several European countries, if anything, the growth of channels available has been more threatening to the audience share of the major free-to-air commercial networks than to the public broadcasters. Public broadcasters are defined most simply as those owned by the government, although many of them like the ABC and BBC have independence built into their role and operations. However, as Table 13.10 shows this does not necessarily mean that government funding is their only source of finance. In 1999, according to a McKinsey international study on public broadcasters, on average, these organisations received two-thirds of their funding from the public purse ($42 out of an average of $63), but there was great variation. In New Zealand, it was less than 10%, while for others (Norway, Finland, Sweden and Japan) it was over 90%, and Australia’s proportion came just behind them. The first column of the table shows the relative funding of the public broadcasters per head of population. The most generously funded broadcasters tend to have the greatest audience shares in the preceding table – Denmark, Austria and Britain. The two worst funded public broadcasters on a per capita basis are Canada and Australia, and they have the lowest audience shares. In terms of dollars

A

per head of population, the ABC received less than half the average for the selected countries, and roughly one-quarter what the Danish public broadcaster, the best funded on this measure, received. On a per capita basis, the BBC’s budget was about two-and-a-half times the ABC’s. (The table does not include the Public Broadcasting System in the United States. It was a much later addition to that country’s already dominant commercial system, and never received sufficient funds from the federal government to make it competitive with the dominant commercial networks.) It points to one problem in funding public broadcasters: there is no objective formula about how much they should receive. According to the ABC, its budget in 2003 in real terms was about 70% of what it had been in 1985, as successive governments cut it for macro-budgetary and political reasons. As the ABC had been forced to contract, the commercial media had been expanding. In 2002, ANU economist Professor Glenn Withers estimated that the average hour of ABC television cost 42% as much as the average hour on commercial TV, while for radio the equivalent figure was 40%. In 1981, the two figures had been 71% and 48% respectively. Taken together, the tables show that the ABC has a more marginal role in Australian television than most of the other public broadcasters in their countries. The international report by the consultancy firm McKinsey and Company cited earlier found three patterns among public broadcasters. Some, such as Italy and New Zealand, relied principally on advertising income, and while they commanded substantial audience share, their programming mix was indistinguishable from commercial broadcasters. In others, such as Britain, Sweden and Germany, they successfully combined substantial audience share with distinctive programming. The ABC was in a third group, which had maintained their distinctiveness in programming, but poorer funding meant they commanded smaller audience shares.

MEDIA

187

Table 13.11 Distribution platforms of television Percentage of TV households receiving via each delivery platform 2005 Country

Cable

Satellite (DBS)

Terrestrial only

Japan Netherlands Switzerland Belgium Germany Ireland Austria Denmark United States Canada Sweden Norway Finland United Kingdom New Zealand France Australia Italy

73 93 99 89 57 57 39 58 59 64 54 42 46 13 2 15 20 0

38 7 31 7 38 38 52 27 25 17 27 26 11 31 29 12 6 15

0 0 0 5 6 6 9 15 16 19 19 32 43 56 69 73 74 84

Mean

49

24

29

For several countries, including Australia, latest year = 2002.

Table 13.12 Digital terrestrial television transition Country Belgium Denmark France Italy United Kingdom Austria Canada Finland Germany Ireland Netherlands Norway Sweden Switzerland United States Australia Japan No data on New Zealand.

188


Analogue switch-off date

HD requirement

Not yet decided 2009 (November) 2010–2011 2008 2007–2012 2010 Market driven 2007 (July) 2010 Aiming at 2012 2006 2009 2008 2008 2009 2010–2013 phased regionally 2011

.. .. .. .. .. No No No No No No No No No No Yes Yes

13.5 New media elevision can be received through three principal means of transmission. Everywhere in the developed world, it began as a terrestrial service. Transmitters sending out electromagnetic waves to antennas receiving the signals allowed viewers to watch the pictures in their own homes. Terrestrial services are received only over a limited area and the possible number of services is limited by the width of the radio spectrum. Next came the development of cable, originating in America as a way of overcoming problems with terrestrial signals. As cable technology has developed further, the number of channels that can be carried has become enormous, and consistent, high-quality reception is assured. Its great drawback is the initial cost of laying out the cable, and it is most suited to densely populated areas. It also allows twoway communication. Last came satellite. Geo-stationary satellites can transmit a television signal over a very wide footprint – the one satellite may allow a service to many countries. This taming of geography is the satellite’s principal virtue, and with digitalisation, the one satellite can provide many channels (although not as many as cable). Installation of satellite dishes to receive the signal can sometimes be costly, and reception can be difficult depending on topography and obstacles such as surrounding buildings and trees. Although cable and satellite are associated with pay TV services, there is no necessary connection between means of transmission and sources of revenue. Now that the technology exists for encrypted terrestrial transmission, any means of delivery can in theory be associated with any means of financial support. Table 13.11 shows that by 2005 most households in most of the selected countries received television by additional means beyond terrestrial transmission. Only Italy still had a higher proportion than Australia confined to terrestrial reception. At the other extreme seven countries had fewer than 10% still receiving television by terrestrial means alone, and in three countries there were no such households.

T

Possible reasons for the differential rates of growth of newer delivery platforms include congestion in the spectrum, governmental or commercial reluctance to invest in the new infrastructure, policy decisions restricting the development of new services, and a lack of content offerings attractive to the public. In Italy and Australia, at least, the major beneficiaries of the slowness of new TV services to penetrate have been the commercial proprietors of free-to-air services. The political influence of media moguls such as Silvio Berlusconi and Kerry Packer was surely part of the reason for those countries’ relative inertia. There are also differences in the relative importance of cable and satellite. As might have been predicted, cable has been most important in geographically small and densely populated countries, such as the Netherlands, Belgium, Switzerland and Japan. An exception is the United Kingdom, where the Thatcher Government in the 1980s allowed the development of satellite (which came to be dominated by Rupert Murdoch’s company), but did not invest in cable. This slowed the development of new media there, and it is one of only four countries where satellite is more prevalent than cable transmission. Cable services developed early in the United States and Canada. Some have predicted that, given their geographic size, satellite will become more prominent, but that has not yet transpired. Apart from the growth of cable and satellite, the other revolution in transmitting television has come from digitalisation, which allows the compression of signals, such that far more can be delivered. All countries have moved towards digital services, and as Table 13.12 shows nearly all have programs for phasing out analogue terrestrial delivery. Only Australia and Japan, however, have opted to use the increased capacity to mandate high definition terrestrial channels rather than simply allow more channels to become available in the available spectrum, a decision which restricts the potential for new competition to existing channel owners.

MEDIA

189

Table 13.13 Cinema attendance Average number of visits per person per year 2006 Country United States Australia Canada France Norway United Kingdom Denmark Belgium Switzerland Austria Italy Sweden Germany Netherlands Finland Japan

4.8 4.0 3.8 3.1 2.6 2.6 2.3 2.3 2.3 2.1 1.8 1.7 1.7 1.4 1.3 1.3

Mean

2.4

No data on New Zealand or Ireland.

Table 13.14 National origin of films Percentage of films attended produced within the country, 2006 Country

90.7 53.2 44.7 26.2 25.8 24.8 22.6 19.0 18.8 16.1 10.9 9.5 6.0 4.6 4.2

Mean

25.0

No data on Ireland, New Zealand or Austria.

190


%

United States Japan France Italy Germany Denmark Finland United Kingdom Sweden Norway Netherlands Switzerland Belgium Australia Canada

13.6 Cinema fter the advent of television, cinema was predicted to go into decline, but it has continued to prosper, and in recent years has even undergone something of an expansion, partly because of the growth of multi-screen theatre complexes. The comparative figures show that going to the pictures is most popular in America, whose average per capita attendance is twice the average for the selected countries. Australia and Canada come next highest. Interestingly, cinema attendance is lowest in those countries where newspaper reading is highest – Japan and Finland. As might be expected, the United States is also the country where most frequently the films attended were produced in their own country. Predictably, the rankings on the

A

relative importance of national production to some extent reflect a country’s population ranking, which determines the size of the home market which can sustain a national film industry. But they also show the importance of language as an effective non-tariff barrier in this industry. The three non-American, English-speaking countries on which there is data are much more dominated by imports than their population size would otherwise suggest. Britain produces a considerably smaller share of the films its audiences see than France, Italy and Germany. Canada and Australia are at the bottom of the rankings with 19 out of every 20 films seen in a cinema originating elsewhere, overwhelmingly from America, of course.

MEDIA

191

Chapter 14 FAMILY

Table 14.1 Age at first marriage Mean age at first marriage, females and males, 1980 and 2003–2004 Females 1980

Females 2004

Males 1980

Males 2003

Sweden Denmark Australia Finland Netherlands New Zealand Norway Switzerland Austria France Germany Ireland Italy Japan United Kingdom Belgium Canada United States

26 25 23 24 23 22 24 25 23 23 23 25 24 26 24 22 24 24

31 30 29 29 29 29 29 29 28 28 28 28 28 28 28 27 27 25

29 27 25 27 26 25 .. .. 26 25 26 27 27 29 25 24 .. ..

33 32 31 30 31 29 32 31 30 30 31 30 30 30 29 29 29 26

Mean

24

28

26

30

Country

Table 14.2 Divorce Number of divorces per 100 marriages Country

1970

1980

1990

2001

Ireland Italy Japan France Denmark Switzerland Norway Netherlands United States Canada New Zealand Germany Australia Finland United Kingdom Sweden Austria Belgium

.. 4 9 10 26 14 12 8 33 16 12 18 11 15 13 30 20 9

.. 4 18 24 51 31 30 29 50 33 27 28 36 32 38 53 29 22

.. 9 22 37 44 28 46 30 48 42 39 30 35 53 44 48 36 32

15 15 36 39 40 44 45 47 48 49 49 51 54 55 55 59 60 70

Mean

16

31

37

46

Table 14.3 Duration of marriage at divorce Mean number of years married when divorced, 2001 Country Canada Italy Belgium France New Zealand Norway Switzerland Finland Germany Netherlands Sweden Austria Denmark United Kingdom Japan United States Australia

14 14 13 13 13 13 13 12 12 12 12 11 11 11 10 10 8

Mean

12

No data on Ireland.

192


2001

14.1 Marriage hile some indicators are volatile and jump around from year to year, many demographic and social variables tend to be stable, with the pace of change seemingly glacial. Nevertheless, over a period of decades or a generation, changes can be substantial, even revolutionary. It is not an exaggeration to say that family life in the selected countries has been undergoing revolutionary changes in practices, attitudes and expectations, and to some extent these changes are captured in the data in these and the following tables. Table 14.1 shows that young people are increasingly delaying marriage. In the almost quarter-century between 1980 and 2004, the mean age at first marriage rose by around four years. In every single country, and among both sexes, the mean age at the time of first marriage rose. The Nordic countries and the Netherlands are marrying the latest among the selected countries, while the English-speaking countries show considerable diversity. While marrying relatively younger is still the norm in the United States, and somewhat less so in Canada and the United Kingdom, Australia and New Zealand have moved more towards later marriage. In Australia, the age at first marriage edged steadily downward over the decades until reaching its youngest point in 1971 (23.8 years for men and 21.4 years for women), but has been climbing since then. Moreover, compared with the previous generations’ gradual movement towards ever-younger marriage, the trend towards older marriage has been very rapid. Not only are people marrying later in these countries, but many more marriages end in divorce. While divorce rates jump around from year to year, the long-term trend towards more frequent dissolution of marriages is unmistakable. Divorce rates trebled in the 31 years covered by Table 14.2. However, countries still differ substantially. Catholic Ireland and Italy have the lowest rates, while other countries with Catholic traditions, Belgium and Austria, are at the other end of the table, with rates

W

more than four times those with the lowest. There are also different trajectories. In 1980, Sweden, Denmark and the United States had the highest rates. While Sweden still has one of the highest rates, the United States has slightly reduced and Denmark substantially reduced their divorce rates since. Australia is in the top third of divorce rates, but for unknown reasons it actually leads Table 14.3, the average number of years of marriage before divorce occurs. In general, however, this table shows a much closer grouping than Table 14.2. It should be remembered that an average may conceal considerable variations, of both fairly short marriages and much longer ones ending. Many explanations have been given for rising divorce rates. However, the starting point must be changes in the legal availability and ease of divorce. In Australia, for example, before the Family Law Act introduced ‘nofault’ divorce, one partner had to be guilty in order to secure a divorce. This was both an expensive and potentially messy process. Once the new Act came into operation in 1976, there was an immediate surge in the number of divorces. Similarly before the increase in women’s employment gave them greater financial independence, divorce was not a practical prospect for many women even if the marital relationship was an unhappy or violent one. Beyond the legal and financial changes, many have hypothesised about more emotional and moral changes in the meaning of marriage and intimacy. It is impossible to jump from the quantitative data in the tables to the personal meanings which might lie behind it. Divorce has also led to much higher rates of re-marriage. In 1911 in only one in 10 Australian marriages had either partner been married before. By the year 2000, one in three marriages involve at least one of the partners being married for the second time. High re-marriage rates suggest that disillusion with one particular marriage does not mean disillusion with marriage as such.

FAMILY

193

Table 14.4 Mother’s age at birth of first child Mean age (years) Country

Table 14.5 Births outside marriage Percentage of births to unmarried mothers Country

1970

2004

New Zealand United Kingdom Germany Japan Netherlands Sweden Switzerland Australia Belgium Denmark Finland France Ireland Italy Norway Austria Canada United States

23 24 24 26 24 26 25 23 24 24 24 24 25 25 24 25 23 25

30 30 29 29 29 29 29 28 28 28 28 28 28 28 28 27 27 25

Mean

24

28

Table 14.6 Births to adolescent women Births to 15–19-year-old women per 1000 women in age group Country

1970

2004

Switzerland Netherlands Japan Denmark Sweden Italy Belgium France Norway Finland Germany Austria Canada Ireland Australia New Zealand United Kingdom United States

22.6 22.6 4.4 32.4 33.9 27.4 31.2 36.8 44.6 32.2 55.5 58.2 42.1 16.9 50.9 64.3 49.4 69.2

4.6 4.8 5.7 6.8 6.9 7.0 8.1 9.3 9.6 10.0 10.1 12.7 13.8 14.0 14.9 24.4 25.8 50.3

Mean

38.6

13.0

194


Japan Switzerland Italy Canada Germany Belgium Australia Ireland Netherlands Austria United States Finland United Kingdom Denmark New Zealand France Norway Sweden Mean

1970

1980

1990

2000

2004

1 4 2 10 7 3 8 3 2 13 11 6 8 11 14 7 7 19

1 5 4 13 12 4 12 5 4 18 18 13 12 33 22 11 15 40

1 6 7 26 15 12 22 14 11 24 28 25 28 46 34 30 39 47

1 20 9 28 23 17 29 32 25 31 33 39 40 45 42 41 49 55

2 13 15 28 28 31 32 32 32 36 36 41 42 45 45 46 51 55

7

13

23

33

34

Table 14.7 Abortions Abortions per 100 live births Country

1996

2003

Ireland Switzerland Belgium Germany Netherlands Finland Italy Japan Canada Denmark Norway United Kingdom France Australia Sweden New Zealand United States

.. .. 7 8 7 10 .. 13 16 16 16 15 15 22 19 17 22

7 7 8 8 9 11 11 13 15 15 15 16 17 20 20 21 21

Mean

14

15

No data on Austria.

14.2 Children ust as the selected countries are undergoing rapid change in the social norms surrounding marriage, so the changes to do with having children are just as dramatic. As we saw in Table 1.7, in the selected countries, the average number of children borne by each woman declined from 2.8 in 1950 to 1.7 in 2005. Table 14.4 shows that not only are women having fewer children, but they are having them at a later age. Indeed this delay is one of the major reasons they are having fewer children. Between 1970 and 2004 the 18-nation mean for a mother’s age at the time of her first childbirth rose by four years, from 24 to 28. Just as the United States was the only country where each woman has on average more than two children, so it has the youngest mean age at first birth, 25. The others are all closely grouped between 27 and 30, with Australia right on the mean of 28. Other OECD data, available for only a few of the selected countries, showed that in all of them while in earlier decades the most common age group in which women gave birth to their first child was 25– 29, now it is 30–34. Changes in social attitudes are also apparent. There used to be a stigma associated with births out of wedlock. In most of the countries, it would seem that view has disappeared, at least among the relevant groups. By 2004 in the selected countries, one in three babies was to unmarried mothers. In Norway and Sweden, half of all births are in this category. It is still however very uncommon in Japan, and still relatively uncommon in such more traditional societies as Italy and Switzerland. Australia is close to the mean. Especially when combined with the trend towards mothers having their first child at a later age, it is likely that for many women it is a deliberate choice to delay marriage until

J

after childbirth. It is likely that most births still occur in stable relationships. British figures (likely to be repeated elsewhere) show that three-quarters of births outside marriage were jointly registered by both parents, and most of them were living together. The rise in the number of single-parent families (see following page) results from later marriage break-ups. Explaining the trends in birth rates involves many potential factors, but one relevant consideration is the increased control women have over their own fertility. This is manifested in the dramatic fall in the number of births to adolescent women. In 1970, the average was for every 1000 young women in the 15–19 age group, 39 would have a baby. By 2004, this had reduced to one-third that figure, now 13. In most of the societies the reduction was marked. In 11 of the countries, it was now 10 or fewer. The English-speaking countries tended to start from a higher level, and they still cluster near the bottom of the table. But all of them except the United States have also shown a substantial fall in the 34 years covered by the table. The United States, with a figure of 50, is now clearly an outlier. It was not possible to get systematic data on contraception, and it is only on legal abortions that it is possible to obtain reliable data. The data on abortions in Table 14.7 suggest that in the selected countries, there is one abortion for around every seven births. The data only goes back a small distance, but there is no evidence of a rising abortion rate. The United States had the highest rate, although it was not the distant outlier as it was on births to teenage mothers. Nevertheless, it is ironic that in the country where, far more than anywhere else, abortion is a politically contentious issue, the abortion rate is also the highest.

FAMILY

195

Table 14.8 Household size Average number of people living in a household Country

Mid-1985

Mid-2005

Ireland Japan New Zealand Italy United States Australia Canada France Austria Belgium Netherlands Switzerland Finland Norway Denmark United Kingdom Germany Sweden

3.22 3.03 2.68 2.89 2.65 2.69 2.60 2.45 2.46 2.43 2.27 .. 2.21 2.19 2.16 2.44 2.18 2.02

2.85 2.71 2.65 2.58 2.57 2.53 2.47 2.38 2.34 2.32 2.28 2.24 2.14 2.14 2.13 2.12 2.09 1.99

Mean

2.50

2.36

Table 14.9 Households and relationships Percentage of adults (20+) living in different types of household arrangements, around 2005 Single, living alone

Married couple

Cohabiting

Other

Ireland Canada Italy United States United Kingdom Japan Netherlands Germany Austria Switzerland New Zealand Australia Norway Belgium Finland France Denmark

10.6 10.7 10.8 13.4 14.9 15.4 15.8 16.4 16.5 17.5 17.6 18.5 19.3 19.5 19.6 22.8 24.1

53.4 39.3 53.9 52.9 47.3 47.5 48.1 47.5 48.3 49.3 48.6 51.2 44.1 48.6 43.6 44.6 40.8

5.9 8.9 2.0 5.5 8.7 2.0 9.3 5.3 6.5 5.9 9.3 8.9 10.7 6.4 11.8 14.4 11.5

30.0 41.1 33.2 28.2 29.0 35.1 26.9 30.7 28.7 27.4 24.5 21.4 25.8 25.6 25.0 18.2 23.5

Mean

16.7

47.6

7.8

27.5

Country

No data on Sweden.

Table 14.10 Child households and sole-parent families Households with children as a % of all households 2005

Sole-parent families as a % of child households 2005

Canada Ireland Australia Italy Austria Belgium United Kingdom France New Zealand Norway United States Finland Netherlands Switzerland Sweden Denmark Germany Japan

61.5 60.7 55.7 54.3 44.7 44.3 43.5 43.2 43.0 40.8 38.9 38.3 36.9 36.7 36.1 35.3 35.3 26.0

19.3 22.0 20.7 17.6 23.8 15.6 26.4 19.7 22.0 21.8 28.3 23.0 15.9 15.2 19.6 18.2 18.1 6.8

Mean

43.1

19.7

Country

196


14.3 Families and households he demographic and social changes associated with living longer, with the delay in getting married, with increased divorce, and with having fewer children, have led to considerable changes in the composition of households. The New York Times reported in 2006 that the latest US Census showed that married couples had finally slipped into the minority, comprising just under 50% of households, having dropped two-and-a-half percentage points in the previous five years. Table 14.9 shows that people living as married couples now comprise a minority of the adult population in nearly all the selected countries. (In all discussions, and particularly here, one must be clear about what the figure is a percentage of. In Australia, for example, one in 10 people live alone, which as shown in Table 14.9 translates into almost one in five adults living alone. In turn if one is comparing households, around one in four are now single-person residences.) Table 14.8 charts two recent decades of the long, slow general trend towards smaller households. By 2005, in none of the selected countries was the average household size greater than three, while Sweden had actually edged below two. The most basic reason for this is the rise of single-person households. In the selected countries, around one in seven adults now live alone. This trend occurs principally among older people, but is also present in other age groups. In addition, as Table 14.9 shows, as well as married couples, there is also a sizable number of cohabiting couples. Around one in 15 adults are now cohabiting, one-sixth as many as are living with a married partner. It is most common in France and the Nordic countries, and still uncommon in Italy and Japan. ABS data show that in Australia among people in cohabiting relationships, 42% said they expected to enter into a registered marriage

T

with their current partner, while 28% said they did not expect to do so, and 25% were unsure. No matter how many cohabitants end up becoming married, cohabiting before marriage has now become the norm. Again ABS data is informative: of people getting married in 1975, only 16% had cohabited, while in 2000, 71% had. In 2007, 11% of couples aged 65–74 and 5% of couples aged over 75 who were currently in a registered marriage reported that they cohabited before getting married. In comparison, of those aged 25–34, 67% reported that they cohabited before getting married, and 46% of these said they did so for three or more years. The major group in the residual ‘Other’ category in Table 14.9 comprises lone parents living with children. A much smaller part comprises group households, usually of young adults. According to the ABS, 3% of the Australian population living in private dwellings live in group households. Table 14.10 shows a rough correlation, as would be expected, between the number of children a woman has on average and the percentage of households with children. In four of the countries, including Australia, they still comprise the majority, while in the other 14 countries childless households are more common, with only one in four Japanese households having a child. The table’s second column shows that of households with children, in around one in five the adult is a lone parent. Again this varies considerably, being highest in the United States (28%) and the United Kingdom (26%) down to only 7% in Japan. Australia is close to the average. In Australia, according to ABS figures, of the 4.8 million children aged 0– 17, 22% had a natural parent living elsewhere. Of these 75% lived in one-parent families, 12% in stepfamilies and 10% in blended families.

FAMILY

197

Table 14.11 Income of different family types Average disposable incomes of different family types as a % of overall average disposable income of working age population (equals 100) in each country, mid-1990s Single adult with children

Single adult, no children

Two adults with children

Two adults, no children

Sweden Australia United Kingdom United States Belgium Netherlands Canada Italy Norway Denmark France Finland Germany Austria

72 57 51 49 69 55 57 52 67 59 66 76 57 87

74 92 92 99 126 80 85 93 73 75 94 75 90 85

101 93 93 93 85 93 94 91 99 100 97 100 95 98

131 129 127 127 125 123 120 118 117 115 113 112 112 110

Mean

62

88

95

120

Country

No data on Ireland, Japan, New Zealand or Switzerland.

Table 14.12 Women’s employment and motherhood Employment rates of women with and without children, 2004 No children

One child

Two or more children

Sweden Norway Denmark Finland Netherlands Canada Austria Switzerland Belgium United States United Kingdom France New Zealand Germany Australia Italy Ireland

81.9 82.9 78.5 79.2 76.8 76.5 79.5 84.3 70.4 78.6 81.6 76.1 80.7 77.6 68.4 57.2 65.8

80.6 83.3 88.1 78.5 73.8 74.9 79.9 75.5 71.2 75.6 72.4 77.0 66.9 70.3 60.1 54.5 51.0

81.8 78.0 77.2 73.5 68.6 68.2 67.6 65.5 65.3 64.7 61.8 61.6 58.9 56.5 56.2 45.7 40.8

Mean

76.2

72.6

64.2

Country

No data on Japan.

198


Table 14.13 Mothers and part-time work Percentage of employed women working part-time, according to their number of children, 2000 None

One child

Two or more

Netherlands Switzerland Australia United Kingdom Germany New Zealand Ireland Belgium Austria Norway Italy France Canada United States Sweden Denmark Finland

38 34 41 24 24 21 17 29 17 25 20 20 17 10 15 19 8

73 58 54 47 45 38 37 35 34 34 27 24 23 16 17 13 9

83 67 63 63 60 51 46 46 44 41 34 32 31 24 22 16 14

Mean

22

34

43

Country

No data on Japan.

14.4 Mothers and employment ormer Australian Treasurer Peter Costello sought to encourage parents to have more children by saying they should have one for mum, one for dad and one for the country. It is now the official position of many of the governments of the selected countries that their birth rate is too low. At the individual level, the OECD cites survey evidence showing that majorities of women in most of the countries would have preferred to have had more children than they did, and also aspire to have more than they end up actually having. This is probably in sharp contrast to their grandmothers. What prevents contemporary families from having more children if the aspiration is still there? Two factors are probably relationships and careers. Many people delay having children until they feel they are in a stable, longterm relationship, and if marriage statistics are a guide, this is tending to happen at a later age. Similarly, with higher education qualifications, most young women have their own career aspirations, and juggling progression at work with having a family can pose many difficulties. However, a final factor may be economic. A report prepared for the Australian Government in 2007 calculated that couples with one child spend 16% of their income on that child; couples with two children spend 28% of their income. A couple on average income with two children may spend around $400 000 over 20 years. This includes direct costs only. Indirect costs stem from interrupted employment. The OECD’s Babies and Bosses volume cites an Australian study which concluded that for women who have completed secondary education, having one child decreases after-tax lifetime earnings by around $162 000. However, this figure has been reducing, and the amount will vary with social practices. The same volume reports that in Nordic countries, mothers at age 45 have earned between 82% and 89% of what non-mothers earned, but at the other extreme in the Netherlands and Germany the same group have only 56–74% of non-mothers’ earnings.

F

This all suggests that if governments are serious about raising the birth rate, the single most important thing they can do is make it easier for families, women in particular, to combine parenthood and work. Table 14.11 shows that the most affluent family type in all these societies is, not surprisingly, two adults with no children. On average, they have around a quarter more disposable income than families consisting of two adults with children. The gap between the two is actually largest in Australia. Similarly, in nearly all these countries single-parent families are the worst off financially. Table 14.12 shows that in broad terms, motherhood, especially the first child, only reduces the employment rate of women slightly, from just above to just below threequarters. A second child reduces it further, but still almost two-thirds combine motherhood and employment. (These figures do not control for the age of the children.) As often on practices involving women’s roles, there is considerable variation. Italian women are less likely to work than women elsewhere, but being a mother does not impinge too greatly on their employment rate. In the Nordic countries, the already high rate of women in employment is barely affected by motherhood. Motherhood reduces women’s employment the most in Ireland, the United Kingdom, New Zealand, Germany and Switzerland. One solution to juggling the demands and enjoying the rewards of both may be for mothers to engage in part-time work. As we saw in chapter 4, this is much more common for women than men, and Table 14.13 shows it is more common for mothers than for women without children. Interestingly, in the Scandinavian countries, which have the highest employment rates for mothers, only a relatively small proportion are working part-time. In contrast, Australia has a relatively low maternal employment rate and a high proportion of it is part-time employment.

FAMILY

199

Table 14.14 Children in child care and pre-school Percentage of children aged 0–3 and aged 4 in formal child care or pre-school centres, 2004 Country

% 0–3

Denmark Norway Sweden Belgium New Zealand Netherlands United States Australia France United Kingdom Finland Canada Japan Ireland Germany Italy Austria Switzerland Mean

Table 14.15 Public expenditure on child care and pre-school Public spending on child care and pre-primary education as a % of GDP, 2003

62 44 40 39 32 30 30 29 26 26 22 19 15 15 9 6 4 .. 26

Child care

Pre-primary education

Denmark France Sweden Finland Belgium Norway New Zealand Italy United Kingdom Netherlands Australia Germany United States Japan Switzerland

1.2 1.0 1.0 0.9 0.8 0.8 0.7 0.6 0.6 0.5 0.4 0.4 0.4 0.3 0.2

0.7 0.4 0.6 0.7 0.2 0.5 0.1 0.2 0.4 0.1 0.2 0.1 0.1 0.2 0.1

0.5 0.6 0.4 0.2 0.6 0.3 0.6 0.5 0.2 0.4 0.2 0.3 0.3 0.1 0.1

Mean

0.7

0.3

0.4

Country

93 87 88 100 95 74 64 65 100 92 46 .. 95 47 84 100 82 34

Austria, Canada and Ireland omitted because of incomplete data.

79

Table 14.16 Child care fees Average cost for a two-year-old attending full-time, as a % of average wage, 2004 Country

%

Sweden Denmark Finland Germany Norway Austria Netherlands Japan Belgium New Zealand United States Canada Australia France Ireland United Kingdom Switzerland

5 8 8 9 9 10 17 19 20 20 20 21 22 25 25 25 34

Mean

17

No data on Italy.

Total

% aged 4

Table 14.17 Net costs of attending child care Percentage of after-tax income, for two children for couples with one parent on median income and other at 67% of median income, 2004 Country

6.1 6.6 6.9 10.2 11.9 14.0 16.7 18.4 18.4 19.0 20.1 22.7 24.5 25.5 26.6 27.2 33.9

Mean

18.2

No data on Italy.

200


%

Germany Sweden Finland Denmark Norway Belgium France Japan Austria Australia Canada United States Netherlands New Zealand Switzerland United Kingdom Ireland

14.5 Child care and early education he UNICEF’s Innocenti Research Centre has captured the situation succinctly: ‘Today’s rising generation is the first in which a majority are spending a large part of early childhood in some form of out-of-home child care. At the same time, neuro-scientific research is demonstrating that loving, stable, secure, and stimulating relationships with caregivers in the earliest months and years of life are critical for every aspect of a child’s development.’ More prosaically, if they want to maintain their material standard of living, for most it will be necessary for the mother to enter into paid employment. Central to this decision, and to their quality of life as parents of young children, will be the availability of affordable and high-quality child care. It is a policy area which has become increasingly important on the political agenda. In interpreting Tables 14.14 and 14.15, a distinction needs to be made between child care and pre-school education. The latter is limited to organised, centre-based programs designed to foster learning and emotional and social development in children from the age of three to the compulsory school age. In many European countries, compulsory primary schooling does not begin until six years of age – later than it is common to start in Australia – but a far greater proportion in many of those countries attend pre-school. At least at the level of national aggregates, it is hard to see that any systematic differences in later capability result, although educationalists and psychologists are continuing to stress the importance of early childhood development. The difference in approach is evident in Table 14.14. For children aged three or less, only around one in four children across the selected countries are attending child care or pre-school, whereas among those aged four it jumps to four in five. However, Australia does not move nearly as much as most of the European countries. Australia is just above the

T

mean for the threes and under, and although this 29% more than doubles to 65% for four year olds, in 11 countries the participation rate of four year olds is over 80%. This is an area where Australian governments have been slow to commit. It has crept up in recent years, but Australia is still well below the mean in Table 14.15, and in terms of the national income committed to child care and pre-primary education, six governments more than double Australia’s efforts. In particular, the mean proportion of GDP these governments commit to pre-school education is double Australia’s figure, and the only countries below Australia here are the historical laggards in childhood support, Japan and Switzerland. The relative commitment of public funds affects the accessibility and the affordability of child care for parents. To some extent, we see that countries that committed the most public funds in Table 14.15 – such as Sweden, Denmark and Finland – have the most affordable child care in Table 14.16. The countries fall into three broad groups – those where the typical fee for a two year old attending full-time is 10% or less of an average wage. At the other end, by itself, is Switzerland, where the fee is fully one-third of an average wage, reflecting that government’s low commitment and not surprisingly its low ranking in participation in Table 14.14. Australia is part of a large group with fees between a fifth and a quarter of average earnings. Table 14.17 takes a different cut, looking at net costs, and at the relative cost of child care for a couple close to the average income. The OECD has done this for various income mixes, but the variations are limited, suggesting that most governments do not see this as a welfare issue, Australia being a bit more redistributive than most. For all of them, child care is a major expense, commanding almost a fifth of net income for two children in full-time care.

FAMILY

201

Table 14.18 Public spending on family benefits Total and components of government spending on support for families, as a % of GDP, 2005 Country

Cash

Services

Tax breaks

Total

France United Kingdom Denmark Sweden Belgium Finland Germany Norway Australia Austria Ireland New Zealand Netherlands Italy Japan Switzerland United States Canada

1.4 2.2 1.5 1.5 1.7 1.6 1.4 1.6 2.2 2.4 2.2 1.9 0.6 0.6 0.3 1.0 0.1 0.9

1.6 1.0 1.6 1.6 0.9 1.4 0.7 1.3 0.6 0.5 0.3 0.7 1.0 0.7 0.5 0.3 0.5 0.2

0.8 0.4 0.0 0.0 0.5 0.0 0.9 0.1 0.0 0.0 0.1 0.0 0.6 0.0 0.5 .. 0.7 0.1

3.8 3.6 3.2 3.2 3.1 3.0 3.0 3.0 2.9 2.9 2.6 2.6 2.3 1.3 1.3 1.3 1.3 1.1

Mean

1.4

0.9

0.3

2.5

Table 14.19 Maternity leave National statutory maternity leave provisions, 2006–2007 Country Finland Germany France Austria Sweden Ireland Japan Norway United Kingdom Canada Denmark Italy Netherlands Belgium Switzerland New Zealand Australia United States

Paid leave?

Maximum duration of unpaid leave (weeks)

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No No

174 162 159 112 84 62 58 57 52 50 50 33 29 27 16 .. 52 12

Table 14.20 Spending on maternity and parental leave payments Public spending on maternal and parental leave payments per child born, 2003 Spending per birth as a % of GDP per capita Country

%

Sweden Norway Finland Denmark Austria France Canada Germany Italy Belgium Netherlands Japan United Kingdom Switzerland New Zealand Australia

65 63 57 50 31 29 24 21 20 17 17 13 10 9 5 3

Mean

27

No data on Ireland or the United States.

202


14.6 Family policies and maternity leave iving families financial assistance – either through child allowances or through tax concessions – has been universal among these countries, although the means and rationales have varied greatly over time and between countries. In many countries, including Australia, assistance is means tested. Like other aspects of social expenditure, family spending has increased in recent decades. In the OECD as a whole, it increased from 1.6% of GDP in 1980 to 2.2% in 2003. Family spending includes only public support that is exclusively for families, such as child payments and allowances, parental leave benefits and childcare support. Other types of spending such as health and housing support are of benefit to families but that is not their primary purpose, so they are not included in this category. In Table 14.18, there is a group of five countries at the bottom, spending just over 1% of GDP, which tend to lag in social expenditure generally – Canada, the United States, Switzerland, Japan and Italy. The other end of the table wholly comprises European countries, although some, such as France and the United Kingdom, do not always figure so strongly among high social spenders. Australia ranks exactly in the middle of the table. The total in the table has three components – the provision of services, the giving of cash benefits to eligible recipients, and the granting of tax breaks of various kinds. Level is more important than type of support, but countries have their own characteristic mixes. The Nordic countries and the Dutch stress the provision of services, while tax breaks are most important in the United States. Australia is one of a number which place the greatest stress on cash grants. The most basic legislative policy for encouraging childbirth is maternity leave. Maternity leave provisions were slow to develop in English-speaking countries, because the traditional view was that mothers did not or ought not to work. In contrast, Norwegian women

G

had the right to maternity leave before they had the right to vote. As female labour force participation increased in nearly all the selected countries, the demands for maternity leave also increased. Over the decades, firstly the right to return to the mother’s previous position was guaranteed, while periods of unpaid and paid leave have gradually been increased. Although the Rudd Government has since moved to legislate for maternity leave, at the end of the Howard Government, Australia was, with the United States, one of only two of the selected countries not to have paid maternity leave as a right. As Table 14.19 also shows, in terms of unpaid leave, Australian mothers had the right of return after 52 weeks. At one stage this was relatively generous, but in recent years the durations of unpaid leave – in many countries available to both parents – have grown substantially. The three most generous countries now allow more than three years of unpaid leave. The table offers only skeletal data on nationally legislated maternity leave provisions. The variety of public policies defies simple summary. In some countries employers have to contribute – although the formulas for doing so differ – but in most government is the major or only contributor. There is almost infinite variation in the many formulas of paid and unpaid, or fractional pay for different periods, which mothers may be eligible for, as well as differing provisions for fathers and the right to make choices about who takes parental leave. Moreover, different groups often have different rights, in federations varying between states, or with different private corporations having different conditions. So even though there was no national right to maternity leave in Australia in 2008, many employees already enjoyed some such provision. One way to cut through the complexity is simply to look at the total sums of money involved, as in Table 14.20. This again has the Nordic countries at the top, and Australia at the bottom.

FAMILY

203

Chapter 15 LIFESTYLES AND CONSUMPTION

Table 15.1 Home ownership Home ownership as a % of all households Country

1960

1975

1990

2000

Ireland Belgium New Zealand Italy United Kingdom Finland Australia United States Canada Sweden Japan Norway Austria France Denmark Netherlands Germany Switzerland

60 50 69 45 42 57 63 64 66 36 71 53 38 41 43 29 29 34

71 55 68 50 49 59 67 65 60 35 59 53 41 45 49 35 36 28

81 62 71 67 68 67 70 64 64 42 61 59 55 54 51 44 38 30

78 74 71 70 69 67 69 65 64 60 60 .. 57 55 53 51 43 ..

Mean

49

51

58

61

Table 15.2 Housing tenure Percentage of households according to the tenure status of the residents, 2004 Country

Owner-occupied

Social rental

Private rental

Other

Ireland Belgium United Kingdom Australia United States New Zealand Canada Austria France Denmark Netherlands Germany Switzerland

77 74 70 69 69 67 66 57 56 53 53 43 35

7 7 20 5 3 7 6 23 17 19 35 6 6

11 16 10 22 29 26 28 17 21 18 12 51 59

5 3 0 3 0 0 0 3 6 10 0 0 0

Mean

61

12

25

2

No data on Norway, Italy, Japan, Finland or Sweden.

Table 15.3 Change in real house prices Average annual % rates of change in real terms in each period Country

1970–1975

1975–1980

1980–1985

1985–1990

1990–1995

1995–2000

2000–2005

United Kingdom New Zealand France Ireland Australia Italy United States Sweden Canada Denmark Norway Finland Netherlands Switzerland Germany Japan

5.0 8.4 1.8 1.3 4.6 6.4 1.6 1.2 6.6 3.9 0.5 0.9 3.0 0.8 0.5 3.0

4.4 7.8 2.2 1.2 4.3 6.4 1.4 1.7 6.8 4.0 0.4 0.4 3.4 0.0 0.0 2.1

4.0 7.3 2.7 1.0 4.0 6.6 1.2 2.0 6.8 3.8 0.6 0.2 4.0 −0.6 −0.4 1.2

3.7 6.9 3.2 0.7 3.6 7.1 1.1 2.5 6.9 3.4 0.7 0.0 4.9 −1.3 −0.7 0.5

−4.4 2.8 −2.7 1.0 −0.2 −1.8 −1.1 −5.8 −1.0 1.8 −0.6 −10.2 4.6 −6.0 0.8 −2.9

8.1 1.7 2.1 17.6 3.5 −0.9 2.3 6.3 0.0 6.7 9.3 7.8 10.8 −2.7 −1.6 −2.6

9.9 9.8 9.4 7.8 7.7 6.6 6.4 6.0 5.9 5.5 4.5 3.8 2.6 1.5 −2.8 −4.6

Mean

2.4

2.2

2.4

2.9

−1.1

2.9

6.0

No data on Austria or Belgium.

Table 15.4 Housing affordability Median house price to median household income multiple, 2008 in major housing markets Country United States Canada United Kingdom Ireland New Zealand Australia

204

Affordable Moderately Seriously unaffordable Severely unaffordable (3.0 and under) unaffordable (3.1–4.0) (4.1–5.0) (5.1 and over) Median 77 10 0 0 0 0


59 15 0 0 0 0

23 5 6 2 1 3

16 4 10 3 7 24

3.2 3.5 5.2 5.4 5.7 6.0

15.1 Housing ome ownership has long been a key aspiration of people in Australia and many of the other selected countries. It offers financial security from instabilities in the rent market, but also a personal security and satisfaction about fashioning people’s own place of residence. It is also the central financial investment that many families make. Home ownership is much easier where land is relatively cheap, so as Table 15.1 shows it was traditionally high among the four New World countries. As early as 1911, half of Australians owned their home, a figure that was reached in Britain only in the 1970s. Home ownership also tends to be higher in rural areas than in major cities. In 1960, Japan topped the table and its declining rate over the next 15 years reflects its rapidly increasing urbanisation. Many families owned their small village homes, but their children could not afford to buy real estate in Tokyo. The countries show considerable divergence and contrasting trajectories. The 2000 home ownership rate is substantially (seven percentage points or more) higher than in 1975 in 10 countries, all European. Many of these started from a comparatively low base. Despite the rising prosperity of the other countries, housing ownership rates have plateaued. In particular, Australia, the United States and Canada (who in the post-World War II decades were in the vanguard) are now just above the mean. In all countries, then, a substantial proportion of the population lives in rental accommodation. Younger people who may eventually go on to own their home form a large part of this group, but many people, especially from poorer socio-economic groups, will always rent. Thus the cost and quality of rental accommodation is of general concern, and also a welfare issue for younger and poorer groups. All the governments on which we have data in Table 15.2 intervene in the housing market to some extent. However, as the second column indicates, in more than half this involves

H

less than 10% of households and seems a largely residual function, lowest in the United States and second lowest in Australia. There is ongoing debate about whether the large social rental sector in some countries also improves the quality and cost of the private housing markets. A central reason why home ownership has not risen further in many of the countries can be seen in Table 15.3, which shows that in the majority of countries house prices have risen more quickly than the general cost of living, sometimes dramatically so. Only in the widespread recession conditions of the early 1990s was this not true. Table 15.3 shows a broad correlation between rising housing costs and population growth rate, with the three countries at the bottom – Japan, Germany and Switzerland – all having among the oldest age profiles, and the slowest population growths. Apart from these three, most of the countries had a housing boom in the first five years of the 21st century, and many also did for the last five years of the previous century. This surge came from a coincidence of sustained low interest rates, more liberal lending policies and previously unmet demand, both for first home buyers and an aspiration among existing home buyers to improve their residences. While to a large extent house prices are cyclical, and the housing boom has slowed almost everywhere in 2009, it has also brought an enduring structural change. Table 15.4, from the research company Demographia, shows housing costs in relation to median incomes in the biggest housing markets, in the six English-speaking countries. The historic norm for affordability was a ratio of 3.0 or lower as indicating affordability. Now in Australia, the average of the 27 leading markets was 6.0 and the figure for the mainland state capitals was over 7.0. If such levels are sustained, home ownership will consume a higher proportion of families’ finances in the future than it did in the past.

LIFESTYLES AND CONSUMPTION

205

Table 15.5 Food Total food consumption, average per capita daily calorie intake

Table 15.6 Fat Average daily fat intake, grams per capita

Country

1970

2003

Japan Australia Finland New Zealand Sweden United Kingdom Denmark Germany Netherlands Norway Switzerland Canada France Belgium Italy Ireland Austria United States

2716 3239 3129 2953 2877 3327 3158 3147 3022 3022 3478 2936 3302 3095 3422 3444 3232 3026

2768 3135 3143 3199 3208 3450 3472 3484 3495 3511 3545 3605 3623 3634 3675 3717 3732 3754

Mean

3140

3453

Table 15.7 Proteins Average daily intake of proteins, grams per capita Country

1970

2003

France Ireland United States Italy Australia Austria Denmark Norway Sweden United Kingdom Canada Netherlands Finland Germany Switzerland New Zealand Japan Belgium

105 106 98 97 108 90 78 88 88 94 94 87 89 88 91 96 82 92

117 117 115 114 111 110 109 108 108 106 105 105 103 100 98 93 92 91

93

106

Mean

206


Country

1970

2003

Japan New Zealand Finland Sweden Australia United Kingdom Ireland Denmark Netherlands Germany Norway Canada United States Italy Switzerland Austria Belgium France

55 114 124 117 117 144 125 141 132 127 132 114 120 111 149 125 128 126

86 119 126 127 132 135 137 139 140 142 145 148 155 156 158 161 163 168

Mean

122

141

Table 15.8 Fruit and vegetables Average per capita consumption of fruit and vegetables, kilos per year Country

1970

2003

Italy Netherlands Denmark New Zealand Canada France United States Austria Ireland United Kingdom Germany Switzerland Belgium Australia Sweden Norway Finland Japan

299 179 122 153 167 219 183 182 97 139 169 217 170 155 125 128 72 180

309 256 249 245 240 238 237 228 220 207 203 201 200 197 194 191 163 159

Mean

164

219

15.2 Food hile the figures in chapter 6 indicated a great increase in the percentage of people being obese and overweight, the increases recorded in Table 15.5 seem less dramatic. They show that on average total food intake increased by about 10% in the selected countries between 1970 and 2003, from just over 3100 calories to just over 3400 calories. Perhaps this relatively small increase was sufficient to impact upon obesity rates, especially in conjunction with what some say has been reduced levels of physical activity. The rankings do show some correlation with rankings on obesity. Japan, by far an outlier in having minimum calories per day, also has fewest obese people, while at the other end of the table, the calorie intake leader, the United States, is also the leader in the proportion of obese and overweight people. However, Australia, the second-smallest eater according to this data, is very high on obesity, and the big-eating Austrians are at the other end of the obesity table. The countries at the top of the table are those that increased their food consumption most in the 33 years, the United States moving from just below the mean to become leader by increasing its daily intake by more than 700 calories daily, and Canada, Belgium and Austria up by amounts nearly as large. In contrast, Australia moved from above the mean to below the mean, because it was the only country, if this data is to be believed, which reduced its average calorie intake in the period. Table 15.6 shows a larger proportionate increase in fat consumption than in total calories. It shows the countries overall increased by around one-sixth. Japan is an even more dramatic outlier here than in the previous table. On average, Japanese eat only two-thirds as much fat as the people in the other countries. Several European countries consume more fat per person than the United States and

W

Canada, while Scandinavia, New Zealand, Australia and the United Kingdom fall below the mean. Similarly, all the countries increased their protein intake, and there is less of a range here than in fat consumption. In 1970, Australia had the highest protein intake, but its increase in the intervening years was considerably less than average, although it is still in the top third. While Japan is again near the bottom, much more surprisingly, so is New Zealand, while the predominantly German-speaking countries also consume fewer proteins. Perhaps the most surprising result for Australians is in Table 15.8, which shows Australia is in the bottom third of countries in terms of consuming fruit and vegetables. This area has actually seen the largest proportionate increase in consumption, of about one-third. Only Japan declined, while others showed spectacular increases: most particularly Finland, Ireland and Denmark increased by more than 100 kilograms per year, suggesting also the convergence of diets, with increasing ease of trade in food, but also the intermingling of influences on lifestyles and tastes. In Australia official surveys found an unexpected drop in Vitamin C intake among both children and adults between 1985 and 1995, mainly due to a decline in fruit consumption among adults and of fruit juice consumption among children. The 1995 National Nutrition Survey found that 42% of Australian adults had not eaten any fruit on the day of the survey, and only 17% had eaten the recommended 300 grams. It also found that 16% had not eaten any vegetables (including potatoes) on the survey day, and only 32% had eaten the recommended 300 grams. These figures are also a reminder that in all these tables we are dealing with averages, and that often it is the variations that are more important to health and lifestyle outcomes.


207

Table 15.9 Alcohol consumption Mean litres of alcohol consumed per head per year Country

1960

1970

1980

1990

2000

2005

Ireland Denmark France United Kingdom Austria Belgium Switzerland Finland Germany Australia Netherlands New Zealand Japan United States Italy Canada Sweden Norway

4.9 5.5 .. .. 10.9 8.9 12.1 2.7 7.5 9.4 3.7 5.3 .. 7.8 16.6 7.0 4.8 3.4

7.0 8.6 20.4 7.1 13.9 11.7 14.2 5.8 13.4 11.6 7.8 9.8 6.1 9.5 17.8 8.8 7.2 4.7

9.6 11.7 19.5 9.4 13.8 13.5 13.5 7.9 .. 12.9 11.5 11.8 7.1 10.4 16.3 10.7 6.7 5.3

11.2 11.7 15.9 9.8 12.6 12.1 12.9 9.5 13.8 10.5 9.9 10.1 9.2 9.2 11.0 7.4 6.4 5.0

14.2 13.1 14.0 10.4 11.1 10.3 11.2 8.6 10.5 9.8 10.1 8.9 8.6 8.2 9.0 7.6 6.2 5.7

13.5 12.7 12.7 11.3 11.1 10.7 10.1 10.0 10.0 9.8 9.7 9.4 8.5 8.4 8.1 8.0 6.6 6.4

7.4

10.3

11.3

10.5

9.9

9.8

Mean

Table 15.10 Types of alcoholic beverages consumed Litres of different types of alcoholic drinks consumed per person per year, 2002

Country

Beer

Wine

Flavoured alcoholic drinks

Ireland Germany Austria Belgium Denmark United Kingdom Australia United States Netherlands Finland New Zealand Canada Switzerland Norway Sweden Japan France Italy

155 119 106 98 98 97 89 85 80 79 78 70 57 56 56 55 41 29

13 26 36 30 32 20 21 7 20 10 19 10 42 11 16 10 47 54

3.9 3.2 2.6 1.1 0.1 4.4 9.8 3.8 0.3 2.8 7.7 2.1 1.5 0.2 0.1 3.5 1.0 0.7

5.3 5.3 3.2 2.6 2.7 3.9 2.6 4.8 4.7 5.7 2.3 4.3 2.4 2.4 2.9 8.2 7.2 2.7

81

24

2.7

4.1

Mean

208


Spirits

15.3 Alcohol lcohol consumption trended steadily upwards until 1980, but has been since declining. Table 15.9 shows that in the selected countries the mean amount of pure alcohol each adult consumed each year peaked at 11.3 litres in 1980, and had declined to 9.8 litres by 2005. Perhaps contrary to the public image, Australia comes in the middle of Table 15.9 consuming exactly the mean amount of alcohol among the selected countries. Ireland clearly heads the list ahead of the French and Danes. At the abstemious end of the table are the Norwegians and Swedes. The countries show several different trajectories, which together have brought more convergence between them. By 2005 the difference between top and bottom was 7.1 litres; in 1970 it had been 15.7 litres. Several countries, including Australia, New Zealand, the United States and Canada, show an initial increase, but then a steady and sustained decrease. One can only speculate on the reasons for this, but it is plausible that in the decades of growing affluence following World War II, increasing alcohol consumption was part of the rewards people reaped. However, from the 1970s and 1980s onwards, there has been a greater sense of the health and social costs of over-consumption, and perhaps this has increasingly tempered alcoholic drinking habits. Several initially high-consuming countries, notably France and Italy, show a trend of steady decline, while the low-consuming Swedes and Norwegians have shown a modest increase, the Finns even more so. Some such as the United Kingdom starting from a stronger base have also steadily increased. There were marked differences among the selected countries in their preference for different types of alcoholic drinks. According to the 2002 data in Table 15.10, based on research from the leading market analysts Euromonitor, the champion beer-drinking nation was Ireland, by a considerable distance, followed

A

by the other traditionally beer-drinking countries of Northwestern Europe. Italy and France were the leading wine drinkers and also the lowest on drinking beer. Wine is less popular in North America, Japan and the Nordic countries. Japan, which is low on the table for overall alcohol consumption, is however the highest on spirits, due no doubt to the popularity of sake and whiskey. France, however, is just behind, while New Zealand and Australia come bottom. Australia is close to the average on both beer and wine: somewhat above on beer and somewhat below on wine. Interestingly, it is a clear winner on flavoured alcoholic beverages, drinks where an alcoholic base is mixed with soft drinks by the manufacturer. These drinks are especially popular among adolescents, which was the reason the Rudd Government gave for seeking to raise taxes on them in 2008. Nevertheless, long-term data suggests that beer is taking a larger share in wine-drinking countries and wine becoming more popular in beer-drinking countries. According to WHO data, in terms of pure alcohol consumed, in 1961 beer formed 74% of Australia’s alcohol intake and wine formed 12%. In 1999, beer formed 50% and wine formed 33%. Despite the general convergence in overall alcoholic intake, globalisation has not yet dissolved the contrasts between national tastebuds. The problems associated with alcohol are not revealed by figures on average per person intake. There is not good comparative data on alcohol’s role in traffic accidents and violence. Serious health and social problems are often associated with binge drinking and/or longterm alcoholism. In Australia, surveys show that 10% of males and 9% of females are consuming alcohol at levels likely to cause longterm harm (more than 29 and 15 standard drinks a week respectively). Overall, 48% of Australian adults (aged 14+) drink alcohol at least weekly, and another 35% consume it more occasionally.


209

Table 15.11 Cars Road motor vehicles per 1000 population Country

1995

2006

United States New Zealand Italy Australia Japan France Germany Canada Switzerland Norway Austria Belgium United Kingdom Finland Sweden Netherlands Denmark Ireland

771 658 573 603 537 520 540 565 498 474 543 487 428 427 447 430 386 318

755 735 666 659 612 595 592 590 573 562 547 540 538 534 512 495 451 433

Mean

511

577

Table 15.12 Price of petrol Retail price of super petrol in US cents per litre at current exchange rates in November of each year Country

1995

2000

2006

United States Canada Australia New Zealand Japan Switzerland Austria Ireland Sweden France Finland Germany Italy Denmark Belgium United Kingdom Netherlands Norway

34 45 46 61 125 102 115 96 117 117 120 112 118 108 118 92 121 133

47 58 57 48 106 78 82 72 94 99 106 91 97 101 96 117 103 119

63 84 93 98 109 127 132 134 146 148 155 155 156 158 163 163 170 180

99

87

135

Mean

Australian 1995 figure is from 1998.

Table 15.13 Travel by train Passenger-kilometres travelled by train per person

Table 15.14 Travel by car Passenger-kilometres travelled by private car per person

Country

1970

2005

Country

1970

2005

Japan Switzerland France Denmark Austria Sweden Germany Netherlands Belgium Italy United Kingdom Norway Finland Australia Ireland United States

2759 1327 808 690 844 572 493 614 860 604 546 490 478 1071 271 48

3062 2178 1257 1071 1032 986 908 901 878 787 717 692 667 570 436 29

United States Australia Italy France Switzerland Finland United Kingdom Norway Denmark Sweden Germany Belgium Netherlands Japan

13742 8011 3937 6007 6763 5145 5080 4592 .. 6975 4485 5106 5085 1746

14472 13319 12088 11949 11860 11799 11231 11183 11097 10775 10730 10440 9117 6643

5095

11207

Mean

780

No data on Canada or New Zealand.

210


889

Mean

No data on Canada, New Zealand, Ireland or contemporary data on Austria.

15.4 National transport patterns ransport in these countries is dominated by cars, and is becoming more so. Table 15.11 reports data on all motor vehicles, including buses, freight vehicles and motor cycles, as well as passenger motor cars. In terms of vehicles per 1000 inhabitants, which of course includes many people too young and too old to drive a car. The table shows that in the 11 years between 1995 and 2006, the average number of cars in the selected countries went up from 511 to 577 per 1000 people. Every country, except the leader, the United States, showed an increase. Perhaps with three motor vehicles for every four people, the United States has reached a ceiling. However, the increases in most other countries, and especially those which began with relatively lower levels, have been substantial. In this relatively brief period of 11 years, the number of cars per 1000 population rose by more than 100 in the United Kingdom, Ireland and Finland, and in five others (Italy, the Netherlands, Japan, Denmark and New Zealand) rose by 65 or more. Australia was a fraction below two vehicles for every three people, and ranked fourth overall. The almost universal dependence on motor vehicles for transport means that the price of petrol is a sensitive issue. Table 15.12 reports data from the German government, tracking retail petrol prices globally. Unfortunately it does not seem to be controlled for inflation, and is based on exchange rates without adjusting for purchasing power parity. Within these constraints, it provides a valuable set of data. There are a few countries where the price of petrol to the consumer is still subsidised, especially some oil-rich ones. Then there are a few, notably the United States, where the retail price seems to reflect little more than the immediate market value. Most other countries impose varying degrees of taxation on petrol. Canada, Australia and New Zealand are the

T

most lightly taxed among the selected countries. All the European countries have a consumer petrol price that is more than double the American price. While the price of petrol showed considerable short-term volatility, its long-term trend has been up. It fell overall in the selected countries between 1995 and 2000, although not in the three cheapest countries. The variety of national trends again showed the importance of national policies in setting prices of this product. Between 2000 and 2006, the price of petrol rose steeply in nearly all the countries, rising by more than 50% on average in these six years, although in several it subsequently declined somewhat from this peak. There are increasing suggestions that the high cost of petrol and problems of traffic congestion are causing people to change to public transport, but the overall trend in the 35 years between 1970 and 2005 was starkly in the other direction. Table 15.13 shows a modest overall increase in how far residents of these countries travelled by train each year by around one-seventh. In contrast, in Table 15.14, the average distance travelled by car more than doubled in the same period. In every country, the average person travels further by car than by train. Even in the greatest train-travelling country, Japan, the ratio is still more than two to one. The two countries at the top of Table 15.14 for car travel in 2005, the United States and Australia, are – with Ireland – at the bottom for train travel in the previous table. Indeed, Australia and the United States are the only countries in Table 15.13 where people on average travelled less by train in 2005 than in 1970. Moreover, assuming these OECD figures are accurate, and they are based on decades of research, in Australia train distances travelled per person almost halved in the period. So the data on this page offers no indication that car travel has been in decline; rather the reverse.


211

Table 15.15 City size and density City Brussels (Bel) Vienna (Aut) Rome (Ita) Amsterdam (Nth) London (UK) Berlin (Ger) Zurich (Swi) Helsinki (Fin) Paris (Fra) Oslo (Nor) Dublin (Ire) Copenhagen (Den) Stockholm (Swe) Chicago (US) Melbourne (Aus)


Population density (persons per hectare)

0.96 1.55 2.81 0.85 7.17 3.39 0.81 0.97 11.10 0.98 1.12 1.81 1.84 8.18 3.37

73.6 66.9 62.6 57.3 54.9 54.7 44.5 44.0 40.5 26.1 25.9 23.5 18.1 15.4 13.7

Table 15.16 Modes of daily transport Percentage of daily trips via each mode of transport City Amsterdam Vienna Berlin Helsinki Zurich Paris Stockholm Copenhagen London Rome Brussels Oslo Melbourne Chicago

Foot and bicycle

Public transport

Private motor vehicles

51 30 36 29 31 36 31 39 31 24 28 26 18 6

15 34 25 27 23 18 22 12 19 20 14 15 6 6

34 36 39 44 46 46 47 49 50 56 59 59 76 88

No data on Dublin.

Table 15.17 Car travel in cities Average Cost of one Cost of private annual private motorised distance motorised transport for Parking travelled per km for the the community spaces (per private vehicle traveller as a % of thousands (km) (0.01 Euros) regional GDP jobs in CBD)

City Melbourne Chicago Rome Zurich Brussels Oslo Copenhagen Berlin Stockholm London Paris Vienna Helsinki Amsterdam

13900 19800 5530 8650 8980 10700 14800 7760 8700 9140 8220 5230 9000 8750

27.9 38.3 42.3 53.3 33.0 51.1 35.8 40.1 44.6 47.3 40.3 58.0 41.0 41.0

11.7 11.0 7.9 7.4 7.4 7.3 6.8 6.4 5.9 5.1 5.0 4.6 4.6 4.5

No data on Dublin.

212


323 116 178 127 289 88 176 .. 153 85 183 224 384 258

Table 15.18 Public transport availability

City London Stockholm Brussels Helsinki Zurich Oslo Vienna Paris Berlin Rome Dublin Copenhagen Amsterdam Melbourne Chicago

Public transport vehicles (per million inhabitants)

Taxis (per 1000 population)

1800 1800 1720 1710 1590 1540 1520 1470 1380 1380 1130 1110 982 847 713

7.8 2.8 1.3 2.5 2.2 2.2 2.9 1.6 2.1 2.1 1.8 1.6 1.8 1.0 0.7

15.5 Urban mobility and transport ities are shaped by their history and limited by their geography. The resulting urban environment then shapes the behaviour of their inhabitants in ways which have profound effects on transport patterns, their benefits and costs, and their energy usage. These patterns are not easily amenable to quick change. Nevertheless, over the long term, the policy settings adopted can shape future evolution because of the way they structure the possibilities, costs and incentives in which people make decisions about their residence, work and transport. It is often impossible to get good comparative data on cities, but there has been pioneering research by two West Australian scholars, Peter Newman and Jeff Kenworthy, and by the International Association of Public Transport, which recently published results from a very large study it undertook of city transport patterns in 2001. Its study included 52 cities, of which 45 were European. The only Australian city included was Melbourne and the only American one Chicago, with no cities from Japan, Canada or New Zealand. City size is an important aspect of transport possibilities, so the tables on the opposite page focus on the largest city included from our selected countries. Defining the boundaries of cities is subject to considerable variation, as we saw in chapter 1. However, five of the 15 cities in Table 15.15 are just under one million. Melbourne and Berlin are of almost equal size, with the three biggest cities considerably bigger, Paris being larger than Chicago and London. Size defines some possibilities. Perhaps a minimum size is needed for a sophisticated public transport system, for example, while no matter how many freeways are built, a city of eight million people depending primarily on cars is going to have considerable congestion. But in addition to size, population density is also a determinant of transport possibilities and constraints. As can be seen, Melbourne

C

and Chicago have by far the lowest population densities among the selected cities. More than half the cities have population densities more than three times that of Melbourne. This urban spread carries with it the attractions and limits of a suburban lifestyle, the much greater private space in many residences is more than the majority of the inhabitants of the larger European cities have. On the other hand, such sprawl makes it much harder to have an economic or effective public transport system. Table 15.16 shows just how contrasting the modes of transport are in these cities. As might have been guessed, the American city Chicago is the most car-dependent, with Melbourne coming second. At the same time, these are the two cities where fewest trips are made by walking or cycling. While in Amsterdam one in two trips is made by foot or bicycle, in Chicago it is only around one in 20, and in Melbourne one in six. Similarly Melbournians and Chicagoans make much less use of public transport than the residents of the European cities. Vienna tops the list for public transport use. As would follow from these patterns, Table 15.17 shows the greatest distances for car travel occur in Melbourne and Chicago, although Melbournians may be surprised to find that relatively they are second-best off in terms of parking spaces in the CBD. The most interesting aspect of the table however is the almost exact reverse correlation between the two middle columns, highlighting how what is rational at the micro level has consequences at the macro level. In those countries where road travel is cheapest for the individual, it ends up consuming far more of the regional GDP than in cities with the opposite tendency. Public transport can only be travelled on if the facilities are there, and Table 15.18 shows the cities’ investments in infrastructure and vehicles, with again Chicago and Melbourne at the bottom.


213

Chapter 16 CRIME AND SOCIAL PROBLEMS

Table 16.1 Victims of crime Percentage replying they had been a victim of crime in the previous year Country

1989

1992

1996

2000

2004

Japan Austria France Italy Finland Germany Norway Sweden Canada Australia United States Belgium Switzerland Denmark Netherlands United Kingdom New Zealand Ireland

.. .. 16.4 .. 13.0 16.6 13.4 .. 22.4 23.3 25.0 13.4 13.0 .. 21.9 15.0 .. ..

.. .. .. 20.3 17.2 .. .. 18.7 24.0 24.0 22.2 15.2 .. .. 25.7 .. 25.7 ..

.. 13.9 20.8 .. 16.2 .. .. 22.0 21.8 .. 21.5 .. 21.6 .. 26.0 24.5 .. ..

11.9 .. 17.2 .. 16.6 .. .. 22.6 20.5 25.2 17.6 17.5 15.6 20.6 20.2 21.6 .. ..

9.9 11.6 12.0 12.6 12.7 13.1 15.8 16.1 17.2 17.3 17.5 17.7 18.1 18.8 19.7 21.0 21.5 21.9

Mean

17.6

21.4

20.9

18.9

16.4

Table 16.2 Total official crime rate Crimes recorded by police per 100 population Country

1990

2000

Ireland Japan Switzerland Italy United States France Austria Norway Finland Netherlands Australia Canada Germany Belgium Denmark United Kingdom New Zealand Sweden

2.5 1.3 5.3 4.4 5.8 6.2 5.9 5.6 8.7 7.1 6.5 9.5 7.0 3.5 10.3 8.9 12.1 14.2

1.9 1.9 3.8 3.9 4.2 6.4 6.9 7.3 7.4 7.4 7.5 7.6 7.6 8.2 9.5 9.6 11.2 13.7

6.9

7.0

Mean

214


16.1 Crime rates t may be a surprise – especially given the media and political attention given to crime – that Table 16.1 shows that crime rates have fallen in the selected countries overall, and sharply fallen in Australia. The table shows somewhat different timings and trajectories for different countries, but as a generalisation crime rose into the mid- or late 1990s, and then fell appreciably in the early years of the 21st century. ‘Crime and Social Problems’ is one of the sections of this book where the capacity of statistics to capture reality is most problematic. There are two main methods of measuring overall crime rates in different countries, both reported on the opposite page, but each has its own problems. The best data, which are becoming steadily more valuable and illuminating, come from surveys of the public. The United Nations has co-ordinated five waves of the International Crime Victims Survey (ICVS) – 1989, 1992, 1996, 2000, 2004–2005 – to collect systematic comparative data on the experience of crime. In the fifth wave, all the selected countries participated, although participation was more uneven in earlier waves, as can be seen from the gaps in the table. The advantage of this type of approach is that it involves large, broadly representative samples of the public, and asks them the same questions, thus overriding differences and inaccuracies in official data. It does rely on the accuracy of the sampling and the willingness of respondents to participate. Sometimes victims of crime are concentrated among deprived groups – ethnic minorities or the very poor, who are often under-represented in survey research. It also depends upon respondents answering honestly and accurately in the survey situation. The professionals designing and executing the research are very aware of such issues, however. Table 16.2 reports crimes officially recorded by the police per 100 population. Official crime statistics are always haunted by the ‘dark figure’ – the gap between the official and the

I

actual rates of crime. The dark figure has two main sources: either that crime is not reported to the police or that reported crime is not recorded. Neither is constant either over time or between countries. It used to be the case, for example, that very serious offences such as sexual assaults and child abuse were not reported because the victim felt powerless to achieve justice or feared the police process that would follow. One suspects that the proportion of such offences now reported has increased substantially. Even after a report is made police have some discretion about whether and how it is recorded. Sometimes ulterior bureaucraticpolitical motives may enter – either deflating the rate of unsolved crimes to make themselves look more effective or inflating it in order to plead for extra resources. More importantly, the recorded rate reflects levels and patterns of policing, especially in some categories, such as drug offences and public order offences. So the differences between countries in official crime rates reported in Table 16.2 may first of all reflect differences in the incidence of crime. But equally the data may be affected by differences in official definitions, levels of policing, routines of reporting, and victims’ willingness to report offences to the police. This table offers only the total official crime rate, partly because different countries have different categories for defining crime, and there is no international body harmonising and publishing their individual efforts. Indeed this data is quite dated, resulting from the efforts of some British analysts, not recently repeated. The most basic contrast between Tables 16.1 and 16.2 is how much higher the figures are in the first table. This is mainly because many people, when they are victims especially of minor crimes, do not report them to police, and this propensity may vary between nations. On the basis of Table 16.2, Sweden would rank as the most crime-ridden, but in Table 16.1 it is just below the mean. In both cases, Japan ranks lowest.

CRIME AND SOCIAL PROBLEMS

215

Table 16.3 Homicide Deaths from intentional assault, per 100 000 population Country

Table 16.4 Gun ownership Percentage owning firearms and handguns

1960

1970

1980

1990

2000

2004

Japan United Kingdom Germany Ireland Austria France Norway Switzerland Sweden Italy Netherlands Denmark New Zealand Belgium Australia Canada Finland United States

1.9 0.5 0.9 0.1 1.2 1.6 0.4 0.6 0.6 1.3 0.3 0.5 1.0 0.6 1.5 1.4 3.0 5.0

1.3 0.8 1.4 0.4 1.5 0.7 0.7 0.7 0.9 0.8 0.5 0.7 1.2 1.1 1.5 2.1 2.1 8.7

0.9 1.0 1.2 0.8 1.2 1.0 1.1 1.0 1.2 1.9 0.8 1.3 1.3 1.5 1.9 2.0 3.0 10.2

0.6 0.7 1.0 0.7 1.6 1.0 1.1 1.3 1.2 2.5 0.9 1.0 2.3 1.3 2.1 2.0 3.0 9.7

0.6 0.4 0.7 1.0 0.9 0.8 1.2 0.8 1.0 1.0 1.1 1.2 1.4 .. 1.6 1.5 2.5 6.1

0.5 0.5 0.6 0.6 0.7 0.7 0.9 0.9 1.0 1.1 1.1 .. 1.2 .. 1.3 1.6 2.3 6.0

Mean

1.2

1.5

1.9

1.9

1.4

1.3

Table 16.5 Robbery with weapons Percentage saying they had experienced robbery in the previous 12 months, 2004 Prevalence of robbery

Country

% involving weapon

% involving knife

0.2 0.3 0.3 0.4 0.4 0.5 0.6 0.8 0.8 0.8 0.8 0.9 0.9 1.1 1.1 1.2 1.3 2.2

0 9 33 19 35 16 36 34 16 37 29 37 23 42 24 29 36 35

0 7 17 10 13 8 16 11 9 16 24 16 8 19 9 17 16 18

0 0 12 6 6 1 14 11 5 9 3 2 7 6 1 7 9 3

Mean

0.8

27

15

6


Firearms 2004

Handguns early to mid1990s

Handguns 2004

Japan Australia United Kingdom New Zealand Ireland Denmark Netherlands Sweden Canada France Norway Germany Belgium Italy Austria Finland Switzerland United States

.. 16.0 4.1 24.4 .. .. 2.3 16.2 26.0 22.6 .. .. 15.6 16.4 15.3 25.4 35.3 43.6

0.8 6.2 6.0 16.6 12.4 12.6 4.8 19.3 15.5 16.1 26.1 12.5 11.4 12.9 15.1 37.9 28.6 42.8

.. 1.6 0.4 1.6 .. .. 0.9 1.7 3.9 4.9 .. .. 6.7 5.5 8.1 6.8 13.8 25.1

0.0 0.3 0.4 0.6 1.0 1.2 1.3 1.6 2.9 3.7 3.7 4.2 5.2 5.3 5.6 6.3 10.3 17.6

Mean

20.2

16.5

6.2

4.0

Country

Table 16.6 Assaults Percentage saying they had experienced assault and threats in the previous 12 months, 2004

% involving gun

Japan Finland Italy Austria Germany Netherlands United States Canada France Norway Switzerland Australia Denmark New Zealand Sweden Belgium United Kingdom Ireland

216

Firearms early-mid 1990s

Prevalence of assaults and threats

% involving weapon

% involving knife

% involving gun

Japan Italy Austria France Finland Switzerland Germany Norway Canada Denmark Australia Sweden Belgium Netherlands United States Ireland New Zealand United Kingdom

0.6 0.8 2.1 2.1 2.2 2.5 2.7 2.9 3.0 3.3 3.4 3.5 3.6 4.3 4.3 4.9 4.9 5.4

13 12 23 23 4 25 18 18 18 14 28 11 19 17 17 15 19 23

0 5 10 12 1 13 8 8 4 2 8 3 8 8 3 5 4 10

0 4 3 4 0 4 3 1 3 3 2 2 1 4 6 0 2 1

Mean

3.2

18

6

2

Country

16.2 Homicide and violent crime n 2004 in the selected countries, 13 people in a million were victims of homicide. Table 16.3 shows that the overall mean of the countries moved within a narrow band in the 44 years between 1960 and 2004, with a minimum of 1.2 victims per 100 000 population and a maximum of 1.9. Since 1990, the trend has been downward. The country which has shown the greatest variation, but which has always had the highest homicide rate by a considerable margin, is the United States. In 2004, an American was still four times as likely as the mean, and 12 times more likely than a Japanese, to be killed in a homicide. Although not quite as consistent, the relativities in the table remain broadly constant. Eight countries had a rate of less than one victim per 100 000, and these countries have consistently been in the lowest half of the rates. In every period, Finland had the second highest homicide rate, although always less than half the American rate. (Homicide includes both murder and manslaughter, with murder comprising about 90% of the total.) Canada, Australia and New Zealand have consistently been in the worst third, although the latter two, at least, have shown an improvement in recent years. Many factors contribute to the total murder rate in a society, but it seems plausible that one factor contributing to the extraordinary American rate is the widespread possession of firearms. In America, 66% of the 15 517 murders in 2000 were committed with firearms. In contrast, in Australia in 2001, only 16% of murders were committed with a firearm. The ICVS survey asks questions about ownership of firearms generally and of handguns specifically. These both show a general decline from the early to mid-1990s to 2004, although the decline is least in the country with the highest rate, the United States. In the early 1990s, fully one American in four professed to owning

I

a handgun, four times the overall mean. By 2004, this had declined substantially to around one in six, but the American ownership rate was still four times the mean. These figures show the effectiveness of the Howard Government’s courageous stance on gun reform following the 1996 Port Arthur massacre. While most countries showed a decline in the period, it was particularly sharp in Australia. In the five years from 1991 to 1995, there were on average 77.4 firearmsrelated homicides in Australia; in the peak year, 1996, there were 104; in the four years from 1998 to 2001, the average was down to 52.8. Just as importantly this policy was associated with a decline in the number of suicides involving firearms. Between 1991 and 1995, there were on average 446 suicides involving firearms per year; between 1998 and 2001, there were 239 per year. The remaining two tables on the opposite page report data on the minority of crimes where there is a direct confrontation between perpetrator and victim. In Table 16.5, 0.8% of people in the selected countries said they had experienced a robbery in the previous 12 months. Of these, one in four involved a weapon, with 15% involving a knife and 6% a gun. Ireland and the United Kingdom had the worst incidence, with Australia close to the norm. The high homicide countries, the United States and Finland did better here, although America does have the highest proportion involving a gun. More people experience assaults and threats of assault, around one in 30 overall according to Table 16.6. Although exact figures were not available, threats outnumbered actual assaults by a very considerable margin. Of these about one in six involved a weapon, with the percentages of both knives and guns lower than in robberies. Usually the weapons involved what might be called weapons of convenience (pipes, glass, screwdrivers etc).


217

Table 16.7 Number of police Number of police officers per 100 000 population Country

2000

Italy France Belgium Austria Ireland Germany Netherlands United Kingdom United States Australia Switzerland Denmark Canada Sweden New Zealand Japan Norway Finland

472 381 360 337 306 289 274 255 230 212 198 190 182 182 181 179 178 156

Mean

253

%

Belgium Austria Denmark New Zealand Italy Sweden United Kingdom France Japan Australia Germany Netherlands Switzerland Norway Finland Ireland United States Canada

63 61 60 59 58 58 58 56 55 53 52 52 52 51 48 48 48 46

Mean

54

Country

Country

%

Denmark Finland Australia Austria Germany Belgium Canada Sweden Switzerland Ireland United Kingdom Netherlands New Zealand United States Japan France Norway Italy

75 72 69 68 67 65 65 64 63 61 61 58 57 57 54 53 53 43

Mean

61


Country

Table 16.10 Perceptions of police performance Percentage who think the police do a good job

Table 16.9 Satisfaction with police response Percentage of those reporting crime who were satisfied with the police response, 2004

218

Table 16.8 Reporting crime to the police Percentage of victims reporting the crime to the police, 2004

Early to mid-1990s

2004

Finland United States Canada New Zealand Australia Denmark Austria Ireland United Kingdom Germany Norway Belgium Netherlands Switzerland Italy Sweden Japan France

55 77 80 79 72 .. 54 .. 68 67 70 47 45 55 50 61 .. 56

89 88 86 84 82 82 81 78 75 74 73 71 70 69 65 65 64 60

Mean

61

75

16.3 Policing s important as the prevalence of crime to people’s feeling of security is their perception of policing. The tables on this page offer data on the numbers of police and attitudes to their performance. Table 16.7 suggests that the number of police officers in relation to population varies considerably among the selected countries, with the highest country, Italy, having around three times as many as the lowest country, Finland. This would seem to be at least as much a matter of definitions as of actual commitment to policing. Italy and the other countries at the top seem to include as police several categories of regulatory and enforcement officials that other nations do not. Perhaps the most remarkable thing about Table 16.7, which may partly reflect its possible lack of reliability, is the lack of relationship between this table and almost anything else. It shows no relationship with either the number of victims or the official crime rates, recorded in Tables 16.1 and 16.2. The country ranking lowest on crime rates, Japan, also has a relatively low number of police, while Austria, France and Italy have relatively high numbers of police and relatively low crime rates in 2004. Nor does the number of police show any relationship to the propensity of people to report crimes when they are victims. Table 16.8 shows a fairly narrow grouping. On average,

A

just over half the time people experienced crime, they reported it to the police. It is likely that most of the time the people who did not report the offence thought that it was too minor and/or the chance of successful apprehension of the offender too remote to bother, rather than for example a belief that the police were corrupt, incompetent or hostile. There is more divergence between the countries on the satisfaction of those victims who report the offence to the police. Around six in 10 were satisfied overall, with Denmark and Finland the only countries where seven in 10 or more reported satisfaction. Australia ranks third, just behind these two. At the other end, only Italy has fewer than half feeling satisfied, despite the apparently high number of police officers that country has. Overall, however, the public has a fairly high opinion of the police, and indeed between the early to mid-1990s and 2004 – a period during which the crime rate fell – public appreciation of the police rose considerably. The overall mean has three in four people saying the police do a good job, and Australia is one of seven countries where between 80% and 90% express such positive sentiment. Australian attitudes were broadly stable in the period, but a few European countries – Finland, Austria, Belgium and the Netherlands – showed very big jumps of 15 percentage points or more.


219

Table 16.11 Public fear of burglary Percentage of population thinking a burglary in the next year is likely or very likely, and the % who experienced a burglary in previous 12 months, 2004 Country

Expect

Experienced

Finland Denmark United States Sweden Netherlands Austria Norway Germany Canada Switzerland Belgium Ireland United Kingdom Australia New Zealand France Italy Japan

13 14 16 17 18 21 21 23 25 26 33 33 34 36 36 38 43 48

0.8 2.7 2.5 0.7 1.3 0.9 1.2 0.9 2.0 1.6 1.8 2.3 3.3 2.5 3.2 1.6 2.1 0.9

Mean

28

1.8

Table 16.12 Public feeling of safety % of the population feeling unsafe or very unsafe on the street after dark, 2004 Country

%

Finland Norway Canada Denmark Netherlands Austria Sweden United States France Switzerland Belgium Australia Ireland Germany New Zealand United Kingdom Italy Japan

14 14 17 17 18 19 19 19 21 22 26 27 27 30 30 32 35 35

Mean

22

Table 16.13 Support for victims Percentage of victims who received support after crime, and the % saying it would have been useful, 2004 Received support

Would have been useful

New Zealand United Kingdom United States Canada Netherlands Austria Belgium Denmark Norway Sweden Japan Australia Ireland France Italy Finland Germany

24 16 16 .. 14 13 13 10 10 9 8 6 6 4 3 2 2

36 45 38 27 30 26 36 30 37 39 20 27 42 38 36 32 27

Mean

10

33

Country


220


16.4 Victim support and public fears he value of the International Crime Victim Surveys is that they chart experiences systematically and also attitudes and perceptions. Tables 16.11 and 16.12 report respectively data on the expectation of a possible home burglary and on feelings of safety. The most notable thing about Table 16.11 is the contrast between the two columns. The first column offers the proportion thinking a burglary of their home is likely or very likely in the next year, while column two reports the proportion who had experienced a burglary in the previous 12 months. While the overall average has 28% who think a burglary is likely in the next year, less than 2% had experience such an event in the past year. In other words, there is far more apprehension about such an event than direct experience of it. Moreover while there is some variation in the second column, with a range from 0.8% to 3.3%, there is much more variation in the first column, from 13% to 48%. There is only a slight relationship between the rankings of the two columns, demonstrating again the problematic relationship between perception of risk and actual risk. While the country with the lowest rate of burglaries, Finland, has the smallest percentage fearing it, the country with the second lowest, Japan, has the highest percentage expecting it to happen. Other relatively highincidence countries, Denmark and the United States, are among those whose populace feels most secure. Australia ranks somewhat above the mean in both columns. Table 16.12 shows a somewhat similar disproportion if one compares it with Table 16.6. Whereas in the earlier table, overall 3.2% of the selected countries’ publics said they had experienced assault or threat of it in the previous 12 months, in the latter table 22% felt unsafe or very unsafe on the street after dark.

T

While fewer expressed fear here than were pessimistic about home burglary, there is still quite a range, from 14% to 35%. The Nordic countries feel least fearful, while the two most fearful countries are Italy and Japan, the two countries having the lowest rate of those actually experiencing assault or its threat. Again, fear bears little resemblance to actual incidence. This is consistent with a sort of cultural pessimism that runs through Japanese responses. They are most fearful about safety after dark despite them objectively being among the safest, most fearful about burglary even though they have almost the lowest rate, and as we saw in health statistics, despite having the greatest longevity, they visit their doctor more frequently than people in other countries, and are much more likely to say they are not in good health. Another aspect of crime is the support victims receive afterwards. Remembering that many of the crimes reported here are relatively minor, 10% of victims in Table 16.13 said they received support afterwards, much less than the 33% who said it would have been useful. The countries varied considerably in how much support they offered. The clear leader was New Zealand, a country which tended to rank high on several of the measures of crime. It is also the country with the smallest gap between the number receiving support and the number saying they would like it. Moreover, four English-speaking countries top the list, but not Australia or Ireland, and especially in the latter there is a sizable gap between those who would appreciate support and those actually receiving it. So while the various tables on crime suggest some progress in recent years, support for victims seems to be an area that is still relatively unattended to.


221

Table 16.14 Imprisonment rates Prisoners per 100 000 population Country

1982

1995

2005

Japan Norway Finland Denmark Sweden Switzerland Ireland France Belgium Germany Italy Canada Austria Australia Netherlands United Kingdom New Zealand United States

46 46 99 62 55 .. .. 59 64 80 62 107 .. 46 32 91 84 301

37 55 59 66 65 80 57 89 75 81 87 131 77 96 66 100 128 600

62 69 75 77 78 83 85 88 90 97 97 107 108 126 127 143 189 738

82

79

94

Mean

Table 16.15 Capital punishment Death penalty in abolitionist countries Country Australia Austria Belgium Canada Denmark Finland France Germany∗ Ireland Italy Netherlands New Zealand Norway Sweden Switzerland United Kingdom ∗

Does country retain death penalty?

Year abolished for ordinary crimes (all crimes)

Year of last execution

No No No No No No No No No No No No No No No No

1985 1950 (1968) 1996 1976 (1998) 1933 (1978) 1949 (1972) 1981 1949 1990 1947 (1994) 1870 (1982) 1989 1905 (1979) 1921 (1972) 1942 (1992) 1973 (1998)

1967 1950 1950 1962 1950 1944 1977 1949 1954 1947 1952 .. 1948 1910 1944 1964

West Germany abolished death penalty in 1949; East Germany in 1987.

Death penalty in retentionist countries Country

Does country retain death penalty?

Number executed in 2007

Number sentenced to death in 2007

Yes Yes

9 42

23 >100

Japan United States

222


16.5 Imprisonment and execution hereas the crime rate fell somewhat in the selected countries between the mid1990s and 2004–2005, imprisonment rates increased, according to Table 16.14. The per capita imprisonment rate is determined by the number of crimes, the rate at which people are arrested, the seriousness of their offences, the rate at which they are convicted (and remanded in custody before that), the proportion of the convicted given a prison sentence and the average length of the term imposed. It is not possible then to conclude definitively how the increased imprisonment rate interacts with the crime rate or whether its increase reflects increasingly punitive attitudes. Imprisonment rates in the selected countries show enormous variation. The United States has a unique profile, with a rate almost four times higher than the second-ranking country, and 12 times the rate of bottom-ranked Japan. Its rate of imprisonment more than doubled between 1982 and 2005. According to American scholar Marie Gottschalk, American incarceration practices were not exceptional for most of the 20th century. Until 1970, it had a rate higher, but not remarkably higher, than other Western countries. From then on, its imprisonment rates escalated far more sharply than any other country’s. The next five countries all show considerably increased imprisonment rates in these two-and-a-bit decades. In Australia, the rate almost trebled. The next country, Canada, is one of the few that reduced its imprisonment rate between 1995 and 2005, dropping down from second to seventh in the rankings. The Scandinavian countries and Japan have the lowest frequency of imprisonment, although some of them have increased their rates recently. Imprisonment is a relatively expensive option, and in the English-speaking countries at least, there is some attention to prison overcrowding. Perhaps the drain on the public purse is one reason why private prisons have become more popular in some jurisdictions.

W

Sixteen of the selected countries have abolished capital punishment, as can be seen in Table 16.15. The two countries still practising execution are the United States and Japan. One has the highest rate of homicides and the other the lowest, so it is hard to draw any conclusions supporting the deterrent effect of capital punishment. None of the other 16 countries has executed anyone for over a quarter of a century, and some of them for the last half century or longer. Ironically, the last execution among them occurred in France in 1977, the year that the United States resumed exercising the death penalty, after a Supreme Court decision the previous year. In late 2005, the 1000th person since then was executed. According to Amnesty International, 91 countries worldwide have abolished the death penalty in law or practice. Four countries accounted for the overwhelming proportion of executions worldwide in 2007 – China (470+), Iran (317+), Saudi Arabia (143+) and Pakistan (135+). The United States ranked fifth (42). In Japan, practices regarding capital punishment seem to be stable. In 2007, Japan executed nine people, its most in a single year for more than 15 years. Its average over the period 1993 to 2007 was about five, and each year there was at least one execution. While the United States is the only longestablished democracy to execute people on a large scale, the practice enjoys majority popular support there and no recent major contender for national office has campaigned for its abolition, in practice it is carrying out fewer executions. That country peaked in 1999 with 98 executions; and since then has trended downwards. A somewhat bizarre aspect of the two countries in our table that retain the death penalty is that they sentence far more people to death than they execute. There were more than 3000 Americans on death row, with an average time of 150 months between sentence and execution.


223

Table 16.16 Suicide Suicides per 100 000 people Country

1960

1970

1980

1990

2000

2003

Italy United Kingdom Netherlands United States Denmark Australia Norway Canada Sweden Germany Ireland New Zealand Switzerland Belgium Austria France Finland Japan

6.2 9.7 7.3 11.4 19.7 11.3 6.2 8.8 15.9 17.5 3.0 10.7 18.6 13.3 21.2 15.0 21.6 25.1

5.6 7.3 8.5 12.3 20.4 13.3 8.1 12.4 20.4 20.2 1.9 10.7 18.2 15.1 23.0 14.7 21.4 17.4

6.7 8.1 9.9 11.6 29.2 11.2 11.9 13.9 17.7 18.5 7.1 11.3 23.8 20.2 23.7 17.9 24.1 17.9

6.5 7.4 8.7 11.9 20.5 12.5 14.4 12.0 15.0 14.5 10.1 13.4 19.1 16.6 20.5 17.7 27.8 14.5

5.8 6.4 8.2 9.8 11.4 11.8 11.6 10.8 10.9 11.0 11.8 12.0 16.2 .. 16.8 15.6 20.4 19.1

5.5 6.1 8.0 10.0 .. 10.2 10.5 10.7 10.7 10.8 10.8 12.5 14.1 .. 14.9 15.3 18.4 20.3

Mean

12.4

13.9

15.8

14.6

12.3

11.8

Figure 16.1 Male suicide rates Male suicides per 100 000

25 20 15 10 5 0 1960

1970

1980 Australia

Figure 16.2 Female suicide rates Female suicides per 100 000

1990

2000

2003

2000

2003

D18 Mean

25 20 15 10 5 0 1960

1970

1980 Australia

Figure 16.3 Suicides and age groups Suicide rates per 100 000 by age group, late 1990s

1990 D18 Mean

35 30 25 20 15 10 5 0 15–24

25–34

35–44

Australia

224


45 –54 New Zealand

55– 64

65 – 74

D18 Mean

75+

16.6 Suicide lthough it receives less media and political attention, each year suicide claims almost 10 times as many victims in the selected countries as does homicide. Table 16.16 shows the overall mean rate in 2003 was 11.8 deaths per 100 000 population, slightly less than it had been in 1960. In the intervening years, it moved in a reasonably narrow band, peaking in 1980 but declining somewhat since. It is not clear what aspects of societies explain the variations in suicide rates, or why they change over time, but the differences are substantial. Finland has treble the rate of Italy. Denmark’s suicide rate rose sharply, until by 1980 it ranked highest, but then fell even more sharply so that by 2000 it had more than halved. Australia is almost exactly in the middle of the table, and has shown less fluctuation than several other countries, although recently it has trended slightly downwards. In 2003, Japan had the highest suicide rate. While it was always among the highest countries, its rate has shown more volatility than most. It began in 1960 with the highest rate, but by 1990 it had dropped to only 60% of that level. Since then it has again risen sharply. Most obviously this rise is due to increased economic stresses, but there are also cultural factors. There is more idea of an ‘honourable’ suicide in Japan, but in addition it is a country that allows few ‘second chances’. According to the Economist, ‘Japanese society rarely lets people bounce back from the perceived shame of failure or bankruptcy’. The statistical study on suicide has a long lineage in sociology, most notably the work of Emile Durkheim who, drawing on the work of the French ‘moral statisticians’ of the 19th century, theorised that suicide rates varied with factors of social cohesion. Much later, this work came under attack, including from scholars arguing that the statistics on suicide were unreliable, involving systematic distortions, reflecting religious and social stigmas, as

A

well as many ambiguities in individual cases. While still a proper caution, as professional forensic techniques have improved and social stigmas reduced, the power of these arguments is not as strong as it once was. None of the patterns which sometimes explain the clustering of countries on other phenomena correlates well with suicide. Catholic Italy has the lowest rate, but Catholic Belgium and Austria have among the highest, while Catholic Ireland is in the middle. Nordic Finland has the second-highest rate, but the three Scandinavian countries are in the lower half of the table. None of the English-speaking countries is in the worst third, but are spread throughout the rest of the table, with Britain having the second-lowest rate. There are, however, in all the societies marked and consistent differences between different groups. As Figures 16.1 and 16.2 show, males commit suicide at around three times the rate of females, and the greater propensity of males to die from suicide is true in all the selected countries. Among both sexes, the Australian rate was consistently just below the mean. Overall, the rates for both sexes peaked in 1980 and have declined since. The other pattern found in most societies is that older age groups are more likely to commit suicide than younger ones. Figure 16.3, based on data from the late 1990s, shows across the countries as a whole a steadily increasing rate with age, with the oldest group being more than twice as likely to commit suicide as the youngest. This trend does not hold nearly as strongly in Australia and New Zealand. New Zealand’s trend is actually the reverse, its suicide rate higher for younger than older age groups. Australia is above the 18-nation mean in younger age groups but below it in older ones. The Australian and New Zealand distributions show that suicide is taking a heavy toll on young males in these countries.


225

Table 16.17 Motor vehicle deaths Fatalities per 100 000 population Country

1960

1970

1980

1990

2000

2003

Sweden United Kingdom Netherlands Norway Japan Ireland Switzerland Finland Germany Denmark Australia Canada France Belgium Austria Italy New Zealand United States

14.4 14.3 17.6 8.6 15.9 9.0 22.0 18.1 25.6 17.1 28.1 21.8 18.1 19.2 27.6 17.8 16.5 22.6

16.5 14.2 24.8 15.0 22.5 16.6 26.1 23.7 32.2 24.2 32.8 25.0 23.2 29.8 33.3 24.3 24.2 27.0

10.5 12.1 13.7 9.1 11.4 17.9 18.5 11.4 20.3 13.5 24.6 22.1 20.4 24.9 25.5 19.2 19.8 22.4

8.8 9.8 8.8 8.1 11.9 13.9 13.1 13.8 13.6 11.2 14.4 13.9 17.5 18.1 18.3 14.9 22.3 18.5

6.3 5.8 7.1 8.6 8.5 10.5 8.2 7.5 9.5 9.1 10.2 9.6 12.5 .. 11.3 12.2 13.4 15.8

5.6 6.1 6.6 6.8 6.9 7.3 7.4 7.6 8.1 8.2 8.4 9.0 9.7 .. 11.0 11.2 13.2 15.6

Mean

18.6

24.2

17.6

13.9

9.8

8.7

Table 16.18 Injuries from road traffic accidents Number per 100 000 population Country

1970

1990

2004

Denmark Finland France Ireland Netherlands Australia Norway Sweden New Zealand Switzerland United Kingdom Germany Italy Belgium Canada Austria Japan United States

516 348 633 314 528 732 303 276 728 574 668 877 424 1101 641 943 937 975

207 256 398 269 348 233 280 263 325 436 604 709 390 865 948 786 639 1295

140 168 179 195 205 214 264 295 348 389 464 534 556 603 645 683 927 949

640

514

431

Mean

226


16.7 Car accidents he figures in Table 16.17 show what a terrible toll car accidents claim in the selected countries, but also what a policy success has been achieved in this area. Especially because of the age structure of its victims – concentrated among young people, especially young males – car accidents remain an important cause of premature death in these countries. For the individuals and families involved, it is a great tragedy. Nevertheless the table also shows how much progress has been made in this area, how dramatically a series of measures has reduced the road toll in all the countries, and especially in Australia. If the Australian rate had stayed at its disastrous 1970 peak, then about 4000 more Australians would have died on the roads in 2008. The 2003 rate is just over a quarter what it was in 1970. As cars became more widely affordable in the decades after World War II, the death toll from car accidents rose enormously. In all the selected countries the road toll seemed to mount inexorably in the post-World War II decades, and increased by more than a quarter between 1960 and 1970 in the countries overall. Indeed, in 1970 at 32.8 deaths per 100 000 population, Australia had the second-worst road toll among the countries, marginally better than Austria, and marginally worse than Germany. Since then, however, there has been consistent and steady improvement, providing testimony to the capacity of well-directed policies to ameliorate the problem. To varying degrees in different countries, the arsenal of changes has included improved car design; compulsory wearing of seatbelts; improved road design, including the identification of ‘black spots’; reductions in speed limits; a much stricter approach to driving under the influence of alcohol, including random testing; and improved driver education. The improvement is the more remarkable, because, as we saw in chapter 15, the density

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of car ownership and the distances travelled in them have continued to increase. Other OECD figures, not reproduced here, and not going back as far as Table 16.17, show a similar dramatic progress when measuring mortality against the incidence of cars as well as against population. Although all of the countries have reduced their rate substantially in recent decades, they have done so to different degrees and have achieved differing rates thus far. The countries which have improved least are those now at the bottom of the table, the United States and New Zealand. Australia’s rate is now slightly below the mean, but 10 other countries still do better, and Australia is still quite a bit behind the safest countries, Sweden and Britain. The data on injuries from road accidents in Table 16.18 also shows substantial improvement, but its data is much less reliable. Differences in definition about how serious injuries are before they are included certainly account for some of the variations. The Australian injury rate, for example, trended downwards through the 1970s, to 640 in 1979, but then dropped precipitately to 218 in 1980. One suspects this is because of a change in definition rather than a real change of that magnitude. One would expect the rankings in the two tables to be broadly similar, and the United States suffers the heaviest toll in both. One possible reason for a discrepancy would be that if a country with dense traffic had a high number of crashes but at lower speeds, then there could be more injuries but fewer fatalities. This could explain Japan’s fall to 17th in this table from fifth in the table on fatalities. The data in Table 16.18 is so confounded by the possibility of different definitions that little confidence can be had in either the precise comparisons or the trends. The most important lesson is that the toll from road traffic smashes is not only in the fatalities. For every fatality, there are on average almost a further 50 serious injuries.


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Table 16.19 Corruption Perceptions Index Transparency International Corruption Perceptions Index Score of 10 = least corrupt; score of 0 = most corrupt Country Denmark Finland New Zealand Sweden Netherlands Switzerland Canada Norway Australia United Kingdom Austria Germany Ireland Japan France United States Belgium Italy

1996

2002

2007

9.3 9.1 9.4 9.1 8.7 8.8 9.0 8.9 8.6 8.4 7.6 8.3 8.5 7.1 7.0 7.7 6.8 3.4

9.5 9.7 9.5 9.3 9.0 8.5 9.0 8.5 8.6 8.7 7.8 7.3 6.9 7.1 6.3 7.7 7.1 5.2

9.4 9.4 9.4 9.3 9.0 9.0 8.7 8.7 8.6 8.4 8.1 7.8 7.5 7.5 7.3 7.2 7.1 5.2

Table 16.20 Bribery Payers’ Index Transparency International Bribery Payers’ Index Score of 10 = least corrupt; score of 0 = most corrupt Country Belgium Canada Netherlands Switzerland Germany Japan United Kingdom Australia France United States Sweden Austria Italy

2002

2006

2008

7.8 8.1 7.8 8.4 6.3 5.3 6.9 8.5 5.5 5.3 8.4 8.2 4.1

7.2 7.5 7.3 7.8 7.3 7.1 7.4 7.6 6.5 7.2 7.6 7.5 5.9

8.8 8.8 8.7 8.7 8.6 8.6 8.6 8.5 8.1 8.1 .. .. 7.4

No data on Denmark, Finland, Ireland, New Zealand or Norway. Austria and Sweden not included in 2008.

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16.8 Corruption orruption is corrosive of good governance and democratic accountability. However, because successful corruption often means that no offence or transgression is officially recorded or even publicly known, it is impossible to measure its extent authoritatively. Since 1995, Transparency International (TI), an international non-government organisation dedicated to combating corruption, has been conducting and assembling annual polls of business people and country analysts on their perceptions of corruption in the countries they work in. Their methodology assigns a score to each country from zero (most corrupt) to 10 (least corrupt). Around seven out of every 10 countries globally scored less than five. Table 16.19 shows that these 18 countries are ranked among the less corrupt governments world-wide. The countries fall into some broad clusters. First is the cleanest group, ranking 9.0 and above, and led by Finland, Denmark and New Zealand. Australia is part of a second group, ranked fairly uncorrupt, and scoring in the mid-eight range. Australia has consistently scored around 8.6. Italy is scored most corrupt, and by a considerable margin at 5.2, with the remaining six countries. Perception of corruption is not the same as the incidence of corruption, and perceptions can be shaped by factors beyond direct experience. Sometimes scores can be shaped by the prevalence of scandals in the news. Sometimes in surveys of expatriates about the countries they are living in, cultural distance, the opaqueness of local procedures and other frustrations can too easily become labelled as corruption. Moreover, although a convenient indicator, a 10-point scale score gives a somewhat spurious air of precision to the exercise. Such qualifications have led to debates within TI itself about the usefulness of the exercise. Despite these inherent problems, the Corruption Perception Index is a useful indicator, as a means of highlighting the extent of corruption in public life, and the relative ranking of

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countries on the scale would seem broadly accurate to most observers. More recently TI has also constructed a Bribe Payers’ Index (BPI), which it has measured three times, in 2002, 2006 and 2008. The BPI is a ranking of leading export countries, according to the propensity of their firms to bribe abroad. It is based on interviews with business executives in many countries throughout the world. Different exporting countries were included in different surveys. The 2008 survey showed a marked improvement from 2006. The extensive samples and common methodologies in both years suggest the change should be substantive rather than a methodological quirk. If so, it may result from the extensive efforts towards combating bribery in international business. The rankings in the three years varied quite a bit, although the eight leading countries in 2008 were tightly grouped between 8.8 and 8.5. There is a small drop to France and the United States, and then a more substantial drop to Italy. However, nearly all the countries showed improvement across the three surveys, particularly Japan and the United States. Among the 22 exporting countries included in 2008, Russia ran last (5.9) with China (6.5), Mexico (6.6) and India (6.8) slightly ahead. Australia did not show the same improvement. Indeed, it topped the list in 2002, but then dipped somewhat in 2006, perhaps its reputation more generally dented by the AWB scandal, where bribes were paid to Saddam Hussein’s regime in Iraq in order to secure wheat sales. We should note in conclusion that corruption, while present in various sectors of the public and business lives of the selected countries, is remote from the lives of most of their citizens. In the fifth wave of the International Crime Victims Survey, less than 1% reported being the victim of a demand for corruption in the previous year in all countries except France (1.1%) and Denmark (1%). For all others, it was 0.6% or lower.


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Chapter 17 THE SEARCH FOR SCOREBOARDS

Table 17.1 Human Development Index (HDI) Scores can range from .000 (lowest) to 1.000 (highest) Country

1985

2005

Norway Australia Canada Ireland Sweden Switzerland Japan Netherlands France Finland United States Denmark Austria United Kingdom Belgium New Zealand Italy Germany

.900 .880 .911 .851 .893 .902 .899 .899 .884 .884 .904 .890 .876 .870 .883 .871 .869 .871

.968 .962 .961 .959 .956 .955 .953 .953 .952 .952 .951 .949 .948 .946 .946 .943 .941 .935

Mean

.885

.952

Table 17.2 Globally lowest ranking countries on HDI Countries scoring less than .500 on HDI Scores can range from .000 (lowest) to 1.000 (highest) Country

2005

Sierra Leone Burkina Faso Niger Guinea-Bissau Mali Mozambique Central African Republic Chad Ethiopia Congo (Democratic Republic) Burundi Ivory Coast Zambia Benin Malawi Angola Rwanda Guinea Tanzania Nigeria Eritrea Senegal

.336 .370 .374 .374 .380 .384 .384 .388 .406 .411 .413 .432 .434 .437 .437 .446 .452 .456 .467 .470 .483 .499

Table 17.3 Greatest improvement in HDI Countries whose HDI increased most, 1995–2005

Table 17.4 Worst deterioration in HDI Countries whose HDI decreased most, 1995–2005

Country

Country

Rwanda Equatorial Guinea Albania Egypt Bangladesh China Latvia Niger Laos Armenia Nicaragua Oman Uganda Lithuania Madagascar Kazakhstan

Change in score

2005 HDI score

.122 .113 .096 .095 .094 .086 .084 .078 .077 .074 .073 .073 .072 .071 .070 .070

.452 .642 .801 .708 .547 .777 .855 .374 .601 .775 .710 .814 .505 .862 .533 .794

Mean

230

.672


Zimbabwe Swaziland South Africa Lesotho Namibia Kenya Malawi Central African Republic Zambia Côte d’Ivoire Botswana Togo Papua New Guinea Mean

Change in score

2005 HDI score

−.100 −.094 −.071 −.067 −.048 −.023 −.007 −.006 −.005 −.004 −.004 −.002 −.002

.513 .547 .674 .549 .650 .521 .437 .384 .434 .432 .654 .512 .530 .526

17.1 Human Development Index he United Nations Development Programme (UNDP) developed an index designed to create a broader view of a country’s development than using average income alone, which on the face of it takes no account of the diffusion of economic benefits through a society or other aspects of human well-being. The Human Development Index (HDI) is a simple summary measure of three dimensions of the human development concept: living a long and healthy life, being educated and having a decent standard of living. The UNDP’s rationale is that:

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Human development is a process of enlarging people’s choices . . . The three essential ones are for people to lead a long and healthy life, to acquire knowledge and to have access to resources needed for a decent standard of living. If these choices are not available, many other opportunities remain inaccessible.

The HDI combines the three dimensions into one index, and scores each country for each year, with a summary measure between zero and one, a higher score meaning greater human development. While, as we shall see, national income correlates strongly with the HDI, the measure also gives weight to distribution and to the development of social infrastructure. Two components of the HDI – longevity and educational attainment – by their nature reflect upon the well-being of the population as a whole. The idea of a composite scale is to go beyond the limits of individual measures to capture more of the integrity and complexity of the social experience. An intrinsic problem of constructing composite indicators is that even if all the elements can be scored satisfactorily there is always an arbitrariness about their weightings, how the components are combined into one scale. Such constructs are inevitably surrounded by methodological disputes. They should not be viewed as more than a convenient means of encapsulating and simplifying complex realities in order to facilitate comparisons between countries and over time.

The HDI is a relatively blunt instrument for distinguishing the finer aspects of social development within the 18 selected rich countries, all of which score very highly on it. While Norway tops the list, only .003 points separate the first six countries, which include Australia. Overall, the 18 countries are closely clustered, the top 16 falling between .942 and .925. Only New Zealand (because of economic performance) and Italy (because of educational performance) lag somewhat. The increase in the mean score from .885 to .952 over 20 years does, however, show that in central respects, life is still improving for people in these 18 high-income democracies, and that their relatively greater wealth is also translated into giving greater life chances to a substantial proportion of their citizens. Globally, the HDI shows a much wider range. While the mean for the 18 selected countries was .952, the mean for the world as a whole in 2005 was .743. What the UN classified as high-income countries averaged .936, middle-income ones were .776, and low-income countries down at .570. Table 17.2 shows the 22 countries ranking lowest on the HDI, all scoring less than .500. All are African. The HDI, originally constructed in 1990, with its value calculated retrospectively back to 1980 for many countries, also allows us to trace changes over time. While many countries showed variation year to year, Tables 17.3 and 17.4 take a decade interval, from 1995 to 2005, to illuminate longer term trends. Table 17.3 gives the greatest improvers over the decade, many reflecting rapid economic growth, a few the advent of peace and stability after early ravages from war, others an improved political environment. In contrast, Table 17.4 lists the 13 countries whose HDI had actually declined. Apart from Papua New Guinea, the others are African. While there are special political factors in the country with the worst slide, Zimbabwe, the other countries in the table are primarily testimony to the devastating effect AIDS has had on these countries.

THE SEARCH FOR SCOREBOARDS

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Table 17.5 Gender Development Index (GDI) Scores can range from .000 (lowest) to 1.000 (highest)

Table 17.6 Gender Empowerment Measure (GEM) Scores can range from .000 (lowest) to 1.000 (highest)

Country

2002

2005

Country

2002

2005

Australia Norway Canada Sweden Netherlands France Finland Switzerland Denmark United Kingdom Japan Belgium Ireland United States Italy New Zealand Austria Germany

.956 .941 .938 .940 .933 .926 .933 .923 .925 .932 .927 .943 .917 .937 .907 .915 .921 .920

.960 .957 .956 .955 .951 .950 .947 .946 .944 .944 .942 .940 .940 .937 .936 .935 .934 .931

Norway Sweden Finland Denmark Netherlands Belgium Australia Germany Canada New Zealand Austria United Kingdom United States France Ireland Italy Switzerland Japan

.837 .824 .803 .821 .781 .706 .759 .765 .777 .765 .745 .684 .757 .. .675 .539 .718 .527

.910 .906 .887 .875 .859 .850 .847 .831 .820 .811 .788 .783 .762 .718 .699 .693 .660 .557

Mean

.930

.945

Mean

.734

.792

Table 17.7 Difference in GDI and HDI ranks Number of places lower these countries are on GDI than HDI Country

GDI

Saudi Arabia Oman Ireland Libya Pakistan United Arab Emirates Luxembourg Japan

232

−13 −13 −10 −9 −7 −5 −5 −5


.783 .788 .940 .797 .525 .855 .924 .942

Table 17.8 Global lowest scores on gender empowerment Countries scoring lower than .400 on GEM Country Yemen Saudi Arabia Moldova Armenia Kyrgyzstan Morocco Iran Nepal Sri Lanka Qatar Pakistan Cambodia Bangladesh Oman

GEM 2004 .129 .254 .263 .298 .302 .325 .347 .351 .369 .374 .377 .377 .379 .391

17.2 Gender development and empowerment he United Nations Development Programme (UNDP), which developed the Human Development Index (HDI), has also constructed two indices to capture women’s relative position in societies – the Gender Development Index (GDI) and the Gender Empowerment Measure (GEM). The GDI is based upon the HDI but then adjusted to reflect the degree of gender differences on its components. The fact that the 18country mean for the GDI is almost identical to the HDI shows that both measures reflect the general affluence and social development of these societies, and that on these aspects of development women are not strongly disadvantaged. There are three dimensions to the GDI. On the first, longevity, women on average outlive men in all the selected countries. On the second, educational attainment, gender differences have broadly disappeared, and in some countries are now slightly reversed with females out-performing males. This leaves only the third component – differences in earned income – where women tend to score substantially lower. It may surprise that Australia ranks top on the GDI. Its premier ranking probably owes most to the increasing educational levels reached by younger Australian females. With one or two notable exceptions, the rankings in Table 17.5 are similar to those in Table 17.1. Globally, because the central key to a high score on the GDI is a high score on the HDI, the lowest scorers on one also tend to be the lowest scorers on the other. It is more illuminating then to look at where there is a discrepancy between the two rankings. Table 17.7 lists the eight countries where their GDI ranking is considerably lower than their HDI ranking. The biggest differences are in Saudi Arabia and Oman, but two of the selected countries – Ireland and Japan – also figure in the table. The GDI gives scores considerably higher than the second index of women’s position in society – the Gender Empowerment Measure. The GEM is designed to reveal women’s

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opportunity to take an active part in economic and political life. It is composed of several dimensions – women’s share of parliamentary seats, their share of senior management and decision-making roles, their proportion of professional and technical positions, and their power over economic resources, as measured by the relative earned income by each sex. (This component is the same as in the GDI.) As with the GDI there is some arbitrariness in the equal weighting of the components, but they are transparent, objective and pertinent and so a convenient means of comparing women’s empowerment across countries and time. The GEM’s 18-country mean of .792 (Table 17.6) trails well behind the GDI’s .945, an indication that in the selected countries inequalities in power have been slower to change than the tangible changes in women’s roles and opportunities. On the GEM, the differences between countries reflect what most feminists would have suspected, and the range from top to bottom is much wider. The Scandinavian countries and the Netherlands fill the top five positions. The English-speaking countries, headed by Australia, cluster around the middle. Japan comes last, with Switzerland, Italy and Ireland filling the next bottom ranks. The discrepancy is even greater at the global level. The global GDI mean is .716, while for the GEM it is .582. However, it should be remembered that there are large gaps in the data. For the HDI, there are scores for 177 countries, for the GDI 157 countries, and for the GEM only 93 countries. Moreover the gaps are not random, and the countries where the gender data is missing are overwhelmingly the countries where there are pronounced issues of female inequality as well as the most acute issues of poverty and governance. Remembering, therefore, that there are 84 countries excluded because of missing data, Table 17.8 gives the 14 bottom countries, all with scores less than .400, with Yemen and Saudi Arabia scoring worst.


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Table 17.9 Global Competitiveness Index Score (0 = least competitive) 2008 Country United States Switzerland Denmark Sweden Finland Germany Netherlands Japan Canada United Kingdom Austria Norway France Australia Belgium Ireland New Zealand Italy

Global rank

Score

1 2 3 4 6 7 8 9 10 12 14 15 16 18 19 22 24 49

5.74 5.61 5.58 5.53 5.50 5.46 5.41 5.38 5.37 5.30 5.23 5.22 5.22 5.20 5.14 4.99 4.93 4.35

Table 17.10 Economic freedom Score (100 = most free, 0 = least free), 2009

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Country

Score

Global rank

Australia Ireland New Zealand United States Canada Denmark Switzerland United Kingdom Netherlands Finland Japan Belgium Austria Germany Sweden Norway France Italy

82.6 82.2 82.0 80.7 80.5 79.6 79.4 79.0 77.0 74.5 72.8 72.1 71.2 70.5 70.5 70.2 63.3 61.4

3 4 5 6 7 8 9 10 12 17 19 20 23 25 26 28 64 76


17.3 Global competitiveness and economic freedom he Global Competitiveness Index (Table 17.9) is prepared annually by the World Economic Forum, a forum for discussions between senior business and political leaders, based in Davos, Switzerland. Competitiveness is a woolly concept much revered by business people, but out of step with orthodox economic analysis. It takes the objectives of a business – to capture market share from its competitors, or to be the most profitable firm – and assumes these are relevant to the objectives of countries in their economic interactions with other countries. It implies a view of international trade as a zero-sum game in which the object is to be a winner – the biggest winner – not a loser. But economists see trade as win-win – both sides are left better off. A global competitiveness report has been issued for many years, but in recent years some leading American economists have been engaged to give the exercise greater academic rigor. In the process, competitiveness has been redefined to mean ‘the set of institutions, policies and factors that determine the level of productivity of a country’. The level of productivity – output per unit of input – sets the sustainable level of the material prosperity that can be attained by a country. For each of the 134 countries assessed, the index examines 110 variables grouped under 11 headings. Some variables are measured using publicly available statistics, but most rely on the results of an annual survey of executive opinion. A sample of business executives in each country is asked to assess their country’s performance on a particular variable on a seven-point scale. This process introduces a large element of subjectivity to the exercise, subjecting it to the preferences and prejudices of senior business people and making it susceptible to changing intellectual fashions. This may help explain why countries’ rankings change more than would be expected.

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The variables are weighted differently according to a country’s level of economic development but, even so, the weights remain essentially arbitrary. Many variables are given equal weight. All of them seem of some relevance in determining a country’s productivity but, in reality, some will be more influential than others. This may explain why the index’s rankings aren’t highly correlated with measures of economic success such as income per capita (Table 3.1) or contemporary rates of economic growth (Table 3.5). It seems to be particularly astray in its rankings of Denmark, Finland, Germany, Norway, Australia and Ireland. The Index of Economic Freedom (Table 17.10) is prepared annually by the Heritage Foundation, a conservative American think tank, in association with the Wall Street Journal. The index scores about 180 countries on 10 broad dimensions of economic freedom using publicly available statistics and the published subjective assessments of other organisations. The 10 components are weighted equally so that, for example, corruption is given the same importance as size of government (with small government rated more favourably than big government). Depending on their scores, countries are divided into five categories ranging from ‘free’ to ‘repressed’. The top five countries shown in the table are classed as free and the next 11 as mostly free, leaving France and Italy classed as moderately free, in the company of countries such as Uganda, Albania, Turkey and Cape Verde. The index is unashamedly ideological, being ‘grounded in the classical liberal economic theories of Adam Smith and Friedrich Hayek’, which leaves it measuring a ‘time-tested formula for sustained economic growth’. Nor does economic freedom seem to equate with political freedom. The index’s highest rankings go to Hong Kong and Singapore, neither of which is a genuine democracy.


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Table 17.11 Most liveable city (1) Economist intelligence unit ratings of 140 cities, 100 = most liveable, 2008 City Vancouver Melbourne Vienna Perth Helsinki Adelaide Geneva Sydney Stockholm Osaka Copenhagen Auckland Hamburg Brisbane Paris Amsterdam Oslo Brussels Pittsburgh London Dublin Milan

Country

Global rank

Rating

Canada Australia Austria Australia Finland Australia Switzerland Australia Sweden Japan Denmark New Zealand Germany Australia France Netherlands Norway Belgium United States United Kingdom Ireland Italy

1 2 3 4 6 =7 =9 =9 12 13 14 =15 =15 18 19 24 25 27 29 =46 50 51

98.8 98.2 97.9 97.3 96.9 96.6 96.1 96.1 95.7 95.2 95.1 95.0 95.0 94.9 94.8 93.5 93.4 92.7 92.3 90.0 89.6 89.5

Table includes top city from each of the 18 countries, plus all Australian cities.

Table 17.12 Most liveable city (2) Mercer ratings of 215 cities, higher = more liveable, with New York scored as 100, 2008 City Zurich Vienna Vancouver Auckland ¨ Dusseldorf Sydney Copenhagen Amsterdam Brussels Melbourne Stockholm Perth Oslo Dublin Honolulu Helsinki Adelaide Paris Brisbane Tokyo London Milan

Country

Global rank

Rating

Switzerland Austria Canada New Zealand Germany Australia Denmark Netherlands Belgium Australia Sweden Australia Norway Ireland United States Finland Australia France Australia Japan United Kingdom Italy

1 =2 4 5 6 10 11 13 14 =17 20 21 24 =25 28 =29 =29 =32 34 35 =38 41

108.0 107.9 107.6 107.3 107.2 106.3 106.2 105.7 105.4 104.8 104.5 104.3 103.7 103.5 103.1 103.0 103.0 102.9 102.4 102.2 101.6 100.8

Table includes top city from each of the 18 countries, plus all Australian cities.

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17.4 Most liveable cities he scoreboard syndrome – the wish to reduce social complexity and the quality of living to a single score – perhaps reaches its peak in the league tables of most liveable cities. Tables based on the two most widely cited ones – those compiled by the Economist Intelligence Unit (EIU) and Mercer Consulting – are given on the opposite page. The EIU ranked 140 cities, giving a score from 0 to 100 for most liveable. Mercer ranked 215 cities. Again a higher score indicates more liveable, but it assigns New York a score of 100, and then ranks others in relation to it. For the EIU, among the 10 most liveable cities, four are Australian, three Canadian, and four European, Vienna and Helsinki with Geneva and Zurich tied for equal ninth. Mercer has a rather different ranking, with Zurich first, marginally ahead of Geneva. It has three Swiss and three German cities in the top 10, plus Vienna, Vancouver, Auckland and Sydney. Both have several Canadian cities ahead of any American ones. Neither has a British or Italian city in their top 30, with London and Milan ranking top of their respective countries in both. Although there are differences among the cities included, as would be expected, both are consistent in the broad bands in which they place cities. So for the EIU, Harare is bottom, with Dhaka, Algiers, Port Moresby and Lagos just above. For Mercer, Baghdad ranks bottom. The cities at the top are closely grouped. For the EIU 19 cities fall within four points between 98.8 and 94.8, while for Mercer 23 cities fall between 108.0 and 104.2. So small changes in scoring or weighting can affect rankings considerably. Both methodologies involve taking a considerable range of criteria – the EIU 30 and Mercer 39, and assigning scores to them. Both consider aspects of personal safety from crime and political unrest, healthcare and sanitation considerations, the economic environment, aspects of residential, transport and commu-

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nications infrastructure, education, and then culture and entertainment. As in all composite indicators, many will find the weighting of factors arbitrary or problematic, but in this case the scoring of individual components is also problematic. The great bulk of the EIU’s 30 criteria involves judgements by their staff rather than objective measures. Nor is there any allowance that people may value different things, that one person’s idea of a climate being too humid may not be another’s. These two, and other such rankings, attract publicity when they are published, with local news media seizing on how their own city is faring. However, much of the publicity is based upon a false premise. Mercer explicitly says that its central purpose is ‘to judge whether an expatriate is entitled to a hardship allowance’. The EIU claims that its index has a broad range of uses from benchmarking perceptions of levels of development to assigning hardship allowances as part of expatriate relocation packages. It quantifies the challenges that might be presented to an individual’s lifestyle in a given location, such that with scores above 80, as are all cities in the table, there are few challenges. So no premium should be paid to expatriate employees in these cities. Both measures have some skew towards what is wanted by affluent expatriates (such as private schools and private health facilities) and towards the international connectivity of the cities. Some of these may be less relevant to native inhabitants. Nevertheless, trying to construct a single score for each city threatens to become an exercise in absurdity. Who would have guessed that Brisbane and Paris would be so close to each other on both tables? And which city would be the more insulted? It is a worthwhile exercise to be sensitive to the different elements that affect people’s quality of life in cities, even if the most common scoreboards have more entertainment than analytical value.


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Table 17.13 Globalisation (1) Foreign Policy /AT Kearney rankings of 72 countries, 2007 Globalisation Index Country

Table 17.14 Globalisation (2) The KOF Index of Globalisation 2009, score 0–100

Global rank

Netherlands Switzerland Ireland Denmark United States Canada Sweden United Kingdom Australia Austria Belgium New Zealand Norway Finland Germany France Japan Italy

3 4 5 6 7 8 11 12 13 14 15 16 17 18 22 25 28 34

Country

Score

Global rank

Belgium Austria Netherlands Switzerland Sweden Denmark Canada New Zealand Finland France Ireland Norway Germany Australia United Kingdom Italy United States Japan

91.51 91.02 89.92 89.87 88.68 87.37 86.32 84.55 84.19 83.68 83.09 82.27 81.75 80.49 79.31 78.80 74.93 63.54

1 2 3 4 6 7 8 12 13 16 12 21 22 26 27 28 38 70

Table 17.15 Globalisation (3) GlobalIndex score (Raab et al.), 2002, 1.00–6.00

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Country

Score

Global rank

Ireland Sweden Belgium Switzerland Denmark Netherlands Finland United Kingdom Austria United States Canada New Zealand France Germany Norway Australia Japan Italy

5.80 5.51 5.34 5.33 5.12 5.11 5.11 5.08 4.95 4.93 4.80 4.74 4.68 4.63 4.56 4.50 4.24 4.09

1 4 5 6 7 8 9 10 12 13 14 16 17 18 20 21 24 25


17.5 Globalisation lobalisation’ is a much-used but ill-defined term. Because people use it in so many ways to allude to so many different phenomena, attempts to measure it have gone off in different directions. Tables 17.13 to 17.15 offer three of the most prominent and analytically sound measures. Table 17.13 reports the original and most widely cited index of globalisation, one updated regularly by Foreign Policy magazine in conjunction with AT Kearney, consultants. Table 17.14, the KOF Index, has been conducted since 2002 by a group of scholars at the Swiss Federal Institute of Technology, led by Axel Dreher. Table 17.15, the GlobalIndex, was constructed by a group of German sociologists, working with the European Social Science Network. It runs only to 2002, but ambitiously has constructed data back to 1970 for 97 countries. All the indicators conceive of globalisation as multi-dimensional. The Foreign Policy index has four major dimensions, and each of the four has several sub-parts. Economic consists of trade and foreign investment, measured against GDP. Personal contact consists of telephone, travel and the transfer of personal remittances. Technological connectivity consists of internet users, internet hosts and secure servers. Political engagement consists of membership of international organisations, contributions to UN peacekeeping missions, international treaties ratified and government transfers. The KOF Index has three dimensions – economic, social and political. As well as looking at flows of trade and investment, it includes data on restrictions of various kinds. Social includes data on personal contact and travel, and information flows. Rather more problematically, the index score for ‘cultural proximity’ includes the numbers of McDonalds restaurants and Ikea furniture stores. Political globalisation includes the number of embassies in a country, the country’s membership in international organisations and ratification of international treaties. Similarly the GlobalIndex includes economic, technological, cultural and political

‘G

globalisation, with many additional indicators. The KOF Index is constructed to score up to 100 for high globalisation, while the GlobalIndex varies between 1 and 6, with a higher score indicating greater globalisation. While there are value and problems with each index, one disadvantage of the first is that it is a measure based solely on rankings. So it can give readings of countries relative to each other but it does not offer any sense of how much they are all increasing in globalisation. GlobalIndex has the longest run of data, and as might have been expected, it they found steadily increasing globalisation, but also that its extent varied between regions and continents. For all the countries as a whole, the average globalisation score rose from 2.38 to 3.30 – which on the restricted scoring scale is a substantial rise. Perhaps the most striking aspect of the three tables is the variation in their rankings. The positions of Australia and the United States, for example, vary a lot across the measures. For others there is some broad consistency. Japan and Italy score towards the bottom on all three. Several small European countries, with contiguous borders and membership of the European Union, such as the Netherlands, Denmark, Switzerland, Sweden and Ireland, tend to score highly on all measures. Globalisation is a misnomer to the extent that these countries interact a lot with a few neighbouring countries, rather than with all areas of the globe. For the sake of simplicity, only the latest year’s score and only the total index scores – rather than all the components of each – are given. But greater detail would decrease rather than increase confidence in the measures. Globalisation, by its nature, involves structural transformation, so the degree of globalisation in a country should not be jumping around from year to year, as they do. In the Foreign Policy index, no country ranks in the top 10 on all components and the rankings on sub-components vary even more. Severe doubt must be thrown on the internal coherence of a construct when the rankings vary so greatly and apparently randomly. THE SEARCH FOR SCOREBOARDS

239

Chapter 18 THE HOWARD IMPACT

How much difference did the Howard Government make to Australian society? The heat and hyperbole of partisan controversy and the passing parade of media excitements mean it is often difficult to get perspective on a government’s achievements and failures. Moreover, because of the credit and blame games that lie at the heart of party competition, the focus is usually introspective, looking first at domestic factors, and especially at party political factors. Such a focus greatly exaggerates a government’s power to influence social and economic developments, but to say a government has more limited power than political debates suggest is not to say that it has no power. The Howard Government was in power for more than 11 years, a sufficient period for its policies to have a cumulative impact on the distribution of public resources and social practices. But equally over that time, social and economic changes, over which the government had little influence, were also occurring. And of course, many important features of Australian society continued with little change. This chapter is guided by two central aspirations. The first is that by examining statistical trends systematically, a more reliable picture of policy developments will emerge. The second is that by examining Australian developments compared with those in other advanced democracies, more perspective on policies, performance and wider social influences can be gained. When people make political judgements, they normally do not employ a comparative perspective. They gauge government performance by referring to their own circumstances, and how these have changed from the recent past. An example of how a comparative view qualifies a solely domestic one would be the economic record of the Menzies Government and its immediate successors. Viewed domestically (compared with the years of depression, war and immediate post-war stringency which preceded it, and compared with the higher inflation and unemployment which followed it), the period 1950–1973 stands as an oasis of 240


growing and relatively problem-free prosperity in Australia. When viewed comparatively, a different and equally valid perspective emerges. As Table 18.1 shows, Australia’s record of economic growth, measured as GDP growth per capita, was mediocre. Among the selected countries, Australia’s growth rate was second lowest, ahead only of New Zealand, and only around two-thirds of the mean of the other countries. What can and can’t statistics reveal? Many aspects of politics involve issues of morality or principle which statistics cannot resolve. No statistics can ever decide the rightness or wrongness of the Iraq War (although statistics can highlight some of the costs of the war, both financial and human). Statistics will not resolve issues surrounding the government’s behaviour in the children overboard incident during the 2001 election campaign. In many areas, however, statistics can show the success or failure of policies. Governments cannot simply stop fatalities from road accidents, for example, but a series of policy measures over the decades has dramatically reduced the road toll. As we saw in Table 16.17, the number of deaths from traffic accidents in Australia dropped from 32.8 to 8.4 per 100 000 population between 1970 and 2003. The problem is not solved, but the reduction is a great public policy success, one that only statistics can reveal. However, even in areas where statistics would be a valid and enlightening tool, they are not always available. This is, unfortunately, especially the case with comparative data. International statistics are slow to be published. Even now, especially in non-economic areas, we do not have data going all the way to the end of the Howard Government in 2007. Nevertheless, looking at statistics that run to 2005 still gives a good indication of the main thrust of government policies and their impact. (In some areas, while we have good recent statistics, there is not a long run of international data allowing us to go back and look at the performance of earlier governments.)

Table 18.1 Economic growth, 1950–1973 Average annual GDP per capita growth rates, 1950–1973, % Country

%

Japan Germany Italy Austria Finland France Belgium Netherlands Norway Denmark Switzerland Sweden Ireland Canada United States United Kingdom Australia New Zealand

8.05 5.02 4.95 4.94 4.25 4.05 3.55 3.45 3.19 3.08 3.08 3.07 3.04 2.74 2.45 2.44 2.34 1.72

Mean

3.63

Figure 18.1 Economic growth Mean per capita GDP growth rates (% per annum) during period of each government 3.5 3 2.5 2 1.5 1 0.5 0 McMahon Whitlam Fraser Hawke Keating Howard Howard 1971–1972 1973–1975 1976–1982 1983–1991 1992–1995 1996–2000 2001–2006 Australia

D18 mean

∗

D18 refers to the 18 democracies, the selected countries with which Australia is compared throughout the book.

Figure 18.2 Unemployment Mean standardised unemployment rates (% of labour force) during period of each government 12 10 8 6 4 2 0 McMahon 1970–1972

Whitlam 1973–1975

Fraser 1976–1982

Hawke Keating 1983–1991 1992–1995

Australia

Howard 1996–2002

Howard 2002–2006

D18 mean

THE HOWARD IMPACT

241

Presenting comparative statistics can anchor and discipline arguments, but they certainly won’t end debate. They will never give finality about causality and governments’ relative contribution to developments. The attribution of causes is always politically charged. Governments typically claim credit for popular developments, and seek to deflect blame for unpopular ones, while oppositions typically seek to accentuate the negative and to promote a single cause for it, arguing that there is a simple solution for whatever problems are present, namely to change the government. Typically in real life, we are dealing with partial and multiple causes, a complexity that does not fit easily into the inflated claims of partisan debate or the moral simplicity of partisan attachments. Comparative data can be enlightening in evaluating relative performance, but comparison is fraught with difficulties. These 17 other advanced liberal democracies are the countries with which it is most enlightening to compare Australia, but each is unique, with its own opportunities and challenges, its own history and geography. Australia occupies a different place in the world from the European countries, for example, with a distinctive pattern of exports, energy use, etc. Moreover, many policies have lead times and lag effects. The strengths and weaknesses of policies are not always manifest during a government’s own term of office. Central to the political credentials of the Howard Government, and, since it left office, to the way its supporters want it remembered, is its claim to have been a successful economic manager. The figures both historically and comparatively give some, but not unqualified, support to this view. Figure 18.1 shows Australia’s per capita economic growth rate moving somewhat but far from perfectly in alignment with the mean of the selected countries. The graph gives little comfort to anyone wanting to draw partisan conclusions. It shows that until 1991, the end of the Hawke Government, Australia had a growth rate rather less than the mean, but 242


then under Keating and Howard it grew more quickly than the mean. The highest rates of growth were between 1992 and 2000, with both the countries as a whole and Australia having a somewhat lower growth rate between 2001 and 2006. Political leaders’ terms do not fit neatly with the economy’s inescapable tendency to move through cycles of boom and bust. One reason for the Fraser Government’s comparatively poor performance is that it bore the brunt of Whitlam’s economic miscalculations, and Hawke’s record was rendered unimpressive by the aftermath of Fraser’s recession of the early 1980s and by his own recession of the early 1990s, whereas Keating and Howard benefited from the economy’s unusually long expansion phase during the rest of the 1990s and the early 2000s. It is also widely agreed among economists that both leaders benefited from a delayed pay-off from the many economic reforms undertaken by the Hawke Government. Figure 18.2 charts a dismal history of progressively worsening unemployment from the mid-1970s to the mid-1990s, and then with the absence of a severe recession, improvement under Howard, at first modest and then considerable. It again shows a tendency for Australia to move in tandem with the other economies, but while at first Australia had a lower unemployment rate than the selected countries as a whole, from the Fraser period on, it was somewhat higher, until the very last period under the Howard Government when it was again less than the mean. The process of averaging the unemployment rates within each leader’s term flatters Whitlam (the long-term deterioration began towards the end of his watch) but maligns Hawke, who made rapid progress in reducing the 10% unemployment rate inherited from Fraser, but then presided over his own recession, which caused the rate to reach a new cyclical peak of 11% early in Keating’s term. The improvement under Howard was considerably better than in the selected countries as a whole.

Figure 18.3 Inflation Mean inflation rates (CPI average annual % change) during period of each government

14 12 10 8 6 4 2 0 McMahon Whitlam Fraser Hawke 1971–1972 1973–1975 1976–1982 1983–1991 Australia

Figure 18.4 Long-term interest rates Average long-term interest rates as a % per annum in each period

D18 mean

12 10 8 6 4 2 0 1990–1995

1996–2000

Australia

Figure 18.5 Taxation Total tax revenue as a % of GDP

Keating Howard 1992–1995 1996–2007

2001–2006

D18 Mean

45 40 35 30 25 20 15 10 5 0 1972

1975

1983

Australia

1991

1996

2005

D18 Mean

THE HOWARD IMPACT

243

It was a proud claim of the Howard Government that it had kept interest rates low, at record lows said one advertisement in the 2004 election. Interest rates move in relation to inflation. Figure 18.3 shows that at the end of the long post-war boom, under McMahon, inflationary pressures were already considerable. Then came a terrible blow-out under Whitlam, only modest improvement under Fraser and Hawke, but a return to low inflation under Keating and Howard. The 18-nation mean exhibits a very similar pattern. The notable exception was Hawke’s term. The return to low inflation began in the 1980s for most of the developed economies, but in Australia it was delayed until the 1990s while Hawke concentrated on using his accord with the union movement to lower real wages and thereby increase employment. Since the 1990–1991 recession, Australia has returned to low inflation. Australian economists tend to attribute this continuing success to the side-effects of economic reform which, by heightening the degree of competition in the markets for many products, reduced the scope for excessive wage settlements (‘sweetheart deals’) and consequent excessive price rises. But this raises the old question: how does this purely domestic argument explain the very low inflation rates in the other developed economies? Inflation under Howard was lower than under any other Australian government except for Keating’s. However, Howard’s term coincided with the selected countries as a whole having their lowest period of inflation since 1970. The Australian rate was still considerably higher than the mean, although some domestic reasons contributed to this, such as the one-off impact following the introduction of the GST, and later the fall-out from the resources boom. Although we do not have such a long run of data on interest rates, Figure 18.4 tells the same story as the inflation figures. Australian rates have moved in the same pattern as the countries as a whole, but always at a higher rate. Indeed while the Australian long-term interest rate was 1.3 points above the mean in the 244


five years preceding Howard, it was also 1.3 points above the mean in its last five years. As Table 3.7 showed, during the Howard years Australia consistently had the second-highest interest rates among the selected countries, with only New Zealand having a worse rate. So while Howard’s claims may appear impressive in relation to earlier periods in Australia, comparatively his was among the highest interest rate regimes in the selected countries. The previous figures together provide ample proof that governments are far from being masters of the economic destinies of their nations. Indeed, the way trends move in common shows how international influences help to set the economic conditions governments must deal with. One area where governments have more direct control over policies is in their own budgeting, in the patterns of taxing and spending that they follow. The differences among the selected countries are considerable, but their relative rankings show great constancy over time. Figure 18.5 shows the total taxation levels in relation to GDP in each of the years when Australia had a change of government, although the latest is 2005. It presents the percentage in the selected countries gradually creeping up, although the change since 1991 has been less than 1%, from 37.5 to 38.3. Australia exhibits a similar trend. Throughout the period, Australia falls towards the low end in terms of taxation. It began 9.6 percentage points below the mean, and finished 7.4 points below. The only time it grew much more quickly than the countries as a whole was the leap during the Whitlam period. Under Howard, taxation as a share of GDP grew more than in the selected countries as a whole – up 1.5 points compared with 0.1. However, Australia was starting from a lower base, and remained at the low end of the selected countries, ranked 14th in Table 5.2, with eight countries having taxation shares 10 percentage points higher than Australia’s. Not surprisingly, government spending shows a similar trend to taxation. Figure 8.6 shows a sharply increasing share of national

Figure 18.6 Government spending Total government expenditures as a % of GDP, average for each period

60 50 40 30 20 10 0 1960–1973 1974–1979 1980–1989 1990–1999 2000–2006 Australia

Figure 18.7 Budget surpluses and deficits Central government net borrowing or lending as a % of GDP

D18 Mean

3 2 1 0 −1 −2 −3 −4 1990

1995 Australia

Figure 18.8 Government debt General government gross financial liabilities as a % of GDP

2000

2006

D18 Mean

80 70 60 50 40 30 20 10 0 1990

1995 Australia

2001

2006

D18 Mean

THE HOWARD IMPACT

245

income was devoted to government spending in every decade between the 1960s and 1980s. From the 1990s, that growth stopped and in the first years of the 2000s it declined. Australia was again substantially below the mean of the selected countries, by around nine percentage points in the first period and a similar amount in the last. The common factor underlying the fall in government outlays was the long economic expansion. Rapidly rising incomes make it easier for the government share to decrease. In addition, many countries, often facing tax revolts among sections of their publics and increasing attention to the effectiveness or lack thereof of government programs, have adopted more stringent attitudes towards public spending. In the early 2000s, as we saw in Table 5.1, only two countries – not coincidentally two of the slowest growing countries, Japan and Switzerland – increased government outlays as a percentage of GDP. While the Howard Government decreased spending in relation to GDP in this period, it actually did so by somewhat less than the average. A comparison of Figures 18.5 and 18.6 shows that government spending decreased more than taxation. This is partly because economic management and budget trends generally tend to produce government surpluses during times of fast economic growth. The data in Figure 18.7 demonstrates this. In the first two years, 1990 and 1995, both the selected countries as a whole and Australia had budget deficits. In the latter two years, 2000 and 2006, both the selected countries as a whole and Australia had budget surpluses. The figures show a remarkable symmetry. In three of the four years, the Australian figure and the mean of the selected countries were the same. The primary explanation for the budget surpluses in Figure 18.7 lies in automatic responses to the business cycle. A secondary explanation for some of the countries is the need to address government debt. Figure 18.8 shows general government debt in relation to GDP. Among the years given, it reached its peak in 1995 for both the selected countries 246


and Australia. Australia was always below the mean of the selected countries. It never had the very high, potentially disastrous debt levels that Belgium and Italy did, where government debt was more than 100% of GDP. However, it also reduced its debt much more sharply under Howard than did the selected countries as a whole, so that by 2006 it was only around a quarter of the mean of the others and had the lowest debt percentage among all the selected countries. Government economic management is also concerned with building future economic performance, and in influencing trends over which it has only very partial control. A basis for building future prosperity is increasing productivity. Figure 18.9 shows that Australia’s performance in increasing multi-factor productivity since 1991 has been better than the selected countries as a whole in each of the three periods, with both increasing fastest in the late 1990s. Other indicators are less propitious. Figure 18.10 shows that the trend in Australia’s current account deficit is worse than for the selected countries overall. Except for 1974–1979, the mean for the other selected countries was to have a surplus on their current account. After 1973, Australia was always in deficit. The biggest period of this deficit was in the 1980s, a period when the Australian dollar went down sharply in value. The situation improved somewhat in the 1990s. However, in the early 2000s, while the current account in the other selected countries continued into a larger surplus, the Australian current account went into a larger deficit. By 2005, it was considerably greater than when Howard came to office. This deterioration is the more remarkable because it occurred when Australia’s terms of trade were the best they had been for a generation. The rising prices of minerals, especially fuelled by growth in demand from China, would normally lead one to expect that Australia’s balance of trade would improve rather than worsen. The comparison with the selected countries is misleading however in the sense that unlike

Figure 18.9 Multi-factor productivity increases Average annual increase % for each period

2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0 1991–1995

1996–2000 Australia

2001–2004

D18 Mean

Figure 18.10 Current account balance Current account balance as a % of GDP, mean for each period

3 0.8

1 0

2.2

1.6

2 0.5

0.0

0.0

−0.3

−1 −2 −3

−2.6

−4

−4.1

−5

−4.0 −4.6

−4.9

−6 1970–1973

1974–1979

1980–1989 Australia

1990–1995

1996–2000

2001–2006

D18 Mean

THE HOWARD IMPACT

247

most of them, Australia has always been a capital importing country. While Australia through almost all its history has had a current account deficit – because of its need to import capital to fund development – this has been paid for in the long term by continuing economic growth. However, the large current account deficit does mean that Australia entered the global financial crisis which began in 2008 in a more vulnerable state than many of the commentaries about its advantages would lead one to believe. Another set of balance sheets deteriorated during the Howard years, one whose future economic consequences are also a matter of conjecture. Figure 18.11 shows that Australian household debt in relation to disposable income has grown considerably over the years. Indeed, it almost doubled during the Howard years. Some other countries have even higher levels of household indebtedness, but Australia is considerably above the mean. Thus while at the macro level, in terms of economic growth, Australia’s performance during the Howard years was strong, at the micro level, many households experienced increased financial stress. A central reason for increased household indebtedness is the increasing price of housing. Table 18.2, from the Economist, gives that magazine’s index of housing prices. Australia experienced one of the sharpest rises, so mortgages in relation to income grew prodigiously during the Howard years (Table 15.4). It would be wrong to extrapolate from this into forecasting a spate of bankruptcies, but it has ramifications on many levels. Home loan interest payments were higher than when housing interest rates peaked at 17% in 1989. The rate of home ownership of those under the age of 35 dropped. Again this suggests increased financial stress for many people, despite the relatively good economic growth. In all these phenomena – trade and current account balances, household indebtedness and house prices – we are dealing with the behaviour of markets, with decisions by individuals and companies, over which the 248


government has limited influence. The Howard Government did not directly or deliberately decide to increase the current account deficit or household debt. How should we evaluate its performance and responsibility in these areas? In 1996, the Liberal Opposition was in no doubt that the current account deficit was Labor’s fault. Part of its campaign was to drive a ‘debt truck’ around with big billboards highlighting that Australia owed $193 billion. By the time of Howard’s 2007 defeat, that figure had grown to $544 billion. Similarly, at first the Howard Government thought that rising home prices was good news: ‘I haven’t found anybody stopping me in the streets, shaking their fists and saying “John, I’m angry that the value of my house has gone up”,’ said Howard in the first years of the housing boom, a tone that would change later as housing affordability became a vexed political issue. While the government’s early attitude was blasé, and while some of its measures, such as cutting capital gains tax, could be said to have exacerbated the problem, the key factors driving the boom in house prices were not due to the government. They arose because of a combination of unmet demand, increasing aspirations for better houses among those who already owned one, low interest rates and the relatively easy availability of money from lending institutions. Even a government determined to restrain the increasing prices would have had limited capacity to do so. Apart from the many reasons already given for why comparative statistical data cannot end debate on the relative performance and virtues of governments, another is that there is rarely a consensus on values, about the relative priorities of different social goals, about what we should and should not expect from governments. Such differences relate to what different people think is best done by government and what best done by businesses and individuals. They also relate to what areas of social life governments should accept responsibility for – insofar as these are decided by principle rather than immediate expedience and convenience. The answer to this last question is not

Table 18.2 The Economist ’s house-price indicators Percentage change 1997–2008 Country

%

Ireland United Kingdom Australia France Sweden Belgium Denmark New Zealand Italy Netherlands United States Canada Switzerland Japan

210 179 173 149 149 147 123 117 107 105 86 70 21 −32

No data on Austria, Germany, Finland or Norway.

Figure 18.11 Household debt Household debt as a % of household disposable income 180 160 140 120 100 80 60 40 20 0 1982 1992 2002

Australia

2007

D18 Mean

THE HOWARD IMPACT

249

static however. The political agenda grows and changes as new challenges emerge, and public expectations of government change. One theme under the Howard Government was changing the balance between public and private. There was an increased emphasis on private delivery of what had previously been public services, often with the introduction of a public subsidy, delivered, for example, by tax rebates. This was very much the case in health, child care and aged care – in each case with vigorous public debates about the merits and weaknesses of the policy direction. Unfortunately, in none of those cases are the international statistics sufficiently penetrating or discriminating to illuminate the discussions. However, in education, the comparative statistics are quite revealing of the divergent policy approaches. Figure 18.12 shows the public share of total education spending Australia was already at the low end of the spectrum in 1995, before the Howard Government came to power. But it became even more so in the following 10 years, making the private share of education spending third-highest among the selected countries and the public share 12 points below their mean. Much of this was to do with the growth in private schools during the Howard era, and that points to another of its distinctive features, the public subsidy of private providers. As we saw in Table 7.10, 20.3% of Australian public spending on education goes to private institutions, almost double the overall mean of 10.5%, a particularly high figure when it is remembered that private universities have a negligible presence in Australia. Of the 16 countries on which we have data, only Belgium is higher and that goes back to historical arrangements between church and state in that country. The data on universities is even more dramatic than for education as a whole. Figure 18.13 shows again on this measure that in 1995 Australia was already at the lower end of the countries in terms of the public share of tertiary education spending, 13 points below the mean. After another decade though, the public 250


share had dropped to less than half, 48%, and Australia was then 26 points below the mean. This reflected an increased emphasis on private funding, but also, uniquely among these developed democracies, a reduction in real terms in public spending on tertiary education. In 2005, according to Table 18.3, Australia spent 0.8% of GDP compared with a mean of 1.1%. In other words, Australian expenditure would have had to increase by around 35% to bring it up to average. The second column shows that for the other countries on which we have data, their public spending on tertiary education was up by 30% in real terms over the decade 1995–2005. Only Australia’s decreased. Investing public money in universities can be seen as part of a government building the country’s future capacity. As was reported in Table 11.1, the OECD has constructed a composite measure which it calls ‘investment in knowledge’, which includes R&D software as well as tertiary education. It is a measure of private sector as well as public sector activity. Figure 18.14 shows that as the Howard Government came to power, Australia was slightly below average on this measure, but because it grew more slowly in the next six years, it had fallen further below the mean in 2004, the latest year for which we have data. A central part of the information economy is in telecommunications and computing, especially the development of broadband. Figure 18.14 shows that Australians are relatively big spenders on telecommunications and became sharply more so in the first five years of the 21st century. In 2000, the revenue generated per person by telecommunications was just above the 18-nation mean, but by 2005 Australia ranked third highest, and was around $US200 per person per year above the mean. As we saw in Figure 12.1, Australian telecommunications were comparatively expensive for the consumer. The cost of what the OECD thought was a representative basket of charges for a small office/home office was more than 50% higher than the mean for the countries overall, $US933 compared with

Table 18.3 Public expenditure on tertiary education Country Australia D18 Mean

Public tertiary (% of GDP, 2005)

Index of change 1995–2004 (1995 = 100)

0.8 1.1

96 130

Figure 18.12 Public share of education expenditure Public expenditure as a % of total education expenditure

100 80 60 40 20 0 1995

2005

Australia

Figure 18.13 Public share of tertiary education expenditure Percentage of tertiary education spending provided by government

90 80 70 60 50 40 30 20 10 0 1995

2005

Australia

Figure 18.14 Investment in knowledge Investment in knowledge as a % of GDP

D18 Mean

D18 Mean

4.4 4.2 4.0 3.8 3.6 3.4 3.2 1997

2004

Australia

D18 Mean

THE HOWARD IMPACT

251

$US562 in 2006. But it was far from clear that Australians were receiving better services for these greater costs. In particular, the provision of broadband infrastructure lagged behind the other countries. In December 2005, when 62% of internet connections in the countries overall were through broadband, only 40% were in Australia. As we also saw in chapter 12, an average representative broadband speed in the selected countries in 2007 was 14 957 Kbit/s, more than eight times faster than Australia’s 1536. Yet despite the slower speeds – and the more restrictive caps on downloads – Australians had the second most expensive average monthly broadband subscriptions in the selected countries. At $US52.26, it was almost $US11 more expensive than the 18nation mean. In the long run, the quality of Australian services may catch up and their relative prices may drop, but it is clear that during the Howard Government period, Australian telecommunication consumers were worse off than their counterparts in most of the other selected countries. How will the Howard Government be viewed in 10 or 20 years’ time? The partisan lines are already forming. According to the coalition, it had a record of good economic management which delivered growth and left the economy in good shape, which Rudd destroyed within years of taking office. According to its critics, the Howard Government squandered the boom. It was lucky to reign during good times, but it did not use that good fortune to build for the future. On several central measures of macroeconomic performance (economic growth, unemployment, productivity) the Howard Government scored comparatively well. On some of the achievements trumpeted most loudly at home, such as inflation and interest rates, its performance was actually worse than the average of the selected countries. The global financial crisis which started in 2008 and its continuing ramifications dramatised the very different economic environments governments face at different times. While a central expectation of the electorate is that the 252


government will be a good economic manager, governments’ control over economic developments is much more limited than political rhetoric would suggest. No government can stop the boom-and-bust cycles that economies generate, and when one is comparing the relative softness of landings or the soundness of the limited counter-cyclical measures governments can deploy, it is unlikely that comparative data will ever, by itself, provide unanimously accepted conclusions. Members of the former Howard Government claimed that they had left Australia better able to cope with the global financial crisis. This was true in terms of the low levels of public debt and the soundness of the banking system, but in other areas, such as the large current account deficit and household debt, Australia had become more vulnerable, although views will differ on the extent to which the government should be held responsible for these. Broadly in line with the government’s electoral appeals, it kept taxation and government spending comparatively low, although during this period of relative economic expansion, many other governments did this at least as well. On all these measures, an unqualifiedly positive evaluation can only be made if one judges that in achieving them the government did not fail to undertake essential tasks. A failure to invest sufficiently in infrastructure, for example, will make the current balance sheet look good, but cost future generations considerably more. Nor are public expectations of governments necessarily constant or consistent. Australians sometimes seem to want Swedish levels of public services with Hong Kong levels of taxation. A change of government brings a sea change in political atmospherics. These atmospherics have their own importance. They give legitimacy to some demands and devalue others. They elevate the status of some groups at the expense of others. But it should not be assumed that tangible consequences follow. The Howard Government talked about family values, but that had no impact on the divorce rate rising substantially during its term. On the

other hand, its moves on gun control had a lasting impact, contributing to Australia becoming a safer society. Whichever party is in government, many of the fundamentals of Australian society continue. It remains a stable democracy with low levels of corruption. It has an educated labour force, with good education and health systems, an independent and well-functioning judiciary, and many resilient aspects of Australian society irrespective of party politics. Conversely some trends and challenges continue whatever the election results. For example, in terms of health, progress towards greater longevity continued during the Howard era as it had under earlier governments. Partly as a consequence, the demands on the health system continue to grow. As a share of GDP total health spending increased at roughly the rate of the selected countries overall, as did public spending on health. In both areas, however, Australia continued to be in the bottom half of spenders, and on public spending ranked second last, as we saw in Table 6.3. In terms of resource allocation, on the international health statistics, one cannot easily distinguish the Howard Government from its predecessors (or in all probability its successors). Whether it increased the effectiveness of that spending requires a qualitative judgement. Health will continue to be an important policy challenge in its own right, but it is also one part of the policy challenges associated with the ageing society. The government talked considerably about this, and it took some financial measures to meet it. It also, in line with its electoral strategy, increased various benefits to older groups which will become increasingly expensive for future governments to maintain. However, in some ways its performance in this area could be criticised by looking at the other end of the life cycle. A key to effectively dealing with the ageing society is to increase labour force participation, and in particular to make it easier for mothers to combine having children with working. The government’s policies moved only tepidly towards marrying

the demands of contemporary pressures and aspirations with parenthood. While the number of children attending child care increased over the decade, as we saw in Table 14.16, Australia had the fifth most expensive child care system for parents, taking 22% of weekly earnings compared with an overall mean of 17%. Moreover as psychologists and others increasingly stressed the importance of early childhood development, Australia still spent only half the average of the selected countries on pre-primary education in relation to GDP – 0.2% compared with 0.4%. Another area where the political agenda grew and changed during the Howard Government’s term was environmental issues, and in particular the issue of global warming, and actions to address it gained political urgency. Before the 2007 election, the then-Environment Minister Malcolm Turnbull proclaimed that Australia led the world on climate change. As we saw in Table 10.7, on a per capita basis Australia in 2005 was still the highest emitter of greenhouse gases among the selected countries, fractionally less than double the mean, and more than three times greater than the best performing countries. Moreover, in terms of meeting its Kyoto target, the greatest progress was made because of the reduction in land clearing in Queensland after the abnormally high levels of 1990, the baseline year for measuring progress. So the most substantial progress Australia made towards meeting its Kyoto targets was before the protocol was agreed and, indeed, before the Howard Government came to office. In a decade or two’s time, what criteria will loom largest for those retrospectively judging the Howard Government’s performance? As with all governments, economic management and foreign policy decisions will be central. In addition, we suggest the ageing society, health care, the challenges of the information economy and society, and the environment will be central concerns. In each of these areas, the government is likely to be marked more harshly in the future than it was when in office.

THE HOWARD IMPACT

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SOURCES AND REFERENCES he OECD is the most common source for the tables used in this book. All OECD publications are published by it in Paris, so apart from the year publication details are not given. In addition, some data is available from the OECD website: www.oecd.org and from www.OECD.Stat. A very convenient way to access OECD publications and databases is via a subscription, such as that held by the Fisher Library, University of Sydney, to SourceOECD.

T

1 People Table 1.1: United Nations Population Division, The World at Six Billion; see also US Census Bureau Total Midyear Population for the World: 1950–2050 at: www.census.gov/ ipc/www/idb/worldpop.html Table 1.2: US Census Bureau International Database at: www.census.gov/cgi-bin/ ipc/ idbrank.pl The Australian figure was slightly smaller than that given by the ABS, so we have included the latter. Text also draws on Alberto Alesina and Enrico Spolace, The Size of Nations (Cambridge, Mass., MIT Press, 2005). Table 1.3: 1990 figures are from B.R. Mitchell, International Historical Statistics. Africa, Asia and Oceania 1750–1993 (3rd ed, NY, Stockton Press, 1998) and the United Nations Statistical Yearbook 1955 (UN, NY, 1957). Figures for 1950 and 2000 from the US Census Bureau International Data Base at: www.census.gov/ cgi-bin/ipc Note: In 1900, Austria was still part of the Austro-Hungarian empire and Ireland was united as a British colony. The table gives estimates for the 1900 population of the territories comprising the contemporary nation states. Similarly, in 1950, Germany was divided into East and West, but the table figure is for a united Germany. Table 1.4: Area is from OECD in Figures 2000 edition; population density is from OECD Factbook 2007. Table 1.5: Calculated from the US Census Bureau International Data Base at: www. census.gov/cgi-bin/ipc

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SOURCES AND REFERENCES

Text also draws on Doug Cocks, People Policy. Australia’s Population Choices (University of New South Wales Press, 1996). Table 1.6: 1900 figures are from the United Nations Statistical Yearbook 1955 (UN, NY, 1957). (For the Netherlands, the figure is for 1910.) Figures for 1950 are from the United Nations World Population Prospects. The 1996 Revision (UN, NY, 1996) Table A26, pp. 318ff. Figures for 2000 from the US Census Bureau International Data Base at: www.census.gov/cgi-bin/ipc Figures 1.1 and 1.2: OECD Factbook 2007. Text also draws on Robert William Fogel, The Escape from Hunger and Premature Death, 1700–2100. Europe, America and the Third World (Cambridge University Press, 2004); Graeme Hugo, A Century of Population Change in Australia (Year Book Australia, 2001) at: www.abs.gov.au/ausstats; OECD Health at a Glance (Paris, 2002); Australian Bureau of Statistics, The Health and Welfare of Australia’s Aboriginal and Torres Strait Islander Peoples, 2008 at: www.abs.gov.au Table 1.7: 1900 and 1950 data are from Jean-Claude Chesnais, The Demographic Transition. Stages, Patterns and Economic Implications. A Longitudinal Study of SixtySeven Countries Covering the Period 1720– 1984 (Oxford University Press, 1992). More recent figures are from the OECD database at: www.OECD.Stat. Tables 1.8 and 1.9: OECD in Figures 2007. Tables 1.10 to 1.13: OECD A Profile of Immigrant Populations in the Twenty-First Century. Data from OECD Countries (Paris, OECD,

2008); OECD International Migration Outlook SOPEMI 2007; and OECD Database on Immigrants in OECD countries (DIOC) at: www.OECD.Stat Text also draws on ABS Australian Social Trends 2007 ‘Migration: Permanent Additions to Australia’s Population’ at: www. abs.gov.au?AUSSTATS/abs@nsf/Latestproducts/928AF7A0CBF969FC; United Nations, World Migration 2005 Chapter 23 International Migration Trends; and on Australian Chamber of Commerce and Industry ‘Why Do One Million Australians Live Overseas?’ ACCI Review, December 2004. Tables 1.14 and 1.15: OECD. International Migration Outlook: SOPEMI 2006 edition, p. 54.

Tables 1.22 to 1.24: United Nations High Commissioner for Refugees, Refugees and Others of Concern to UNHCR 1999 Statistical Overview (Geneva, July 2000) at: http://www.unhcr.ch, Table I.2. Later data from UNHCR, Asylum Level and Trends in Industrialized Countries, 2007 (Geneva, 18 March 2008), plus OECD International Migration Outlook: SOPEMI 2006 edition and OECD International Migration Outlook: SOPEMI 2007 edition. Text also draws on Kazimierz Bem et al. ‘A Price Too High: The Cost of Australia’s Approach to Asylum Seekers’ (August 2007, A Just Australia and Oxfam Australia).

Table 1.17: OECD Factbook 2007.

Tables 1.25 and 1.26: United Nations Department of Economic and Social Affairs/Population Division, World Urbanisation Prospects: The 2005 Revision, pp. 31–5; pp. 130–42 at: www.un.org/esa/population/publications/ WUP2005/2005wup.htm

Tables 1.18 to 1.21: UNHCR, The UNHCR 2007 Statistical Yearbook 2006 at: www.unhcr. org/statistics/STATISTICS/478cda572.html and UNHCR 2007 Global Report UNHCR Statistical Online Database UNHCR at: www. unhcr.org/statistics/populationdatabase

Table 1.27: D. B. Barrett (ed) World Christian Encylopaedia (Oxford University Press, 1982). Reproduced in Jan-Erik Lane, David McKay and Kenneth Newton, Political Data Handbook: OECD Countries (Oxford University Press, 1991) p. 21.

Table 1.16: OECD PISA 2006: Science Competencies for Tomorrow’s World Vol 1 and Vol 2: Data (2007).

2 Government and politics Table 2.1: The dates for the beginning of continuous elections come from Robert Dahl, Polyarchy: Participation and Opposition (Yale University Press, 1971 pp. 42, 249). The table does not include interruptions due to external occupation, e.g. some European countries during the Nazi occupation in World War II. The dates for independence and current constitution come from Jan-Erik Lane, David McKay and Kenneth Newton, Political Data Handbook. OECD Countries (Oxford University Press, 1991 p. 112.) Arend Lijphart, Democracies: Patterns of Majoritarian and Consensus Government in

Twenty-One Countries (New Haven, Yale University Press, 1984). Tables 2.2 and 2.3: Jan-Erik Lane, David McKay and Kenneth Newton, Political Data Handbook. OECD Countries (Oxford University Press, 1991) p. 111, and Inter-Parliamentary Union at: www.ipu.org. Table 2.4: Arend Lijphart, Democracies: Patterns of Majoritarian and Consensus Government in Twenty-One Countries (New Haven, Yale University Press, 1984); Jaap Woldendorp, Hans Keman and Ian Budge, Party Government in 48 Democracies (1945–1998).


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Composition – Duration – Personnel (Dordrecht, Kluwer Academic Publishers, 2000); and national sources. Table 2.5: Arend Lijphart, Democracies: Patterns of Majoritarian and Consensus Government in Twenty-One Countries (New Haven, Yale University Press, 1984) and CIA World Fact Book. Table 2.6: OECD Revenue Statistics 1965– 2000 (Paris 2001) and OECD Revenue Statistics 1965–2006 (Paris 2007). The OECD figures for Central Government’s tax share excludes social security on the grounds that ‘Social security funds may be distinguished by the fact that they are separately organised from the other activities of government units and hold their assets and liabilities separately from the latter. They are separate institutional units.’ OECD Revenue Statistics 1965–2000, p. 277. On the other hand, social security in all other ways looks just like a central government tax, and we have included it that way in the table. The Australian figure is from Australian Bureau of Statistics, Taxation Revenue 2006– 07 (Canberra, 2008). Text also draws upon Tim Colebatch, ‘It’s a Federal Election, on State Issues’ The Age 20 November 2007. Table 2.7: Arend Lijphart, Democracies: Patterns of Majoritarian and Consensus Government in Twenty-One Countries (New Haven, Yale University Press, 1984). Other information drawn from George Tsebelis and Jeanette Money, Bi-Cameralism (Cambridge University Press, 1997). Table 2.8: Jaap Woldendorp, Hans Keman and Ian Budge, Party Government in 48 Democracies (1945–1998). Composition – Duration – Personnel (Dordrecht, Kluwer Academic Publishers, 2000). Final column from G. Bingham Powell, Jr., Elections as Instruments of Democracy. Majoritarian and Proportional Visions (Yale University Press, New Haven, 2000) pp. 34, 39.

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Table 2.9: Lawrence Le Duc, Richard G. Niemi and Pippa Norris, ‘Introduction: The Present and Future of Democratic Elections’ in Lawrence Le Duc, Richard G Niemi and Pippa Norris (eds), Comparing Democracies. Elections and Voting in Global Perspective (London, Sage Publications, 1996) pp. 13–15. The Index of Disproportionality comes from Arend Lijphart, Patterns of Democracy. Government Forms and Performance in Thirty-Six Countries (New Haven, Yale University Press, 1999) pp. 157–89, 313. Table 2.10: Lawrence Le Duc, Richard G Niemi and Pippa Norris, ‘Introduction: The Present and Future of Democratic Elections’ in Lawrence Le Duc, Richard G Niemi and Pippa Norris (eds), Comparing Democracies. Elections and Voting in Global Perspective (London, Sage Publications, 1996) pp. 13–15. The number of elections is compiled from several sources, including the IDEA website at: www.idea.int/vt/country_view.cfm and www.electionworld.org, plus Thomas T. Mackie and Richard Rose, The International Almanac of Electoral History (3rd ed., Macmillan, London, 1991). The text also draws on Gerard Newman and Scott Bennett Electoral Systems (Parliament of Australia, Parliamentary Library, 2006) and Malcolm Mackerras (personal communication). Table 2.11: Arend Lijphart, Patterns of Democracy. Government Forms and Performance in Thirty-Six Countries (New Haven, Yale University Press, 1999) p. 312. Table 2.12: G. Bingham Powell, Jr., Elections as Instruments of Democracy. Majoritarian and Proportional Visions (Yale University Press, New Haven, 2000) pp. 74, 78. Table 2.13: Adapted from Jaap Woldendorp, Hans Keman and Ian Budge, Party Government in 48 Democracies (1945–1998). Composition – Duration – Personnel (Dordrecht, Kluwer Academic Publishers, 2000). Note: This is the proportion of governments formed in the various ways, not the length

of time each country had such governments. Their category of caretaker government – by nature usually very short-lived – has been eliminated, and the proportions re-calculated, in order to give a more accurate comparative picture. This most substantially affected the figures for the Netherlands and Germany, for which, respectively, fully 20% and 16% of governments were listed as caretaker.

the government changed between elections, because of changing support in the parliament, the results report the result for the incumbent government contesting the election.

Table 2.14: Jaap Woldendorp, Hans Keman and Ian Budge, Party Government in 48 Democracies (1945–1998). Composition – Duration – Personnel (Dordrecht, Kluwer Academic Publishers, 2000).

Table 2.18: Later figures from InterParliamentary Union at: www.ipu.org. Earlier figures are from Jan-Erik Lane, David McKay and Kenneth Newton Political Data Handbook. OECD Countries (2nd ed., Oxford University Press, 1995) p. 134.

Table 2.15: Kaare Strom, ‘Parties at the Core of Government’ in Russell J. Dalton and Martin P Wattenberg (eds), Parties without Partisans: Political Change in Advanced Industrial Democracies (Oxford University Press, 2000) pp. 198–9. Table 2.16: Calculated using data from several sources, including Jaap Woldendorp, Hans Keman and Ian Budge, Party Government in 48 Democracies (1945–1998). Composition – Duration – Personnel (Dordrecht, Kluwer Academic Publishers, 2000); Thomas T. Mackie and Richard Rose, The International Almanac of Electoral History (3rd edn, Macmillan, London, 1991); Ian Gorvin (ed.), Elections since 1945: A Worldwide Reference Compendium (Longman, Essex, 1989); plus www.terra.es and www.parrties-and-elections.de This table involved making several judgements and decisions. The United States only allows a president two terms, so if the candidate from the same party as the retiring president won, this was considered continuity. In the semi-presidential countries, the results are for parliamentary elections, but the dual executive creates problems of interpretations, especially in periods of divided government. President Mitterand, for example, twice used his power to appoint a Prime Minister with only minority support, who then won the election. These have been included as continuity. Similarly, sometimes the composition of

Table 2.17: Manfred G. Schmidt, ‘The Impact of Political Parties, Constitutional Structures and Veto Players on Public Policy’ in Hans Keman (ed.), Comparative Democratic Politics (London, Sage, 2002) p. 169.

Table 2.19: United Nations Development Programme, Human Development Report 2007– 08 (NY, UNDP, 2008); 2000 figures from United Nations Development Programme, Human Development Report 2002 (NY, Oxford University Press, 2002); 1994 figures from United Nations Statistics Division at: www.un.org/ Depts/unsd/ww2000/table6a. htm Table 2.20: www.guide2womenleaders.com/ women_heads_of_governments.htm Table 2.21: Compiled from data at the International Institute for Democracy and Electoral Assistance (IDEA) at: www.idea.int/vt/ country_view.cfm. Data for nearly all countries goes back to the first election after World War II. US presidential voting turnout data (as proportion of registered voters) only dates back to 1964, but as proportion of the voting age population, it goes back to 1946. In countries with voluntary voting, there is differential turnout for different types of elections. The national elections chosen for the table are included on the basis that they are the crucial ones in the formation of the national government. For the United States that is presidential elections. The mean voting turnout for congressional elections was 58%. Conversely, parliamentary elections were used in


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the semi-presidential systems of Finland and France. However, in those countries, voting turnout tends to be somewhat higher for presidential elections. Table 2.22: Susan Scarrow, ‘Parties without Members? Party Organisation in a Changing

Electoral Environment’ in Russell J. Dalton and Martin P Wattenberg (eds), Parties without Partisans. Political Change in Advanced Industrial Democracies (Oxford University Press, 2000) p. 90.

3 Economics Table 3.1: OECD Factbook 2008. Table 3.2: Angus Maddison, The World Economy. A Millennial Perspective (Development Studies Centre, OECD, Paris, 2001) pp. 185, 215. Tables 3.3 and 3.4: Angus Maddison 2001 (see above) pp. 186, 216. Table 3.4 has been calculated from data in Angus Maddison Monitoring the World Economy 1820–1992 (OECD Development Centre, Paris, 1995). In his 2001 work, Maddison revised some of these figures, but all by small amounts. The figures for Ireland and Switzerland are incomplete in the earlier years. In order to calculate mean growth rates for the entire half century, we have substituted the 1890 figure as the 1889 figure for Ireland. More problematically, we have interpolated a Swiss figure for 1889 from the data for 1870 and 1900. Table 3.5: Most recent figures calculated from www.OECD.Stat. Earlier data is from OECD Historical Statistics (CD-Rom, Paris, 2001). Table 3.6: OECD Economic Outlook No 82 Statistical Annex with earlier data from OECD Historical Statistics (CD-Rom). Table 3.7: OECD Economic Outlook No 82 Statistical Annex. Table 3.8 and 3.9: Last two columns from UNDP Human Development Report 2007–2008; earlier from OECD Historical Statistics CD-Rom. Tables 3.10 and 3.11: OECD Foreign Direct Investment Statistics (OECD, 2002).

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Final column from OECD International Investment Perspectives 2007 edition p. 23. Table 3.12: Latest data from OECD Economic Outlook No 82 Statistical Annex; earlier from OECD Historical Statistics CD-Rom. Table 3.13: ‘Sizzling the Big Mac Index’ Economist 7 July 2007. Tables 3.14, 3.18, 3.21 and 3.23: Most recent data are from OECD Labour Force Statistics 1986 – 2006 (Paris 2007). In first three tables, earlier data is from OECD Labour Force Statistics 1978–1998 (Paris, 1999) and Historical Statistics 1960–1995 (OECD, Paris, 1997). Tables 3.15, 3.19 and 3.22: Later data is from OECD Factbook 2008; earlier data is from OECD Historical Statistics CD-Rom (2001). Table 3.16: Later data is from OECD Factbook 2008; earlier data is from Food and Agriculture Organisation Compendium of Food and Agriculture Indicators 2001 at: www. fao.org Table 3.17: Latest data is from OECD in Figures 2008; earlier data is 2001 figure from OECD in Figures, OECD Observer 2002/ Supplement 1. Table 3.20: OECD Science, Technology and Industry Scoreboard 2007, Innovation and Performance in the Global Economy. Tables 3.24, 3.25, 3.26 and 3.28: OECD Economic Outlook No 82 December 2007 Statistical Annex for latest figures. For Tables 3.24 and 3.25, earlier data from OECD Historical Statistics CD-Rom, and for

3.26 from OECD Economic Outlook 2002 Annex Table 26. Table 3.27: www.OECD.Stat and national sources. Table 3.29 and 3.30: OECD Economic Outlook No 82 December 2007 Statistical Annex for

latest figures. Earlier data for Table 3.30 from OECD Economic Outlook 2002 and for Table 3.31 from OECD, The Sources of Economic Growth in the OECD Countries (Paris, OECD, 2003). Table 3.31 and 3.32: UNDP Human Development Report 2007–2008.

4 Work and labour Table 4.1: Source for earlier years is OECD Historical Statistics (CD-Rom). For 2000–2006, figures are calculated from OECD Labour Force Statistics 2008.

Sacerdote, ‘Work and Leisure in the US and Europe. Why so Different?’ Harvard Institute of Economic Research Discussion Paper 2068, April 2005 (especially Table 3).

Table 4.2: Annex to OECD Society at a Glance: OECD Social Indicators (2nd ed., Paris, 2003). Data available at Source: Annex to OECD Society at a Glance, Table GE3.2, at: www.oecd.org/els/social/indicators

Table 4.20, 4.21: www.OECD.Stat

Table 4.3: OECD Pensions at a Glance 2007. Tables 4.4–4.7: OECD Employment Outlook 2008. Some earlier periods from OECD Historical Statistics (CD-Rom) and ILO Key Indicators of the Labour Market. Table 4.8: OECD Economic Outlook No 82 Statistical Annex (2007). Table 4.9: OECD Labour Force Statistics 2008. Table 4.10 –4.12: OECD Employment Outlook 2008. See also ILO, Geneva, Key Indicators of the Labour Market. Tables 4.13 and 4.14: OECD Employment Outlook 2008. Table 4.15: www.OECD.Stat Table 4.16: 1980 and 1990 figures from OECD Factbook 2007; 2000 and 2007 figures from www.OECD.Stat Table 4.17–4.18: www.OECD.Stat Table 4.19: OECD Babies and Bosses (2007). Alberto Alesina, Edward Glaese and Bruce

Table 4.22: OECD Health Data, December 2008 Update. Table 4.23: Knud Knudsen and Kari Waerness, ‘National Context and Spouses’ Housework in 34 Countries’ in European Sociological Review, vol. 24, no. 1 2008, pp. 97– 113. Table 4.24: Jelle Visser ‘Union Membership Statistics in 24 Countries’ in Monthly Labor Review, January 2006, pp. 38–49. Table 4.25: Dominic Hale, ‘International Comparisons of Labour Disputes in 2006’ in Economic and Labour Market Review, vol. 2, no. 4, April 2008 (London, Office for National Statistics). For earlier years, these rates of annual days lost per 1000 employees are the authors’ compilations based upon two sources. The first is the ILO Yearbook of Labour Statistics 2002 (ILO, Geneva, 60th ed) plus several earlier editions for total days lost. The second is the OECD’s figures for total employment for various years from OECD Labour Force Statistics 1980–2000 (OECD, Paris, 2001). There were several gaps in the data for industrial disputes, which have been averaged out (a less than perfect procedure given the volatility of annual rates of industrial disputation).


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5 Government taxation and spending Table 5.1: OECD Historical Statistics 1960– 1995 (Paris 1997) and OECD Historical Statistics 1970–1999 CD-Rom (Paris, 2000). For 2000–2008, source is OECD Economic Outlook 82 (2007) Statistical Annex. Table 5.2: OECD Revenue Statistics 1965–2001 (Paris 2002) pp. 73–4; and OECD Revenue Statistics 1965–2006. Tables 5.3 and 5.4: OECD Revenue Statistics 1965–2006. Figures in tables for several countries differ slightly from the OECD’s published

figures because there is a small number where income tax and social security contributions are not able to be disaggregated to individual or corporate sources. In these cases, the residue has been distributed according to their existing proportions. Table 5.5: Statistical Annex to OECD Economic Outlook 82 2007. Table 5.6: Statistical Annex to OECD Economic Outlook 82 2007.

6 Health Tables 6.1–6.20, 6.22–6.26, and 6.28–6.34, and Figures 6.1–6.7: The source for all these is OECD Health Data, updated December 2008, and OECD Health at a Glance 2007.

Sixty-Seven Countries Covering the Period 1720–1984 (Oxford University Press, 1992) Appendix Four p. 582ff. Later data are from OECD Health Data.

Table 6.2: Also draws on data from Uwe Reinhardt, Peter S. Hussey and Gerard F. Anderson ‘Cross-National Comparisons of Health Systems using OECD Data, 1999’ in Health Affairs, vol. 21, no. 3, May 2002, p. 170. For 1990–2000, see Gerard F. Anderson, Uwe Reinhardt, Peter S. Hussey and Varduhl Petroyan, ‘It’s the Prices, Stupid: Why the United States is so Different from Other Countries’ Health Affairs , vol. 22, no. 3, May 2003. 2000–2005 figures based on authors’ calculations from OECD Health Data December 2008.

Table 6.21: Colin D. Mathers et al., ‘Healthy Life Expectancy: comparison of OECD countries in 2001’ Australian and New Zealand Journal of Public Health, vol. 27, no. 1, 2003, p. 9.

Table 6.18: 1900, 1925, 1950 and 1975 data are from Jean-Claude Chesnais, The Demographic Transition. Stages, Patterns and Economic Implications. A Longitudinal Study of

Table 6.27: World Health Organization, World Health Statistics 2007 (Geneva, 2007). The text also draws on UNAIDS. The First 10 Years 1996–2006 (UNAIDS, Geneva, 2008). Tables 6.35, 6.36 and 6.38: UNICEF, The State of the World’s Children 2009, Maternal and Newborn Health (NY, December 2008). See also: www.childinfo.org. Table 6.37: UNDP, Human Development Report 2007–2008.

7 Education Tables 7.1–7.13, and Figures 7.1 and 7.2: The basic sources for all these are OECD Education at a Glance 2007 (OECD, Paris, 2007) and OECD

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Education at a Glance 2008 (OECD, Paris, 2008).

Data for earlier years in Tables 7.3 and 7.4 is drawn from OECD Education at a Glance 1997. Text also draws on: Simon Marginson, ‘Education: Australia and the OECD’ Australian Policy Online Background Paper at: www.apo.net.au. On international students in Australia, see also ABS Australian Social Trends 2007 4102.0 p. 1. Paul Kniest, ‘Who is Being Selective in Their Choice Of University Funding Data?’ in NTEU Advocate, March 2007, p. 27. Tables 7.15–7.24 and Figures 7.3 and 7.4: The basic sources are Sue Thomson and Lisa De Bor-

toli, Exploring Scientific Literacy: How Australia measures up (Melbourne ACER and OECD PISA, 2008); OECD PISA 2006: Science Competencies for Tomorrow’s World, Vol 1 (OECD, Paris, 2007); OECD PISA 2006 Volume 2: Data (Paris, 2007). Text also draws on Barry McGaw, ‘International Benchmarking of Australian Schools’ Paper to VCAA Curriculum Branch Conference Day, Melbourne, December 2007; and ‘The Race is Not Always to the Richest’ The Economist 8 December 2007. Tables 7.21–7.23: The data for these tables was kindly provided by Sue Thomson of ACER.

8 Inequality and social welfare Tables 8.1–8.8: All these tables are drawn from or calculated from OECD Growing Unequal? Income Distribution and Poverty in OECD Countries (2008). For Tables 8.4 and 8.6: See also the Luxembourg Income Study (LIS) at: www.lisproject. org/keyfigures/ineqtable.htm

Society at a Glance. OECD Social Indicators Edition 2002.

Table 8.9: OECD Factbook 2007.

Table 8.16: Latest data from Growing Unequal? Earlier data from A League Table of Child Poverty in Rich Nations (UNICEF Innocenti Research Centre, Florence Italy, Issue No 1, June 2000) and Roderick Beaujot and Jianye Liu, ‘Children, Social Assistance and Outcomes: Cross National Comparisons’ Luxembourg Income Study Working Paper, No. 304, June 2002.

Table 8.10: Latest data is from Willem Adema and Maxime Ladaique, Net Social Expenditure, 2005 Edition. More Comprehensive Measures of Social Support (OECD Social, Employment and Migration Working Papers, No 29). Earlier data is from Willem Adema Net Social Expenditure (2nd ed, Labour Market and Social Policy Occasional Paper No. 52, OECD, 2001). Both include public health spending. Table 8.11: Annex to OECD Society at a Glance. OECD Social Indicators Edition 2002. Table 8.12: OECD Growing Unequal? Table 8.13: Latest figure from Growing Unequal? Earlier data is from Annex to OECD

Table 8.14: OECD Pensions at a Glance 2007. Table 8.15: OECD Society at a Glance. OECD Social Indicators 2006.

Table 8.17: OECD Growing Unequal? Table 8.18: OECD Growing Unequal? Percentage of households with children data comes from Peter Whiteford and Willem Adema, What Works Best in Reducing Child Poverty: A Benefit or Work Strategy? (OECD Social, Employment and Migration Working Papers, No. 51, 2007).


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9 International relations Tables 9.1 to 9.3: These tables are all taken from data supplied by the Stockholm Institute for Peace Research Incorporated (SIPRI). Much of it is taken from databases available at their website at: www.sipri.org. In addition, their data is reproduced in their yearbooks, such as SIPRI Yearbook 2008 (Oxford University Press, 2008) and in the annual Human Development Report, produced by the United Nations Development Program. Some of this data is taken from the Human Development Report 2002 (Oxford University Press, 2002), and more recent data from its website at: http://hdr.undp.org/en/statistics/ Figures for 1970, 1980 and 1990 are from SIPRI as found in the Comparative Welfare States Data Set, assembled by Evelyne Huber, Charles Ragin and John D. Stephens. It can be found at: www.lisproject.org. Because of revi-

sions over time in estimating size of GDP and in re-assessing data, there may be small discrepancies in the estimates of military expenditure as a proportion of GDP in earlier years. Tables 9.4 and 9.5: Later data is from OECD Development Assistance 2008; earlier data is from OECD Development Assistance 2002. GNI stands for Gross National Income. Since the OECD and other international organisations co-sponsored a new System of National Accounts, this measure has replaced the old GNP. Table 9.6: Center for Global Development Commitment to Development Index at: www.cgdev.org. Table 9.7: UNDP Human Development Report 2007–2008.

10 Environment Tables 10.1–10.4: Data comes from the World Resources Institute Biodiversity and Protected Areas searchable database at: http://earthtrends.wri.org/searchable_db/ index.php?theme=7 Table 10.5: International Energy Agency CO2 Emissions from Fuel Combustion (Paris, 2008). Table 10.6: United Nations Framework Convention on Climate Change ‘National Greenhouse Gas Inventory Data for the Period 1990–2006’ (2008). Table 10.7: 1990 figures from Hal Turton and Clive Hamilton, ‘Updating Per Capita Emissions for Industrialised Countries’ (The Australia Institute, Canberra, 2002) at:

www.tai.org.au; 2005 figures calculated from UNFCCC, op. cit. Tables 10.8 and 10.9: IEA Electricity Information 2008. Tables 10.10–10.13: OECD Environment at A Glance. OECD Environmental Indicators 2005. Table 10.14: Ecological footprint data is from the ‘Global Footprint Network’ at: www.footprintnetwork.org/en/index.php/ GFN/page/footprint_for_nations/ Text also draws on ‘Ecological footprint’ entry on Wikipedia at: http://en.wikipedia.org Jason Venetoulis and John Talberth ‘Refining the Ecological Footprint’ (Oakland California, Redefining Progress, December 2006).

11 Science and technology Tables 11.1 to 11.10: All are drawn from OECD Science, Technology and Industry Scoreboard 262


2007. Innovation and Performance in the Global Economy (2007).

12 Telecommunications and computing Tables 12.1–12.3: International Telecommunication Union Yearbook of Statistics 2008, Telecommunication Services 1997–2006 (Geneva, ITU, 2008).

Table 12.13: OECD Science, Technology and Industry Scoreboard 2007.

Tables 12.4 and 12.5: OECD Outlook 2007.

Communications

Table 12.14: OECD Communications Outlook 2007.

Table 12.6: OECD Science, Technology and Industry Scoreboard 2007.

Tables 12.15–12.18: OECD Broadband Portal at www.oecd.org.

Figure 12.1 and Tables 12.7–12.12: OECD Communications Outlook 2007.

13 Media Table 13.1: For 1980, see UNESCO Statistical Yearbook 1999 (UNESCO Publishing, Paris, 1999) pp. IV–114ff. For 2007, see World Association of Newspapers World Press Trends 2008 (World Association of Newspapers, Paris, 2008).

centration in Europe. Commercial Enterprise and the Public Interest (The European Institute for the Media, Media Monograph, no. 16, 1993) for the European countries, and 1999 data for all countries comes from OECD Communications Outlook 2001.

Tables 13.2 and 13.3: World Association of Newspapers World Press Trends 2008 (World Association of Newspapers, Paris, 2008).

Tables 13.7–13.9: OECD Communications Outlook 2007.

Table 13.4: Data for 1987–2000 is from Richard van der Wurff, Piet Bakker and Robert G Picard, ‘Economic Growth and Advertising Expenditures in Different Countries’ Journal of Media Economics, vol. 21, no. 1, pp. 28– 52, 2008. For 2007, see World Association of Newspapers World Press Trends 2008 (World Association of Newspapers, Paris, 2008). Table 13.5: World Association of Newspapers, World Press Trends 2008 (World Association of Newspapers, Paris, 2008). Table 13.6: The columns on the 1970s come from Alfonso Sanchez-Tabernero, Media Con-

Table 13.10: OECD Communications Outlook 2001. Text also draws on ABC Triennial Funding Submission Summary 2003–2006 p. 3, available at: www.abc.net.au; Glenn Withers ‘Funding Public Service Broadcasters’, Southern Review, vol. 35, no.1, 2002, pp. 107– 19. McKinsey and Company, Public Service Broadcasters Around the World (1999). Tables 13.11 and 13.12: OECD Communications Outlook 2007. Tables 13.13 and 13.14: Focus 2007. World Film Market Trends (European Audiovisual Observatory, Strasbourg, 2007).

14 Family Table 14.1: Recent figures are from OECD Society at a Glance 2006.

1980 figures for EU countries are from European Social Statistics Demography


263

2001 edition at: http://europa.eu.int. Australian figures are from Australian Bureau of Statistics, Year Book Australia 2003 – Population, Marriages and Divorces at: www.abs. gov.au/Ausstats. Figures for other European and North American countries come from United Nations, Economic Commission for Europe, Trends in Europe and North America 2001 (United Nations, NY, 2001). New Zealand figures are from Maureen Baker, Families, Labour and Love (Sydney, Allen & Unwin, 2001). Japanese figures are from Japan Almanac 1998 (Tokyo, Asahi Shimbun). Table 14.2: Recent figures are from OECD Society at a Glance 2006. Earlier figures are from the Annex to OECD Society at a Glance, OECD Social Indicators Edition 2002 (Paris, 2003). Table 14.3: OECD Society at a Glance 2006. Table 14.4: OECD Society at a Glance 2006. For Australia and several other countries, the latest figure is 2000; 1970 figure for Austria is from 1980. Table 14.5: 2004 data is from OECD Society at a Glance 2006. Figures for 1970, 1980, 1990 are from Jean-Paul Sardon ‘The Demographic Situation of Europe and the Developed Countries Overseas: An Annual Report’ Population: An English Selection, vol. 12 (2000), pp. 293– 328. Table 14.6: 2004 figures from OECD, Babies and Bosses: Reconciling Work and Family Life, A Synthesis of Findings for OECD Countries (2007). Earlier figures are from Innocenti Report Card, A League Table of Teenage Births in Rich Nations (UNICEF, Florence, 2001), available at: www.unicef-icdc. org Table 14.7: Gilda Sedgh, et al., ‘Legal Abortion Worldwide: Incidence and Recent Trends’, International Family Planning Perspectives, vol. 33, no. 3, September 2007, pp. 106–16.

264


Research from the Guttmacher Institute, available at: www.gutmacher.org. Table 14.8: OECD Growing Unequal? Income Distribution and Poverty in OECD Countries (2008). Table 14.9: OECD Family Database at: www. oecd.org/els/social/family/database. Table 14.10: OECD, Babies and Bosses: Reconciling Work and Family Life. A Synthesis of Findings for OECD Countries (2007). Table 14.11: Michael Forster and Mark Pearson, ‘Income Distribution and Poverty in the OECD Area: Trends and Driving Forces’, OECD Economic Studies, no. 34, 2002/1. Table 14.12: OECD Society at a Glance 2006. Table 14.13: OECD Employment Outlook 2002, p. 78. Discussion also draws on Anna C d’Addio and Marco M d’Ercole, ‘Trends and Determinants of Fertility Rates. The Role of Policies’ (OECD Social Employment and Migration Working Papers, no. 27, 2005). Tables 14.14 and 14.15: OECD Family Database at: www.oecd.org/els/social/family/database. Table 14.16: OECD Benefits and Wages 2007. OECD Indicators. Table 14.17: OECD Babies and Bosses: Reconciling Work and Family Life. A Synthesis of Findings for OECD Countries (2007). Text also draws on UNICEF, The Child Care Transition. A League Table of Early Childhood Education and Care in Economically Advanced Countries (UNICEF Innocenti Research Centre, Florence, 2008). Table 14.18: OECD Family Database at: www. oecd.org/els/social/family/database See also OECD Babies and Bosses op. cit., p. 72. Tables 14.19 and 14.20: OECD Family Database at: www.oecd.org/els/social/family/database

15 Lifestyles and consumption Table 15.1: Figures to 1990 from Francis G Castles, Comparative Public Policy: Patterns of Post-War Transformation (Cheltenham, UK, Edward Elgar, 1998) p. 251 and Francis G Castles, ‘The Really Big Trade-Off: Home Ownership and the Welfare State in the New World and the Old’, Acta Politica, vol. 32, Winter 1997, p. 8. Figures for 2000 or latest available year from N Girouard et al., (2006) ‘Recent House Price Developments: The Role of Fundamentals’ OECD Economics Department Working Papers No. 475. Table 15.2: Julie Lawson and Vivienne Milligan, ‘International Trends in Housing and Policy Responses’, AHURI Final Report No. 110, December 2007, Australian Housing and Urban Research Institute, Sydney Research Centre p. 20. Table 15.3: OECD (2006), ‘Are House Prices Nearing a Peak? A Probit Analysis for 17 OECD Countries’, OECD Economics Department Working Papers, No 488, OECD Publishing. Table 15.4: Demographia 5th Annual Demographia International Housing Affordability Survey: 2009 at: www.demographia.com/ dhi.pdf. In addition to the above, the text draws upon chapter 3 of the Senate Select Committee on Housing Affordability in Australia available at: www.aph.gov.au/senate/ committee/hsaf_ctte/ report/c03.htm, and Lois Bryson ‘Australia: The Transformation of the Wage-Earners’ Welfare State’ in Peter Alcock and Gary Craig (eds), International Social

Policy: Welfare Regimes in the Developed World (NY, Palgrave, 2001). Tables 15.5–15.9: OECD Health Data 2008, December 2008 update. Text also draws on Australian Institute of Health and Welfare Australia’s Health 2002 (Canberra, AIHW, 2002) p. 140. Table 15.10: Global Market Information Database (GMID), published by Euromonitor. They were accessed at: www.euromonitor. com. Text also draws on Australian Institute of Health and Welfare Australia’s Health 2002 (Canberra, AIHW, 2002) p. 142–3. Table 15.11: OECD Factbook 2008. Table 15.12: International Fuel Prices 2007 (5th edition, Sector Project, Transport Policy Advisory Service, Federal Ministry for Economic Cooperation and Development, Berlin, 2008). Tables 15.13, 15.14: These per capita figures are calculated from OECD/International Transport Forum Trends in the Transport Sector 1970–2006 (2008). Tables 15.15–15.18: Data is drawn from the Mobility in Cities Database, directed by Jean Vivier and Jerome Pourbaix, for the International Association of Public Transport (UITP), Brussels, 2006. Text also draws considerably on Peter Newman and Jeff Kenworthy, ‘Greening Urban Transportation’ in M O’Meara, State of the World 2007: Our Urban Future (Worldwatch Institute, Norton Publishers, Washington DC).

16 Crime and social problems Table 16.1: Jan van Dijk, John van Kesteren, Paul Smit, Criminal Victimisation in International Perspective: Key Findings from the 2004–2005 ICVS and EU ICS (WODC, 2007, The Hague).

Table 16.2: Gordon Barclay and Cynthia Tavares ‘International Comparisons of Criminal Justice Statistics 2000’ available at: www.homeoffice.gov.uk/rds/


265

Table 16.3: OECD Health Data (December 2008 update). Tables 16.4–16.6: See van Dijk et al. op. cit. Text also draws upon Jenny Mouzos and Catherine Rushforth, ‘Firearm Related Deaths in Australia, 1991–2001’ in Australian Institute of Criminology, Trends and Issues in Crime and Criminal Justice, no. 269, November 2003. Table 16.7: Gordon Barclay and Cynthia Tavares, ‘International Comparisons of Criminal Justice Statistics 2001’ UK Home Office Issue 12/03 24 October 2003 at: www.csdp.org/ research/hosb1203.pdf. New Zealand figure is from ICVS wave four. Tables 16.8–16.13: See van Dijk et al., op. cit. Table 16.14: Figures for 1982, 1990 from OECD Society at a Glance Statistical Annex; and Economic Commission for Europe Statistical Division Trends in Europe and North America 2001. The Statistical Yearbook of the Economic Commission for Europe (United Nations, Geneva, 2001). Irish figure for 1990 = 1994. Figures for 2000 are from Roy Walmsley World Prison Population List (3rd ed). (Findings 166; London, UK Home Office, 2002); for 2006, see OECD Factbook 2008. Text also draws on Marie Gottschalk, ‘Black Flower: Prisons and the Future of

Incarceration’ The Annals of the American Academy of Political and Social Sciences, no. 582, July 2002, p. 206. Table 16.15: Economic Commission for Europe Statistical Division Trends in Europe and North America 2001, The Statistical Yearbook of the Economic Commission for Europe (United Nations, NY and Geneva, 2001) p. 229 plus Amnesty International at: www.web.amnesty.org Amnesty International ‘Death Sentences and Executions in 2007’ ((International Secretariat, 1 Easton Street, London WC1X 0DW, UK, 15 April 2008). See also The Economist ‘Revenge Begins to Seem Less Sweet’, 1 September 2007. Table 16.16 and Figures 16.1 and 16.2: OECD Health Data (December 2008 update). Figure 16.3: OECD Society at a Glance. (OECD 2001) Statistical Annex Table D3. Text also draws on ‘Death Be Not Proud/ Suicide in Japan’ The Economist, 3 May 2008. Tables 16.17, 16.18: OECD Health Data (December 2008 update). Table 16.19: Transparency www.transparency.org

International

at:

Table 16.20: Transparency International ‘2008 Bribe Payers Index’ at: www.transparency.org

17 The search for scoreboards Tables 17.1–17.8: The data for these tables comes from United Nations Development Programme Human Development Report 2007/2008. Fighting Climate Change: Human Solidarity in a Divided World (NY, UNDP, 2007). Table 17.9: Michael E Porter and Klaus Schwab, The Global Competitiveness Report 2008– 2009 (Geneva, World Economic Forum, 2008).

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Table 17.10: Heritage Foundation, 2009 Index of Economic Freedom, at: www.heritage.org/ index/Default.aspx. Table 17.11: Economist Intelligence Unit, The Economist Intelligence Unit’s Liveability Survey 2008 at: www.eiu.com. Table 17.12: Mercer 2007 World-wide Quality of Living Survey (April 2008) at: www.mercer.com. See also City Mayors:

Best Cities in the World (Mercer) at: http://citymayors.com Table 17.13: ‘The 2007 Foreign Policy Index’ Foreign Policy November-December 2007. See also: www.foreignpolicy.com and www.atkearney.com Table 17.14: Axel Dreher, The KOF Index of Globalisation 2009. See: http://globalization. kof.ethz.ch/ (Swiss Federal Institute of Technology, Zurich).

Table 17.15: Marcel Raab, Michael Ruland, Benno Schonberger, Hans-Peter Blossfeld, ¨ Dirk Hofacker, Sandra Buchholz and Paul ¨ Schmelzer, (2008): ‘GlobalIndex – A Sociological Approach to Globalization Measurement’ International Sociology, vol. 23, no.4, pp. 596–631. See also: www.transeuropeproject.org/globalindex (Social Science Network, European Science Foundation).

18 The Howard impact Table 18.1: Angus Maddison, The World Economy: A Millenial Perspective (Development Centre of the OECD, Paris, 2001) pp. 186, 216. Table 18.2: The Economist, 13 September 2008, p. 68. Table 18.3: OECD Education at a Glance 2008 (Paris, OECD, 2008). Figures 18.1–18.3: Source for earlier years is OECD Historical Statistics 1970–1999. For later years, source is OECD Economic Outlook 82 Statistical Annex (2007). Figure 18.4: OECD Economic Outlook No 82 Statistical Annex (2007). Figure 18.5: OECD Revenue Statistics 1965– 2001 (2002) pp. 73–4; and OECD Revenue Statistics 1965–2006 (2007). Figure 18.6: OECD Historical Statistics 1970– 1999 CD-Rom (Paris, 2000). For 2000–2008, source is OECD Economic Outlook 82 Statistical Annex (2007).

Figures 18.7, 18.8: OECD Economic Outlook 82 Statistical Annex (2007). Figure 18.9: Earlier years from OECD The Sources of Economic Growth in the OECD Countries (Paris, OECD, 2003) pp. 174–5; later years from OECD Factbook 2008. Figure 18.10: OECD Historical Statistics 1970– 1999 CD-Rom (2000); OECD Economic Outlook No 82 Statistical Annex (2007). Figure 18.11: OECD Economic Outlook No 82 Statistical Annex (2007). Figures 18.12, 18.13: OECD Education at a Glance 2008 (Paris, OECD, 2008). Figure 18.14: OECD Science, Technology and Industry Scoreboard 2007. Text also draws upon Tim Colebatch ‘Contenders Have a Day to Treasure’ The Age, 31 October 2007; Matt Price ‘House that John Built has Cracks’ The Australian, 7 September 2006; Thomas Hunter ‘Yes, Malcolm, We do Lead the World in Changing the Climate’ Crikey, 31 October 2007.


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