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ADVANCES IN AIRLINE ECONOMICS The Economics of Airline Institutions, Operations and Marketing

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ADVANCES IN AIRLINE ECONOMICS

The Economics of Airline Institutions, Operations and Marketing VOLUME 2 Edited by

Darin Lee LECG, LLC Cambridge, USA

AMSTERDAM • BOSTON • HEIDELBERG • LONDON • NEW YORK • OXFORD PARIS • SAN DIEGO • SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands Linacre House, Jordan Hill, Oxford OX2 8DP, UK First edition 2007 Copyright © 2007 Elsevier B.V. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-444-53027-1 For information on all Elsevier publications visit our website at books.elsevier.com Printed and bound in The Netherlands 07 08 09 10 11 10 9 8 7 6 5 4 3 2 1

Working together to grow libraries in developing countries www.elsevier.com | www.bookaid.org | www.sabre.org

Contents

Advances in Airline Economics, Volume II

vii

Preface

ix

List of Contributors

xi

1 Institutions, Regulation, and the Evolution of European Air Transport

1

Jan K. Brueckner and Eric Pels

2 Wage Determination in the US Airline Industry: Union Power Under Product Market Constraints

27

Barry T. Hirsch

3 Toward Rational Pricing of the US Airport and Airways System

61

Daniel P. Kaplan

4 An Interpretative Survey of Analytical Models of Airport Pricing

89

Leonardo J. Basso and Anming Zhang

5 What if the European Airline Industry had Deregulated in 1979?: A Counterfactual Dynamic Simulation

125

Purvez F. Captain, David H. Good, Robin C. Sickles and Ashok Ayyar

6 State Aid to European Airlines: A critical Analysis of the Framework and its Application

147

Pietro Crocioni and Chris Newton

7 The Implications of the Commercialization of Air Transport Infrastructure

171

Kenneth Button

8 The Role of Regional Airlines in the US Airline Industry

193

Silke Januszewski Forbes and Mara Lederman

9 Airport Substitution by Travelers: Why Do We Have to Drive to Fly? Gary M. Fournier, Monica E. Hartmann and Thomas W. Zuehlke

209

CONTENTS

vi

10 Assessing the Role of Airlines and Airports in Multi-airport Markets

235

Jun Ishii, Sunyoung Jun and Kurt Van Dender

11 Airline Ticket Taxes and Fees in the United States and European Union

255

Joakim Karlsson, Amedeo Odoni, Célia Geslin and Shiro Yamanaka

12 Are Passengers Willing to Pay More for Additional Legroom?

275

Darin Lee and María Jose´ Luengo-Prado

13 Assessing the Potential Success of the Low-Cost Business Models

in Asian Aviation Markets

287

David Gillen and Natthida Taweelertkunthon

14 Pricing Strategies by European Traditional and Low Cost Airlines: Or,

when is it the Best Time to Book on Line?

319

Claudio A. Piga and Enrico Bachis

15 The Long-Run Distributional Effects of Industry and Carrier Changes

in the US Air Transport Market

345

Aisling Reynolds-Feighan

16 Air Travel Demand Elasticities: Concepts, Issues and Measurement

365

David Gillen, William G. Morrison and Christopher Stewart

Index

411

Advances in Airline Economics,

Volume II

Darin Lee, Editor

The second in a new series of books on the economics of the airline industry. The series is comprised of a collection of original, cutting-edge research papers from an international panel of distinguished contributors. Volume 2 focuses on topics related to airline institutions, operations and marketing such as wage determination, airport and airway pricing, taxation and low-cost carrier business strategies.


Preface

Following the deregulation of the US airline industry in 1978, papers analyzing the industry were a regular feature in prominent economics journals such as the American Economic Review, the Quarterly Journal of Economics and the Journal of Political Economy. While important research on the airline industry continued throughout the mid to late 1990s, the number of academic economists actively pursuing research on the airline industry had clearly wanted. After a brief hiatus however, there has been a resurgence in academic research on the airline industry, both in North America and throughout the rest of the world. Indeed, one could argue that the changes over the past several years – including the growing prominence of ’low-cost carriers’ and their interplay with the ’legacy carriers’, the advent of the Internet and its affect on industry pricing and the proliferation of international alliances – have resulted in changes that rival those following the passage of the Airline Deregulation Act. The purpose of the Advances in Airline Economics series is to provide a comprehensive overview of the current state of economic research on the airline industry. Each volume will consist of several previously unpublished research papers written by an international panel of distinguished academic and industry economists, as well as a select number of reprints of influential papers by prominent researchers in the field. Volume 2: The Economics of Airline Institutions, Operations and Marketing features 16 essays covering topics such as airline industry wage determination, airport and airway pricing, taxation and low-cost carrier business strategies. I hope readers find the essays contained in Volume 2 enlightening and that they help to stimulate further debate and research in this continually evolving and fascinating industry. Darin Lee, Editor


List of Contributors

A. Ayyar

Chicago Partners, LLC, New York.

E. Bachis L. J. Basso

Nottingham University Business School. ∗

Sauder School or Business, The University of British Columbia. Department of Civil Engineering, Universidad de Chile.

J.K. Brueckner

Department of Economics, University of California, Irvine, 3151 Social Science Plaza, Irvine, CA 92697.

K. Button∗

University Professor and Director of the Aerospace Policy Research Center, School of Public Policy, George Mason University, Fairfax, Virginia.

P.F. Captain P. Crocioni

∗

Ernst & Young, LLP, Houston, TX. Senior Economist, Chief Economist Team, Office of Communications (Ofcom).

S.J. Forbes

Department of Economics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0508, USA.

G.M. Fournier∗

Department of Economics, Florida University, Tallahassee, FL 32306-2180.

C. Geslin

Department of Civil and Environmental Engineering, Massachusetts Institute of Technology.

D. Gillen∗

Sauder School of Business and Director, Centre for Transportation Studies, University of British Columbia.

D.H. Good

Indiana University, Bloomington, IN.

M.E. Hartmann

Economics Department, St. Thomas University, 2115 Summit Avenue, St. Paul, Minnesota, 55105.

B. Hirsch∗

E.M. Stevens Distinguished Professor of Economics, Trinity University, San Antonio, TX 78212.

J. Ishii

Department of Economics, University of California, Irvine, CA 92697-5100.

S. Jun


D. Kaplan∗

Director, LECG, LLC.

J. Karlsson∗

Division of Aviation, Daniel Webster College, 20 University Drive, Nashua, New Hampshire 03063-1300.

M. Lederman∗

Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario, Canada, M5S 3E6.

LIST OF CONTRIBUTORS

xii

D. Lee∗

LECG, LLC, 350 Massachusetts Ave. Suite 300.

M.J. Luengo-Prado

Department of Economics, Northeastern University, 301 Lake Hall, Boston, MA 02115-5000, USA.

W.G. Morrison

School of Business and Economics, Wilfrid Laurier University, 75 University Avenue West, Waterloo, ON Canada N2L 3C5.

C. Newton

Director, Frontier Economics, UK.

A. Odoni

Massachusetts Institute of Technology, Room 33-219, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139.

E. Pels

Department of Spatial Economics, Free University of Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam.

C.A. Piga∗

Economics Department, Loughborough University, Leicestershire, LE11 3TU, UK.

A. Reynolds-Feighan∗

School of Economics and Geary Institute, University College Dublin, Belfield, Dublin 4.

R.C. Sickles∗

Corresponding author. Rice University, Houston, TX.

C. Stewart

School of Business and Economics, Wilfrid Laurier University, 75 University Avenue West, Waterloo, ON Canada N2L 3C5.

N. Taweelertkunthon

Centre of Transportation Studies, University of British Columbia.

K. Van Dender∗


S. Yamanaka

Department of Civil and Environmental Engineering, Massachusetts Institute of Technology.

A. Zhang

Sauder School of Business, The University of British Columbia.

T.W. Zuehlke

Department of Economics, Tallahassee, FL 32306-2180.

Florida

University,

Advances in Airline Economics, Vol 2 Darin Lee (Editor) © 2007 Elsevier B.V. All rights reserved

1 Institutions, Regulation, and the Evolution of European Air Transport Jan K. Brueckner∗ and Eric Pels†‡

ABSTRACT This paper provides an overview of the institutional and regulatory developments underlying European airline deregulation. The paper has argues that the old flag-carrier regime led to a proliferation of airlines and airlines routes, leading low traffic densities in European networks and thus high operating costs. While international alliances and open skies agree ments helped to boost traffic densities, the low-cost carriers unleashed by deregulation, though generating substantial passenger benefits through lower fares, threaten to drain traf fic out of the major carriers’ networks. A defensive response is needed, and part of this response must involve concentration of the major carriers’ traffic on fewer routes through network reorganization and cross-border mergers. The paper also highlights the need for additional policy steps, especially formation of a Common Atlantic Aviation Area and new rules for airport operations.

1 INTRODUCTION An economy’s institutional and regulatory structure can have profound impacts on economic activity. This impact has been significant in the aviation sector, and the impact is starkly revealed when institutions and regulations change abruptly as a result of deliberate public policy decisions. Such a change occurred in the United States in the late 1970s when the previous regulatory structure governing airline operations was ∗ Department of Economics, University of California, Irvine, 3151 Social Science Plaza, Irvine, CA 92697, Phone: (949) 824-0083, Fax: (949) 824-2182, e-mail: [email protected]. † Department of Spatial Economics, Free University of Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam, e-mail: [email protected]. ‡ We thank Darin Lee for his helpful comments. The usual disclaimer applies, however.

2

JAN K. BRUECKNER AND ERIC PELS

abruptly eliminated. Over the next decade, airline route structures were reorganized, flight frequencies increased, many new airlines began operations (with many ultimately failing), and real airfares began a long secular decline that has continued to the present. Europe is now reaping some of the benefits of its own process of airline deregulation, a process that has been more gradual than in the United States. The most noteworthy change is the explosive growth of low-cost carriers, whose share of European traffic, though still relatively small, has shown a remarkable upward trend. These carriers are not burdened by the high labor costs of the major European carriers, and they are exploiting the new opportunities for route entry in the most aggressive fashion, serving many routes that lie entirely outside their home countries. While the major airlines have been slow to exploit the freedoms granted by dereg ulation, strong forces are at work behind the scenes that will ultimately reshape these carriers’ operations. The new possibility of cross-border mergers within the EU will lead to consolidation of the industry, with some former flag carriers disappearing and others growing while reorganizing their route systems to achieve greater efficiency. Many observers argue that such consolidation is sorely needed to reduce the number of European airlines, which is viewed as needlessly inflated under the flag-carrier regime.1 The first major step toward industry consolidation has been achieved with the recent completion of the Air France–KLM merger, and this event is bound to be followed by other combinations of existing carriers. Deregulation faced a more difficult challenge in Europe than in the United States. because the process had to dismantle an international institutional structure, as opposed to the purely domestic one in the United States. In particular, while freeing the domestic operations of its carriers, Europe had to sweep away the web of bilateral agreements between its countries, which governed international traffic. Such an achievement was only possible, of course, because of existence of a supra-national authority like the EU. The legacy of this old institutional structure is still very much in evidence, with European airline service still reflecting the patterns established under the old flag-carrier regime. Restructuring of Europe’s aviation sector will undoubtedly take time, although this process will be accelerated by the formidable competitive pressure emanating from the low-cost carriers. The purpose of the present paper is to provide an overview of the recent evolution of air transport in Europe, with special attention to the impact of public policies. The goal is to show how institutions and regulatory history affected the initial conditions for the process of European deregulation, while exploring how changes in these institutions and regulations have begun to transform the aviation sector. While it attempts to predict the course of the aviation sector’s future evolution, the paper also discusses further regulatory changes that are needed to fully realize the benefits of European deregulation.

1

As of 1998, the EU had 13 major carriers serving a population of 374 million, while the United States had seven major carriers serving a population of 269 million. Thus, the number of carriers per million people was almost 50 per cent higher in the EU relative to the United States (0.035 vs. 0.026). In this count, the EU carriers are Austrian, Sabena, SAS, Finnair, Air France, Lufthansa, Olympic, Aer Lingus, Alitalia, KLM, TAP, Iberia, British Airways. Major US carriers are American, United, Delta, Northwest, Continental, US Airways, and TWA.

EUROPEAN AIR TRANSPORT

3

The discussion starts in section 2 by showing how the old flag-carrier regime affected the structure of European airline networks. It is argued that this regime precluded the emergence of efficient hub-and-spoke networks, which concentrate traffic on relatively few routes. Instead, the old regime led to a profusion of point-to-point airline routes, with too many carriers providing service. By leading to relatively low traffic densities, this point-to-point system prevented European carriers from fully exploiting economies of traffic density, partly contributing to their high operating cost per passenger. Sections 3 and 4 argue that the traffic deficiency of European airlines was partly remedied in the 1990s by regulatory changes that occurred in parallel with the main course of EU deregulation. These changes allowed the emergence of immunized airline alliances along with the linked phenomenon of US open skies agreements, which were signed by a number of EU countries. Alliances and open skies agreements provided a notable stimulus to international traffic between the United States and EU countries, raising passenger flows within the networks of European carriers in a beneficial fashion. Section 5 explores the initial effects of EU deregulation itself, discussing the growth of low-cost carriers and the competitive threat that they constitute. The discussion argues that, to compete against these new entrants, major carriers need to restructure their route networks to achieve greater efficiency, while renegotiating costly labor contracts in the current US fashion. It is argued that the new freedom to pursue cross-border mergers provides one path to more rational route systems, with the new potentially larger carriers able to concentrate traffic in pan-European hub-and-spoke networks. Section 6 points out that negotiation of a Common Atlantic Aviation area may be prerequisite to such mergers. Such an agreement would eliminate the threat of losing US traffic rights following a merger, which may impede some otherwise attractive combinations of carriers. Section 7 argues that a reform of airport institutions may be needed to realize the full benefits of deregulation. The current rigid system for allocating airport slots must be replaced by a system capable of delivering slots to the carriers best able to use them, with a slot auction system being an attractive possibility. Airport congestion must also be attacked, either by appropriate use of the slot system or by congestion pricing. Finally, airport privatization may be required to ensure that airports operate efficiently, although the exercise of market power by privatized airports may be a concern.

2 EUROPEAN NETWORK STRUCTURE BEFORE DEREGULATION The structure of European airline networks in the period prior to deregulation was governed largely by geography and by the institutional and regulatory features of the old regime. Since the current network structure under deregulation partly reflects the heritage of the past, it is important to understand the sources of that heritage.

2.1 Hub-and-Spoke Versus Point-to-Point Networks To begin, it is helpful to discuss the nature of a common airline network structure that has emerged over the last several decades, especially in the United States. This


4

A

H B

C

Figure 1 HS and PP Networks.

structure is known as a hub-and-spoke (HS) network, and it is illustrated in Figure 1. For simplicity, suppose that an airline serves four cities, denoted H, A, B, and C, as in the Figure. To serve these cities, the airline could operate a point-to-point (PP) network, under which each pair of cities is connected by an airline route, allowing nonstop service in each city-pair market. Under a PP network, airline routes in Figure 1 would consist of both the solid lines and the dotted lines, with a total of six routes being operated by the carrier. Under an HS network, by contrast, the airline uses city H, which is centrally located, as a hub, and it operates just three routes, indicated by the solid lines in the Figure. While passengers in city-pair markets AH, BH, and CH still benefit from nonstop service, passengers in city-pair markets AB, BC, and AC must now make a connecting trip, changing planes at the hub H on the way to their eventual destinations. In the United States, prior to deregulation, the structure of airline networks was largely determined by regulators, who controlled entry and exit on individual routes. In the interest of providing convenient service to the public, regulators encouraged extensive provision of nonstop service, leading to a structure that resembled the PP network. With deregulation, however, airlines were free to choose the routes they served, and as a result, the pursuit of profit maximization dictated that routes be reorganized an economically efficient manner. Economic efficiency, along with desire to serve the full range of city sizes, dictated the formation of HS networks. While such a network obviously allows a carrier to operate fewer routes, as seen in Figure 1, the true source of the efficiency gain is a phenomenon known as “economies of traffic density.” With economies of density, cost per passenger falls on an airline route as the traffic volume on the route rises. This effect arises in part because high traffic volumes allow the use of larger aircraft, which have a lower cost per seat mile.2 In addition, the fixed cost of airline operations at the endpoints of the route (operation of ticket counters and other ground facilities) can be spread over more passengers as traffic density rises.

2 Without adjustment of aircraft sizes or flight frequencies, larger traffic volumes translate into higher load factors, which also reduce cost per passenger. Average load factors indeed rose following deregulation.


5

By concentrating traffic on the spoke routes in and out of the hub, the HS network reduces cost per passenger on these routes.3 Because of this cost reduction, the cost of transporting passengers in city-pair markets AH, BH, and CH, who make nonstop trips, clearly falls relative to the PP case. However, passengers in the remaining city-pair markets, who must connect at the hub, have longer flight distances than under the PP network. But, because the cost of carrying these passengers along the spoke routes is relatively low due to high traffic densities, the overall cost of transporting them is likely to be lower than under the PP network. The upshot is that the total cost of carrying passengers among the six cities in Figure 1 will be lower under the HS network than in the PP case. An additional benefit of the HS structure is that the high traffic volumes on the spoke routes allow an increase in flight frequency relative to the PP case. Offsetting this gain, however, is the reduced convenience of travel for connecting passengers, who could make a nonstop trip under the PP network but undergo a time-consuming transfer at the hub under the HS network.4

2.2 European Network Structure Under the Regulated Regime With this background, consider the structure of European airline networks under the regulated regime. Initially, it is useful to focus just on intra-European traffic, considering intercontinental traffic later. First, observe that, as European carriers were public enterprises, their incentives for profit maximization were relatively weak. Losses could be covered by government subsidies, and any profits accrued to the government and not to private owners. As a result, European carriers had little incentive to hold down labor costs, allowing their workers to enjoy the benefits of an uncompetitive environment and unlimited government support. In addition, the carriers had little incentive to achieve operational efficiencies. Against this backdrop, airline operations within Europe were governed by an extensive regulatory structure. Airline service between any two European countries was regulated by a bilateral agreement between the two countries. These agreements typically specified the routes that could be flown and the allowable capacities on these routes. The identities of the carriers providing service were also specified, with the chosen carriers usually being the two flag carriers of the countries involved. With this structure ruling out competition between the carriers on routes between European countries, and with little concern for the magnitude of profit, air fares were set in a mechanistic fashion. Generally, fares corresponded to those set under fare “conferences” organized by the International Air Transport Association (IATA). At these conferences, carriers determined mutually agreeable fares for tens of thousands of

3 A downside to hub operations that has gained prominence recently is the potential for reduced aircraft

utilization, a result of the need to expand aircraft ground time at the hub in order to facilitate passenger

connections. However, this effect does not offset the many advantages of HS networks.

4 For a discussion of the effects of US deregulation on airline networks, see Morrison and Winston (1985,

1995). For a discussion of economies of traffic density as well as empirical evidence, see Brueckner and

Spiller (1994) and Caves et al. (1984).


6

G

E

D A

C

B

F

Figure 2 European Airline Networks.

international city-pair markets. The pricing of intra-European trips under the old regime relied mechanically on these IATA fares.5 As a result of the web of bilateral agreements between European countries, each flag carrier operated a radial route network connecting its home city to the major cities of the other countries, as seen in Figure 2. In the Figure, each square represents a different European country, with the major cities indicated by A, B, C, D, and E. For convenience, let the countries be identified by a lower case letter matching the given city, so that city B is contained in country b, and so on. As can be seen, country a’s flag carrier operates routes from its home city A to the major cities B, C, D, and E of the other countries, with country b’s flag carrier serving A, C, D, and E from its home city B (these latter routes are indicated by the dotted lines in the Figure). As a result, city-pair market AB is served by the flag carriers of countries a and b, and similarly for other markets. In this market, each carrier’s flight capacity is governed by the bilateral agreement between countries a and b, and fares are set at the IATA level. Country a’s flag carrier also serves domestic endpoints within that country, as seen in Figure 2 (these cities are unlabeled and shaded in grey). Routes to Africa (country f)

5

For a discussion of IATA fares, see O’Connor (1989).


7

and the United States (country g) are also shown in the Figure, but these are considered after the discussion of intra-European traffic patterns.

2.3 HS Networks in Europe? The route network operated by country a’s flag carrier is clearly radial in nature, with routes emanating from the home city A to many destinations, both outside the country and within it. While the network thus seems to resemble the HS network of Figure 1, a question is whether the network indeed functions in the HS manner, with the carrier transporting significant volumes of connecting passengers who change planes at city A. The answer to this question is negative: despite their radial structure, European route networks prior to deregulation did not function as true HS networks, carrying large volumes of connecting traffic. Instead, these networks functioned mostly as point-to point networks, with connecting traffic apparently modest in volume. Several observations help to explain this pattern. First, the pattern of flag carrier service between countries meant that a given country’s carrier could not attract connecting passengers flying between a second and a third country. To understand this point, observe that while country a’s airline could provide connecting service between B and D via city A, passengers in the BD city-pair market already enjoyed nonstop service between these cities, which was provided by the flag carriers of countries b and d. As a result, a connecting trip on country a’s airline would hold little attraction. While this conclusion might been have been overturned in a competitive environment, where country a’s carrier could have attempted to attract BD connecting passengers by substantially undercutting the nonstop BD fare, the weak profit motive felt by flag carriers would have made such an action unlikely. Another potential group of connecting passengers, those traveling between domestic cities within country a, would also find such a trip unattractive. Two key features of the European setting account for this conclusion. First, compared to the United States, the spatial size of European countries is relatively small. As a result, domestic travel between different cities within country a may involve a relatively short distance, making airline travel unappealing, a conclusion that applies even more strongly to a circuitous, inconvenient connecting trip through city A. The effect of relatively short domestic distances is compounded by the availability of widespread and convenient rail service within Europe. Rather than flying between two domestic endpoints, a preferred choice would be to simply take the train, using a route indicated by the curved line in Figure 2. These obstacles to connecting airline travel by domestic passengers were compounded by the nature of the pricing environment. Because of the weak profit motive felt by flag carriers, they had little incentive to make connecting trips more attractive by offering relatively cheap fares. By contrast, a third group of passengers represented more plausible candidates for connecting intra-European air travel. This group consists of passengers traveling between a small city in one country and a city in a second country, either large or small. For example, a passenger traveling between one of the small domestic endpoints in country a, shown in Figure 2, and city C in country c would find a connecting trip via city A on country a’s flag carrier to be an appropriate choice. Similarly, a passenger traveling

8


between two small endpoints, one in country a and one in country c, would need to make a connecting trip using both flag carriers. The passenger originating in country a would change planes at city A and would change both planes and airlines (switching to country c’s carrier) at city C. Because both types of connecting passengers make international trips within Europe that involve at least one small endpoint, their total number was likely to be relatively small compared to the total volume of intra-European traffic. As a result, connecting traffic within Europe under the old regime was undoubtedly of limited importance. With connecting traffic limited, European airline networks thus functioned mainly as pointto-point networks, with HS operations of little importance despite the radial form of the networks. The US air travel market, by contrast, offers much greater scope for HS networks, mainly as a result of a different geography. First, while the relatively compact size of Europe means that many major cities are so close together that a circuitous con necting trip would be unacceptable, the spatial expanse of the United States leads to a greater average distance between cities. Greater distances tend to reduce the circu ity of connecting trips, with layover time also being less significant compared to total travel time. Second, the US population, which is comparable in size to that of Europe, lies within a single national boundary. There is thus no analog to flag carrier system, which automatically generates nonstop service between most pairs of major European cities. As a result, even in the US city-pair markets involving relatively large end points, nonstop service may not be available, with passengers forced to rely instead on connecting travel.6 Third, the large physical size of the United States, as well as the limited nature of rail service, means that air travel is usually necessary for trips between one small domestic endpoint and another, unlike in the European case. Such travel by necessity requires a connecting trip. Moreover, since these small-endpoint trips occur between cities in the same country, they presumably involve larger pas senger volumes than for analogous trips in Europe, which are often international in nature. Thus, connecting passengers in the United States come from two groups of travelers who, in Europe, would enjoy nonstop service or shun air travel altogether: passengers traveling in some city-pair markets involving medium and large size cities, and travelers making trips between small endpoints. The presence of these groups of passengers allows HS networks to play a more important current role in the United States than they did under the old regime in Europe. The point-to-point nature of European airline networks under the old regime was undesirable from an efficiency perspective. In effect, these networks involved the oper ation of too many airline routes. With traffic dispersed over this large number of routes instead of concentrated on fewer segments, European carriers were unable to fully exploit economies of traffic density. One result was a higher cost per passenger than could have been achieved under a more efficient HS-style route structure. This cost escalation compounded the underlying problem of high labor costs, which resulted from union

6

An example might be the Boston-Portland, OR city-pair market.


9

power coupled with public ownership of the carriers. The upshot was notoriously high airline operating costs throughout Europe.7 A second deleterious effect of the inadequate traffic densities caused by the pointto-point network structure lay in the area of service quality. As mentioned above, one byproduct of large traffic densities is high flight frequency, which raises the convenience of air travel. By depressing densities, reliance on a PP route system imposed a cost in this dimension of passenger convenience. It is important to note that the source of these inefficiencies lies both in geography and in the fundamental institutional aspects of the old regime, neither of which was easily changed. The fact that Europe is divided into separate nations, with each naturally operat ing its own flag carrier under the old regime, helped to predetermine the nature of airline networks, leading to an excessive number of airlines and airline routes. This outcome, com bined with the relative unattractiveness of domestic air travel within individual countries (a consequence of a compact geography and good rail service), helped to depress traffic densities, leading to high cost per passenger and relatively low flight frequencies.8 Mirroring the flag-carrier system of the old regime, the European air traffic control (ATC) system was similarly balkanized. Each country operated its own ATC authority, and control over each international flight within Europe was handed from one ATC authority to another as the flight progressed through European air space. Relative to a system like that in the United States, which is uniform across a broad geographical area, the presence of many separate national ATC systems introduced various inefficiencies. Coordination problems between the different systems contributed to the problem of flight delays within Europe. Moreover, the sovereignty of each country over its own air space and existence of many restricted military areas undoubtedly tended to generate inefficient flight paths, with greater circuity than necessary. Both effects contributed to high airline operating costs as well as reducing the convenience of air travel within Europe.

2.4 Intercontinental Aspects of Network Structure for European Carriers Under the old regime, Europe’s flag carriers operated many international routes to other continents, with the intercontinental routes to North America being the most important. Service on these routes was governed by bilateral agreements similar to those existing between European countries, with the routes and carrier identities specified along with flight capacities. While the observations on network structure based on Figure 2 sometimes remain relevant in the intercontinental case, important exceptions arise. The most important 7 Oum and Yu (1998) offer evidence on cost differences between EU and US carriers. They compute a composite output measure, which represents passenger, freight, and mail volumes carried by the airlines, and divide total input cost by this measure. For 1995, the resulting average unit cost was 0.95 for US carriers and 1.28 for EU carriers, for an EU cost premium of more than 30 per cent (these numbers are scaled so that the value for American Airlines is 1.00). Higher EU costs are due to the combined effects of higher input costs and lower productivity. Marin (1998) computes productivity measures for EU and US carriers, and under one measure, technical efficiency for the period 1985–1989 averaged 0.83 for US carriers and 0.69 for EU carriers. 8 For further discussion of European industry under the old regime, see Doganis (1985, 2001), Good et al. (1993), McGowan and Seabright (1989), and Neven and Roller (1996).

10


observation is that, because of the distances involved and weak condition of many non-European flag carriers, these carriers provided spotty or nonexistent service to many important destinations outside their home countries. This fact provided service opportunities for European carriers that did not exist in the case of intra-European traffic. To understand this point, return to Figure 2, and consider the intercontinental routes from country a to the African country f and the United States (country g). While a bilateral agreement may have existed between the African country and the United States, no carrier from either country may have provided the service that the agreement allowed. However, country a’s flag carrier may have served the African country under its own bilateral, while also serving the United States, as shown in the Figure. In this situation, that carrier could provide connecting service from the African city F to the US city G via its home airport in A.9 Such connecting service by European carriers to countries with weak flag carriers appears to have been commonplace, and it may have involved Western endpoints in Europe rather than in the United States. In this case, the endpoint G would instead be a city in another European country, whose relatively small flag carrier did not serve the African country. Country a’s large flag carrier could then have provided connecting service linking the African country to the European neighbor. Such connecting service is beneficial from a network perspective, helping to raise traffic densities for a’s flag carrier on important routes like that to city G. However, the volume of traffic involved is likely to be low given that the other endpoint is in Africa, or some similar location, that does not generate or attract much traffic compared to the United States. As a result, the salutary network effects of this connecting traffic were likely to have been small. Thus, the previous conclusion that European airline networks functioned largely as point-to-point networks is largely unaltered when intercontinental routes are considered.

3 THE IMPACT OF AIRLINE ALLIANCES 3.1 The Emergence of Alliances In the 1990s, the old regime of European air transport was altered by several new develop ments. The first of these changes, which coincided with the initial major steps in European airline deregulation, was the emergence of international airline alliances. The ultimate effect of these alliances was to raise the number of intercontinental passengers carried by Euro pean airlines, with beneficial effects on their traffic densities and hence costs per passenger (and ultimately profit). The growth of alliances, however, has generated regulatory con cerns both in Europe and North America. As discussed further below, these concerns have been resolved mostly in favor of the alliances, allowing their growth to proceed. The fundamental force driving the emergence of international alliances is globalization of the world economy, which has spurred intercontinental business travel while also stimulating leisure trips. In competing for this new breed of international passengers,

9 An example of this phenomenon is air service to and from India, which appears to be disproportionately provided by non-Indian carriers, despite the enormous size of the country.


11

airlines have sought to enhance the convenience and attractiveness of intercontinental trips. An obstacle to achieving this goal, however, is the fact that many international trips cannot be carried out using just one airline. Travelers are thus forced to make an “interline” trip, typically flying on two airlines (and occasionally more than two). This need for interline travel arises because no existing airline is large enough to serve most of the world’s endpoints. While the desire to better serve international passengers creates an incentive to build such an airline through cross-border mergers, airline regulation has historically ruled out such combinations, even though the last round of European deregulation makes intra-EU mergers feasible, as discussed further below. Short of a merger, airlines can try to serve more international destinations by extending their own route networks, but such efforts are hampered by unwillingness to acquire the necessary equipment and labor force and by existing bilateral agreements, which limit the number of carriers that can provide service on any given international route. With these avenues to improving international service blocked, airlines instead attempted to improve the quality of interline trips by forming alliances. Under a typi cal arrangement, the alliance partners attempt to coordinate their schedules in order to ease interline connections at gateway airports. While this coordination reduces passen ger layover times, the airlines have also strived to rearrange gate facilities to shorten walking distances. Alliance partners have also worked to improve baggage transfers for their passengers, reducing the problem of mishandled luggage that plagues traditional interline travel. Finally, the frequent flier programs of the partner airlines are typically merged, allowing passengers to earn more miles than under a usual interline trip and giving elite members reciprocal access to the alliance partners’ airport lounges. All of these changes serve to make interline travel more like a trip on a single airline, and the resulting improvement in travel convenience has allowed alliances to capture a growing share of international traffic. The major alliances are built around pairings of large US and European carriers. The key partners are United and Lufthansa for the Star Alliance, American and British Airways for the Oneworld alliance, Delta and Air France for the Skyteam alliance, and Northwest and KLM for the “Wings” alliance.10

3.2 The Effect of Alliances on Fares Alliances also generate economic benefits for interline passengers by lowering the fares they pay. The fact that airline cooperation reduces, rather than increases, interline fares may appear counterintuitive. However, the reason for this outcome in the case of interline trips is that such travel is a “joint product” resulting from the combined efforts of two carriers. Economic theory shows that cooperation between the providers of a joint product leads to a price lower than the one emerging under noncooperative behavior. To understand this point more fully, note that the airlines relied on IATA fares in pricing traditional interline trips. Such fares can be viewed as the result of noncooperative

10 It is expected that the latter alliance will be blended into the SkyTeam alliance as a result of the Air France–KLM merger.

12


behavior, where each airline specifies (in the context of an IATA fare conference) the amount it requires to carry a passenger over its portion of an interline journey, with the total interline fare equal to the sum of these amounts for both airlines. The problem with this fare-setting process is that, in determining its own required revenue from an interline passenger, an airline does not consider that a high revenue requirement hurts the other airline by raising the overall fare for the trip, which in turn depresses traffic and reduces the other airline’s profit. If the airlines were instead able to cooperate in setting the interline fare, with a goal of maximizing their joint profit, each would recognize the harm done to the other when it attempts to extract extra revenue from the interline passenger. Each airline would then restrain its own pursuit of higher revenue, and the overall interline fare would fall. Moreover, the combined profits of the carriers would rise relative to that earned under the IATA fare.11 In order to engage in this kind of cooperative pricing of interline trips, the carriers must enjoy “antitrust immunity,” which legalizes interfirm cooperation that would otherwise be disallowed. Such immunity is granted formally by the US regulatory authorities and through a less-formal process by the European Commission. Antitrust immunity is granted to carrier pairs and not to alliances more generally, and most of the pairings in the key alliances are immunized. With antitrust immunity leading, via airline cooperation, to lower interline fares, the benefits of alliance travel are enhanced. With lower fares and greater convenience reducing the full economic “cost” of interline travel for the passenger, the volume of such trips has grown in step with the expansion of alliances.12 As a result, traffic flows within the networks of the European alliance partners have expanded, and the resulting gains in traffic density have reduced cost per passenger and enhanced airline profits. To better understand the pattern of alliance traffic, consider Figure 3, which also highlights the regulatory concern that alliances have generated. Suppose that a US passenger wants to travel from city I, a small or medium-size endpoint, to city J overseas, which is not served by a US carrier. To do so, the passenger would fly on a US alliance member from I to city G, the airline’s hub, connecting to one of the carrier’s transatlantic flights to city A, the home airport of the carrier’s European alliance partner (the US airline’s routes are shown as dotted lines). At city A, the passenger would then connect to one of the partner’s flights to J. Note that while Figure 3 shows city J as being located in a third country, it could alternatively be located in country a itself. Note also that the trip pattern would be similar if the origin for the US passenger were the hub city G rather than the smaller endpoint I (in both cases, travel on the two airlines would be required). Finally, observe that a key feature of alliances is implicit in Figure 3. In particular, alliances effectively link the networks of two different carriers, making a trip within the combined network equivalent to a trip on a single airline.

11 For empirical evidence on this fare effect as well as a general discussion of the economics of alliances, see Brueckner and Whalen (2000). 12 For evidence on interline traffic growth, see US Department of Transportation (1999, 2000) (both studies can be found on the DOT website). As an example of the kind of data presented, the 1999 study shows that traffic between Northwest’s US gateways and Amsterdam, the hub of its partner KLM, increased nine-fold between the pre-alliance year 1992 and 1998. However, origin-destination traffic on these hub-to-hub routes showed only a modest increase, testifying to the huge surge in interline traffic resulting from the alliance.


13

G I

A

J

Figure 3 Travel on an Airline Alliance.

3.3 Regulatory Concerns Engendered by Alliances While clarifying the nature of a typical interline alliance trip, Figure 3 also shows a feature of alliances not considered up to this point. In particular, the Figure shows that, because the European alliance partner also serves the route between G and A, the two airlines provide overlapping service on this route. While this fact means that the US interline passenger could just as well have used the European alliance partner for both the transatlantic portion of his journey and the onward flight to J, this overlap has broader implications. In particular, the overlap may have consequences for a different group of passengers, namely, those making nonstop trips between the major cities G and A. These passengers obviously can make their journey on one airline or the other, having no need for interline travel. Normally, this choice would enhance a passenger’s prospects, with competition between the two carriers guaranteeing an affordable fare. However, antitrust immunity gives the carriers full scope for cooperation in the fare-setting process, and on a route where overlapping service is provided, this cooperation may be anticompetitive. In other words, the carriers’ license to cooperate may be used in a collusive manner in the AG city-pair market, with the carriers raising the fare in an anticompetitive fashion, knowing that passengers may have no alternative choice of service. This concern has motivated regulatory action on alliances. The European Commission recently gave its approval to the Star and Wings alliances after a multi-year inquiry, rec ognizing that the AG-type markets were relatively small in each case, and that mild mea sures could address anticompetitive concerns. By contrast, antitrust immunity for Ameri can and British Airways has been denied by US regulators. The regulators argued that the large size of the AG-type overlap markets, which consist of the heavily traveled routes between US gateways and London’s Heathrow airport, meant that losses from potential


14

anticompetitive behavior by the alliance partners could be substantial. Rather than being mild, the proposed remedy was so draconian (involving a substantial slot divestiture at Heathrow) that the carriers rejected it, settling instead for an unimmunized alliance. International alliances will prosper as long as the regulatory environment prevents cross-border mergers between the US and European carriers. In the absence of such mergers, alliances provide the only means by which airlines can compete for a larger share of international traffic. While alliances have not generated a fundamental change in the nature of European airline networks, they have led to a beneficial growth in traffic densities within the existing networks of the alliance partners. This growth has reduced, but not eliminated, the problem of inadequate traffic flows, which is caused, as explained above, by route proliferation under the flag-carrier regime as well as the compact geography and good rail service of European countries.

4 THE EFFECT OF OPEN SKIES AGREEMENTS The 1990s witnessed the signing of a host of “open skies” agreements between the US and European countries. In a typical case, an open skies agreement completely eliminates the capacity and route restrictions of the prior bilateral agreement. The US carrier is then allowed to provide unlimited service to any endpoint in the other country, and that country’s carrier(s) are allowed to fly anywhere in the United States, with capacities and frequencies of their choosing. In addition, the most-liberal open skies agreements provide unlimited “beyond” rights (or fifth freedom rights), allowing one country’s carrier(s) to provide continuing service beyond the other country to additional destinations, service that may be used both by the US passengers and local passengers originating in the other country. The proliferation of open skies agreements is intimately tied to the growth of airline alliances. In particular, as a condition for signing such an agreement, the European country typically demands that the US regulators grant antitrust immunity to the country’s flag carrier and its US alliance partner. This requirement grows out of a fear that the much larger size of the US carriers will confer an unfair advantage under open skies unless a mechanism exists to provide the smaller European carrier, which may lack the resources to massively expand service, with equivalent effective access to US endpoints. Antitrust immunity, which effectively allows the two carriers to act as a single airline in providing interline service, achieves this goal. Traffic between the United States and the open skies signatories grew more rapidly in the 1990s than on other international routes, partly reflecting the elimination of service restrictions.13 But this traffic growth partly reflects the favorable effects of immunized alliances themselves, effects that arise only because open skies and antitrust immunity are linked. As mentioned above, the traffic growth associated with open skies and alliances has been beneficial for European carriers, helping to raise traffic densities and generally strengthen their operations. Moreover, even though the beyond rights associated with

13

See US Department of Transportation (1999, 2000).


15

open skies agreements raised potentially negative consequences for European carriers, who stood to lose traffic that they previously carried, this outcome has not materialized to any significant degree. Rather than exercising their beyond rights, US carriers typically relied instead on their alliance partners to provide such service, deploying their resources elsewhere.

5 THE IMPACT OF EUROPEAN DEREGULATION Following the lead of the United States, Europe in the late 1980s launched its own process of airline deregulation. The process proceeded in stages, with a sequence of three deregulation “packages” introduced by the EU over the succeeding decade. Deregulation culminated with the “third package,” introduced in 1993, which by 1997 removed the last restrictions limiting the activities of European carriers. Currently, European airlines enjoy complete pricing freedom and the freedom to enter and exit routes anywhere in the EU, including domestic routes in another country. In addition, previous prohibitions on cross-border mergers within the EU were removed, so that the old flag-carrier regime, where airlines are associated with particular countries, can in principle be replaced by a system of broader ownership. In effect, European carriers now enjoy exactly the same freedoms within the boundaries of the EU as do carriers within the United States, despite the presence of the European national borders. The response to deregulation proceeded slowly. The initial liberalization in the first half of the 1990s apparently produced little effect, with route structures and fares showing little change relative to the old regime.14 By the end of the 1990s, however, dramatic impacts of the new regime were becoming evident. The most striking change was the launching and subsequent explosive growth of low-cost carriers, especially EasyJet and Ryanair, both based in the British Isles. The growth of these carriers was partly fueled by acquisition of other, less-successful low-cost operators, although a number of these lesser carriers still compete for business. The low-cost carriers have followed the model of Southwest Airlines in the United States by relying on flexible work rules to generate high labor productivity, by flying just one or two aircraft types to economize on maintenance and crew training, by emphasizing fast aircraft turnarounds to maximize daily usage hours, and by serving large city-pair markets but doing so from secondary airports. This airport strategy avoids the congestion that plagues major European airports, facilitating the carriers’ quick-turnaround standard, and it also economizes on airport charges, which are lower at secondary airports. In the United States, low-cost carriers mostly operate point-to-point networks. For example, although some Southwest passengers make connecting trips, the airline appears not to explicitly schedule its operations to facilitate connections.15 Because of this point-to-point strategy, Southwest is unable to serve small endpoints, which would not generate enough traffic to justify point-to-point operations. Such service is instead left to

14

See Commission of the European Communities (1996) for details.

Although JetBlue’s network also offers mainly point-to-point service, AirTran and ATA appear to rely

more on connecting passengers. For a discussion of Southwest’s service patterns and market-entry decisions,

see Boguslaski, Ito and Lee (2004).

15

16


the network carriers, which link small endpoints to their hub airports. Because all traffic to and from the small endpoint, regardless of its origin or destination, travels along the spoke route to the hub, the volume is large enough to justify service by the network carrier. By shunning such endpoints, low-cost carriers in the United States thus follow a “cherry-picking” strategy, serving only the most attractive markets. Their European counterparts, which also favor a point-to-point style of operation, have in effect adopted the same strategy. The likely impact of this type of competition on the major EU carriers provides a key to predicting the subsequent course of European deregulation. Some clues as to the effect of low-cost competition come from observing the US case. Evidence for the United States shows that, in attempting to preserve market shares, network carriers dramatically reduce their fares in city-pair markets also served by lowcost carriers, despite their cost disadvantage. Because low-cost competition has spread to an ever greater number of the network carriers’ markets, the result has been severe downward pressure on their profits. This pressure, combined with the effects of the recent overall slump in air travel, has helped push several major US airlines into bankruptcy, while threatening other network carriers with the same fate.16 With the US example providing guidance, it is possible to speculate about the likely effect of the low-cost revolution in Europe. Recall from above that, under the old regime, the flag-carrier system, geography, and intermodal competition led to the operation of too many airlines routes, most with inadequate traffic densities. Low densities, compounded by high labor costs and various operating inefficiencies, in turn led to exorbitant operating costs for European airlines. With such costs, EU carriers had to rely on high IATA fares to avoid substantial losses. This negative picture was improved somewhat in the 1990s by the traffic stimulus provided by international airline alliances. Moreover, the trend toward full or partial privatization of EU carriers, which has proceeded apace with deregulation in the 1990s, has strengthened the profit motive, and helped to hold down labor costs at a number of airlines. But the growth of low-cost competition is likely to produce the same dramatic impact on the fortunes of EU carriers as has occurred in the United States.17 First, by draining traffic in the large city-pair markets out of the major carriers’ net works, low-cost competition will exacerbate the problem of inadequate traffic densities, putting upward pressure on cost per passenger. Second, as the major carriers attempt to cut their fares to stem the traffic loss, the resulting downward pressure on revenue will interact with higher costs to cut profits. The picture is thus similar to the US case, but the EU carriers’ plight is compounded by their lower operating efficiency relative to US airlines. One effect of these developments is likely to parallel the US experience. In particular, EU carriers are likely to attack the problem of high labor costs by asking for wage concessions from their workers. Such concessions have been extracted mostly through

16

For evidence on the competitive effects of low-cost carriers in the United States, see Morrison (2001). The more favorable profit positions of EU relative to US carriers in recent years poses a puzzle given their higher operating costs. Possible explanations include the lower EU penetration of low-cost carriers relative to the US case, which results in less competitive pressure, and the greater reliance of EU carriers on transcontinental traffic, which tends to generate a higher profit than domestic traffic. 17


17

the bankruptcy process in the United States, although American Airlines gained a broad reduction in the wages of its workforce through a credible threat of bankruptcy. However, greater labor militancy in Europe relative to the United States may make this process more difficult, and its result less effective, than in the US case. A second likely response to low-cost competition is a push for greater operating efficiency through cross-border mergers between EU carriers. By allowing replacement of the flag-carrier system, such mergers would allow a rationalization of European route networks. The current proliferation of airlines and routes would be reduced, with the merger partners reorganizing their point-to-point operations in favor of US-style HS networks. Traffic densities would rise, reducing cost per passenger and improving profits. Greater densities would in turn lead to higher flight frequencies on key routes, although some passengers would be forced to make more circuitous connecting trips. The Air France–KLM merger is likely to generate some of these beneficial effects, at least in the long run. But these gains may come at the expense of a reduction in competition on routes that were jointly served by the two carriers prior to the merger. However, the widely perceived need for consolidation of the industry led EU regulators to discount these possible negative effects in approving the merger.18 Through efficiency improvements, industry consolidation may lead to some reduction in the current disadvantage EU carriers face relative to the low-cost competition, putting the airlines more or less in the situation of the US network carriers prior to the latest upheaval. But ultimate survival in the midst of the European low-cost revolution requires more draconian cost reductions of the kind currently being secured by US airlines. Whether EU carriers will be able to gain such reductions is an open question. It should be noted that European deregulation is likely to have an impact on a segment of the aviation sector that lies mostly outside the purview of government regulators: charter operations. Partly in response to high European airfares under the old regime, a substantial share of leisure passengers used charter flights rather than scheduled service to reach their vacation destinations. With deregulation putting downward pressure on fares, it is likely that leisure travelers will increasingly opt for scheduled air service rather than using charter flights. However, this change will unfold gradually as the effects of deregulation take hold. Finally, EU deregulation has been accompanied by planned changes in Europe’s air traffic control system. The changes are designed to foster greater coordination between ATC personnel in different countries under a proposal known as Single European Sky, thus reducing delays and eliminating excessive flight distances. It is expected that the proposal will be implemented in 2004, although its effectiveness in reducing ATC fragmentation in Europe remains to be seen.

6 THE ROLE OF A COMMON ATLANTIC AVIATION AREA While internal deregulation of transport in the EU is now complete, intercontinental service outside of the EU is still governed by the various bilateral agreements, some of 18

See Brueckner and Pels (2005) for an analysis of these anticompetitive effects, which include those resulting from consolidation of the Northwest–KLM and SkyTeam alliances.

18


which have been liberalized through open skies agreements. This intercontinental traffic is exceedingly important for EU carriers, accounting for a much greater share of their total traffic than in the case of US carriers.19 Thus, internal airline deregulation within the EU affects a smaller share of the airline sector than did US deregulation. Accordingly, most observers argue that the last step in the deregulation process must be elimination of the remaining restrictions on the important North American routes through creation of what is known as a Common Atlantic Aviation Area. Under this proposal, individual bilateral agreements would be replaced by a single agreement governing traffic between the United States and the EU as a whole. Anticipating such an agreement, the European Court of Justice ruled in a widely noted 2002 decision that existing bilateral agreements are illegal under EU law because they award US service rights only to the given country’s flag carrier, effectively discriminating against other EU airlines (in other words, the agreements contain a “nationality clause”). Under a common aviation area, this restriction would disappear, with any EU carrier able to provide US service from any European endpoint. At first glance, such new freedom would appear to hold little value for European carriers. For example, a carrier like Lufthansa would appear to have little incentive to provide US service from Paris, a city where Air France operates most of the flights. With limited Lufthansa operations in Paris, few connecting opportunities would be available for the airline’s passengers, making US service unattractive. Since other EU carriers similarly lack the incentive to initiate service from the home airports of other airlines, the gain from eliminating the nationality clause in existing bilaterals would not appear to be substantial. This argument, however, overlooks the effect of the nationality clause on the incen tives for cross-border mergers within the EU. The problem is that, because bilateral agreements give traffic rights to a country’s national airline, another carrier acquiring control of that airline through a merger may lose these traffic rights, thus being unable to replicate existing service to the United States. Although some remedy might ultimately be available in such a case, uncertainty about the disposition of international traffic rights greatly reduces the incentive for airline mergers within the EU.20 However, if existing bilaterals were replaced by a common aviation area, with any EU carrier able to operate any route to the United States, then this merger disincentive would be eliminated. An acquiring carrier would be free to operate all of its merger partner’s previous US routes, removing the potential merger penalty inherent in the current system.21 Cross-border mergers hold the key to survival of many major European carriers in the face of the ongoing low-cost revolution, and a key ingredient to facilitating such mergers is the kind of route-authority liberalization inherent in a common aviation area.

19

See Good et al. (1993).

This uncertainty appears to partly explain the structure of the Air France–KLM merger, where the two

carriers will initially operate as separate entities but under common ownership. This arrangement does not

jeopardize KLM’s traffic rights to the United States.

21 For a discussion of the effect of a common aviation area on potential European mergers, see Brattle Group

(2002).

20


19

Until such an agreement is in place, the mergers that are needed to achieve consolidation of the European industry may be delayed.22

7 THE INTERACTION BETWEEN AIRPORT OPERATIONS AND AIRLINE DEREGULATION The deregulation of European air transport has the potential for leading to dramatic improvements in the functioning of the aviation sector within the EU. However, full exploitation of the benefits of deregulation may be blocked if the operating procedures and pricing policies of EU airports are not reformed. The airport slot allocation system, airport congestion, and the determination of airport charges are key issues that may help determine the course of deregulation in the EU.

7.1 The Slot Allocation Mechanism As argued above, Europe currently has too many carriers and too many routes. In a fully deregulated market, these problems would vanish over time as redundant routes are dropped and inefficient carriers disappear, either through bankruptcy or mergers. These developments would mean that some airports now serving as the hubs of smaller flag carriers would lose traffic, while the secondary airports served by low-cost carriers would gain passengers. In addition, as these carriers gain an ever-larger share of European traffic, pressure will build to extend their services to the major airports. Pressure to increase traffic at the major endpoints will also come from the flag carriers (or their descendants created via mergers) as these carriers attempt to concentrate traffic in more efficient, HS-style route structures. While the demand for capacity thus can be expected to grow at the larger airports, this outcome may be blocked by the current slot allocation system. This system controls landing rights at the great majority of European airports, with a carrier needing a landing slot for a particular time of day in order to operate a flight at that time. The problem is that slots are allocated using “grandfather rights.” In other words, carriers that used their slots last year have the right to continue using the slots this year. As a result, current slot allocations reflect a heritage from the past, with slot holdings largely reflecting past allocations to the pre-deregulation flag carriers. This slot allocation system implies that inefficient, high-cost airlines can have access to an airport even though a new low-cost carrier or an efficient, former flag carrier could use the slot much more productively. To fully realize the benefits of deregulation, the slot allocation system must avoid this outcome by allocating slots to the carriers best able to use them. Under a market system, such a carrier would be one willing to pay the highest amount to acquire the slot. Given this fact, an efficient allocation system could rely on the price mechanism, auctioning scarce airport slots to the highest bidder. Since airlines are currently granted the rights to use specific slots but do not actually own them, such an auction system is

22

As of mid-2006, an agreement had not been reached, reached, despite intensive negotiations by EU and US officials.


20

institutionally feasible. By contrast, if the airlines themselves had actual ownership of the slots, such a system would not be workable. A slot auction system will generate substantial revenues, and a key question is who will receive these revenues or, equivalently, who will organize the auction. Individual airport authorities could acquire control over the slots and thus the right to organize an auction, but as discussed below, this arrangement may give the airports considerable market power. Moreover, at a number of airports in Europe, the national government currently limits the number of available slots, in which case it would be natural for the government to organize the auction. The revenues from slot auctions could be used to finance capacity, or to invest in other airport facilities that improve passenger benefits (for instance, airport accessibility). Alternatively, it could be argued that since airlines need matched pairs of slots, one at the origin airport and one at the destination airport for a given flight, the auctions should be implemented at a European level. While such “network auctions” are theoretically very complex, they are in essence no different from the spectrum-rights auctions held in the United States, which were generally considered to be a success.23 The alternative of uncoordinated slot auctions by individual national governments would be an improvement over the current slot allocation system. But since such auctions would not take into account the carriers’ need for matched pairs of slots at airports in different countries, the resulting slot allocation may not be fully efficient, preventing the full benefits of deregulation from being realized.

7.2 Airport Congestion Airport congestion may also reduce the benefits of airline deregulation. When a lack of airport capacity causes delays, airlines and passengers incur congestion costs in the form of higher operating expenses and wasted personal time. At slot-constrained airports, congestion is determined partly by the slot allocation system, which assigns slots by time of day and thus determines the daily time pattern of airport usage. Given this fact, it could be argued that excessive congestion at European airports is a result of a failure of the slot allocation system, with too many slots allocated at peak periods at a number of airports. However, other factors may contribute to existing congestion levels, absolving the slot system from some of the blame. For example, congestion at a smaller airport that is not slot-constrained may cause a flight from that airport to arrive late at a large airport, disrupting the pattern of arrivals and causing excess congestion. Delays due to in-flight congestion of the airspace, whose management is the responsibility of the air-traffic control system, may similarly cause late arrivals, disrupting traffic and generating airport congestion. Regardless of the apportionment of blame for congestion at EU airports, it must be recognized that, because of the high demand for air travel at the most convenient times during the day, some level of congestion during these peak periods should be tolerated. In other words, a conservative allocation of slots that totally eliminates airport congestion throughout the day is not in society’s interest. It is difficult, however, for authorities

23

Rassenti et al. (1982) developed a numerical model for airport slot auctions in a network setting.


21

running a traditional slot allocation system, or managing a slot auction, to tell exactly how much peak-hour congestion should be tolerated. In other words, it is hard to know how many peak-hour slots to allocate relative to the airport’s design capacity, or how many peak slots to sell under an auction system. This indeterminacy could be solved by the alternate system of airport congestion pricing. Under such a system, the first step is to calculate the external congestion costs that are generated when an airline operates another flight at the airport. These external costs equal the increased operating cost for other airlines plus the value of the extra time lost by their passengers when the given airline schedules another flight, adding to congestion at the airport. Since each airline fails to take these external costs into account, it over-schedules peak-hour flights. A congestion-pricing system corrects this problem by charging the airline a fee per flight equal to the external congestion costs it generates. Faced with this fee, the airline reduces peak flights, partly alleviating airport congestion. The congestion fee could also include other external costs beyond those directly related to congestion, such as the costs of environmental damage from airline flights (noise and pollution).24 Under a congestion-pricing system, slots are no longer used. As long as a carrier can pay the appropriate congestion fee at a given time of day, it gains airport access at that time. It is important to recognize that, because the congestion fee captures all the external costs generated by a flight, the number of peak flights, and the corresponding level of congestion, end up being the correct ones from society’s point of view.25 Even though slots are absent, there is an important equivalence between the congestion-pricing and slot allocation systems. In particular, a slot allocation system replicates the outcome under congestion pricing if the total slots allocated over the day match the flight totals chosen by the airlines when faced with congestion fees. The problem, however, is that there is no guarantee that this correspondence will actually be realized, given that choosing the number of slots to allocate is mostly a matter of guess work. For example, a well-meaning slot allocation manager may mistakenly allocate or sell too few peak-hour slots on the belief that peak congestion needs to be dramatically restricted. By contrast, the congestion-pricing system automatically generates the correct flight totals over the course of the day. It does so by basing congestion fees on hard evidence regarding congestion costs, which is derived from engineering data on the air port’s congestion properties along with data on airline operating costs and information on the value of passenger time. Note that the potential for misallocation inherent in a slot allocation system exists even when the manager relies on the price system, running a slot auction, to distribute slots among the airlines. While an auction guarantees that the slots the manager chooses to sell are allocated efficiently, going to the carriers who value them most, the problem

24

See Daniel (1995) and Brueckner (2002) for analyses of airport congestion pricing. Congestion fees need not impose a larger financial burden on the airlines than existing landing fees. The latter fees, which are constant over the day at a typical airport, can be reduced at off-peak hours while being increased during peak periods. Despite this fact, airlines usually oppose any kind of new fee system. In addition, the general aviation lobby in the United States strongly opposes congestion pricing, which would effectively exclude many small aircraft from busy airports at peak hours by imposing prohibitive costs. 25


22

of selecting the number of slots to sell still involves guesswork. Use of the auction mechanism provides no guidance in making this quantity choice. It has been argued that appropriate congestion fees cannot be computed reliably, creating an equally serious drawback for a system of congestion pricing. Some experts would dispute this point, however, arguing that reliable operating-cost and value-of-time information can be gathered to compute appropriate fees. Such concerns, along with a common preference for quantity restrictions over the price mechanism on the part government regulators, mean that use of a slot allocation system is likely to continue. However, reliance on such a system should include a recognition of its potential pitfalls.

7.3 Airport Prices While slot auctions or congestion fees could provide substantial new revenue sources for airports, the large institutional changes needed to implement such systems may not occur soon. Therefore, it is useful to consider the current system of airport pricing, recognizing that piecemeal, temporary changes may be beneficial on the path to broader reform. Given that the provision of airport capacity exhibits constant returns to scale for large airports and increasing returns for smaller facilities, economic theory says that airport charges should roughly cover the cost of operations for major airports.26 However, existing charges, which include landing fees based on aircraft weight, occasional noise surcharges, and facility rents paid by airlines and airport retailers, often bear little relation to airport costs. As a result, airports in some cases incur losses that must be subsidized by general tax revenues, while profits are earned in other cases, indicating an excessive level of charges. In a deregulated environment, airport charges that are too high put inappropriate upward pressure on the fares charged by the carriers, leading to an unwarranted economic transfer from passengers to the airport authorities. Charges that are too low, on the other hand, force the general public to subsidize users of the air transport system, while also prolonging the lifespan of inefficient carriers, whose operations may be fostered by cheap airport fees. Both problems are exacerbated when airports are operated inefficiently, with labor and capital costs higher than the levels that could be incurred under best-practice methods. A potential solution to the joint problems of inappropriate airport charges and oper ational inefficiencies is airport privatization. Private airports have an incentive to keep operational costs as low as possible and to set their prices to at least recover costs. But while airport privatization eliminates inefficiency and the need for taxpayer subsidies, it may confer market power on the airport operator, raising concerns about excessive airport charges. These concerns may be especially strong for airports that enjoy high passenger demand, because they are important destinations (or origins) for business and leisure traffic. Abuse of the resulting market power will be reflected in the level of airport charges, which the airport authority may set too high, or in airport capacity, which the authority may set too low (by limiting expansion, for example).

26

See Doganis (1992) for evidence.


23

A natural remedy for potential airport market power is government regulation of airport charges. Various characteristics of the aviation sector, however, make the result of such regulation uncertain and its use potentially counterproductive. First, price regulation may lead to under-investment in airport capacity, potentially exacerbating the problem of airport congestion. Second, it is not completely clear that airports will actually abuse their market power, in which case regulation of charges would be inappropriate. Airports may restrain their charges because the profitability of complementary activities (shopping, catering etc.) is negatively affected when they are set too high, a consequence of the resulting loss in passenger volumes. More generally, an airport may recognize that if charges are set too high, it may lose the totality of an airline’s operations, either because the carrier relocates to another more affordable facility or because it is forced into bankruptcy. This threat of a dramatic revenue loss may help to restrain the level of charges levied by the airport.27 The potential exercise of airport market power remains a problem under both an auction-based slot allocation system and a congestion-pricing system. If a private airport authority controls the slot auction, it has an incentive to limit the number of slots sold in an attempt to extract more auction revenue. Similarly, the authority could charge congestion-sensitive landing fees but set these fees at an excessive level in an attempt to extract additional revenue. These problems could be overcome if the government ran the slot auction or the congestion-pricing system, with the privatized airport operator reaping the resulting revenue. In pursuit of profit, the operator would then minimize airport operating costs as well as making appropriate capacity investments.

8 CONCLUSION This paper has provided an overview of the institutional and regulatory developments underlying European airline deregulation. It is hoped that by clarifying the nature of the air transport system as it existed at the outset of deregulation, particularly the structure of airline networks, the paper allows a better understanding of the evolutionary process initiated by this important policy action. The paper has argued that the old flag-carrier regime led to a proliferation of airlines and airlines routes, with one effect being ineffi ciently low traffic densities in European networks. By raising cost per passenger, these low densities amplified the problem of high labor expenses, contributing to the high operating costs of European carriers. While international alliances and open skies agree ments helped to boost traffic densities, the low-cost carriers that have been unleashed by deregulation, though generating substantial passenger benefits through lower fares, threaten to drain traffic out of the major carriers’ networks. A defensive response is needed, and part of this response must involve concentration of the major carriers’ traffic on fewer routes through network reorganization and cross-border mergers. While the paper has also highlighted the need for additional policy steps, especially formation of a Common Atlantic Aviation Area and new rules for airport operations, one further

27

See also Starkie (2001) for a discussion of the consequences of airport price regulation.

24


recommendation is in order. This recommendation relates to the task of measuring the effects of deregulation. The problem is that, currently, the EU lacks a systematic means for tracking changes in airfares paid by European passengers. Since the ultimate goal of deregulation is to reduce the cost of air travel for passengers by generating a more efficient transportation sector, this measurement deficiency is a critical problem. To better grasp this point, consider the case of the United States, where the Department of Transportation collects extensive data on airfares that allow researchers to investigate a host of questions regarding the performance of the air transport sector. This data source, known as the Passenger Origin and Destination Survey, is generated from a 10 per cent quarterly sample of all airline tickets. The survey indicates the origin and destination cities for a passenger, the route traveled and the carriers used, and the overall fare paid for the trip. Given the nature of the data, average fares in individual city-pair markets can be measured and tracked over time, and the effect of competition in the market and other factors can be evaluated. An alternative to using such data is to rely on the published airfares available in various sources. These data, however, do not reflect the actual fares paid by traveling passengers. For example, some published fares may hardly ever be used, making them irrelevant in any attempt to measure the performance of air transport sector. Alternatively, some researchers have collected private survey data on fares, but the volume of such data is necessarily limited. With air transport deregulation now achieved in the Europe, a high priority is for the EU to institute a system that allows its effects on fares to be measured. The relevant EU authorities should create a data collection system like the ticket-sampling system used in the United States. Such a system imposes a slight cost on the airlines, who must carry out the actual ticket sampling and report the detailed results, while also generating some cost for the government authority. However, without the resulting ability to track fares, the EU can never fully evaluate the success of its historic deregulation effort.28

REFERENCES Brattle Group, 2002. The Economic Impact of an EU-US Open Aviation Area, Brattle Group, Washington, D.C. Boguslaski, C., Ito, H. and Lee, D., 2004. Entry patterns in the Southwest Airlines route system, Review of Industrial Organization, 25(3), 317–350. Brueckner, J.K. and Spiller, P.T., 1994. Economies of traffic density in the deregulated airline industry, Journal of Law and Economics 37, 379–415. Brueckner, J.K. and Whalen, W.T., 2000. The price effects of international airline alliances, Journal of Law and Economics 43, 503–545. Brueckner, J.K., 2002. Airport congestion when carriers have market power, American Economic Review 92, 1357–1375.

28 The EU should also collect data analogous to the “service segment” data compiled by the US DOT (known as database T100). These data provide detailed information about airline operations on individual non-stop route segments (flight frequency, total seat capacity, etc.). Such data are useful in tracking route entry and exit by the airlines.


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Brueckner, J.K. and Pels, E., 2005. European airline mergers, alliance consolidation, and consumer welfare, Journal of Air Transport Management, 11, 27–41. Caves, D.W., Christensen, L.R., and Tretheway, M.W., 1984. Economies of density versus economies of scale: Why trunk and local service costs differ, Rand Journal of Economics 15, 471–489. Commission of the European Communities, 1996. Impact of the Third Package of Air Transport Liberalization Measures, Communication of the Third Package of Air Transport Liberalization Measures, 22.10.1996 COM (96) 514, final, Brussels. Daniel, J.L., 1995. Congestion pricing and capacity at large airports: A bottleneck model with stochastic queues, Econometrica 63, 327–370. Doganis, R., 1985. Flying Off Course: The Economics of International Airlines, George Allen & Unwin, London. Doganis, R., 1992. The Airport Business, Routledge, London. Doganis, R., 2001. The Airline Business in the 21st Century, Routledge, London. Good, D.H., Roller, L.-H., and Sickles, R., 1993. U.S. airline deregulation: Implications for European transport, Economic Journal 103, 1028–1041. Marin, P.L., 1998. Productivity differences in the airline industry: Partial deregulation versus short run protection, International Journal of Industrial Organization 16, 395–414. McGowan, F. and Seabright, P., 1989. Deregulating European airlines, Economic Policy 9, 282–344. Morrison, S.A. and Winston, C., 1985. The Economic Effects of Airline Deregulation, Brookings Institution, Washington, D.C. Morrison, S.A. and Winston, C., 1995. The Evolution of the Airline Industry, Brookings Institution, Washington, D.C. Morrison, S.A., 2001. Actual, adjacent, and potential competition: Estimating the full effect of Southwest Airlines, Journal of Transport Economics and Policy 35, 239–256. Neven, D.J. and Roller, L.-H., 1996. Rent sharing in the European airline industry, European Economic Review 40, 933–940. O’Connor, W.E., 1989. Introduction to Airline Economics, 4th edition, Praeger, New York. Oum, T.H. and Yu, C., 1998. Winning Airlines: Productivity and Cost Competitiveness of the World’s Major Airlines, New York, Kluwer Academic Press. Rassenti, S.J., Smith, V.L, and Buffin, R.L., 1982. A combinatorial auction mechanism for airport time slot allocation, Bell Journal of Economics 13, 402–417. Starkie, D., 2001. Reforming U.K. airport regulation, Journal of Transport Economics and Policy 35, 119–135. U.S. Department of Transportation, 1999. International Aviation Developments (First Report): Global Deregulation Takes Off, Office of the Secretary, U.S. Department of Transportation, Washington, D.C. U.S. Department of Transportation, 2000. International Aviation Developments (Second Report): Transatlantic Deregulation—The Alliance Network Effect, Office of the Secretary, U.S. Depart ment of Transportation, Washington, D.C.



2 Wage Determination in the US Airline Industry: Union Power Under Product Market Constraints∗ Barry T. Hirsch†

ABSTRACT The chapter analyzes wages in the US airline industry, focusing on the role of collective bargaining in a changing product market environment. Airline unions have considerable strike threat power, but the exercise of bargaining power is constrained by the financial health of carriers. Since airline deregulation, compensation has waxed and waned in response to the industry’s economic environment. Airline workers capture sizable rents following good times and provide concessions following lean times. Compensation at legacy carriers has been restructured, some from within and some from outside of bankruptcy, but it remains to be seen whether compensation will continue its long-run movement toward opportunity costs. Evidence from the CPS for 1995–2006 shows that wage premiums for airline industry workers, particularly for pilots, remain with existing premiums almost entirely a union phenomenon. Much of the gap in wage scales between major and mid-size carriers was erased in the mid-2000s concessionary cycle, but these rates remain much higher than rates

∗ Helpful comments were received from Gary Fournier, Jim Gillula, Darin Lee, Nick Rupp, and seminar participants at the University of Kentucky and the Southern Economic Association meetings. I thank Dan Kasper and Darin Lee for providing Form 41 labor cost data. Numbers reported in Table 3 reflect work done with Michael Wachter and James Gillula, presented in United Airlines’ 1113(c) bankruptcy hearing. The views expressed in this chapter are mine and need not reflect the opinion of others. Work for this chapter was conducted while the author was at Trinity University, San Antonio, Texas. † W.J. Usery Chair of the American Workplace, Department of Economics, Georgia State University, Atlanta, GA 30302; e-mail [email protected].

BARRY T. HIRSCH

28

at regional carriers. Compensation levels at regional carriers may approximate opportunity cost – the compensation that would be necessary to attract and retain qualified employees throughout much of the industry. Because unions retain bargaining power at the major carriers, wages are likely to head upward as carriers’ financial health returns. Such wage levels may or may not be sustainable in the inevitable next downturn.

1 INTRODUCTION The air transportation industry has realized rapid growth throughout its history. Despite this growth, carrier profitability since deregulation has proven volatile and corporate viability far from certain. With one exception, every major carrier at the time of deregu lation in 1978 has either failed, had its operations merged into another airline, or been in bankruptcy protection. The exception, American Airlines, narrowly avoided bankruptcy in 2003 following wage concessions from its unions. As is the case for most companies, labor compensation among airlines accounts for a substantial share of total costs.1 In much of the industry, compensation is determined through collective bargaining; thus, workers’ pay may deviate substantially from oppor tunity costs. While union density economy-wide has sharply declined, the airline industry has remained highly unionized. The percentage of workers who are union members in the air transportation industry was 49.2% over the 1973–1978 regulatory period and 49.4% in 2005. Union coverage rates for flight personnel and ground workers are higher. In contrast, private sector union density economy-wide fell from 24.2% in 1973 to 7.8% in 2005.2 No private sector industry has union density as high as does air transportation.3 More than any other private industry, airlines face unions who possess substantial bargaining power, that power emanating from the ability of a strike to shut down and bankrupt a carrier. Of course, it is not in the interests of workers and their unions to destroy their employers, so union demands are constrained by the financial health of carriers. Hence, the airline industry has developed a compensation pattern in which its union workers “tax” potential profits following the onset of good times, but agree to moderate contractual pay increases or provide wage and benefit concessions following the onset of bad times. For many if not most airlines and their unions, this product market

1 During much of the 1980s and 1990s, labor costs accounted for about a third of total expenses. This share peaked at 38% in 2002, a level not seen since 1979 and in the earlier regulatory period. The labor cost percentage fell substantially after 2002, to 36% in 2003, 30% in 2004, and 26% in 2005 (24% in 2005:4). Fuel costs, which accounted for 12% of total expenses in 2002, rose to 23% of expenses in 2005 (Air Transport Association, 2006, Labor and Fuel tabs). 2 Union density figures are compiled from the Current Population Survey (CPS). The 1973–1978 air trans portation figure is in Hirsch and Macpherson (2000, p. 136), while the 2005 figures for air transportation and the private sector are from Hirsch and Macpherson (2003, updated annually at www.unionstats.com). Prior to 2003, the air transportation industry included air courier services (e.g., largely nonunion FedEx), which were small during 1973–1978. Were these included in the 2005 figure, union density would be about 10 percentage points lower. 3 Two industries have higher union density, the predominantly public railroad transportation industry and the entirely public US Postal Service (www.unionstats.com).

WAGE DETERMINATION IN THE US AIRLINE INDUSTRY

29

union wage cycle has been accompanied by a contentious labor relations environment with no small amount of distrust on all sides.45 Following the strong financial health of the industry in the late 1990s, generous labor contracts and high labor costs took force in the early 2000s. The increased compensa tion was accompanied by a “perfect storm” of negative events – a recession in 2001, sharp declines in traffic following the 11 September, 2001 attacks, Internet pricing, increasing market shares among “low-cost carriers” and concomitant declines among hub-based legacy carriers, and, more recently, high fuel costs over a sustained period. The convergence of high operating costs and intense price competition resulted in bankruptcies among four legacy carriers (US Airways, United, Delta, and Northwest) and several mid-size and regional carriers. During 2004–2006, wages and benefits among the legacy carriers have been falling, either under the threat of or following bankruptcy.6 The recent restructuring of labor costs in an increasingly competitive airline industry has been substantial. Lower labor costs, a decrease in debt burden among carriers emerging from bankruptcy, relatively strong demand, and reduced capacity among the legacy carriers have improved major carriers’ financial prospects. At the same time, high fuel costs and, more fundamentally, the emergence of more competitive product markets and a high level of price competition, have served to keep profits at low levels, at least through mid-year 2006. But the future will not be an extension of the present. During the two decades following airline deregulation, periods of union wage concessions have been followed by rebounding wages as airlines’ profits recovered. Continuation of this pattern requires not only the presence of strong unions that can appropriate company profits, but also product market innovations and a degree of pricing power that generate profits to be taxed.7 The purpose of this chapter is to examine the role of unions and describe recent wage determination in the airline industry. A key question posed in this study is whether or 4 There is a large industrial organization literature on the airline industry, but little on the airline labor market. References to past studies are provided in Hirsch and Macpherson (2000); see, for example, Card (1998), Crémieux (1996), and Johnson (1995). Nay (1991) provides an early statement on union wage cycles in the airline industry. 5 Airlines differ from other US private sector industries in that collective bargaining is governed not by the National Labor Relations Act (NLRA), but by the Railway Labor Act (RLA) of 1926, amended in 1936 to apply to the airline as well as railroad industry. As compared to the NLRA, the RLA provides more specificity as to the negotiation and mediation procedures that parties must adopt in a labor dispute prior to a strike. The bargaining structure that evolved under the RLA was decentralized, with separate unions by craft and carrier-specific contracts. 6 Companies in bankruptcy cannot unilaterally void their union contracts and implement lower pay but, under U.S.C. § 1113(c), can request that a bankruptcy judge do so. The company must show that wage and benefit cuts are necessary for the company to successfully emerge from bankruptcy and that the cuts are equitable. The equity provision can be examined through a comparison of contract rates with estimates of market compensation and by showing how pay cuts are distributed across employee groups. In most cases, the employer and union agree on new wage and benefit terms, often with prodding from the judge, prior to a decision being made on voiding a contract. 7 Although not addressed in this chapter, union wage demands may be constrained by a company’s level of debt, given that increasing leverage reduces liquidity. Knowing this, union companies’ optimal debt levels will be higher than for nonunion companies. For theory, supporting evidence, and references to prior literature, see Matsa (2006).

30

BARRY T. HIRSCH

not the current decrease in wages and benefits in the industry represents a permanent shift in the level of compensation, or whether there will be a resumption of the historical cycle of rising union wage premiums following the onset of good times and subsequent wage concessions following lean times. In order to address this question, it is critical to estimate the level of opportunity cost wages in the airline industry. Subject to a number of caveats, well know in the labor economics literature, compensation in competitive markets will tend toward opportunity wages – what similar workers in similar jobs might have obtained in alternative employment.8 Compensation cannot be expected to fall below a competitive level, at least not for any sustained period. Thus, a reasoned judgment as to the pattern of future wages in the airline industry requires that we know how airline wages diverge from opportunity wages. To estimate this divergence, it is necessary not only to compare the wages of unionized airline employees at legacy carriers to wages elsewhere in the airline industry, but also to the opportunity wages outside the industry. The plan of the chapter is as follows. Section 2 provides a brief discussion of how the level and dispersion in airline labor costs have changed over time. Section 3 provides analysis on overall airline industry wage differentials using the Current Population Survey (CPS) for 1995 through 2006, focusing on the unionized sector of the air transportation industry. Section 4 follows with a more detailed focus on union and nonunion CPS wage differentials by airline industry “craft” (pilots, flight attendants, mechanics, fleet service, agents, and other). In Section 5, carrier contract data are presented that permit a comparison of pay by craft at major carriers with pay for those same occupations at regional airlines. A final section of the chapter addresses, but does not fully answer, the two questions stated above. First, given the evidence, what is the level of opportunity cost wages? Second, will the future be one in which earnings move toward opportunity costs or will we continue to observe cycles in which union wages rise well above and subsequently fall toward opportunity costs, depending largely on airlines’ ability to pay?

2 AIRLINE LABOR COSTS OVER TIME Labor cost is only one of many determinants of an airline’s financial health, but it is an important one. In each of the three years from 2001–2003, the four airlines with the highest compensation per employee (Form 41 salaries and benefits, as presented

8 A wage premium is defined here as payments to labor beyond long-run opportunity costs; that is, what workers could have earned in an alternative job path entailing similar investments in training and similar working conditions. Employees’ current pay is often greater than the pay they could get at an alternative job. These short-run premiums (quasi-rents) derive from costs associated with job mobility, firm- and industryspecific skills, and implicit contracts in which earnings deviate from spot marginal products. Efficiency wage theory proposes that in some settings, wages in excess of opportunity cost may lower per unit costs and are thus consistent with profit maximization. The reasoning is that in workplaces with high monitoring costs, voluntary effort may increase in response to high wages, either to reduce the risk of firing or as a result of positive reciprocity (these explanations seem to apply less readily to union than nonunion workplaces). For discussion, see Cahuc and Zylberberg (2004, pp. 353–360).


31

below) were US Airways, United, Northwest, and Delta. Dispersion in compensation across airlines was relatively high. Not coincidentally, these four airlines ended up in bankruptcy protection.9 American, a close fifth in labor cost per employee during 2001–2003, went to the brink of a bankruptcy filing in 2003, backing off from filing following concessions from its unions. Wage and benefit concessions at high-cost carriers have led to declines since 2003 in average industry compensation per employee and in pay dispersion across airlines. Much of the analysis in the chapter utilizes the CPS, the monthly household survey of individuals conducted jointly by the US Bureau of the Census and Bureau of Labor Statistics. The CPS, however, is not ideally suited to track year-to-year changes in airline labor costs among large national carriers. First, sample sizes of air transport workers each year are not large. Second, a portion of air transport workers do not work for passenger airlines and, among those working for airlines, one cannot differentiate employees of major versus regional or other airline services. And third, the CPS allows one to measure earnings, but not the dollar cost of benefits. Form 41 data reported by certificated carriers to the Department of Transportation (DOT) is better suited than CPS data to track airline labor costs over time. Figure 1 presents average total compensation (real salaries and benefits, in 2005 dollars) per

$95,000

18.0

Compensation (2005$)

16.0 $85,000 15.0 $80,000 14.0 $75,000 13.0 $70,000 12.0 $65,000

Coefficient of Variation (CV)

17.0

$90,000

11.0

$60,000

10.0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year Compensation


Compiled from figures reported by US Department of Transportation, Bureau of Transportation Statistics, Form 41. See Appendix Table A1 and text for a listing of the numbers and further details.

Figure 1 Airline Wages and Benefits, Level and Dispersion, 1990–2005.

9 US Airways entered bankruptcy protection in 2002 and again in 2004, United in late 2002, and Delta and Northwest on the same day in September 2005.

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BARRY T. HIRSCH

airline employee during 1990–2005, and the dispersion across airlines in average com pensation (Appendix Table A1).10 The data include all major and most national carriers.11 The number of carriers differs by year, as smaller airlines move in and out of the industry or mergers occur; there was a maximum of 19 in 2000 (with 12 in 1990 and 13 in 2005).12 Calculations are based on weighted averages, with airline employment by year as weights. Compensation and, subsequently, costs per available seat mile (ASM) are expressed in 2005 dollars using the CPI-U (current series). As is evident in Figure 1, average real compensation among carriers (shown by the “diamonds”) increased briskly through 1994, stayed relatively flat (or fell slightly) throughout the rest of the 1990s, and then increased after 1999. One sees large increases in average real compensation in 2000, 2001, and 2002, followed by small, moderate, and large decreases in 2003, 2004, and 2005, respectively. The real level of compensation in 2005 is similar to that seen in the mid-1990s. Also shown in Figure 1 (see the “squares”) is the dispersion in compensation across carriers, measured by the employment weighted coefficient of variation. High pay disper sion generally produces cost differences that cannot be sustained. Dispersion decreases when low-pay airlines play catch-up and/or when high-pay airlines fall back toward the pack. Pay dispersion had declined during the late 1990s, but increased following pay hikes taking effect in 2001–2003. Wage and benefit concessions since 2004 among the high-cost carriers have reduced pay dispersion. Figure 2 provides an alternative measure of labor costs constructed from Form 41 data, measuring cents per ASM, in 2005 dollars, for 1990–2005. Obviously, labor costs per seat mile are affected not only by costs per worker, but also by employment, productivity, airline capacity, and the like. The pattern evident in Figure 2 (see the “diamonds”) is one of a gradual but steady decline in real labor costs per ASM from 1990 through 1997, modest increases in costs until 2000, an upward break with sharply increased costs in 2001 and 2002, followed by substantial decreases after 2002, from 4.7 cents per ASM in 2002 to 3.3 cents in 2005. The recent decline in costs per seat mile came about not only through decreases in compensation per worker, but by steep declines in employment at the legacy carriers. Figure 2 also shows the dispersion across carriers in labor costs per ASM. The coefficient of variation (the “squares”) stayed constant at about 20 through the 1990s, but declined sharply in 2003–2005 to about 15. Undue weight should not be placed on this single statistic, but by this measure the cost structure across airlines was more similar

10

The values shown in Figures 1 and 2 are provided in Appendix, Table 1. Daniel Kasper and Darin Lee of LECG kindly made available Form 41 information on compensation and labor costs per ASM by airline. Employment data for certificated carriers, used to construct weights, were obtained from the Bureau of Transportation Statistics at http://www.bts.gov/programs/airline_information/number_of_employ ees/certificated_carriers/index.html. 11 The DOT defines a national airline as having at least $100 million in annual revenue and a major airline $1 billion. 12 In 2000, included airlines accounted for 91% of total employment among all DOT 41 “major” and “national” certificated carriers (excluding Airborne Express, FedEx, and UPS). In 1990 and 2005, the corresponding numbers were 87% and 81%, respectively. The “low” figure in 2005 reflects sharp declines in employment at the included large legacy carriers included in Figure 1, coupled with growth in employment among small airlines not included.

33

5.00

26

4.75

24

4.50

22

4.25

20

4.00

18

3.75

16

3.50

14

3.25

12

3.00


Labor Cost per ASM (2005$)


10 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year Labor Costs per ASM


Compiled from figures reported by US Department of Transportation, Bureau of Transportation Statistics, Form 41. See Appendix Table A1 and text for a listing of the numbers and further details.

Figure 2 Labor Costs and CV Per Available Seat Mile, 1990–2005.

in 2005 than at any time since at least 1990. All else the same, similar cost structures across airlines should be associated with more stable prices and financial outcomes.

3 WAGE DIFFERENTIALS IN THE AIR TRANSPORTATION INDUSTRY: MEASUREMENT AND DATA Are unionized airline workers paid wages above long-run opportunity cost? If so, how large are these premiums? Do wage premiums vary across airline crafts? And do nonunion as well as union airline workers receive premiums? These seemingly straight forward questions are not easy to answer, at least not in a precise manner. The difficulty arises from a combination of methodological issues (e.g., what are the appropriate com parison groups for airline workers) and data limitations (e.g., company level data do not provide measures of worker attributes, while public data on individuals and their attributes do not permit one to easily examine differentials within the industry – say across major versus regional carriers or among those at passenger airlines versus air freight companies). Of course, limitations arise to some greater or lesser degree in all research endeavors. For the research questions posed in this chapter, a variety of evi dence allows one to paint a reasonably clear picture of wage determination in the airline industry. This section follows and extends the approach utilized by Hirsch and Macpherson (2000) in their study of wage determination in the airline industry from 1973 through

34

BARRY T. HIRSCH

1997. The CPS analysis uses individual wage and salary worker data for September 1995 through May 2006.13 Following Hirsch and Macpherson, six air transportation groups of workers are identified using the CPS – five airline crafts plus a residual category. The five craft groups are pilots, flight attendants, mechanics, fleet service (ramp and utility) workers, reservation agents and clerks, and an “other” category. For the five airline craft groups, comparison groups of individuals comprising nonairline workers employed in specific sets of occupations are identified. Workers in those occupations serve as comparison (control) groups in order to measure relative wages. For the “Other” category of airline workers, a comparison group of nonairline workers across the economy is used. Relative wage differentials between the air transport and comparison group workers are estimated within a regression framework, controlling for measurable worker, location, and job characteristics. Section 4 and Appendix Table A2 describe the construction of the CPS comparison groups for each of the six air transport groups. The empirical approach is as follows. Separate wage equations by craft are estimated, with each regression sample from the 1995–2006 CPS including both an airline “treat ment” group (pilots, etc.) and a large comparison group of workers. From each wage equation, whose coefficients are determined largely by the nonairline comparison group, I calculate log wage differentials for union and nonunion air industry workers, rela tive to measurably similar comparison group workers outside the air transport industry. Industry-wide wage differentials based on the full sample of air transport workers are calculated based on the weighted average across the six groups, using fixed air transport employment weights over the time period. In addition to controlling for a typical set of worker human capital, demographic, and location characteristics reported in the CPS (e.g., schooling, age, region), an occupational skill level and working condition variable, constructed by the BLS, is matched to the CPS. The principal purpose of this additional control variable is to account for occupational skill differences not captured by worker schooling and experience measures. Specifically, let ln Yigt = kgt Xikgt + g U Air igt + g N Air igt + c Occcit + ln Skilli + it

(1)

where ln Y is the natural logarithm of the wage, i designates individual, g indexes six airline craft groups and their corresponding control groups, and t is year. Included in X are k worker and labor market control variables (listed below) with k the corresponding coefficients. A “level of work” variable, Skill, defined at the detailed occupation level is shown separately since results are presented with and without its inclusion. Air is a dummy variable set to 1 for each of the g air industry craft groups. Air is interacted with index variables designating whether a worker is covered (U ) or not covered (N ) by a collective bargaining agreement. Occ is a set of c broad occupation dummies used only in the regression for “Other” air industry workers – the nonspecified craft group

13 September 1995 is the first month following 1994 CPS revisions in which imputed earners, excluded from the analysis (see below) can be identified. May 2006 was the latest CPS file released when this paper’s empirical analysis was executed. This 10-plus year period includes both low and high points in airline wage-profit cycles.


35

and an economy-wide control group. Year dummies for 1997 through 2006 are included in X, with 1995–96 the omitted base period. Coefficients g and g provide estimates of log wage differentials by airline craft group g for union and nonunion workers, respectively, in both cases as compared to the appropriate comparison group made up as a mix of union and nonunion workers.14 Weighted averages of these coefficients thus provide estimates of the airline wage differentials d of interest. That is du = wug g

(2)

dn = wng g

(3)

Estimates of the air transport log wage differentials are shown for union air transport workers (du ), nonunion air transport workers (dn ), and union and nonunion combined. The differentials are estimated with and without control for ln Skill. The weights wg for union and nonunion workers represent the CPS employment shares of the six air industry worker groups fixed over the 1995–2006 period.15 CPS wage differentials were also estimated by year, but are not presented. Little systematic pattern is found, presumably due to large year-to-year variation in the air transport industry samples reporting earnings. The air transport and comparison group samples include full-time nonstudent wage and salary workers ages 18 and over. To enhance the relevance of the comparison group, excluded are workers with less than a high school degree (with the GED categorized as high school) and education beyond a masters degree. No education restrictions are placed on the air transport sample. In the regression analysis, the relatively few airline workers with less than a high school degree are assigned to the high school category and those few with a degree beyond the masters level are assigned to the masters category. With the exception of flight personnel (pilots and flight attendants), full-time status is defined as reporting 35 or more usual hours per week on the principal job. The reporting of hours worked by flight personnel presents a problem, however, since some report only paid flight hours, while others report all hours away from home. Flight personnel who report 15 or more hours worked per week are retained as full-time workers. Usual weekly earnings reported by pilots and flight attendants is only weakly related to their reported weekly hours worked, ruling out the calculation of an hourly wage based on weekly earnings divided by weekly hours (construction of the wage is described below). Approximately 25–30% of workers in the CPS are either unwilling or unable to report their earnings. These individuals have weekly earnings “allocated” by the Census based on an imputation procedure in which nonrespondents are assigned the earnings of a “donor” with an identical set of match characteristics (Hirsch and Schumacher, 2004).

14 That is, union status is not included as a control in X. The assumption here is that the opportunity cost wage for each group is best approximated by an implicitly weighted average of union and nonunion wages. 15 The weights are calculated prior to omission of imputed earners and using CPS employment weights. Use of fixed weights over time means that changes in the wage gap estimates result from wage changes and not from worker mix changes. Since imputation rates can differ across airline craft groups, weights are determined prior to the exclusion of earnings nonrespondents.

36

BARRY T. HIRSCH

All those with imputed earnings are excluded from the analysis. It is important that they be excluded in order to avoid severe attenuation toward zero in wage gap estimates with respect to the airline industry and union status. Neither industry nor union status is a match criterion used to assign a donor’s earnings to a nonrespondent. Hence, air transport industry nonresponents will typically be assigned the earnings of nonairline donors. Union nonrespondents will typically be assigned the earnings of nonunion donors. Broad rather than detailed occupation is an imputation match criterion, thus nonresponding pilots (aircraft mechanics, etc.) will typically not be assigned the donor’s earnings of other pilots (aircraft mechanics, etc.). Unless imputed earners are excluded (or an explicit bias correction method used), wage differentials with respect to industry, union status, and other nonmatch criteria will be seriously attenuated. Hirsch and Schumacher (2004) show that “match bias” (i.e., the attenuation in coefficient estimates) roughly equals the proportion of nonrespondents.16 Imputed earners cannot be identified in the CPS between January 1994 and August 1995. Hence the analysis in this chapter begins with September 1995. Public use files of the CPS include an edited usual weekly earnings measure that is topcoded (i.e., capped). For years prior to 1998 (and after 1989), weekly earnings are capped at $1,923 ($100,000 annually) and for years since 1998 at $2,885 ($150,000 annually). Apart from pilots and a few managerial or professional workers, few air transport industry workers have top-coded earnings. For nonpilot air transportation workers and all comparison group workers with weekly earnings at the cap, they are assigned the estimated mean earnings above the cap based on year and gender-specific estimates that assume a Pareto distribution for earnings beyond the median (see Hirsch and Macpherson, 2006, p. 6; posted at www.unionstats.com). Values are moderately higher than 1.5 times the cap, with somewhat smaller female than male means and growth over time. Top-coded earnings among pilots is widespread, more so than for any other occupation in the CPS, but the right tail of their earnings distribution is probably less skewed than implied by the Pareto distribution (i.e., fewer extremely high earnings). During September 1995–August 1996, the first 12 months used in our sample, 20.0% of pilots who reported earnings were above the $1,923 weekly earnings cap, as compared to 9.6% in 2000 and 14.3% in 2005 with the higher $2,885 cap that began in 1998 (Hirsch and Macpherson, 2006).17 Because many senior pilot contracts are for amounts not far above the cap, I assign pilot means above the cap that are much lower than the Pareto means. For the years prior to 1998, pilots with weekly earnings greater than $1,923 have their earnings set at 1.25 times the cap, or $2,404. For years beginning in 1998, pilots with weekly earnings greater than $2,885 have their earnings set at 1.25 times the cap, or $3,606. These estimates seem likely to be conservative (i.e., produce too low a pilot/nonpilot wage differential). Moreover, use of the same multiple for all years

16

Match categories include education, age, gender, race, hours worked, broad occupation, and receipt of tips,

commission, or overtime. Bias due to imperfect matching (e.g., a PhD matched to an earnings donor from the

BA or above category) is analyzed in Bollinger and Hirsch (2006).

17 The pilot sample in 2005 has an unrepresentative number of high earners as compared to earlier years and

2006.


37

fails to capture some of the highest pilot contract increases and subsequent concessions realized over this period.18 For air transport workers apart from pilots and flight attendants, plus all comparison group workers, the wage is defined as follows. Hourly earnings are calculated as equal to usual weekly earnings (which includes typical overtime, tips, and commissions) divided by usual hours worked per week.19 For pilots and flight attendants, reported hours worked per week are ignored, since variability across workers contains little information.20 For pilots, the wage is calculated as weekly earnings divided by 40, while for flight attendants, weekly earnings are divided by 36. This approach is explained below. Finally, the earnings measure for all workers is converted to 2005 dollars using the CPI-U (Current Series). One cannot avoid making some rather arbitrary assumption as to how job-related hours among flight personnel compare to work hours among other workers. The earnings measure that is used implicitly assumes that job-related time spent by pilots (flight hours, wait time, and travel time) entails similar disutility on average as does 40 hours of paid work plus nonpaid travel time for nonflight air transport and comparison group workers. For flight attendants, the assumption is that a typical week is equivalent to 36 hours of work in comparison group jobs. Pilots’ mean reported hours worked in the CPS is 40.9 overall (and 39.7 for union pilots). Flight attendants’ mean reported hours worked in the CPS is 32.5 overall (and 32.0 for those unionized). If the hours assumptions of 40 and 36 for pilots and flight attendants, respectively, overstate (understate) the disutility associated with hours worked by flight personnel, then the wage differential estimates for these groups are too low (high). Included in X – the control variables – are education dummies (5) reflecting levels from a minimum of a high school degree (including a GED) through a masters degree, potential experience in quartic form separately and interacted with gender (experience being proxied by the minimum of age minus years schooling minus 6 or years since age 16), gender, race/ethnicity (4), foreign born, region (8), metropolitan area size (6, with nonmetro the base), year dummies (10), and broad occupation dummies (11, included only for the “Other” group regression). In addition to the control variables in X, earnings differentials are estimated with an included occupation or job duties variable, ln Skill, compiled by the BLS for the approx imately 500 Census occupation groups. As described in Pierce (1999), the unit of anal ysis for the National Compensation Survey is the detailed occupation cross-classified by work level. The NCS uses the Census occupation codes (COC) included in the CPS. For each Census occupation, 10 job attribute factors are defined, each with various levels.

18 Regression estimates of pilot earnings premiums are about .10 log points higher when Pareto means rather than the more conservative 1.25 multiples are used. 19 A small number of individuals do not report usual hours worked per week and instead have their hours worked value imputed (i.e., assigned) by the Census. These individuals are excluded from the estimation sample. For nonflight personnel and all comparison group workers, individuals who report “variable” weekly hours have the wage determined by usual weekly earnings divided by hours worked last week, which adds noise to the independent variable but is unlikely to bias coefficients. 20 Commercial airlines hire few part-time pilots or flight attendants. Recall that those reporting less than 15 hours worked per week are excluded from the sample.

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BARRY T. HIRSCH

These are as follows: knowledge (9 levels), supervisory controls (5), guidelines (5), com plexity (6), scope and effect (6), personal contacts (4), purpose of contacts (4), physical demands (3), work environment (3), and supervisory duties (5). Each of these job attribute factors and levels were awarded “quality points” by BLS analysts in order to develop a single occupational job attribute index. This occupational job factor index is highly correlated with earnings (Pierce, 1999). Allegretto et al. (2004) have previously merged this BLS index with the CPS and used it in their study of public school teacher salaries. The job factor index, referred to here as “Skill” (but which measures a broad range of attributes, as indicated above), was obtained from the BLS for 1990 COC, used in the CPS through 2002. Beginning in 2003, the CPS adopted 2000 COC, many of which cannot be mapped one-to-one with the 1990 COC. Codes used for the five airline crafts could be mapped cleanly. For the remaining air transport industry workers and all comparison group workers beginning in 2003, each worker was assigned a 1990 COC based either on a direct match to their current COC or from a probabilistic mapping between 1990 and 2000 COC provided by the Census. “Skill” was then matched to each worker’s assigned 1990 COC. Included in the earnings equations is ln(Skill). Its coefficient represents an elasticity; e.g., = 025 implies that earnings increase 2.5% for each 10% increase in the skill index. The BLS skill index does not cover Census occupations that are exclusively federal (e.g., Postal Service workers), private household, and agriculture, forestry, and fishing occupations. The exclusion of these occupations from the analysis reduced sample sizes very little. Earnings equation results (not including “Skill”) with and without these occupations are nearly identical.

4 EARNINGS IN AIR TRANSPORTATION AND AMONG COMPARISON GROUPS: DESCRIPTIVE EVIDENCE This brief section provides descriptive evidence from the CPS on earnings differentials between union and nonunion air transportation workers and “comparable” workers out side the airline industry. A subsequent section examines the earnings premium estimates derived from the regression analysis. Table 1 provides the CPS sample sizes, employment weights, mean earnings (in 2005$), and “BLS Skill values” for the air transportation industry, for each airline craft group (separately by union status), and for the corresponding comparison groups. As noted previously, the earnings sample for September 1995 through May 2006 includes only those who respond to the earnings question and not those whose earnings have been imputed (assigned) by the Census. The CPS sample size of air transportation industry workers over the period 1995–2006 is 6,835, with roughly equal numbers of pilots, flight attendants, and mechanics (about 900 each). The sample size of agents (reservation agents, gate agents, and stores employees) is moderately larger (about 1,200), while the sample size of the fleet service workers (i.e., baggage handlers, cleaners, and other ground workers) is substantially smaller. The residual group of “Other” air transport workers is quite large, about 2,600. Estimates of industry wage differentials are based on the weighted average of estimates across the six employee groups (jointly and separately by union status). The group weights (shown in rows labeled “Weights”) are calculated


39

Table 1 CPS Mean Wages (2005$) and Skill Index, by Airline Craft and Comparison Groups Union and Nonunion

Union

Nonunion

Comparison Groups

All air transport Wage Skill index N

$22.88 1,274 6,835

$27.03 1,241 2,971

$19.68 1,299 3,864

$19.29 1,282 877,302

Pilots Wage Skill index N Weight

$43.09 2,225 879 0.125

$49.38 2,225 580 0.197

$30.86 2,225 299 0.072

$27.30 1,864 76,702

Flight attendants Wage Skill index N Weight

$21.24 933 893 0.134

$22.09 933 648 0.219

$18.99 933 245 0.070

$15.56 896 278,593

Mechanics Wage Skill index N Weight

$23.73 1,577 924 0.131

$26.58 1,578 465 0.156

$20.84 1,577 459 0.112

$18.75 1,204 36,419

Fleet service Wage Skill index N Weight

$15.38 508 343 0.042

$17.67 446 155 0.046

$13.49 560 188 0.038

$12.85 437 16,050

Agents Wage Skill index N Weight

$16.41 733 1,203 0.175

$17.84 727 523 0.157

$15.32 737 680 0.189

$13.69 661 14,682

Other Wage Skill index N Weight

$20.23 1,312 2,643 0.393

$21.55 1,019 609 0.225

$19.83 1,400 2,034 0.520

$19.29 1,282 877,302

Means are compiled from the CPS monthly earnings files, September 1995–May 2006. Wages, shown in 2005$, measure the hourly earnings for non-flight personnel, calculated over the sample (of size N) excluding imputed earners. For flight personnel, wages are calculated based on weekly earnings and an assumed 40 hours week for pilots and 36 hours week for flight attendants. The airline and comparison worker groups are described in the text. The BLS Skill index points are described in text and in Pierce (1999). Group weights, calculated from CPS employment weights for the CPS sample including imputed earners, are used to compile the overall industry and combined craft wage differentials shown in Table 2.

40

BARRY T. HIRSCH

from the CPS sample, including those who do not report earnings, using the employment weights that the Census attaches to each surveyed worker. For most craft groups, the raw mean union wages are considerably higher than for the comparison group, while the nonunion air transport means are modestly higher. Interesting are means of the BLS occupational skill index. In some cases, including the overall industry comparison to the economy-wide comparison group, the skill index mean for the air transport and comparison groups are highly similar. Where the skill values are similar, the suggestion is that the comparison group is closely matched to the air transport treatment group. Where there is a difference, it illustrates the potential importance of the skill index control for more precise estimates of wage differentials. For example, aircraft mechanics (engine and non-engine) have higher occupational skill ratings than do the other mechanics with whom they are compared. Apart from pilots and flight attendants, who have unique CPS occupation codes, mean values of Skill are not identical for union and nonunion workers within a craft, since craft groups can include more than one CPS occupation (e.g., mechanics include aircraft engine mechanics, aircraft mechanics excluding engine, and mechanic supervisors) and union and nonunion workers need not be equally distributed across these detailed occupations.

5 EARNINGS DIFFERENTIAL ESTIMATES IN THE AIR TRANSPORT INDUSTRY AND BY AIRLINE CRAFT In this section, earnings differential estimates between air transport workers and “compa rable” workers and levels of work economy-wide are examined. The results are presented in Table 2, first the differentials for the entire air transportation industry and then for each airline worker group. Estimates of d are presented separately for union and nonunion workers and from earnings equations with and without inclusion of the BLS skill index. Estimates are for the entire 1995–2006 period, since sample sizes by year and by craft are too small to reliably identify year-to-year movements. Appendix Table A3 provides information identical to that shown in Table 2, except that results are estimated for the years 2003–2006 rather than 1995–2006. The reason for showing estimates beginning in 2003 is a change that year in CPS occupation and industry definitions (the switch from 1990 to 2000 Census codes). Because of similarity in results, discussion is restricted to Table 2, apart from noting that small sample sizes for the 2003–2006 estimates reduce their reliability, particularly for the individual crafts. It is worth emphasizing that our CPS analysis includes only wages and salaries and not benefits. Economy-wide, unionized workers realize a “benefits premium” that is larger than the wage premium (Freeman, 1981). In the airline industry, union contracts among the major airlines provide benefit levels well beyond those seen economy-wide for full-time workers in the private sector (Wachter, 2004). As evident in Table 1, the overall skill index rating for workers within the airline industry is nearly identical to that seen for the economy-wide comparison group (1,274 versus 1,282). This makes the comparison of benefits among major carriers with the average economy-wide particularly relevant, even though such analysis lacks worker and job controls. Were it possible


41

Table 2 CPS Log Wage Differentials by Airline Worker Group and Union Status, 1995–2006 Group

Skill Index Included

All

Union

Nonunion

No Yes

0.130 0.108

0.249 0.226

0.040 0.019

No Yes

0.189 0.154

0.283 0.249

0.072 0.037

No Yes

0.290 0.245

0.407 0.365

0.066 0.013

No Yes

0.209 0.182

0.246 0.224

0.110 0.070

No Yes

0.189 0.115

0.297 0.223

0.080 0.005

No Yes

0.114 0.112

0.220 0.219

0.008 0.006

No Yes

0.118 0.107

0.182 0.171

0.069 0.058

No Yes

0.038 0.036

0.132 0.147

0.010 0.003

All air transport industry

Industry crafts

Pilots

Flight attendants

Mechanics

Fleet service

Agents

Other

See note to Table 1. Estimates are based on the CPS monthly earnings files, September 1995–May 2006. The “Industry Crafts” group includes the five airline crafts but excludes “Other”, while “All Industry” includes “Other” as well. The “All Industry” and “Industry Craft” differentials are compiled based on the weighted average of their component parts, using the employment weights shown in Table 1 (with separate weights by union status). Estimation of differentials explained in text. Differentials are shown with and without control for BLS occupational skill index, ln Skill. Other control variables are education dummies (5) reflecting levels from a minimum of a high school degree (including a GED) through a masters degree, potential experience in quartic form separately and interacted with gender, gender, race/ethnicity (4), foreign born, region (8), metropolitan area size (6, with non-metro the base), year dummies (10), and broad occupation dummies (11, included only for the “Other” group regression).

to estimate a total compensation differential within a regression framework (i.e., with controls), the strong suggestion is that compensation premiums would exceed the wage premiums presented in Table 2.21 21

A minor caveat is that our CPS economy-wide sample of full-time workers excludes those with schooling less than a high school and greater than a masters degree, while the BLS benefits sample makes no such restriction.

42

BARRY T. HIRSCH

5.1 Industry Differentials The top line of Table 2 contains the earnings differential results for the air transport industry over the combined 1995–2006 period, separately by union status and both with and without inclusion of ln Skill. The industry differential d is the weighted average across wage differentials estimated for the five airline craft groups and a remaining “Other” air transport workers group. The “standard” log wage differential d for 1995–2006, compiled from estimated wage gaps absent control for Skill, is 0.13 log points.22 The “expanded” earnings differentials, compiled from regressions that control for Skill, reduce d by 0.02 log points, from 0.13 to 0.11. The smaller expanded gap estimate reflects not only that airline occupations tend to have somewhat higher skill (and other job attribute) ratings than do comparison group workers, but also that these higher skills are not fully accounted for by CPS measures such as schooling and potential experience. The average differential across all air transport workers masks what are large earn ings premiums for union workers and little apparent earnings advantage for nonunion workers. Our preferred measure of d is the expanded measure, which controls for Skill. Nonunion air transport workers have an estimated d of only 0.02, indicating that nonunion earnings in the industry are roughly comparable to earnings realized by similar workers (union and nonunion) performing comparable levels of work outside the indus try. By contrast, union air transport workers realize a substantial earnings premium of 0.23 log points, well above the level dictated by comparability and a competitive labor market.23 A sizable share of the air transport sample (in particular the nonunion sample) is in the “Other” category, which includes workers in a wide range of occupations and some working for air transport companies other than airlines. In general, these workers tend to have smaller wage advantages than do the traditional airline crafts. If the weighted average is constructed from just the five “craft” groups (the row labeled “Industry Crafts” in Table 2), higher estimates of d are obtained – a combined union and nonunion earnings advantage (controlling for Skill) of 0.15, a union premium of 0.25, and a nonunion differential of 0.04. In short, the air transportation industry is a high wage industry, with earnings premiums concentrated among union workers, particularly workers in the standard airline craft groups.

5.2 Pilots Earnings differential estimates by airline worker group are included in Table 2. Pilots are first examined. The CPS pilot category includes “aircraft pilots and flight engineers”

22

All differentials are presented as log point wage gaps. Percentage gap estimates can be obtained by

[ed – 1]100, where d is the log point gap. For reasons of space and because sample sizes are large, standard

errors are not presented. Standard errors for the industry gaps are approximately 0.007. Standard errors vary

across craft group, but are approximately 0.015 (but somewhat larger for fleet service and smaller for “other”

workers).

23 The airline union wage advantage is higher, but the same order of magnitude, than are economy-wide union–

nonunion wage gaps during this period (Hirsch and Macpherson, 2006, Table 2a). Note that the union airline

differential compares unionized air transport workers to a mix of union and nonunion nonairline workers.


43

(pre-2003 the occupation is labeled “airplane pilots and navigators”). The comparison group for pilots includes full-time workers outside the air transportation industry in occupations within the following broad categories beginning in 2003: business and financial operations, computer and mathematical, architecture and engineering, and life, physical science, and social science occupations. Pre-2003, the categories are labeled professional specialty occupations (except health) and technologists and technicians (except health). As for all the comparison group samples, workers with less than a high school education or a degree beyond a masters are excluded. The largest earnings premiums for any airline craft group are found for union pilots. Absent control for the BLS skill index, the earnings differential for all pilots is 0.290; with ln Skill included as a control the differential is 0.245. The earnings premium (with Skill included) is driven principally by unionized pilots, estimates of d for union pilots being a sizable 0.365 and for nonunion pilots being 0.013, effectively zero (corresponding estimates without the Skill control are 0.407 and 0.066). There are no doubt some unmeasured differences in skill and experience between union and nonunion pilots, the latter more likely to have less flying experience and to pilot smaller planes. Having said that plane size differs, however, it is not clear how large rate differentials with respect to aircraft size would be in a competitive labor market. Whatever those differences, they could not account for such large earnings premiums.24 Finally, it is important to note that estimates of pilot earnings differentials are sensitive to the assumed level of mean earnings above top-coded weekly earnings. As stated previously, pilots’ mean earnings above the cap have been “conservatively” assigned as being equal to 1.25 times the top-code amount. This compares to the approximate 1.7 times the cap for men (and 1.6 for women) based on the Pareto distribution, the multiples used for the comparison group sample (shown at www.unionstats.com). Had the Pareto distribution estimates been used for pilots, estimated earnings premiums for union pilots would be about 0.10 log points higher than those shown. Because annual pilot sample sizes in the CPS are not large and the number of pilots at the top-code varies quite a bit from year to year, it is difficult to reliably estimate the time pattern of changes in pilot earnings using the CPS.

5.3 Flight Attendants Flight attendants earnings are compared to those of a comparison group of workers scat tered across occupations within the broad categories of sales, service, and administrative support. I focus on the earnings equation results that include the BLS occupational

24

Reinforcing the finding of a large earnings premium for unionized pilots is the evidence that union pilots at the major carriers have quit rates that are close to zero (Wachter, 2004). No doubt a part of this low quit rate reflects the fact that wage scales for pilots display substantial growth with respect to seniority, but seniority cannot be transferred across airlines with union contracts. As pilot layoffs have become common at the legacy carriers, some have been willing to “start over” at FedEx or at other carriers where greater job security is expected (Dade, 2006). Although the wage is not the only determinant of the quit rate, a quit rate close to zero is hard to imagine absent a sizable premium. Economy-wide quit rates in the private sector (including part-time workers) are about 25% annually, while for private transportation and public utilities the rate is over 15% (US BLS, 2006).

44

BARRY T. HIRSCH

skill index, whose inclusion lowers estimates of flight attendant earnings differen tials by about 0.02–0.03 log points. The estimate for combined union and nonunion flight attendants is an earnings premium of 0.18 log points. As is the case for pilots, the premium varies by union contract coverage. Unionized flight attendants realize a 0.22 premium, whereas nonunion flight attendants have a small earnings advantage of 0.07. Several of the caveats that arise with respect to pilot earnings premium estimates do not arise for flight attendants. First, all but a few transportation attendants employed in the air transport industry are likely to work for passenger airlines, whereas pilots and some other air transport crafts are employed in air freight or some other air transport support industries. Second, neither skill requirements nor adverse working conditions systematically increase with plane size (this issue is discussed in Section 5). And third, the entire 0.22 log point difference between union and nonunion flight attendants is likely to represent a premium. Although unionized flight attendants are concentrated at major carriers and nonunion flight attendants at nonunion midsize and regional carriers (Delta’s nonunion flight attendants are an exception), large airlines should be able to attract and retain productive flight attendants at wages similar to those received by nonunion workers at small airlines.

5.4 Mechanics Aircraft mechanics include workers in the air transportation industry whose detailed occupations are aircraft engine mechanics, aircraft mechanics (except engine), and mechanic supervisors. The comparison group includes workers in all mechanic occu pations (including supervisors) employed outside the air transportation industry. The aircraft mechanic occupations are awarded higher skill index ratings than are all other mechanic occupations; hence wage differential estimates with a control for ln Skill are substantially lower, by about 0.07 log points, than those excluding ln Skill. Over the 1995–2006 period, the estimate of d for mechanics with the skill index (union and nonunion combined) is 0.11 log points, compared to a 0.19 estimate without the skill index. As with pilots and flight attendants, the wage premium story is really a union story. Over the entire period, the log wage premium for union aircraft mechanics (with skill included) is 0.22, as compared to effectively zero (0.01) for nonunion aircraft mechanics. There exist skill differences (e.g., licenses to work on different planes) among aircraft mechanics within the air transport industry that are not observed. If unmeasured skills are positively correlated with union status, estimates of within-industry union–nonunion wage differences are overstated, although wage gap estimates for all mechanics need not be biased. As with the other employee groups, a sizable wage premium for union, but not nonunion, aircraft mechanics is observed. Airlines have limited opportunity to substitute nonunion for union pilots or flight attendants when facing large within-industry wage differences. In contrast, airlines have some ability to substitute away from their union ized mechanics by outsourcing scheduled maintenance and other work to specialized companies employing licensed aircraft mechanics (Goodwyn [2006] reports a recent example of union “in-sourcing”). Although an airline’s mechanics union will bargain to


45

limit such substitution, the possibility of substitution should constrain the magnitude of union premiums among mechanics.25

5.5 Fleet Service (Ramp) Workers There are a variety of ground workers, apart from mechanics, who service airplanes. These include baggage handlers, airplane cleaners (utility workers), workers who guide planes into and out of their gates, and workers who refuel airplanes. Fleet service or ramp workers category includes those who work in the air transportation industry and whose occupations are freight, stock, and material handlers; and vehicle washer and equipment cleaners. The comparison group of workers includes those employed outside the air transportation industry in the following occupational categories: nonconstruction laborers and freight, stock, and material handlers; garage workers; washer-cleaners; and packers. Inclusion of the skill index has little effect on estimates of d for ramp workers, the log wage gap being 0.11 with or without control for ln Skill.26 As with other crafts, nonunion fleet service workers appear to be paid roughly their opportunity costs, with a d estimate of 0.01. Unionized fleet service workers realize an estimated wage premium of 0.22 log points. As with mechanics, carriers facing high contract rates among fleet service workers have incentive to outsource some of this work, substituting lower-cost contract workers for their own union employees.

5.6 Reservation Agents and Stores Employees Airlines have a large number of customer service employees – ticket reservation agents outside of airports, ticket and gate agents within airports, and “stores” employees who oversee the recording and distribution of supplies and parts. “Agents” are defined as those employed in the air transportation industry within the following occupations: reservation and transportation ticket agent; shipping, receiving, traffic clerks; stock clerk and order filler; and customer service representative. The comparison group includes workers outside the air transportation industry employed in the same occupations as above, plus those listed as other information and record clerks and as order clerks.

25

When faced with a strike by mechanics in August 2005, Northwest eliminated a large share of their mechanics jobs through outsourcing and hired (in advance of the strike) replacement workers for the remaining mechanics jobs. One should be reluctant to generalize from the Northwest example. Northwest mechanics were represented by a “rebel” union (AMFA) which had unseated the IAM, in the process alienating IAM’s remaining Northwest workers and Northwest’s other unions. Northwest’s unionized workers crossed the AMFA picket lines and allowed Northwest to continue operations despite the strike (Carey, 2005). An agreement, ratified in November 2006, allow striking AMFA workers to receive limited amounts of layoff or separation pay. Those accepting layoff status can bid on open technician positions. 26 The small effect of the Skill index is not surprising, since those working in and outside the air transportation industry (i.e., the treatment and comparison groups) are drawn largely from the same Census occupations and hence are assigned the same Skill values. It seems unlikely to me that the combination of required skills and adverse working conditions in these occupations is so different that it should lead to highly disparate wages in and outside the air transportation industry.

46

BARRY T. HIRSCH

The combined union–nonunion wage differential estimate of d is 0.11 with control for ln Skill. Union–nonunion differences here are less than seen with other crafts, with a union wage advantage relative to the nonairline comparison group of 0.17 and a nonunion wage advantage of 0.06.

5.7 Other Air Transport Industry Workers The “other” or miscellaneous category of air transport workers, all those not included in the previously discussed five crafts, are distributed over a broad range of occupations. The comparison group includes the entire sample of full-time workers outside of the air transportation industry (recall that the sample excludes those with very low and high education levels and for whom the BLS skill index is not defined). Most of these air transport workers are nonunion. Inclusion of the occupational skill index has little effect on estimates of the differential (broad occupation dummies are included in the “other” earnings equation). The overall earnings differential for the “other” group of workers is 0.04. This reflects an earning premium of 0.15 for the small union portion of the group and a zero estimate for the large nonunion group. More so than for the five airline craft groups, a nontrivial number of the air transportation industry workers in the “other” occupation category are likely to work at companies other than a passenger airline. Taking the occupational groups as a whole, a clear pattern emerges from the earnings analysis in this section. First, there exists a sizable earnings premium among union workers in air transportation, relative to a mix of union and nonunion comparison group workers. Second, nonunion air transport workers appear to realize little premium com pared to similar workers doing similar levels of work outside the industry. Although there was evidence of rent sharing among nonunion as well as union airline workers during the pre-1978 airline regulation period and in the immediate years after deregu lation (Hirsch and Macpherson, 2000), any remaining rents are now small. What might be labeled an airline earnings premium is for the most part a union premium.

6 WAGE DIFFERENCES ACROSS AIRLINES: DO REGIONAL AIRLINE WAGES APPROXIMATE OPPORTUNITY COSTS? In prior sections, average compensation among national carriers reported in DOT Form 41 data have been used to measure changes over time in industry labor costs, while worker data from the CPS have been examined to estimate wage differentials for union and nonunion workers throughout the air transport industry, relative to similar workers and jobs outside the industry. In this section, evidence on contractual “top rates” for airline workers across national carriers and regional airlines is reviewed. On the basis of this and prior evidence, a question that is explored is whether opportunity cost wage rates for major carriers might be approximated by the rates currently seen at regional airlines. Airline contract data are not publicly available (i.e., not reported to the government), but are assembled by trade groups. The Airline Industrial Relations Conference (Air Con ference) is made up of a consortium of scheduled national airlines. Each provides their


47

labor contracts by craft to the Air Conference, which assembles contract information and terms of employment in their database. Member airlines are provided access to contract information from all participating airlines. J. Glass & Associates (a consultancy division overseen by Ford & Harrison, LLP) manages a Regional Airline Association database with union and nonunion contract rates and terms of employment for regional airlines. Wage schedules for national and regional carriers, drawn from the Air Conference and Glass & Associates databases, are provided in a December 2004 analysis by Michael Wachter (2004), who provided expert testimony for United Airlines in their 1113(c) bankruptcy hearing.27 It’s useful to recall the economic setting. In late 2004, highcost airlines were in a serious financial situation following September 11, a recession, Internet pricing, increased price competition and rising market shares of low-cost carriers, and rising fuel prices. United had received wage concessions in 2003 following their 2002 bankruptcy filing, but were asking for further concessions to help achieve a viable business plan that would allow them to emerge from bankruptcy protection. US Airways, which had preceded United into bankruptcy, had recently obtained reduced wage scales for their employees in their bid to emerge from bankruptcy. American had earlier received concessions from their workers that allowed them to avoid bankruptcy. Delta and Northwest had relatively high contract rates at this time despite prior wage concessions; these subsequently would be reduced further leading up to and following their 2005 entry into bankruptcy. A relatively “healthy” Continental was less threatened by bankruptcy, but did receive salary relief from its unions. Compared with the legacy airlines, Southwest was the anomaly in 2004 and remains so today. Although having high contractual top rates, Southwest has a smaller share of employees at its top rates, lower benefit costs, higher labor productivity, lower operating costs, lower debt, and defined contribution rather than under-funded defined benefit pension plans. Evidence presented in Wachter (2004) allows one to compare wage rates at the major carriers to those among similar crafts at regional airlines. The analysis included two sets of United Airlines contract rates, those in force in December 2004 and those then proposed by the airline (or, in the case of pilots, rates from a tentative agreement). The existing December 2004 rates reflected pay concessions United’s unions had agreed to previously in 2003. The proposed United rates were nearly identical to those implemented previously at US Airways. In Table 3, United’s post-2004 rates are compared to rates at other major airlines, at mid-size national airlines, and those at regional airlines. The significance of United’s post-2004 rates is that they, along with those at US Airways, can be thought of as setting, at least for a couple of years, a new industry standard.28 It is this “standard” that is compared to wage schedules at mid-size and regional carriers. Salary schedules are provided for eight separate worker crafts, summarized in Table 3. These are pilots, flight attendants, mechanics, utility workers, ramp workers, stores

27 The Wachter analysis was conducted with assistance from James Gillula of Global Insight and from me.

Views expressed in this chapter are my own and need not reflect those of United, Michael Wachter, or Global

Insight.

28 Delta and Northwest, which entered bankruptcy in 2005 with pay rates well above United, eventually

implemented wage schedules similar to United’s post-2004 rates. American and Continental, which received

concessions from their unions outside of bankruptcy, have rates somewhat above those of United.

Table 3 Contractual Top-Rates and Log Wage Differentials between United Airlines and Major, Mid-Size, and Regional Carriers, December 2004 Employee Group

United Airlines Dec 2004

United Proposal Dec 2004

Average at Majors

Average at Mid-size

Average at Regionals

United Post-2004 vs. Majors

United Post-2004 vs. Mid-size

United Post-2004 vs. Regionals

Pilots (monthly) FAs (monthly) Mechanics Utility Ramp Stores CSR RSR

$12,374 $3,073 $31.09 $17.50 $21.06 $21.06 $21.75 $21.01

$10,554 $2,895 $29.82 $16.65 $19.61 $19.61 $20.25 $19.56

$12,627 $3,447 $31.99 $16.83 $20.09 $19.86 $20.31 $19.58

$11,311 $2,863 $28.39 $13.49 $17.05 $16.82 $16.86 $15.95

$5,861 $2,198 $22.73 $12.39 $13.69 $13.93 $13.82 N/A

−0.179 −0.175 −0.070 −0.011 −0.024 −0.013 −0.003 −0.001

−0.069 0.011 0.049 0.210 0.140 0.153 0.183 0.204

0.588 0.275 0.271 0.296 0.359 0.342 0.382 N/A

The dollar rates are reported in Wachter (2004). The United proposed wages are treated as a rough approximation of prevailing wages at the major carriers following wage concessions at major airlines during 2005 and 2006. The last three columns show the difference in log of the average wages between the United proposal and the respective averages at the majors, mid-size, and regional airlines. All wages shown reflect top-rates (maximum seniority). For pilots and flight attendants, monthly rates are based on a 75-hours yield. Other rates shown are hourly rates. RSR (reservation service representatives) are not employed by most regional carriers. Averages at six major carriers (excluding United), mid-size, and regional airlines are unweighted. A list of carriers included in each category is provided in the text and in footnote 29.


49

employees, customer service representatives (CSR), and reservation service representa tives (RSR). Recall that the CPS analysis had five airline craft groups. The first three groups in Table 3 – pilots, flight attendants, and mechanics – align exactly with CPS categories. The next two – utility (cleaners) and ramp workers – were included in the CPS fleet service worker category. The next three categories – stores, CSR, and RSR employees – were included in the CPS agent category. The first two columns of Table 3 provide the top-rate salary rates by craft for United before and after December 2004. It is the post-2004 rate that will be treated as an approximation of the industry standard for major and national airlines. The next three columns present the unweighted average of rates at the six major airlines other than United (American, Continental, Delta, Northwest, Southwest, US Airways), midsize national airlines, and at regional airlines.29 The use of top rates (maximum seniority) means that what is being compared is a wage contract structure across airlines rather than payroll cost differences. At the legacy airlines, a large proportion of workers are at the top rates. Generally, the average wage within an airline will be below the top rate, although this need not be true since average wages include overtime pay and possible pay supplements (e.g., international rates for flight attendants) not included in the top rate. New or expanding airlines will have fewer workers with high seniority, hence differences in top rates across carriers may not fully reflect current payroll differences between legacy and low cost carriers. Over time, there should be a narrowing payroll cost gap as the age structure of the legacy and low cost carriers becomes more similar. For all crafts other than pilots and flight attendants, hourly wage rates are provided. The rate for mechanics is an “all-in top rate” that includes the top-step base pay and maximum license, skill, line, and longevity pay. For pilots at the major and mid-size national carriers, the pay shown is a monthly pay based on a 75-hour yield for a 12th year captain flying a weighted average of planes within each airline’s fleet. Pilot rates at regional carriers are for a 12th year captain flying a weighted average of 50-seat and larger jets. Pay shown for flight attendants is likewise based on a 75-hour yield, with top-step base and incentive pay (but excluding international pay). The last three columns of Table 3 provide the log wage differential between United’s post-2004 rates of pay and the end-of-year 2004 pay in the three sectors of the airline industry – other major airlines, mid-size national airlines, and regional carriers. As evident from these columns, United’s proposed (and eventual) rates for pilots, flight attendants, and, to a lesser extent, mechanics, would be below the average of other major airlines. In 2005 and 2006, rates at Delta and Northwest would decrease to a level similar to those at United. The United top rates for pilots, flight attendants, and mechanics were similar to those seen at mid-size national airlines. Rates for the remaining crafts would be similar to December 2004 rates at other major airlines and above rates at mid-size carriers. The importance of Table 3 stems from the results reported in the final column, the difference in log wages between the United proposed wages, a stand-in for what would emerge as the national carrier “industry standard,” and the unweighted averages of up

29

The mid-size national airlines are AirTran, Alaska, America West, ATA, Frontier, JetBlue, and Midwest. The regionals are Air Wisconsin, Allegheny, American Eagle, Atlantic Southeast, Chautuaqua, Comair, ExpressJet, Horizon, Independence, Mesa, Mesaba, MidAtlantic, Midwest Connect, Piedmont, Pinnacle, PSA, SkyWest, and Trans States. Rates were not provided for all airlines in every craft.

50

BARRY T. HIRSCH

to 18 regional airlines (but fewer in some crafts). These craft-specific wage gaps are large – 0.59 log points (80%) for pilots, 0.28 (32%) for flight attendants, 0.27 (31%) for mechanics, 0.30 (34%) for utility, 0.36 (43%) for ramp workers, 0.34 (41%) for stores workers, and 0.38 (46%) for gate agents (there are few reservation agents among the regional airlines).30 Do wages at regional airlines approximate opportunity costs? By opportunity cost wages, what is meant is a compensation structure that in a competitive labor market could in the long run attract and retain a labor force with “appropriate” skills (appropriate mean ing profit-maximizing, with there being a trade-off between compensation and produc tivity). Wachter (2004) suggests that the wage scales seen at regional airlines provide an approximation of opportunity cost wages, based on the similarity of jobs at the major and regional carriers and small differences between regional wage scales and average published wage rates within the same broad occupation categories economy-wide. Although this claim is difficult to establish in a rigorous manner, it is plausible. The earlier CPS analysis implements comparability through the estimation of earnings models intended to compare air transport workers with measurably similar workers in broadly similar jobs outside the air transport industry. Jobs are made statistically equivalent, at least in principle, through measures of worker and job attributes. The analysis found rough equivalency between nonunion wages among craft workers in the air transportation industry and “comparable” workers outside the industry. Given high rates of union coverage among major carriers (Delta being the exception), then many of these nonunion workers are employed by mid-size and regional carriers, as well as air transportation companies other than certificated carriers. The CPS analysis cannot compare identical jobs, but it does approximate what airline workers might have earned in an alternative career path (i.e., long-run opportunity costs). The regional airline comparison seen in Table 3 provides an alternative way to assess comparability. The analysis compares workers in the same (i.e., comparable) occupation within the same industry. Such a wage comparison provides a control for skills, worker preferences, and working conditions. This is an important advantage, but has the disadvantage that wages for all jobs within an industry may be impacted by noncompetitive wage determination (e.g, union bargaining power), resulting in wage levels above opportunity cost.31 Although comparing wages within the industry provides a seemingly precise jobs match, it cannot be asserted that jobs and workers within the industry are literally identical. Some (unknown) portion of each of the gaps between wages at the major and at regional carriers reflects differences in worker skills or in the nature of the job. Even were there competitive wage determination throughout the airline industry, wage differences between the major and regional carriers would remain. Today’s wages at regional

30 The stated percentage differences are calculated using the “low” regional airline average wage as the base. The log gaps (times 100) provide a value in between percentages calculated using the low and high wages as base. The log of the average wage across airlines (used in the calculation) is a little larger than the average of log wages. 31 In particular, the concern is that union power in the industry (both union coverage and the threat of organizing uncovered workers) raises the level of nonunion wages and regional carrier wages to exceed opportunity costs.


51

carriers are presumably higher than they would be were airline labor markets perfectly competitive (e.g., absent union coverage or the threat of organizing). A competitive or opportunity cost wage structure throughout the industry might produce salaries at the major carriers that are similar to or slightly above what regional carriers pay today. How similar are workers and jobs at the major versus the regional carriers? The answer to this question will differ across craft. Clearly, pilots at major carriers are flying larger jets and typically have greater flying experience. A competitive wage structure would produce higher salaries for pilots flying larger planes and with more experience. But it does not follow that the wage gradient with respect to plane size or experience would be as large as is evident today, or that current salaries at regional carriers would not be sufficient to attract to major carriers a sufficient number of pilots skilled at flying large jets. Pilots are highly skilled and there is considerable trust placed on pilots not to make errors. But competitive salaries are determined at the margin and there are large numbers of individuals who want to be pilots – and who are able and willing to acquire the skills necessary to be a pilot.32 Regional airlines are able to attract qualified applicants, even where the possibility of moving to a major carrier at far higher pay is low. A high proportion of these pilots could and would acquire the licensing to fly larger planes were such jobs available. Nothing in the analysis permits us to say that a competitive salary for pilots of large jets would be precisely at the pay level seen today for regional jets. But we know that current levels of pay at major carriers (as seen in the 0.59 log wage premium for major carriers over regional carriers) far exceed the compensation necessary to attract and retain qualified pilots. And we know from the CPS analysis that unionized pilots (averaged across the entire air transport industry, including regionals and freight carriers) realize substantial earnings premiums, 0.37 log points, relative to what they might have earned in alternative career paths. Thus, salaries seen today for regional pilots may well be a reasonable approximation of what average salaries would be for airline pilots across a competitive airline industry labor market. It is worth noting that a fully competitive labor market would allow movement of pilots and other workers across carriers, without placing workers at a starting wage scale (zero seniority).33 If an industry were such that most worker skills were firm specific (i.e., not valued at other firms), then we would expect there to be promotion from within and little hiring at other than a junior level. Yet far more than in most industries, worker skills in the airline industry are highly transferable across firms. The skills of a pilot (or flight attendant or mechanic) that are valued at one airline are also valued at other airlines. What makes airline skills difficult to transfer and minimize cross-carrier mobility of airline workers are not differences in skill requirements, but provisions in union contracts that strictly tie pay to seniority with one’s current employer. Absent worker mobility across carriers, we cannot know what would be a competitive wage structure. Mobility would act to limit demands for “high” pay since carriers can hire

32 Ideally, we would like to measure applicant queues and turnover at regional carriers to help determine if

wages are at market clearing levels. Currently, there is an excess supply of pilots throughout the industry.

During 2005 FedEx had 14,000 applications for the 420 pilot jobs it filled. UPS hired 233 pilots from among

10,000 applicants, 8,000 of whom were passenger pilots (Dade, 2006).

33 Defined benefit pension plans also reduce mobility across firms, but these are becoming increasingly rare

for new private sector workers.

52

BARRY T. HIRSCH

experienced workers from other carriers. Likewise, mobility would limit the ability of financially strapped carriers to pay below opportunity cost wages, since workers could move to other carriers. Flight attendant pay is approximately 0.28 log points higher at major carriers than at the regionals. The principal difference between the two jobs is that flight attendants at the majors work on larger planes, work in teams rather than solo, and service longer but fewer flights. It is not at all clear that the differences in required skills and the desirability of working conditions between working on a large jet versus a small plane should lead to higher pay at the major carriers. Many (but not all) flight attendants will prefer to work as part of a team and to service longer but fewer flights. Some flight attendants will prefer the more limited range of travel typical of regional airlines; while others will prefer the wider range of travel to larger cities, both in the US and abroad. If regional airlines can readily attract and retain flight attendants at their current levels of pay, absent the expectation that they will move to higher paying job at a major carrier, then it is reasonable to argue that competitive pay for flight attendants would not be higher (or substantially higher) than the pay seen today at the regional carriers. The 0.22 log point CPS wage premium estimated for union flight attendants (and 0.18 for all flight attendants) reinforces the argument that wage scales at regional carriers roughly approximate opportunity costs. As with pilots, one would expect to see aircraft mechanics who service larger planes and work at major carriers to be paid more than mechanics at regional carriers. But it does not follow that competitive differentials between rates at major and regional carriers need be 31% for mechanics (as in Table 3). The estimated CPS premium for union aircraft mechanics relative to other types of mechanics economy-wide (conditional on schooling, age, and the occupational skill index, in which aircraft mechanics are rated highly) is 0.22 log points. If the CPS estimate is correct, then it suggests that competitive wage rates for aircraft mechanics would be lower throughout the industry, with a smaller wage gap between the regional and major carriers. The remaining airline crafts – ground workers (ramp and utility employees), agents, and stores employees – receive wage rates from 0.30 to 0.38 log points higher at the major airlines than at regional airlines. The CPS premium for union workers in these occupations was about 0.20 log points. Although there are some differences in the nature of these jobs between large and small carriers, the requisite skills and working conditions should not require such substantial wage differentials as seen in Table 3. Obviously, competitive wage levels across the entire industry would not precisely equal what is seen today at regional airlines, but these levels might not be too bad an approximation. In short, both the CPS analysis, comparing unionized workers throughout the air transport industry with similar workers and levels of job skill outside the airline industry, and the within industry comparison of contract scales at the majors and the regional carriers, indicate a wage structure in the airline industry that is well above opportunity cost. Were the labor market in the airline industry a competitive one, absent unions that possessed and exercised strong bargaining power, we would see a substantially lower level of compensation in the industry, coupled with easy worker mobility across carriers and few contractual restrictions on outsourcing. Whether airline compensation is headed toward opportunity costs is addressed in the final section of the chapter.


53

7 THE FUTURE – OPPORTUNITY COST WAGES OR UNION WAGE CYCLING? Workers in the air transportation industry are relatively highly paid. Some of this high pay reflects the training and skills required for jobs in the airline industry. Analysis in this chapter, however, provides evidence of substantial wage premiums in the air transportation industry. The premiums are realized primarily by union employees at major and mid-size airlines. Wages at regional carriers are substantially lower than at large national carriers and may roughly approximate what would be opportunity cost earnings for the rest of the airline industry. There is little evidence for earnings premiums among nonunion workers in the industry, many of whom work in occupations outside the traditional airline craft groups of pilots, flight attendants, mechanics, fleet service, and agents. Pay premiums are particularly large for unionized pilots, but are also substantial for other union workers. Compensation premiums are tied closely to union bargaining power (i.e., the ability to inflict costs through a strike), a strike threat power that appears unparalleled in private industry in the US. Union ability to acquire wage gains, however, depends crucially on the financial health of carriers. During good times, unions capture or “tax” some sizable share of potential profits. During bad times, unions moderate these demands or agree to wage concessions when firm survival and jobs are threatened. Because wages and benefits are negotiated and specified in long-term contracts, but the future financial fortunes of the firm are sometimes poorly predicted, changes in compensation (either through new contracts or renegotiation of contracts) lag changes in the product market. What might stop or substantially weaken this lagged wage-profit cycling; that is, a variable union tax on carrier profits? In most US industries, such cycles are not readily evident because union density is low and competition forces product prices to approximately reflect opportunity costs (including a normal return on capital). Were there a sufficient number of carriers that had competitive or opportunity cost compensation and were air fares not determined in partially segmented markets, pricing would consistently reflect the costs at these low-cost carriers. There would be little ability for unions to acquire and sustain noncompetitive wages and benefits. Certainly the airline industry is not immune to such forces. Increased penetration of low-cost carriers has limited the pricing power of major carriers, particularly on heavily traveled point-to-point routes.34 There also exists competition across cities (carriers) when customers prove willing to drive to alternative airports (Fournier et al., 2007). And during time periods and in markets with excess capacity, price competition can be keen.35 Such price competition clearly constrains union bargaining power, but does not eliminate it.

34 Low-cost carriers, however, have low penetration in low-density origin-to-destination routes, which continue to depend heavily on the hub-based legacy carriers. Analysis by Darin Lee shows that lower cost carriers’ share of domestic passengers increased from about 10% in 1990 to about 30% in 2004. He also estimates that by 2004, 75% of domestic passenger “trips” were exposed to LCC competition. See http://www.darinlee.net/stats.html. 35 Busse (2002) finds that carriers in the worse financial condition, particularly those highly leveraged, are most likely to start price wars. Carriers which most directly compete with price war leaders are more likely to join the price war.

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BARRY T. HIRSCH

The bankruptcies of major carriers and concomitant downward adjustment in labor compensation throughout much of the industry can certainly be seen as a move toward a more competitive wage structure. The increased penetration of low cost carriers and the enhanced competition within major city hub airports suggest that price competition will constrain the future growth in labor costs. I do not predict, however, an imminent or smooth transition to an era of opportunity cost compensation. The airline industry remains highly unionized. As in the past, airlines are likely to reestablish market positions where they can be profitable, possibly through innovations or in other ways that cannot be anticipated. As this is written, airlines are close to the point of solvency due to healthy demand and reduced capacity. If fuel prices moderate and seating capacity remains tight, airlines will resume profitability. Then the test begins. Unions retain substantial bargaining power and will attempt to make up for wage and benefit concessions. How this bargaining will play out is hard to predict, but it seems unlikely that airlines can hold compensation down to the levels acquired in 2005–2006. Of course, the major carriers and their unions will not return quickly to the types of contracts seen in the early 2000s. It is clear to companies and their unions that such rates cannot be sustained. Union demands will be less affected by the opportunity cost of labor than by carriers’ ability to pay. It is unclear whether or not demands well in excess of opportunity costs will be or can be rejected by management.36 For the foreseeable future, airline unions will continue to tax carrier profits and we shall see a continuation of union wage cycling, hopefully at levels more sustainable than in the past. The labor relations environment in the airline industry has long been contentious and characterized by mutual distrust.37 The bankruptcies at US Airways, United, Delta, and Northwest, along with labor concessions at American, Continental, and several smaller airlines, have further strained management–labor relations.38 There are mutual benefits to a more cooperative labor relations environment, however, if it can pro duce a high level of productivity and sustainable labor costs. Although there is little reason to expect such an outcome industry-wide, there are forces that may well push some carriers in that direction. The financial troubles at major and mid-size carriers, coupled with increasing product market competition, make unions and their members more aware than ever that their long-run well-being requires a financially healthy

36 An interesting example of such a dynamic can be seen at largely nonunion FedEx, which is currently highly profitable. At the same time that pilot salaries have fallen in the passenger airline industry, union pilots at FedEx emphasized their company’s profitability and pushed for large pay increases. A lengthy impasse began in 2004, and remained unresolved until a four-year agreement with industry-leading pay was reached in August and approved in October 2006 (their 1999 contract remained in force during this period). Similarly, a new UPS pilots’ contract was ratified in August 2006 (the prior contract became amendable at the end of 2003). The new contract runs through 2011 and includes substantial pay increases. Pay scales for senior pilots at the cargo carriers now exceed those for the major carriers. Some employed passenger pilots, concerned about job security at their current employers, have tried to “start over” at UPS or FedEx, despite the loss of seniority and a large initial sacrifice in pay (Dade, 2006). 37 Exceptions include Southwest Airlines and recent labor relations at Continental. For a discussion, see Gittell et al. (2004). 38 Survey evidence in 2005 indicates high levels of anger and militancy among pilots and flight attendants (Comstock, 2006).


55

employer. At the same time, Southwest and, to a lesser extent, Continental, provide exam ples where relatively cooperative labor relations environments are possible and jointly beneficial.39 Although it is possible that labor relations at the legacy carriers will improve, this is just a possibility.40 Nothing guarantees that such environments will emerge, or even that cooperative labor relations can be maintained at Southwest or elsewhere in the industry. What can be predicted is that in absence of the emergence of more cooperative labor relations environments, we are likely to observe a return to wage and profit cycles, increased penetration of carriers that can achieve and maintain low costs (a function of productivity as well as labor compensation), and an uncertain future for the remaining legacy airlines. Whatever the labor relations path followed in the airline industry, all parties must continue to respond to the competitive forces that have been and will continue to ultimately shape the direction of the industry.

APPENDIX

Table A1 Average Compensation and Labor Costs per Available Seat Mile, Major and National Airlines, 1990–2005 Year

Salaries and Benefits (2005$)

CV

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

$73,244 $74,164 $76,447 $77,586 $81,012 $81,147 $81,893 $80,764 $80,156 $79,318 $81,656 $86,339 $89,984

13.5 11.1 13.1 17.3 17.2 15.3 17.4 15.8 14.1 12.8 12.1 16.6 15.7

Labor Costs, cents per ASM (2005$) 4.70 4.66 4.54 4.43 4.41 4.33 4.24 4.23 4.29 4.30 4.36 4.60 4.66

CV 21.3 18.2 18.2 20.5 20.3 20.4 23.4 21.3 19.7 20.1 18.4 19.1 19.1 (Continued)

39 Little is known about the labor relations environments or human resource strategies employed by low-cost carriers, apart from Southwest. This topic is the subject of research by the Labor and Employment Relations Association (LERA) Airline Industry Council (Gittell and Kochan, 2006). The limited evidence to date suggests that there exists substantial heterogeneity across carriers. 40 An example of mutually beneficial labor-management cooperation can be seen at American Airlines, a legacy carrier with a rocky labor relations history. A redesign of maintenance operations, based in large part on worker input, has led to significant “in-sourcing” of maintenance from other airlines (Goodwyn, 2006).

BARRY T. HIRSCH

56

Table A1 Average Compensation and Labor Costs per Available Seat Mile, Major and National Airlines, 1990–2005—Cont’d Year

Salaries and Benefits (2005$)

CV

2003 2004 2005

$89,213 $87,279 $82,098

15.6 14.8 14.1

Labor Costs, cents per ASM (2005$) 4.28 3.80 3.27

CV 17.7 16.1 14.8

These numbers are shown in Figures 1 and 2. Based on compensation, employment, and ASM information reported by the US Department of Transportation, Bureau of Transportation Statistics, Form 41. Daniel Kasper and Darin Lee kindly provided current dollar figures by carrier and year on compensation and cost per ASM. Current dollar figures were converted to 2005$ and weighted averages were formed based on carrier employment counts provided in Form 41 data. CV measures the weighted coefficient of variation (standard deviation divided by mean). See text for further details.

Table A2 Construction of Airline Craft and Comparison Groups in the CPS Air transportation groups

Workers employed in air transport industry (code 421 for 1995–2002; code 6070 for 2003–2006)

CPS Occ code Occupation name Pilots 1995–2002 226 Airplane pilots and navigators 2003–2006 9030 Aircraft pilots and flight engineers Flight attendants 1995–2002 463 Public transportation attendants 2003–2006 4550 Transportation attendants Mechanics 1995–2002 508 Aircraft engine mechanics

515 Aircraft mechanics, except engine

503 Supervisors, mechanics and repairers

2003–2006 7140 Aircraft mechanics and service technicians 7000 First-line supervisors/managers of mechanics, installers, and repairers Fleet service (ramp) workers 1995–2002 883 Freight, stock, and material handlers, n.e.c. 887 Vehicle washers and equipment cleaners 2003–2006 9620 Laborers and freight, stock, and material movers, hand 9610 Cleaners of vehicles and equipment Agents and stores 1995–2002 318 Transportation ticket and reservation agents

364 Traffic, shipping, and receiving clerks

365 Stock and inventory clerks

2003–2006 5410 Reservation and transportation ticket agents and travel clerks 5610 Shipping, receiving, and traffic clerks 5620 Stock clerks and order fillers 5240 Customer service representatives Other air transport workers: All full-time air transport workers not in one of the above crafts


57

Table A2 Construction of Airline Craft and Comparison Groups in the CPS—Cont’d Comparison groups Comparison group workers are not employed in the air transportation industry Occupation codes (occupation codes and names posted at www.unionstats.com) Pilot comparison group 1995–2002 43–79; 173; 213–233; 235 2003–2006 500–1960 Flight attendant comparison group 1995–2002 243–285; 303–389; 433–447; 456–459 2003–2006 3600–3650; 4000–4160; 4300–4650; 4700–4960; 5000–5930 Mechanic comparison group 1995–2002 505–549 2003–2006 7000–7620 Fleet service comparison group 1995–2002 883; 889; 885–888 2003–2006 9620; 9360; 9610; 9640 Agents and stores comparison group 1995–2002 318; 323; 364; 365; 327 2003–2006 5410; 5420; 5610; 5620; 5350 Other worker comparison group: All full-time workers not in air transport (plus other sample criteria) See text for additional details and discussion on the CPS sample.

Table A3 CPS Log Wage Differentials by Union and Nonunion Airline Worker Groups, 2003–2006 Group


All

Union

Nonunion

No Yes

0.132 0.117

0.240 0.224

0.042 0.027

No Yes

0.220 0.194

0.284 0.261

0.131 0.102

No Yes

0.318 0.285

0.422 0.391

0.131 0.096

No Yes

0.156 0.148

0.209 0.207

0.009 −0.013

No Yes

0.229 0.180

0.321 0.271

0.092 0.042

No Yes

0.200 0.197

0.126 0.126

0.258 0.254

All air transport industry

Industry crafts

Pilots

Flight attendants

Mechanics

Fleet service

(Continued)

BARRY T. HIRSCH

58

Table A3 CPS Log Wage Differentials by Union and Nonunion Airline Worker Groups, 2003–2006—Cont’d Group


All

Union

Nonunion

No Yes

0197 0173

0.229 0.206

0167 0142

No Yes

−0007 −0006

0.085 0.093

−0043 −0045

Agents

Other

Identical to Table 2, except that the sample period is restricted to the years 2003–2006 following a new set of occupation and industry codes. Sample sizes for specific airline crafts are very small. See note to Table 2 and discussion in the text.

REFERENCES Air Transport Association. 2006. U.S. Airline Cost Index: Major & National Passenger Carriers, Fourth Quarter 2005, Washington, DC, July 14, http://www.airlines.org/economics/finance/ CostIndex.htm. Allegretto, S.A., Corcoran, S.P., Mishel, L. 2004. How does teacher pay compare? Methodological challenges and answers. Washington, DC: Economic Policy Institute. Bollinger, C.R., Hirsch, B.T. 2006. Match bias from earnings imputation in the CPS: The case of imperfect matching. Journal of Labor Economics 24 (3), 483–519. Busse, M. 2002. Firm financial condition and airline price wars. RAND Journal of Economics 33 (2), 298–318. Cahuc. P., Zylberberg, A. 2004. Labor Economics. Cambridge, Mass: The MIT Press. Card, D. 1998. Deregulation and labor earnings in the airline industry. In Regulatory Reform and Labor Markets, edited by J. Peoples. Norwell, Mass: Kluwer Academic Publishing, 183–230. Carey, S. 2005. Northwest, striking mechanics are to meet on talks. Wall Street Journal, October 12, p. B5. Comstock, P. 2006. Work-related views of pilots and flight attendants: Turbulence ahead? Per spectives on Work (The magazine of the LERA) 9 (2), 57–59. Crémieux, P. 1996. The effect of deregulation on employee earnings: Pilots, flight attendants, and mechanics, 1959–1992. Industrial and Labor Relations Review 49 (2), 223–42. Dade, C. 2006. Why some passenger pilots take huge pay cuts to fly cargo. Wall Street Journal, June 2, p. A13. Freeman, R.B. 1981. The effect of unionism on fringe benefits. Industrial and Labor Relations Review 34 (4), 489–509. Fournier, G.M., Hartmann, M.E., Zuehlke T. 2007. Airport substitution by travelers: Why do we have to drive to fly? In Advances in Airline Economics, Vol. 2: The Economics of Airline Institutions, Operations and Marketing, edited by D. Lee, Amsterdam: Elsevier. Gittell, J.H., Kochan, T.A. 2006. Low cost competition in the global airline industry. Perspectives on Work (The magazine of the LERA) 9 (2), 55–56. Gittell, J.H., von Nordenflycht, A., Kochan, T.A., 2004. Mutual gains or zero sum? Labor relations and firm performance in the airline industry. Industrial and Labor Relations Review 57 (2), 163–180.


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Goodwyn, W. 2006. American Airlines “insources” maintenance work. All Things Considered. National Public Radio, Dec. 7, at http://www.npr.org/templates/story/story.php?storyId= 6594273&sc=emaf. Hirsch, B.T., Schumacher, E.J., 2004. Match bias in wage gap estimates due to earnings imputation. Journal of Labor Economics 22 (3), 689–722. Hirsch, B.T., Macpherson, D.M. 2000. Earnings, rents, and competition in the airline labor market. Journal of Labor Economics 18 (1), 125–55. Hirsch, B.T., Macpherson, D.M. 2003. Union membership and coverage database from the Current Population Survey: Note. Industrial and Labor Relations Review 56 (2), 349–54 (accompanying database at http://www.unionstats.com, updated annually). Hirsch, B.T., Macpherson, D.M. 2006. Union Membership and Earning Data Book: Compilations from the Current Population Survey (2006 Edition). Washington, DC: The Bureau of National Affairs. Johnson, Nancy Brown. 1995. Pay levels in the airlines since deregulation. In Airline Labor Relations in the Global Era: The New Frontier, edited by P. Cappelli. Ithaca, NY: ILR Press, 101–15. Matsa, D.A. 2006. Capital structure as a strategic variable: Evidence from collective bargaining. Working paper, September 28. Available at SSRN: http://ssrn.com/abstract=933698. Nay, L.A. 1991. The determinants of concession bargaining in the airline industry. Industrial and Labor Relations Review 44 (2), 307–23. Pierce, B. 1999. Using the National Compensation Survey to predict wage rates. Compensation and Working Conditions (Winter), 8–16. US Bureau of Labor Statistics. 2006. Job openings and labor turnover: April 2006. News Release, Table 8, at http://www.bls.gov/news.release/jolts.toc.htm. Wachter, M.L. 2004. Declaration and Expert Report of Michael L. Wachter. Exhibit 103, in the United States Bankruptcy Court for the Northern District of Illinois, Eastern Division, In re Chapter 11, UAL Corporation, et al., Case No. 02-B-48191, December.



3 Toward Rational Pricing of the US Airport and Airways System Daniel P. Kaplan∗�1

ABSTRACT The taxes and fees flights presently pay for use of the airports and airways in the United States presently bear little relationship to the cost of providing those services. As a result these prices generate significant distortions. Most notably, the present system of prices actually subsidizes flights operating at congested airport, and thereby foster delay. If the prices of the airport and airways system better reflected costs, there would not only be fewer delays, but more prudent investment decisions as well. This chapter considers how such a pricing system might be implemented and estimates the subsidies and overcharges to commercial aircraft operating at New York’s LaGuardia airport in 2004.

1 INTRODUCTION AND OVERVIEW For decades, US airlines have complained about the delays and the costs at the nation’s airports, as they fretted about the pace of improvements to the Air Traffic Control (ATC) system. These concerns have spawned a variety of policy proposals ranging from the imposition of congestion fees to the privatization of airports and the ATC system. Regardless of their merits, these proposals all face substantial political opposition. For example, air carriers believe they already pay too much for airport services, and therefore, wholeheartedly resist paying yet another charge. Organized labor, meanwhile, wants to keep ATC jobs in the public sector.

∗ Director, LECG, LLC 1725 Eye Street NW, Suite 800, Washington, DC 20006, Direct: 202-973-9877, Main: 202-466-4422, Fax: 202-466-4487, [email protected] 1 The author appreciates the comments of Darin Lee and David Gillen and the assistance of Zachary Kaplan. The chapter has benefited from conversations with Sandy Rederer, Mark Kahan, and Dorothy Robyn.

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DANIEL P. KAPLAN

Despite the various complaints about the performance of the airport and airway system, there has been surprisingly little analysis of the prices users are currently paying.2 Price plays a central role in the efficient operation of a market by determining how much is produced and how that output is allocated. Price serves neither function in the case of the airport and airways system. Because prices for airport and airways services bear little relationship to cost, they actually foster delay by subsidizing low-valued services at congested facilities. Moreover, the system charges different users vastly different prices for the same service, thereby suppressing an important indicator of the value of additional capacity and distorting investment decisions. More rational pricing, therefore, has the potential not only to produce short-run gains at congested facility, but lead to more sensible long-run investments. Various government agencies in the United States (federal, state, and municipal) own and operate the airports and the ATC system, and there are significant monopoly elements in the provision of these services. Consequently, as either an owner or regulator, the continued role of the federal government in the pricing of the airport and airways system is virtually assured. A range of alternative pricing systems would likely lead to significant efficiency gains. In addition to discussing the deficiencies of the existing system, this chapter advocates a particular approach to pricing, which should reduce many of the existing distortions and could be implemented at relatively low cost. The potential impact of the new system is illustrated by considering the effect its adoption would have on prices currently paid by flights at New York’s LaGuardia Airport. Key features of the proposed system include: • Airport and airways services would be segregated into three separate activities and users would face charges for each. In addition to a fee for the use of an airport’s airfield, a flight would pay distinct fees for terminal services at each airport as well as for the en route control services it uses in traveling between them. • Flight operators would pay a price at least equal to the average variable cost (an approximation of marginal cost) of the relevant services, although those flying during periods when a facility is congested would pay more than users during uncongested periods. • Total revenue from the fees for any service would not exceed the operating costs of providing that service. Though aircraft operators would pay higher fees at certain periods, users during less congested periods would pay less. Accordingly, the proposed system does not involve congestion fees as the term has typically been used. • All system users would face the same set of fees, ending the existing distinction both between passenger and freight carriers and between commercial and private aviation. • Because airports and the ATC system offer complementary services, prices for both would be jointly established. This chapter consists of seven additional sections. Section 2 provides an overview of the taxes and fees aircraft operators currently pay for the use of the airport and airways system. Using FAA data, Section 3 provides rough estimates of the cost of

2 Michael Levine, however, did consider a number of these issues in an article in the 1960s. See “Landing Fees and the Airport Congestion Problem,” Journal of Law and Economics XII (April 1969), pp. 79–108.

TOWARD RATIONAL PRICING OF THE US AIRPORT AND AIRWAYS SYSTEM

63

providing these services and highlights the wide discrepancy between costs and price. This misalignment is largely caused by prices being more closely tied to the value of the service to the user than the cost of producing the service. Section 4 discusses some basic issues the federal government should consider in designing a new price framework including the complementarities between ATC and airport services. Section 5 describes the proposed pricing system. New York City’s LaGuardia Airport is one of the nation’s most congested, and Section 6 estimates the gap between the prices paid by different flights and the costs of the services they receive under the existing system of charges. Though passenger carriers overall pay substantially more than the cost of the service they receive, a move to a more cost-based system would reduce the profitability of a substantial number of LaGuardia flights. Thus a move to a more cost-based system could reduce congestion at the same time that it reduced the overall amount carriers paid for the use of the airport and airways system. A concluding section offers some remarks about implementing the new system along with a discussion of the special treatment that might be afforded to flights serving small communities as well as for some private aviation.

2 EXISTING TAX AND FEE SYSTEM Two sets of agencies provide airport and airways services. The major (but certainly not the exclusive) role of the Federal Aviation Administration (FAA) is providing ATC services. The FAA is financed by general fund revenues as well as a variety of aviation taxes flowing through a trust fund. Receipts from these aviation taxes, however, reasonably approximate the cost of ATC services. These ATC services are provided in conjunction with the services of airports, which are, for the most part, owned and operated by various municipal governments. Airports provide a variety of services, but the analysis here focuses exclusively on the airfield. Airports have traditionally recovered these airfield costs through landing fees.

2.1 Federal Aviation Administration A combination of general fund revenues and aviation related taxes fund the ATC system. Technically, these taxes are paid into the Airport and Airway Trust Fund (Trust Fund), and the Trust Fund is the FAA’s major funding source. The Congress established the Trust Fund in 1970 to procure navigational aids and to develop airports. Since it established the Trust Fund, Congress has changed some rates and created some new taxes, but the present panoply of aviation taxes is largely consistent with those originally adopted.3 Though the taxes have remained more or less the same, the Trust Fund’s role has changed significantly. Now most Trust Fund revenues are used to underwrite the FAA’s operations, with only a portion devoted to the Trust Fund’s original purpose

3

There were aviation taxes prior to 1970, but these taxes went directly to the general fund. By creating the Trust Fund, the airlines hoped they would benefit directly from the fees they paid.

DANIEL P. KAPLAN

64

Table 1 Aviation Excise Tax Revenues, FY 2004 (In Millions) Excise Tax

Domestic Passenger

Domestic Freighter

General Aviation $52 $20

Foreign Carriers

TOTAL

$64 $21 $746

$4,929 $1,747 $1,539

Domestic passenger ticket tax Domestic flight segment tax International arrival and departure tax Domestic cargo and mail Fuel tax Alaska-Hawaii

$4�813 $1�706 $793 $28 $423 $59

$452 $60

$317

$4 $9 $12

$484 $810 $70

TOTAL

$7�893

$512

$317

$856

$9,579

Percent of total Percent of domestic

82.4% 90.5%

5.3% 5.9%

3.3% 3.6%

8.9%

Note:

1) Fractional ownership payments of $51.9 million in Ticket Tax; $20.2 million in Segment Tax; and

$8 million in fuel taxes are included under General Aviation. 2) The tex rate for commerical fuel is 4.3 cents per gallon, and the tax rate for general aviation av gas is 19.3 cents per gallon and 21.8 for jet fuel. Source: FAA.

of underwriting infrastructure investments.4 Operating the ATC system is the most significant of the FAA’s activities, but it also oversees airport improvements and the safety of aircraft and airlines, in addition to performing a variety of other aviation services.5 Receipts from nearly a dozen aviation related taxes flow into the Trust Fund, and they totaled over $9.58 billion dollars in FY 2004, of which $8.04 billion were raised by taxes on domestic service (Table 1).6 The tax rates applicable to any given flight, however, depend very much on its purpose. Flights by a commercial passenger carrier, a freight operator, and a corporate jet, each making precisely the same demand on the ATC system pay, very different amounts.7 4

See Federal Aviation Administration, “Budget in Brief, Fiscal Year 2006.” Trust Fund revenues pay for the FAA’s capital expenditures (specifically outlays for the Airport Improvement Program and for Facilities and Equipment) with the balance of Trust Fund revenues to be used to support FAA operations. In recent years, however, the budget has established a Trust Fund contribution to the FAA, which has exceeded Trust Fund revenues. As a result, the uncommitted balance of the Trust Fund has been reduced. (The General Fund contributed 26 per cent of the FAA revenues in 2004.) Also see General Accounting Office, Airport and Airway Trust Fund, GAO-03-979, September 2003, p. 12. 5 The ATO, a performance-based organization, was established in 2004 to incorporate functions relating to operating the ATC system. It does not have a separate funding source. 6 This is approximately equal to the FAA expenditures on operating the ATC system. Expenditures on ATC are not the same as operating costs, because the federal government does not distinguish between current and capital expenditures. International flights use some of the same services consumed by domestic flights. 7 Users of the transportation service nominally pay some of these taxes. Nevertheless, the identity of the person paying a tax has relatively little to do with the incidence of the tax. The following discussion assumes all taxes are paid by the entity operating the flight, which is unlikely to be the case.


65

The ticket tax, which is a 7.5 per cent tax on domestic airfares, accounts for over half of the revenue generated by the various Trust Fund taxes.8 Commercial passenger carriers also pay a $3.10 per passenger segment tax. Carriers transporting cargo domes tically, whether by freighter or in the belly of a passenger aircraft, pay a 6.25 per cent fee on the value of the air transportation provided. In addition, commercial carriers also pay a 4.3 cent per gallon fuel tax. General aviation flights, on the other hand, pay only a fuel tax: 21.8 cents per gallon for jets and 19.3 cents per gallon for non-jets. The taxes on passenger and cargo revenues are valued based: taxes are tied to the amount the passenger or shipper pays for air service, which in turn is a reasonable approximation of the value consumers attach to the service. While not as directly tied to value, the segment tax is also value based because the amount paid increases with the number of passengers, and the more passengers onboard the greater the value of the flight. Even the amount a flight pays in fuel taxes is highly correlated to a flight’s value, because larger aircraft not only carry greater numbers of passengers but they also burn more fuel. Likewise both fares and fuel use tend to be correlated with distance. While within any category of flights, the taxes paid by a flight tend to be highly correlated with its value, there may be little if any correlation between taxes and values across categories of flights. In 2006, a general aviation jet flying from New York to Los Angeles paid $545 in fuel taxes, while a commercial B-767 flying the same route and using the same ATC services paid $2,500 dollars more.9 More generally, commercial passenger airlines, however, pay 90 per cent of the taxes associated with domestic aviation taxes, while accounting for only 60.7 per cent of the flights and 70.3 per cent of the flying hours of the principal users of the air traffic control system (Table 2).10 This disparity between their share of taxes and their share of activity has prompted claims of unfairness by, among others, the major carriers’ trade association.11

8 For all the Trust Fund taxes as of March 2006, see “Current Aviation Excise Tax Structure” on the Federal Aviation Administration Website (http://www.faa.gov/about/office_org/headquarters_offices/aep/aatf/media/ Simplified_Tax_Table.xls). 9 James C. May, “Smart – and Fair – Skies: A Blueprint for the Future,” Speech to the International Aviation Club, Washington, DC, April 18, 2006. (http://www.airlines.org/news/speeches/speech_4-18-06.htm). The Air Transportation Association, the trade group of the commercial carriers, calculates that a Buffalo to Philadelphia roundtrip flight on a commercial carrier would pay $900, while a business aircraft could pay as little as $22. Wall Street Journal, June 1, 2006. p. 1. 10 The output estimates include only those flights captured in the Enhanced Traffic Management System (ETMS), which records ATC use of flights operating under instrument flight rules (IFR). IFR flights tend to be the most intensive users of the en route control system. Though the vast majority of commercial passenger flights are recorded by ETMS, it includes about 35 per cent of general aviation flights. See Federal Aviation Administration, “Air Traffic Organization: Airports Data for Stakeholders, November 15, 2005.” 11 For Fiscal 2004, the Air Traffic Organization, which operates ATC, accounted for approximately 75 per cent of ATC outlays. See Federal Aviation Administration, Performance and Accountability Report, FY 2004, p. 90. (http://www.faa.gov/about/office_org/headquarters_offices/aba/offices/financial_management/ performance_accountability/media/2004_PAR.pdf) The aviation taxes fund FAA activities other than ATC operations.

DANIEL P. KAPLAN

66

Table 2 Use of Air Traffic Control for Domestic Service, FY 2004 User Classification

Passenger carriers Freighters Fractionals/non-sched part 135 General aviation-turbine Other TOTAL

Flights

10�746 901 1�809 2�884 1�361 17�701

En Route Activity Miles Flown

Hours

6�098�171 458� 328 644�476 659�734 343�393 8�204�101

15�933 1�257 2�211 2�063 1�204 22�668

Source: FAA.

When it originally established the aviation taxes, Congress probably gave little con sideration to the relative benefits and burdens they imposed on various segments of the industry. In any case, the regulatory structure established by the Civil Aeronau tics Board almost certainly limited the impact of the taxes on either fares or service.12 Moreover, private business jets were not very plentiful, and the express cargo services (i.e., services provided by the likes of Federal Express and UPS), which account for the bulk of the freighter service in the United States, had yet to be introduced. In short, in developing the current array of taxes, the government could not have possibly conceived the uses of the airspace or the demands on the system in the twenty-first century. The aviation taxes were also established with little regard for the cost of operating the ATC system. Nevertheless, in fiscal 2004 the revenues generated by these taxes were roughly in line with FAA expenditures on ATC. As noted previously, FAA generated $9.58 billion in 2004 taxes, which was less than 3 per cent higher than ATO expenditure. This comparison, however, overstates the correspondence between the two. Both the revenue and cost estimates include international service, and this analysis focuses on domestic services. In addition, the FAA records expenditures but not operating expenses, and the actual operating costs could be significantly different. Accordingly, this analysis proceeds on the assumption that the existing aviation fees pay for the operation of the ATC and the other FAA activities are funded with revenues from the general fund. This chapter’s inquiry, therefore, focuses on the issues surrounding the development of a more sensible and efficient method of collecting the revenues currently derived from the aviation taxes.

12 A person will only take a flight if the value attached to the flight exceeds its price, and the difference between a flight’s value and revenue is equal to its consumer surplus. The value of a flight to consumers, therefore, cannot be lower than the flight’s revenues. The percentage by which the value of the flight will exceed its revenues depends on, among other things, the elasticity of demand and passenger fares. The following discussion assumes that the revenues among flights are highly correlated with the value of the flights.


67

2.2 Airport Fees In addition to a variety of subsidiary services, airports provide an airfield for aircraft landing and take-offs.13 The United States’ Department of Transportation (DOT) has established a policy with respect to airport rates and charges that, among other things, require airports to establish landing fees that do not exceed the cost of the airfield14 (DOT defines the airfield to include the runways, taxiways, and various other parts of airport properties). Though not required by DOT, airports, almost without exception, recover the cost of operating the airfield with a weight-based landing fee. While weight-based landing fees recover the cost of the airfield, the fee for any given flight does not necessarily reflect the cost of accommodating that flight.15 Instead the fee paid by any flight tends to be tied to the value of that flight. Heavier aircraft generally carry more passengers and more cargo, and consequently they generate more value. In that regard, landing fees resemble FAA taxes. Unlike the FAA taxes, however, aircraft regardless of purpose are subject to the same weight-based fees.

3 THE COST OF AIRPORT AND AIRWAYS Because economic efficiency requires prices to be aligned with costs, an understanding of both the output of the airport and airways system and the effect of variations in output on costs is a prerequisite to the development of a sensible system of charges. The current aviation taxes not only bear little relationships to cost, but the taxes are not even levied on the output of the system, which is an aircraft movement. This section begins by defining an aircraft movement for the purpose of developing an alternative price system and provides cost estimates of ATC services. The airport and airways system produces a service, which cannot be stored. The cost of a service, therefore, very much depends on the number seeking to use the service at any time.

3.1 Defining Output Price allocates goods and services among consumers and signals producers as to how much to produce. Though flight operators presently pay to use the ATC system, these

13

An airfield is only one part of an airport. Airports also facilitate passenger movement to and from flights as well as provide airlines with the space and facilities for needed services. If an airport operator was able to earn sufficient rents from airlines, passengers, and concessionaires for the use of the terminal and parking facilities it could conceivably recover its costs even if it offered use of the airfield at no charge. 14 Airports also establish rates and charges for non-airfield services, but these are not part of providing airport and airway services, and they are not considered here. See, Department of Transportation, “Policy Regarding Airport Rates and Charges,” Federal Register Vol. 61, No. 121, p. 31994. 15 In addition, to landing fees, most major airports also levy a Passenger Facility Charge (PFC) of up to $4.50 per departing passenger to fund capital projects. PFCs, unlike landing fees, are not calibrated to recover a particular set of costs but represent a source of funds for airport capital projects. Some of these projects relate to the airfield and others relate to terminal improvements. PFC payments among flights do not seem to be particularly aligned with the demands those flights place on the infrastructure. It would undoubtedly increase system efficiency if PFCs were incorporated into the proposed pricing system. This, however, is not explicitly considered here.

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DANIEL P. KAPLAN

payments do not directly correspond to the service the aircraft operator purchases. For example, the ATC system guides flights between airports, yet the largest component of the price depends on the revenues generated by that flight, which is only remotely related to the cost of the service provided. The use of taxes unrelated to output is a common method of financing the provision of public goods, such as police services, with large spillovers. It is not appropriate, however, for essentially private transactions such as an aircraft operator purchasing ATC services. A market is where the purchasers and producers exchange some consideration, usually money, for a good or service. For a market to operate efficiently, the output of the good or service should be clearly defined and the price paid by the consumer and received by the producer should be directly related to the amount being produced. Because the airport and airway system enables aircraft to travel between places, the most appropriate definition of output is an aircraft movement.16 In the present context, an aircraft movement incorporates both a landing or take-off at an airport and an aircraft’s flight between airports.17 En route control can be best measured in terms of time, although mileage can be used as a reasonable approximation. There is an element of imprecision in defining the output of airport and airways system as simply aircraft movements.18 For example, heavier aircraft often require runways that are both longer and have more reinforcement; they may also require greater taxiway clearance. In other words, an airport with a capacity to accommodate 50 regional jet operations per hour may not be able to handle the same number of widebody jet (i.e., Boeing 747) operations. In addition, with the present technology, aircraft travel between airports along designated traffic lanes, and the capacity of these lanes are similarly affected by the size of the aircraft. Factoring in aircraft size, however, would likely affect long-run and short-run costs differently. Despite the higher cost of building an airfield built to accommodate larger aircraft, the variable costs of operating the airport would remain quite small regardless of the size of the aircraft using it. The effect of aircraft size on operating costs is not explicitly factored into this analysis, and including the effect of aircraft size on costs would be unlikely to have a material effect on the welfare gains from adopting a new system.

3.2 Defining Cost The FAA does not report operating costs like firms in the private sector.19 While the FAA distinguishes between expenditures made on “facilities and equipment” and from those on operations, it does not report the useful lives of its assets nor does it incorporate

16 Airport policies with respect to the pricing of non-airfield services are not nearly as uniform. Because

the various airports provide disparate non-airfield services and because of the wide array of contractual

arrangements between airports and flight operators, it would likely be counterproductive to attempt to dictate

a price-setting mechanism in this analysis.

17 As discussed below, ATC includes both control of aircraft in the terminal areas surrounding airports as

well as the control of airports traveling between terminal areas.

18 For some short flights, the terminal area where the flight originates is adjacent to the terminal area of the

flight’s destination. Flights between such terminal areas do not require en route control.

19 Federal Aviation Administration, Air Traffic Organization, “Data Package for Stakeholders”,

November 15, 2005.


69

an interest charge. Consequently, calculations of fixed costs are imprecise. Most major airports, on the other hand, report financial results consistent with private sector practices. To begin with, most airports rely on capital markets to fund projects, and they must comply with various accounting processes in reporting their results. Moreover, the cost of operating an airfield is little affected by the number of operations, and thus virtually all the operating costs of the airfield are fixed. The efficiency of any cost-based pricing system can be improved by making the data more accurately reflect the cost of service. 3.2.1 ATC Establishing prices to recover costs requires estimates of both the costs to be recovered and the output to be produced. Combined with an understanding of the relationship between how costs change in response to fluctuations in output, these data permit the calculation of prices necessary to recover the costs. Estimates of the relevant rates are determined by using data provided by the FAA. These rates are subsequently used in Section 6 to analyze the costs of service at LaGuardia. Identifying Cost Pools. Table 3 provides an overview of FAA’s costs of operating the ATC system. The FAA has grouped its 615 operating facilities into three functional areas, and for each it has established four categories of costs. For each facility, it distinguishes between capital expenditures and other expenditures, which are for the most part, labor.20 For the purposes of the current analysis, we assume non-capital expenses at a facility to be variable.21 The FAA also allocates its administrative and overhead costs to each operating unit, and this analysis treats these overhead costs along with capital expenditures as fixed. This analysis focuses on establishing prices to recover the costs associated with terminal control and en route control. The costs associated with Table 3 Overview of Air Traffic Control Costs, FY 2004 Facility Type

Number of Facilities

Noncapital Operating Expenses of Facility

Capital Expenditures on Facilities and Equipment

Overhead Expenses

Total

Percentage of Costs which are Variable (%)

4�152 4�626 554 8�777

48�5 50�6

(in millions of dollars) Total en route Total terminal Flight station ATC TOTAL

26 528 61 554

2�016 2�342 375 4�358

1�333 1�462 60 2�795

803 822 119 1�625

Note: Honolulu (en route and terminal) is counted as one facility under terminal.

Other costs are included in overhead.

Source: FAA.

20

Also included with expenditures on equipment and facilities are contract expenditures for weather.

It is likely that at least some of these so-called variable costs do not vary with output and should be

classified as fixed. For example, during off-peak periods a facility that is staffed at a minimum level may not

have to add personnel to handle additional flights.

21

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DANIEL P. KAPLAN

the operation of Flight Stations as well as other FAA activities, such as licensing and safety expenses, would need to be funded through either a dedicated set of taxes and fees or general fund revenues.22 Terminal control guides aircraft approaches at an airport as well as controlling take offs and landings. At many airports, a radar terminal provides both functions. In areas with several airports (including military as well as civilian), terminal radar approach control (TRACON) provides approach control while a limited radar tower handles the landings and take-offs. Of the 500 airports in the United States, 200 have a radar tower or a limited radar tower operated in conjunction with a TRACON.23 Ninety-five per cent of commercial passenger operations occur at these airports.24 Other airports have more limited service. For example 73 airports have VFR Towers, which control landings and take-offs but not approaches. Other towers are staffed by contract employees, while some have no staff at all and provide only automated services. In recovering the costs of terminal control, separate cost pools could be established for each of the more than 500 facilities or, as is done here, all the facilities could be lumped together into a single cost pool. Alternatively, several separate cost pools could be established by combining various facilities with similar characteristics, for example, size or location. Limiting the number of cost pools would make the ratemaking process more transparent to users and easier to administer. En route control involves both domestic and international operations. This analysis does not explicitly consider international services, but in practice one or more separate cost pools could be established for international service.25 The system would likely be most efficiently administered if the costs of domestic en route control were allocated to a single cost pool. Aircraft regularly use tens of thousands of routings, and each flight path requires a unique set of control services. With multiple cost centers, each routing would potentially be subject to a unique charge, increasing administrative difficulties and making price signals unnecessarily opaque to system users. Computing Unit Costs. In FY 2004, ATO spent $8,777 million on Terminal and En route control, with 47.3 per cent of the total dedicated to en route control. For both activities, the non-capital expenditures at each facility were assumed to be variable and to represent one-half of the total cost. Table 4 calculates the unit costs by dividing the costs of operating the relevant ATC service in 2004 by the number of operations. On average, the terminal control cost per landing or take-off was $130.67 and the cost of the en route control was $171.01 per hour.26

22

Flight Service Stations consist of 58 facilities that provide weather briefings, flight plan filing services, and

other assistance to private pilots. The cost of operating these facilities was $554 million in 2004, although

the FAA expects to reduce those costs significantly by turning their operation over to a private contractor.

See Robert W. Poole, Jr, “Outsourced Flight Service Stations Save FAA $2.2 Billion,” Reason Foundation

Commentary, September 1, 2005. (http://www.reason.org/commentaries/poole_20050901.shtml.)

23 See “Data Package for Stakeholders,” p. 8.

24 In contrast, 35 per cent of general aviation operations occur at these airports. Around 60 per cent of general

aviation flights provided in jet aircraft (which for these purposes include fractional ownership aircraft) operate

at these large airports. Ibid, p. 10.

25 For example, separate international cost centers could be established for the Atlantic, Pacific and Latin

America.

26 A flight requires terminal operations at the departing as well as the arriving airport.


71

Table 4 Unit Costs of Air Traffic Control, FY 2004 ATC Operation

Cost ($)

Landings and Take-offs

Hours En Route

Unit Cost ($)

(in thousands) Terminal control En route control

4,625,900 3,876,500

35,402 22,668

130.67

171.01

Source: Tables 2 and 3.

3.2.2 Airports Though the costs of operating the various ATO facilities providing terminal control (or for that matter, en route control) can be combined into a single cost center, the operating costs of the various airports cannot be similarly aggregated. The various airports are owned and operated by separate entities, each of which have made financing and other commitments tied directly to the operation of the facility.27 Thus, airfield cost pools will continue to be calculated as they are presently. As discussed in detail below, however, the method for recovering those costs will change for some airports.

3.3 Effect of Demand on Cost Because airport and airway services cannot be stored, average cost pricing may not be a reasonable method of recovering costs. Excess capacity at 5 a.m. is of little value to some one wanting to fly at 5 p.m. Faced with insufficient capacity to serve peak period demand, an operator would have to ration the available supply in the short run. In most markets, price is that rationing device, but where the price mechanism is suppressed, other rationing devices evolve. In the case of the airport and airways system, that mechanism is delay.28 It is generally efficient for peak period users of a facility to pay more. Peak period demand determines the size of a facility – a smaller facility could accommodate demand if the use of the facility were spread evenly throughout the relevant time period. Thus a facility operator could profitably expand the size of a facility if two conditions were met: 1) the facility could not otherwise accommodate peak period demand and 2) the revenues generated as a result of the added capacity were sufficient to recover the cost of the added capacity. Because extra capacity is required to accommodate peak period demand, the peak period users should bear the additional cost.29 The addition of a flight during a peak period increases the delays experienced by existing users without affecting the costs of producing the service provided. Thus, a 27 Some entities, for example the Port Authority of New York and New Jersey, own and operate several airports. 28 High prices encourage suppliers to expand output. In the absence of price, mounting delays prompt expansion decisions. Delay statistics, however, do not provide the same quality of information as price. Consider, for example, the case in which delay is caused by low value users. 29 See, for example, W. Kip Viscusi, John M. Vernon, and John E. Harrington, Jr, Economics of Regulation and Antitrust, 2nd Edition (MIT Press: Cambridge, MA. 1995) pp. 399–403.

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transaction involving two parties (an aircraft operator and the airport) imposes costs on those not party to the transaction. This phenomenon, commonly referred to as an externality, is discussed below.

4 BASIC PRINCIPLES UNDERLYING A NEW PRICING SYSTEM Competitive markets generally produce efficient outcomes. They provide consumers with low prices by forcing prices down to producers’ costs and by forcing producers to operate at low costs. Markets for airport and airways services, however, are not competitive. Neither ATC nor airports face much competition, and the facilities are government owned and operated. Relying on the competitive market is, therefore, not an alternative, and the federal government will continue its major role in either establishing or regulating prices of airport and airways services for the foreseeable future. Competitive markets efficiently allocate goods and services by providing both con sumers and producers with meaningful signals to guide their consumption and production decisions. The existing prices for airport and airways services bear virtually no relation to the cost of service, and accordingly, do not provide any guidance to producer or consumers as to their efficient allocation. Numerous government agencies have designed regulatory regimes to encourage firms with market power to make price and output decisions consistent with the regulators’ notions of social welfare.30 These efforts, however, have met with only limited success. The pricing mechanism proposed here has much more limited goals; it seeks to create a new set of prices that lack the perverse incentives of the current system. The proposed pricing regime does not treat congestion (and the resulting delays) as an externality, and therefore, an inevitable consequence of providing airport and airways services. The political process – and not the underlying supply and demand conditions – is preventing government agencies from establishing market-clearing prices. The existing economic literature has mistakenly categorized the inability of the political process to craft a satisfactory pricing mechanism as a market failure.31

4.1 Basic Criteria for More Efficient Prices As both a producer and a regulator, government agencies should strive to establish prices consistent with economic efficiency. In the absence of externalities, competitive markets establish efficient prices by establishing prices equal to marginal cost. Moreover, such prices generate sufficient revenues to cover a firms’ operating costs.32 In addition, the

30

For a discussion of the regulation of industries from electric power to trucking, see Viscusi et al. op.cit.,

pp. 377–652.

31 See, for example, Christopher Mayer and Todd Sinai, “Network Effects, Congestion Externalities, and

Air Traffic Delays: Or Why All Delays are Not Evil,” American Economic Review 93 (September 2003),

pp. 1194–1215.

32 Competitive prices cover the costs of efficient firms. The efficiency of government operated enterprises

relative to private firms is not considered here.


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new pricing scheme should require prices to be reset periodically to reflect changes in costs and demand. It should also reflect the complementarities between airport and ATC services. 4.1.1 Establishing Prices Equal to Costs Economic efficiency very much depends on the relationship between price and marginal cost.33 With price equal to marginal cost, the value a purchaser attaches to an additional unit of output just matches the cost of the resources needed to produce that added output. A government agency charging such cost-based prices may be unable to generate revenues sufficient to recover fully the costs it incurs in producing an efficient level of output. This is most likely to be a complication where economies of scale are present. Under those circumstances, it is generally most efficient to recover the revenue shortfall through a value-based fee. Variable Cost Recovery. In a competitive market, a firm finds it profitable to expand output so long as price exceeds marginal cost, which is the cost of an additional unit of output. Marginal costs, however, are notoriously difficult to calculate. In the short run, capacity is fixed, and marginal costs consist mostly of labor. Accordingly, average variable cost has generally been accepted as a reasonable proxy, and it serves that function under the proposed pricing scheme.34 Fixed Cost Recovery. By definition, price equal to average variable cost does not recover the fixed costs of providing a service. While it would be inefficient to charge less than average variable cost, short-run efficiency does not require the recovery of fixed costs. Fixed costs are incurred regardless of use, and it would be inefficient to discourage demand during periods of excess capacity by burdening some users with an unnecessarily large share of those costs. Two factors – economies of scale and demand fluctuations – are important in determining how these fixed costs should be recovered. First consider the case where the service is produced subject to constant returns to scale. With constant returns to scale, the size of the facility can be matched with peak period demand. Capacity will be expanded so long as peak users place a sufficiently high value on the added capacity to finance the requisite investment. In the presence of constant returns to scale, therefore, price could vary over time as it balances demand with capacity. All users operating during periods in which there was no excess capacity would bear the fixed costs of the facility, although users during periods of higher demand would pay more. In other words, the charges to recover fixed costs would be established with the goal of reducing variations in demand over time. In no case, however, would a user pay less than average variable cost and the total revenues would not exceed the costs of operating the facility.

33

The output that equilibrates price and marginal cost is efficient, because it would be inefficient to produce either more or less. If too much were produced, users place a lower value on the added output than its cost of production, and thus consumers are unwilling to pay the cost of the extra unit of production. Price above incremental cost is also inefficient, because users place a higher value on additional output than its cost to product, and accordingly output should be expanded. 34 See, for example, Phillip Areeda and Donald Turner, “Predatory Prices and Related Practices Under Section 2 of the Sherman Act,” Harvard Law Review, Volume 86, 1975, pp. 697–733.

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In the presence of economies of scale, a different cost recovery system may be required. Indivisibilities may necessitate investing in too much capacity at any given time.35 As a result, excess capacity may be present even during periods of high demand. In that case, fixed cost recovery would require at least some users to pay more than marginal cost. It has long been recognized that the most efficient method of recovering fixed costs in the presence of excess capacity is through Ramsey prices.36 Ramsey prices allocate fixed costs among users based on their elasticities of demand – those with less elastic demand contribute a disproportionately large share toward the fixed costs. The lower a purchaser’s elasticity of demand, the smaller the impact a given percentage change in price will have on the amount purchased. Accordingly, Ramsey prices are efficient, because they recover the fixed costs and produce the smallest deviation from the output produced by marginal cost prices. A strict implementation of Ramsey prices is technically not possible, because price elasticities of individual purchasers are not observable. As an alternative, variations in prices among purchasers would be based on some proxy The greater the value a consumer attaches to a good or service, the smaller the impact a given percentage change in price has on the quantity demanded. As previously noted, many of the present aviation taxes and fees are value based. The proposed pricing scheme employs aircraft weight and aircraft weight minutes (i.e., an aircraft weighing a thousand pounds flying for 100 miles minutes generates 100,000 aircraft weight minutes) to measure value. The value of a flight is related to its payload, which in turn is likely to be highly correlated with the size of the aircraft. Similarly, longer flights tend to be more valuable.37 Aircraft weight is an equitable and transparent measure of value, because the relationship between aircraft weight and capacity exists regardless of what the flight transports or whether it is a commercial or private service.38 4.1.2 Responsive to Changes in Costs and Demand An added flight during a congested period may significantly degrade the service quality of others. Yet the degradation in service quality reduces demand. A higher price, therefore, might not only be profitable, but could also actually improve the quality of service. (In fact, because of the improved service quality, the higher price would actually increase demand.) Because users would be charged more during periods where congestion resulted in consistent delays, the price at any time depends not only on the costs at the facility but on demand as well. With demand and capacity held constant, prices would be changed periodically to reflect changes in costs of producing the service – a 10 per cent increase in cost would produce a 10 per cent price increase. If, however, increased demand produced increased

35 An investment in too much capacity may be prudent in anticipation of future growth or to employ a lower

cost technology.

36 Viscusi, et. al., op.cit., pp. 365–367.

37 Time is a more accurate measure of value than distance, because the cost per mile of an aircraft’s operation

is lowest when the aircraft reaches cruising altitude.

38 This relationship is not exact. Newer aircraft use lighter materials and are therefore can carry greater

payloads per unit of aircraft weight. In fact, a whole new class of very light jets, which are expected to be

widely employed as air taxis, should begin operating in 2006.


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congestion during a particular period, a larger price increase during that period might be appropriate. Specifically, the price for peak period users would be established sufficiently above average variable cost to limit the delay faced by users of the facility at the time. Because the total revenues generated by the fees cannot exceed cost, an increase in the price above the percentage change in cost at any given time requires a corresponding lower rate of increase during other periods. Determining the necessary adjustments to be made is not straightforward. There is uncertainty with respect to the effect of price changes on demand as well as their effect on revenues. Increases in peak period fees would be dictated by delay statistics with higher fees generally associated with periods of time experiencing longer delay. Fees in adjacent periods may also need to be raised to limit the likelihood of congestion being shifted into those periods. For example, raising fees for flights between 5 and 5.30 p.m. may lead some users to simply shift their flights to a later or earlier time period. This may simply shift the congestion to a different period. While it might be appropriate to adjust adjacent period prices, a period with a higher fee should not have fewer delays than a period with a lower fee. 4.1.3 Airports and ATC Offer Complementary Service A flight uses both airport and airways services, and a change in the price of one of the services affects demand for the other. An increase in an airport’s peak period fees would affect the timing and the mix of aircraft using ATC services as well. The relationship is especially close in the case of airports and terminal operations, because aircraft employ both in fixed proportions.39 Suppose, for example, an airport experiencing congestion moved to a cost-based movement fee for the use of the airfield. Independently adjusting terminal operations to reflect congestion could produce prices too high and as a result generate excess capacity during peak demand periods. Because the use of airports and ATC services are so closely related, the prices for the services of airports and the ATC should be established in conjunction with one another.

4.2 The Economics and the Politics of Airport Delay A number of economists consider delay at a congested airport to be the result of a market failure – users do not pay the costs associated with the increased delays that is associated with an additional flight at the airport. Advocacy of congestion pricing began in the mid-1960s in response to a significant increase in delays at a number of airports, and the view among some economists that the problem could be best viewed as an externality. These congestion problems were ultimately resolved with Congress limiting aircraft operations at five airports. Congestion has been a recurring problem, even as restrictions at those airports are actually being relaxed. The government has been exploring alternative methods of controlling access including a “market solution”, which is a euphemism for congestion pricing.

39

Flights use the services of terminal control and the airfield in fixed proportions – much like the sale of left and right shoes. Unlike shoe manufacturing, however, the same firm does not produce both terminal control and airfield services, and it would be sensible if the entities coordinated the price-setting process.

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Delay can be considered an externality because the transaction between a flight oper ator and, for example, the airport, can affect other operators. Establishing a congestion fee to reflect the delay costs imposed on others would more closely align the price a user had to pay for a service with the full social cost of the service. By increasing the costs of operating during congested periods, such a fee discourages those flights that place a relatively low value of operating at the facility during peak periods. This is economically efficient because a well-functioning market allocates a scarce resource to those valuing it most highly. Thus, even if the congestion fee were established to maintain existing levels of delay, the change in the flight mix at the airport could yield welfare gains. A higher price would reduce delay and could thereby yield even further gains.40 Explicitly incorporating demand into the establishment of prices would yield similar welfare gains at a lower overall cost to users. By charging a higher price, a so-called congestion fee would internalize the externality. While delay is an externality, it is not a natural outcome of producing airport and airways services. As already noted, the present pricing system actually subsidizes system use during high demand periods. In other words, delay is at least partly the result of the peculiar pricing system established by the political process. Users fear that the imposition of congestion prices will increase carrier costs with no assurance of a corresponding improvement in service quality. Congestion fees increase the cost of all the flights operating during peak periods – high-value and low-value flights would both pay higher fees in order to encourage the low-value flights to move to either less congested time periods or different airports. Yet the existing pricing system actually subsidizes these low-valued flights. Thus the imposition of congestion prices would require high-value flights to continue to sub sidize airport and airways services received by these low-value flights, and then pay yet another fee as part of an effort to encourage these subsidized flights to operate differently. When combined with the present pricing system, a congestion fee would require high-value flights to pay twice – an above cost fee to subsidize low-value flights and then a congestion fee to undo the effect of the subsidy. Clearly, it would be far more efficient to align prices more closely with cost before even considering imposing congestion fees. Not only may it be a mistake to classify delay as the product of an externality, recent economic research has suggested that, at least at some airports, delay may not even be a reliable indicator of market failure.41 At many major airports, a hub carrier accounts for a large share of the operations. In order to minimize the time passengers must spend on the ground between flights, a hub carrier often bunches its arrivals and departures. An increase in the hub carrier’s flights will increase delays at the airport, but it is the hub carrier’s own flights that will experience most of the increased delay. Delays a carrier imposes on itself are not an externality. With hub carriers typically accounting for more than half of the flights at their hubs, delays at such airports should not be considered as the actions of two parties affecting a third.

40 It would be both efficient and profitable for an airport to raise price in the face of congestion so long as the value of the resulting reduction in delay exceeds the additional revenue generated by the price increase. 41 See, for example, Mayer and Sinai, op.cit.


77

The proposed pricing system is not congestion pricing per se, although it recognizes congestion as a factor in allocating the costs of the airport and airways system among system users. The higher prices during more congested periods do not reflect the costs of congestion as much as they provide a clearer signal of the value of expanding a facility. Moreover, unlike congestion prices, the charges under the proposed scheme will not generate revenues in excess of the cost of the service provided.

5 DEFINING THE NEW SYSTEM While representing a movement toward cost-based prices, the proposed price system nevertheless maintains important characteristics of the existing system. Most notably, the proposed pricing system generates revenues equal to the costs of providing the relevant services, and it maintains important attributes of the current system of value pricing. It, however, eliminates different prices for different types of users, and it establishes consistent pricing between airports and airways, which are complementary services. Under the proposed system, a flight would be assessed charges for the airfield and for the terminal operations at the airport where the flight originates as well as at the destination airport.42 These charges would be established to recover specific and welldefined costs. In addition, no user would pay less than average variable cost, a proxy for marginal cost. During periods of congestion, however, this base fee would be increased in order to reduce delay at the facility. Flights operating at the airport would, therefore, pay the greater of average variable cost- or a congestion-based fee. If the revenues from these fees failed to generate revenues sufficient to cover the relevant costs, flights would also be assessed a weight-based fee to make up the shortfall.

5.1 Airports In the hypothetical competitive market, an airport would charge all flights uniform fees with the specific fee at any time reflecting the level of congestion. During periods of low demand, at night for example, price would approach zero, because the marginal cost at airports is quite low. Because the levels of congestion may differ between the time an aircraft arrives at an airport and when it departs, it would likely be efficient to institute separate charges for landings and take-offs. In the subsequent discussion, such a charge is referred to as an airport use fee. While efficient, the revenues generated by these congestion-based prices might be less than the operating cost for the airfield Weight-based fees would recover the shortfall. At airports with substantial excess capacity, therefore, virtually the entire airfield costs would be recovered through a weight-based fee, which is precisely how landing fees

42 As discussed in detail below, at uncongested airports the airfield fees will be constant over time. As a result, these airports can continue to charge a single fee to cover both landings and take-offs as is the case with existing landing fees.

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DANIEL P. KAPLAN

are currently established.43 There are likely to be many such airports. Runways are not scalable: a runway built to handle one operation per hour can also accommodate up to 45 per hour, resulting in excess capacity for large portions of the day, and in some cases, the entire day.44 This two part charging system – a uniform fee based on congestion coupled with a weight-based fee to recover the shortfall – requires large aircraft operators to continue paying fees well in excess of the cost of service at airports with limited or no congestion. As noted earlier, however, weight-based fees are likely to be reasonable approximation of Ramsey prices, and therefore, a relatively efficient means of recovering fixed costs. A shift to more cost-based prices generates an efficiency gain by providing some basis for quantifying the value of the expanded capacity. That portion of the airport use fee that is influenced by the level of congestion at the airport would be an important input into any analysis of the added value. Added capacity benefits peak period users. In a pricing environment with a minimum airfield use fee, additional airfield capacity would lower these minimum fees and encourage operations by lower valued flights. The decision to expand capacity should be based on whether the revenues generated by the additional flights would be sufficient to justify the added cost of expanding the facility. Decisions to expand capacity should not be based on the ability to recover the cost of the expansion from users that would be accommodated by the existing facilities if they were being priced efficiently. In other words, the ability to extract higher fees from heavier aircraft should not be considered in valuing capacity additions.

5.2 ATC Services Under the proposed system, the two components of ATC services, terminal control and en route control, would be priced separately. Terminal control costs, like airfield costs, are very much influenced by take-offs and landings at a particular airport. En route control, on the other hand, is influenced by the amount of time a flight is airborne. This analysis assumes ATC services are subject to constant returns to scale over a wide range of outputs, and unit costs of ATC services are uniform across the country. A cost pool for terminal operations at each airport, therefore, would be derived by applying a nationwide unit cost (e.g., cost per aircraft movement) to the expected activity at the airport.45 5.2.1 Terminal Control Because the cost of terminal control is airport specific, the derivation of the price of terminal control is also airport specific. As in the case of airfield services, each flight (and each take-off and landing) is priced separately.

43 Weight-based landing fees are also justified by larger aircrafts’ requirements for longer runways, greater reinforcement and wider taxiways. 44 The capacity of the airfield, however, can be expanded by constructing more taxiways. By permitting aircraft to spend less time on the runway, an expansion increases the amount of time the runway can be used to for landings and take-offs. 45 In practice it may be advisable to establish more disaggregated cost pools – for example, by metropolitan area or by a characteristic of the metropolitan area such as size.


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All flights, regardless of when they operate, would pay at least average variable cost for terminal control.46 Additions to airport capacity can sometimes be only made in relatively large increments – a runway, for example, represents a significant increment to capacity. In contrast, terminal operations at an airport are much more likely to exhibit relatively constant returns to scale, and, as a result, the facilities needed to provide the appropriate level of services can be tailored to match demand. Because of the flexibility in determining the size of the terminal operations at an airport, there is less likely to be excess capacity, which also reduces the need to employ weight-based pricing to recover fixed costs. Unlike airfields, therefore, value pricing would ultimately likely play only a very small role in the recovery of the costs of terminal operations. Nevertheless, because of the importance of value pricing under the current system, the continued use of value as a component in the pricing of terminal services may be warranted in any transition. Some aircraft operators may have made investments in equipment and other resources based on the existing system of charges. Continuing to have a significant – although over time diminishing – component of the terminal price based on value may soften the financial impact of the shift and make implementing a new pricing regime more politically palatable. 5.2.2 En route control En route control provides ATC services between the arriving and departing airports. Unlike the space surrounding an airport, the space between airports is virtually limitless. In practice, aircraft are routed along defined traffic lanes, which effectively limit capacity at any given point in time. Yet because these traffic lanes are not made of brick and mortar, they are generally less a source of chronic congestion than either terminal control or the airports themselves. First, the FAA has some flexibility to determine the route of any given flight. In addition, over time, FAA has substantial flexibility to reconfigure these highways in the sky, and can add traffic lanes to meet demand growth. More significantly, the FAA is working on a system to increase a flight’s flexibility in selecting its own course in moving between airports. Such “free flight” not only reduces travel times between airports, but it further diminishes the possibility of aircraft experiencing en route congestion. The variable cost of providing en route control services to an aircraft depends directly on the length of time it travels between airports.47 Identifying peak travel periods and assessing fixed charges is more difficult in the case of en route control than it is for terminal control. For example, simply defining a traffic peak would be challenging – different areas experience peak traffic at different times. Moreover, the use of a weightbased measure to recover fixed costs is unlikely to introduce significant distortions. 46

Because unit costs of terminal control are the same at all airports, average variable costs are also the same. This assumes that average variable costs are constant over time. In fact, average variable cost may be lower during off-peak periods. 47 During take-off and landing flights not only travel more slowly, but they also do not fly in a straight path because of the need to position themselves. After leaving terminal control, flights are nearing their cruising speeds, and thus the time for which a flight uses en route control is closely related to distance. The variable cost of operating en route control, therefore, can be allocated to a flight based on either the amount of time or the number of miles, although the relationship between mileage and cost would not necessarily be linear.

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DANIEL P. KAPLAN

Nevertheless, such weight-based prices involve subsidizing low-valued flights, and this may be a problem at airports where congestion remains even after the imposition of cost-based prices for both the airfield and terminal operations. At such airports, therefore, it may be prudent to recover the fixed costs of en route control through prices that are tied to congestion.

6 EXAMPLE OF LAGUARDIA AIRPORT There is substantial demand by aircraft to operate at New York’s LaGuardia Airport. This airport, however, can only use one of its two intersecting runways at a time, and because it is surrounded by water and Queens, expansion is not a realistic option. Congestion has been a major problem at the airport for over 40 years, and the federal government has limited access to it since 1968, when it was one of a handful of airports governed by the High Density Rule (HDR). The HDR set hourly limits on the number of take-offs and landings at the airport, and it allocated operations among various different classes of carriers. The Congress has ordered an end to the use of the HDR at LaGuardia in 2007.48 General aviation accounted for less than 4 per cent of operations at the airport in 2004, but there is considerable unmet demand by private aircraft. Even if private aircraft were subject to the same prices as other aircraft using the airport, their use of the airport would undoubtedly increase substantially unless otherwise constrained. The following analysis assumes general aviation operations at LaGuardia would continue to be capped. Indeed, it is likely that even with the proposed pricing system, additional measures might be needed to limit congestion at the airport. Despite the apparent great demand to serve LaGuardia, nearly half the passenger aircraft serving the airport in 2004 had 50 seats or less.49 The proposed system would increase the amount these aircraft would pay more for the use of the airport and airway system, and thereby have an adverse effect on the profitability of flights using such equipment. In contrast, the cost of using larger aircraft would decline. The ultimate impact of the new pricing system, however, would depend on how carriers change their existing services as a result of these changes in profitability and the new services they introduce.50 The estimates in Tables 5–11 are based on services patterns at LaGuardia in 2004, and they provide a rough approximation of the costs and revenues of the various services offered at the airport. The calculations are merely illustrative. Most notably, no attempt

48 In 2000, the Congress exempted regional jets from small and medium communities from the HDR. This relaxation of the rule produced a flood of new service and dramatically increased delays at the airport. 49 These statistics are derived from DOT May 2004 T-100 statistics and exclude international flights. Passengers on international flights accounted for 5 per cent of the total at the airport during 2004. See Port Authority of New York and New Jersey, “December 2004 Passenger Report” (http://www.panynj.gov/). 50 While carriers can and do sell their operating rights, it is unlikely that the current mix of flights represents the highest valued services that could be offered at the airport. By refusing to sell an operating right to a higher valued user, a carrier preserves its option to realign its schedule in the future while preventing a rival’s introduction of a competitive service in the near term. Such strategic considerations may limit the ability of a free market in operating rights to result in an optimal pattern of service.


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has been made to factor a flight’s contribution to the carrier’s network in developing the revenue estimates.51

6.1 Taxes Under the Existing System To understand the impact of a new pricing system at LaGuardia, the revenues generated by the existing tax and fee system must first be estimated. To do this, flights are grouped into five categories based on aircraft size: the largest consists of aircraft with more than 120 seats, and the smallest has aircraft with fewer than 30 seats. Table 5 shows, the number of departures for each size category as well as averages of the number of seats, distance, and number of passengers. The three smallest size categories of aircraft, each with 50 seats or less, are operated by regional carriers. Though regional carriers are increasingly operating jets with more than 50 seats, these represented a very small proportion of the operations at LaGuardia in 2004. Thus, flights with more than 50 seats are assumed to have been operated by mainline carriers. Estimating the taxes and fees for the average flight in each aircraft group requires information on both aircraft weight and average fare. To determine aircraft weight, a representative aircraft was selected for each size class.52 The average fare for each aircraft was based on the statistical relationship between distance and local fares fare for all LaGuardia markets with nonstop service in the second quarter of 2004.53 Table 6 provides an estimate of the revenues generated by the average flight of each of the five aircraft types as well as the taxes and fees such flights would pay. In computing revenues, a flight is assumed to carry the average number of passengers of its respective size class, with each passenger paying the average fare of local LaGuardia passengers traveling that distance. The ticket tax is 7.5 per cent times those revenues, and the segment fee is $3.10 times the number of passengers.

Table 5 LaGuardia Flights by Aircraft Size, May 2004 Aircraft Seats

120 and up 51–119 40–50 30–39 less than 30

Departures Number

Per cent

7,263 788 2,659 4,046 364

48.0 5.2 17.6 26.8 2.4

Average Seats

Average Passengers

Average Minutes

Average Distance

146�5 107�7 49�4 36�8 19�6

105�8 82�0 30�5 20�4 9�1

103�2 106�2 78�5 67�8 52�1

742�0 772�6 496�8 328�9 178�7

Source: DOT, T-100.

51

For example, the economics of a flight between New York and Boston with only local passengers is very

different from a flight between the two cities where a significant proportion of the passengers are connecting

transatlantic passengers.

52 Maximum gross take-off weights were taken from the websites of the various manufacturers.

53 This is likely to overstate the onboard yields because connecting passengers typically have lower yields

than local passengers.

DANIEL P. KAPLAN

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Table 6 Taxes and Fees Under Existing System, 2004 Aircraft

A-320 B-717 ERJ-145 ERJ-135 Twin Otter

Landed Weight

Yield per Mile ($)

Landing Fees ($)

Aviation Taxes ($)

TOTAL ($)

145.5 102.0 42.5 40.8 12.5

0.216 0.208 0.315 0.464 0.825

578.36 405.45 140.94 135.10 41.41

1,599.79 1,241.98 453.17 296.58 128.53

2,178.15 1,647.43 594.11 431.68 169.93

Source: Manufacturers websites and DOT Origin and Destination Survey.

Most airports assess landing fees for a flight’s landing and its subsequent take-off, although this analysis assumes landings and take-offs are assessed separate airfield use fees. Because the landing fee at LaGuardia is relatively high, it is assumed that the mainline aircraft operate to airports where the appropriate fee is one-half as large, and the smaller aircraft operate at airports where the landing fee is one-fourth the fee at LaGuardia. This analysis does not specifically incorporate the taxes on fuel and cargo or the PFCs charged by most large airports. As already noted, these taxes and fees, like the ones considered here, are for mostly value based and including them would not fundamentally affect the analysis.

6.2 Cost of Service Table 7 estimates the average cost of providing airport and airways system for the five hypothetical flights considered above. The average cost estimates use the ATC estimates derived in Section 3 and are movement based. Airfield use fees were derived by assuming the existing landing fees recover airfield costs. The existing difference in taxes and fees among aircraft is quite large. A flight in an A-320 flight pays fees that are more than 10 times the amount paid by the Twin Otter flight and three times the

Table 7 Average Cost of LaGuardia Flights, 2004 Aircraft


Terminal Control

Landing Fees

LaGuardia ($)

Other ($)

LaGuardia ($)

Other ($)

131 131 131 131 131

131 131 131 131 131

249 249 249 249 249

124 124 62 62 62

Source: Author’s calculation.

En Route Control ($)

Total Cost ($)

294 303 224 193 149

929 937 796 766 721


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Table 8 Price–Cost Differential, 2004 Aircraft


Current Taxes and Fees ($)

Average Cost ($)

Difference ($)

2,178 1,647 594 432 170

929 937 796 766 721

1,249 710 −202 −334 −551

Note: Aviation Taxes derived by assuming all passengers pay estimate of

average local fare for the appropriate stage length.

Source: Authors calculation.

amount of a flight by a 50-seat EMB-145.54 Because the costs of the airport and airway services are predominately movement based, these price differences are largely unrelated to differences in the cost of the services provided. Accordingly, the A-320 flight pays $1,240 more in taxes and fees than the average cost of the service it receives (Table 8). In contrast, the Twin Otter pays $551 less than its average cost of service, and even the average flight by 50-seat ERJ-145 pays significantly less in taxes than the average cost of the service it receives. Table 9 compares the total taxes and fees generated by LaGuardia flights with the cost of the airport and airways services at the airport. These estimates assume that each of the five representative flights operates with the same frequency as the flights in its representative size class. For example, there are 18,912 operations of flights with between 50 and 120 seats, and these calculations assume there are an identical number of B-717 operations. Table 9 Comparision of Revenues and Costs of Serving LaGuardia Domestic Passenger Flights, 2004 Aircraft

A-320 B-717 ERJ-145 ERJ-135 Twin Otter TOTAL

Current Revenues ($)

Average Cost ($)

Flights

Revenues from Taxes and Fees ($)

Cost of Services ($)

2,178 1,647 594 432 170

929 937 796 766 721

174�312 18�912 63�816 97�104 8�736

379�678 31�156 37�914 41�918 1�485 492�150

161�912 17�727 50�800 74�344 6�299 311�082

Note: The number of flights is annualized from operations in May. Source: T-100 and Table 8.

54

Assuming aircraft at the other airport pay a lower airfield use fee does not have a substantial effect on the differential. If the Twin Otter operate at an airport with the same airfield use fee as the A-320 its taxes and fees would increase by $8. The taxes and fees of the EMB-145 would increase by $28.

DANIEL P. KAPLAN

84

Payments by Commercial passenger carriers at LaGuardia substantially exceed the cost of the airport and airways services they consume. The estimated discrepancy is entirely due to the aviation taxes, because the landing fees cover the airfield costs. The observed discrepancy may be partly the result of relatively high fares and correspond ingly high-ticket tax revenues at LaGuardia.55 The disparity, however, also reflects the disproportionate share of the ATC costs paid by passenger carriers and their passengers.

6.3 Imposing Cost-Based Fees Consider a case in which it is assumed LaGuardia is uniformly congested through its operating hours. As shown above, smaller aircraft pay well below the average cost of the services they receive, while the larger aircraft pay well above. Under the proposed system, each flight would pay the sum of a minimum airfield use fee consistent with some acceptable level of congestion and, if needed, a weight-based airfield fee assessed on all flights to cover any revenue shortfall. As Table 10 shows, while the Twin Otter would face a substantial increase in landing fees, the increase to other aircraft would be more moderate. Given the pent-up demand for service at LaGuardia, the imposition of a flat rate airport use fee may not be sufficient to solve the congestion problem. At other airports, however, shifting to a weight-based movement fee during congested periods would likely have a significant salutary effect. Table 11 shows the total taxes and fees paid by the LaGuardia flights if the fees for both airfield use and terminal operations were set at average costs. This analysis assumes the other airports are not congested, and they charge weight-based airfield use fees. It is also assumed the flights pay average variable cost both for terminal operations at the other airport as well as for en route control. The fixed costs of these two components

Table 10 Impact of Instituting Average Cost Airfield Use Fees LaGuardia Airport, 2004 Aircraft


Average Cost Fee ($)

249 249 249 249 249

Existing Fee ($)

Change in Fee ($)

Flight Revenues ($)

386 270 113 108 33

−137 −21 136 141 216

16�956 13�170 4�780 3�112 1�338

Change as Per cent of Flight Revenues (%) −0.8 −0.2 2.8 4.5 16.1

Note: Existing fees are one-half of existing landing fees. Source: Author’s calculations.

55

If the same relationship between distance and yields existed at LaGuardia as it does at other major cities, the LaGuardia flights would have generated 15.7 per cent less revenue. This analysis is based on markets with nonstop service, and like the LaGuardia fares does not reflect the lower yields of connecting passengers.


85

Table 11 Impact of New Fees on LaGuardia Flights, 2004 Aircraft


New Fees ($)

Existing Fees ($)

Difference ($)

929 937 796 766 721

2,178 1,647 594 432 170

−1,249 −710 202 334 551

Flight Revenues ($)

16�956 13�170 4�780 3�112 1�338

Change as Per cent of Flight Revenues (%) −7.4 −5.4 4.2 10.7 41.2

Source: Author’s calculations.

of ATC services, however, are value priced.56 Under this scenario, and assuming fares remained the same, the taxes and fees paid by the A-320 would decline by $1,249, while the taxes and fees paid by the 50-seat ERJ-145 would increase by $202. The increases would be substantially greater for the smaller aircraft.57 These cost estimates assume no congestion at the other airport. If there were congestion at those airports, however, the impact on the smaller aircraft would be somewhat greater. Aircraft with fewer than 40 seats account for 29 per cent of LaGuardia operations. The increase in taxes and fees for the 37-seat ERJ-135 accounts for more than 10 per cent of the revenues of those flights. The average increase for the ERJ-145 is 4 per cent, which of course means a greater increase for half of those flights. The impact on profitability would be substantially greater. If the operating margin on the average ERJ-145 flight were 15 per cent, then the profitability of the average flight would fall by more than a quarter, assuming fares remained constant. The effect of an increase in costs on flight profitability also depends on the impact on revenues. Fares increasing in line with the higher costs would reduce the impact of the new pricing system on a flight’s profitability. The price impact on revenue – and profitability – of the new set of prices depends on the forces of supply and demand, which are market specific. Compare, for example, two markets served with regional equipment. In a market served by a single carrier, the increase in the price of using the airport and airways system will be distributed between the carrier and its passengers based on the elasticities of supply and demand. If the elasticity of demand in the market were relatively low, the new price system would have a relatively small effect on flight profitability, because passengers would bear most of any cost increase. The effect would be greatly magnified, if the regional equipment service were provided in competition with another carrier’s mainline service. In contrast to flights provided in

56

Using value prices for the fixed component is part of a transition process. Because terminal and en route control operations are likely to exhibit constant returns to scale, value pricing would not be efficient in the long run. 57 In practice, the minimum fee might vary over time, and the impact of the new system may be greater on some flights during those periods. This would most likely be the case when the peak demand on a route fails to match the peak demand for the airport overall.

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DANIEL P. KAPLAN

regional equipment, the switch to cost-based prices would actually reduce the costs of operating mainline equipment on a route. The lower costs could put downward pressure on fares in the market, in which case the flight using regional equipment would be hard pressed to recover of any of the added cost from the new tax and fee system. If the carrier offering the regional service needed to reduce its fares to remain competitive, it would be effectively absorbing more than 100 per cent of the higher fee.

7 CONCLUSION The current system for pricing the airport and airways system certainly contributes to the strains associated with its operation. The system subsidizes low-valued operations when congestion is a problem and suppresses use of price to signal the value of capacity additions. Indeed, a cursory review of the existing set of prices reveals a complex web of subsidies and cross-subsidies, which impose substantial costs but have no clear public policy objective. The present system should be replaced. This chapter has advocated requiring all flights to pay at least the marginal cost of the service it receives, with that minimum price increasing as warranted by congestion. In no case, however, would the prices be permitted to generate revenues in excess of the cost of the service. On the other hand, any revenue shortfall would be recovered through a weight-based fee. The new fee system, therefore, encourages efficient operation while maintaining an element of value pricing, a cornerstone of the existing prices for use of the airport and airways system. While this proposal represents a significant improvement over the current system, a number of factors complicate its adoption. While this analysis has focused on the subsidies presently received by regional aircraft, the existing system provides even greater subsidies to general aviation jet operations. Moreover, a switch to the new system could both put upward pressure on small community airfares as well as discouraging some service. This would likely generate significant political opposition. Because the airport and airways system is both operated and regulated by government agencies decisions concerning pricing and output decisions are fundamentally political ones. A move to a more rational pricing system might therefore require compromise. Crafting a political solution would involve a continuation of at least some of the existing subsidies. Continuing those subsidies in their current form, however, would be counter productive. Most notably, there should be a concerted effort to limit subsidies during periods of congestion. Moreover, any subsidies that are provided should be carefully targeted, and they should be discounts off the normal prices.

BIBLIOGRAPHY Areeda, Phillip and Donald Turner. 1975. Predatory prices and related practices under section 2 of the Sherman Act. Harvard Law Review 86, pp. 697–733. Brueckner, Jan K, 2002, “Airport Congestion When Carriers Have Market Power,” The American Economic Review 92, 1357–1375.


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Federal Aviation Administration, Air Traffic Organization: Airports Data for Stakeholders, November 15, 2005a. Federal Aviation Administration, Air Traffic Organization: Data Package for Stakeholders, November 15, 2005b. General Accounting Office, Airport and Airway Trust Fund, GAO-03-979, September 2003. Kahn, Alfred E. 1970. The Economics of Regulation, Volume 1, Wiley, New York. Levine, Michael E. 1969 Landing fees and the airport congestion problem, Journal of Law and Economics XII, 79–108. May, James C. Smart – and Fair – Skies: A Blueprint for the Future, Speech to the International Aviation Club, Washington, DC, April 18, 2006. Mayer, Christopher and Todd Sinai. 2003 Network effects, congestion externalities, and air traffic delays: Or why all delays are not evil, The American Economic Review 93, 1194–1215. Poole, Jr. and Robert W. Outsourced Flight Service Stations Save FAA $2.2 Billion, Reason Foundation Commentary, September 1, 2005. Transportation Research Board, 1999. Entry and Competition in the U.S. Airline Industry: Issues and Opportunities, National Academy Press, Washington, DC. Viscusi, W. Kip, John M. Vernon, and John E. Harrington, Jr., 1995, Economics of Regulation and Antitrust, 2nd Edition, MIT Press, Cambridge, MA.



4 An Interpretative Survey of Analytical Models of Airport Pricing∗ Leonardo J. Basso† and Anming Zhang‡

ABSTRACT In this chapter, we review analytical models of airport pricing, from 1987 onward. We argue that articles in the literature can be grouped into two approaches, the traditional approach and the vertical structure approach. In the traditional approach, the demand for airports depends on airport charges and on congestion costs of both passengers and airlines; the airline market is not formally modeled under the assumption that airline competition is perfect. In the vertical structure approach, airports are recognized as providing an input for the airline market, which is modeled as an oligopoly where firms have market power. It is the equilibrium of this downstream market that determines the airports’ demand: the demand for airports is thus a derived demand. We present and discuss both approaches and the papers within each of them, highlighting how they have analyzed different aspects of airport pricing such as the efficiency of weight-based airport charges, the effects of concession revenues on pricing and capacity investments, or the effects of airlines’ market power on optimal runway congestion pricing. We study the connection between the approaches and the transferability of results, and also discuss a handful of articles that have looked at the pricing of airport networks, i.e., three or more connected airports, as opposed to airports in isolation. We conclude by providing what we think should be the lines of future research.

∗ Acknowledgement: We would like to thank Darin Lee and Monica Hartmann for helpful comments. Finan cial support from the Social Science and Humanities Research Council of Canada (SSHRC) is gratefully acknowledged. † Corresponding author. Sauder School of Business, The University of British Columbia. Department of Civil Engineering, Universidad de Chile. Contact information: 2053 Main Mall, Vancouver BC, Canada V6T 1Z2, Tel.: 1-604 822 0288, Fax: 1-604 822 9574, [email protected]/Casilla 228-3, Santiago, Chile, Tel.: 56-2 978 4380, Fax: 56-2 689 4206, [email protected]. ‡ Sauder School of Business, The University of British Columbia. Contact information: 2053 Main Mall, Vancouver BC, Canada V6T 1Z2, Tel.: 1-604 822 8420, Fax: 1-604 822 9574, [email protected].

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LEONARDO J. BASSO AND ANMING ZHANG

1 INTRODUCTION Airport pricing has attracted the attention of economists for some time now, starting with Levine (1969) and Carlin and Park (1970). Most of the attention has been devoted to the efficiency of pricing practices by airport authorities and the need to take into account congestion which, even in the early 1970s, was afflicting passengers and airlines. The alleged inefficiencies of actual pricing practices plus the increase in delays at airports around the world have made understanding the models of airport pricing very germane in today’s world. Airport delays in the United States have grown dramatically in recent years. In 2004, 20 per cent of flights arrived more than 15 min late, with Chicago’s O’Hare airport being last with 30 per cent. The US Department of Transportation in its “National Strategy to Reduce Congestion on America’s Transportation Network” (2006) has estimated that aircraft delays cost passengers $9.4 billion. Congestion is perhaps even more acute at some of the major European, Japanese, and Chinese airports. Furthermore, the recent trend of airport privatization and/or commercialization induced, in addition, a focus on the effects of privatization and the efficiency of different regulatory schemes (this trend started in the late 1980s throughout the world following the examples in the United Kingdom). More specifically, privatized airports would pur sue maximization of profits. On the other hand, it has usually been accepted that airports enjoy a local monopoly position because they have a captive market. Besides, sizeable economies of scale on airport infrastructure provision and airport operations may exist (Doganis, 1992). Out of the concern that private airports would exert market power in user charges, many private (and public) airports are under some type of economic regulation such as rate-of-return or price caps. The work on airport pricing has been considerable. Some old questions, such as how we should use the price mechanism to signal congestion problems, have persisted in the literature. New questions, such as whether privatization would induce better capacity investment, have appeared. As far as we know, there has been no paper that is devoted to putting together all the questions and answers that have been obtained in the literature since the late 1980s. We attempt to do that in this chapter. Specifically, we review the airport pricing literature, with a focus on analytical papers. Indeed, we are narrowing the scope of our work, by leaving aside a number of important empirical papers. By this we do not mean that the empirical work is irrelevant, but as it will be seen, a comprehensive survey of the analytics of airport pricing easily use up the space in a paper, and we believe that a good command of theoretical and analytic results helps to better grasp empirical findings. Also, we will focus on papers in the last 20 years. We believe that this is enough to understand what is known today about the theory of airport pricing, since earlier contributions such as Levine (1969), Carlin and Park (1970), and Morrison (1983) have been incorporated into the papers we will review. While there are many survey papers on airlines, the survey work on airports is relatively rare. One exception is a recent survey paper by Forsyth (2000), in which he focused mainly on the pre-1990 airport-pricing papers and on models of airport costs and production efficiency. We shall summarize the findings and provide directions of what we think should be future research. In order to do this in an orderly manner, we group the papers into two broad “approaches”. Papers within one approach share many features regarding the analytical modeling, which makes it easier to explain what characterize them, while

INTERPRETATIVE SURVEY OF ANALYTICAL MODELS

91

also enabling a better description of the contributions of each of the individual articles. Therefore, Sections 2 and 3 will be devoted to explain what we have called “the tra ditional approach” and “the vertical structure approach” to airport pricing respectively and, within each approach, what we have learned from individual articles. Because an obvious question is whether results from one approach can be transferred to the other, in Section 4 we discuss connections between the approaches as a means to better understand how the results stemming from the two approaches relate to each other. In what follows, Sections 2 and 3 deal with a single airport’s decision or, at most, two (complementary) airports, given the complexity of the economics of airport pricing. However, there is a handful of articles that have looked at the pricing of airport networks, i.e., three or more connected airports. We discuss these papers in Section 5, noting that the previous classification may still be applied. We conclude in Section 6 by providing what we think should be the lines of future research.

2 THE TRADITIONAL APPROACH TO AIRPORT PRICING The main characteristic of the traditional approach is that it typically follows a “partial equilibrium” analysis in which an airport’s demand is directly a function of the airport’s own decisions. As will be explained below, since airlines’ decisions (and airline com petition) are not directly considered, the derived characteristic of the airport’s demand is not formally recognized. In this section, we consider papers by Morrison (1987), Morrison and Winston (1989), Oum and Zhang (1990), Zhang and Zhang (1997, 2001, 2003), Carlsson (2003), Oum et al. (2004), Lu and Pagliari (2004), and Czerny (2006). Most of these papers follow essentially the same model: the demand for an airport is assumed to be a function of a “full price”. This full price includes the airport charge and, in an additive fashion, some cost measure of the delays caused by congestion. Delay functions have always been measured through some non-linear function of traffic and capacity, although the modeling has not been unique: the main discrepancy has been whether the function should (or not) be homogenous of degree one in the traffic to capacity ratio. Delay is assumed to affect both airlines and passengers, and consumers’ surplus is measured by integration of the airport’s demand. When the airport capacity is variable, the cost function has been usually assumed to be separable in operating and capacity costs. This approach has been used to analyze a variety of issues regarding airport pricing and capacity decisions and under many different sets of assumption, as can be seen in Table 1. Initially, the focus was on deriving optimal prices and capacities in the presence of congestion but, lately, it has been used to assess the effects of privatization and regulation as well. The basics of the traditional approach may be synthesized in a fairly concise analytical manner, which we present below.1 In order to provide aviation services, an airport

1 Certainly, not all the papers can directly be assimilated to this presentation – particularly Lu and Pagliari (2004) and Czerny (2006) may seem more distant – but most of them fit through some adjustments, which will be indicated where relevant.

Table 1 Summary of Papers Using the Traditional Approach (from 1987 on) Author

Goal of the Paper

Objective Functions

Capacity

Delay

Observations

Morrison (1987)

Uncover the importance regulators give to each type of aircraft when they max SW

Max SW st BC

Fixed

NHDO

Many periods with independent demands

Morrison and Winston (1989)

Efficient pricing and capacity with congestion

Max SW

Variable and continuous

HDO

Many periods with independent demands

Oum and Zhang (1990)

Analyze budget adequacy under congestion pricing when capacity investments are lumpy

Max SW

Variable and lumpy

NHDO

Many periods with dependent demands

Zhang and Zhang (1997)

Effects of concessions. Should the BC be common to both concessions and airside activities or separate?

Max SW st BC


NHDO

Many periods, independent demands. First model to formally incorporating concessions


Analyze whether public airport should have a strict (short run) brake-even constraint or a longer run constraint

Max SW st BC

Lumpy

NHDO

Many periods, independent demands

Carlsson (2003)

Efficient pricing and capacity with congestion and emissions

Max SW


NHDO

One period. Social cost of emissions added to SW


Analyze privatization and the effects of concessions on pricing and capacities

Max SW Max profits (private case) Max SW st BC

Variable and lumpy

NHDO

One period. They include concession operations. BC is in the long run

Lu and Pagliari (2004)

Regulation and concessions: single-till versus dual-till cap

Max profits st two different forms of regulation

Fixed

No delays

Rather than having delays, they assumed that capacity is a restriction on feasible output: potential for excess demand

Oum, et al. (2004)

Efficiency implications of alternative forms of regulation

Max SW st BC Max profits (private case) Max profits st four different forms of regulation


NHDO

One period. They include concession operations. BC is in the long run

Czerny (2006)

Effects of concessions on aeronautical charges. Regulation: single-till versus dual-till cap

Max SW Max Profits st two different forms of regulation

Fixed but large: no excess demand

No delays

Both airside and concession charges determine the number of consumers.

SW: social welfare; BC: budget constraint; NHDO: the delay function is non-homogenous of degree one in the traffic to capacity ratio; HDO: the delay function is homogenous of degree one in the traffic to capacity ratio.


94

incurs both operating and capital expenses. It collects user charges to cover these costs and, in the private-airport case, to make a return on capital investments. For a given capacity, congestion will start to build up at the airport as demand grows, inducing delays and therefore extra costs on passengers and airlines. It is usually assumed that airlines fully pass airport charges to passengers; the same is assumed for airlines delay costs.2 Therefore, passengers will perceive a full price consisting of the airport charge, the flight delay cost, travel-time costs plus other airline charges (e.g., air ticket). It has been argued that since other airline charges are exogenous as far as the airport is concerned, the demand an airport faces may be considered to be a function only of the airport charge P and the flight delay cost D, which includes the delay costs to both airlines and passengers. The variables in the model would be3 Q�� Demand for airport facilities measured by the number of flights, which is a function of the full price � perceived by passengers � = P + D the full price that determines the airport’s demand P airport charge per flight D = D�Q� K� flight delay cost experienced by each flight, which depends on traffic Q and airport capacity K K capacity of the airport C�Q� operating costs of the airport r cost of capital. The capacity may be lumpy or continuously adjustable. The assumption of adjustable capacity has been justified based on the observation that capacity would be defined not only by the number of runways – which can only be increased discretely – but also by air traffic control technology, air navigation systems and other infrastructures, which can be increased or enhanced continuously. One of the first issues that was analyzed using the traditional approach is the nature of the airport’s choices of user charge P and capacity K, for the benchmark case in which social welfare is maximized subject to a budget constraint – the public airport case. The problem the public airport faces is given by �� max P�K

Q��d� + PQ − C�Q� − rK

(1)

�

s�t�PQ − C�Q� − rK = 0

2

(2)

Morrison (1987, p. 48) makes this assumption by equating the airlines’ elasticity of demand for airport services to the elasticity of passengers’ demand with respect to full price times the fraction that airport charges and congestion costs represent in total flight costs (see also Raffarin, 2004, p. 115). Oum et al. (2004) make this assumption explicitly, arguing that this will be the case under perfect competition. 3 Here, for notational simplicity, we present a model with no intraday variations in demand, i.e., a “single period” model. The model can be extended in a straightforward fashion to the case of many periods so long as the demands in these periods are independent. The independence assumption has been made in most papers that deal with multiple periods; the only exception is Oum and Zhang (1990).


95

The first term in the objective function would correspond to consumer surplus, the remaining terms are the airport’s profit. Forming the Lagrangean and taking derivatives with respect to P and K, first-order conditions are obtained. From them, the following pricing and capacity investment rules follow: �D � �� P = C� + Q + (3) �Q 1 + � � −Q

�D =r �K

(4)

where � denotes the Lagrange multiplier of the budget constraint, and � is the (positive) elasticity of demand with respect to the full price. According to Morrison (1987) and Zhang and Zhang (1997, 2001), the interpretation of the pricing rule is as follows: The first two terms on the right-hand side (RHS) of Equation (3) represent the social marginal cost (SMC) of one flight (operational marginal cost plus the marginal cost of congestion), whereas the third term represents a markup that is inversely related to � and depends on the severity of the budget constraint. Hence, the difference with the usual Ramsey-Boiteux pricing is that the pricing rule needs to take into account the congestion that a new flight imposes on others. Regarding the optimal capacity rule – Equation (4) – Zhang and Zhang (1997) note that it does not depend on � and hence it is identical to the one obtained when a budget constraint is not imposed, as in Morrison and Winston (1989). Therefore, airport authorities that adopt Ramsey pricing should still pursue the same optimal policy of capacity investment. In this policy, the socially optimal level of capacity is set such that the marginal benefit of capacity in terms of reduction in delays, equates the marginal cost of capacity (Morrison and Winston, 1989; Zhang and Zhang, 1997). This concludes the explanation of the basic setup of the approach. In what follows then, we will look at how this approach has been used – and modified when needed – to analyze issues other than second best pricing and capacity investment. Authors have used the traditional approach to (i) study the efficiency of weight-based airport charges, (ii) analyze the effects that lumpy investments in capacity may have on bud get adequacy, (iii) examine the effects of concession revenues on pricing and capacity investments, (iv) derive efficiency implications of alternative forms of regulation, and (v) study how environmental costs could be incorporated into airports’ charges.

2.1 On Weight-Based Airport Charges Because in general, aircraft are not charged by the contribution they make to congestion but by their weight, Morrison (1987) wanted to uncover the importance regulators give to each type of aircraft when choosing the runway landing fees. For this, he assumed that the demand is Qi , where i denotes a class of airport users, that is, different types of aircraft. Then, assuming that capacity is fixed, he put weights on the contribution of each class of users to the social-welfare function. Hence, the objective function (1) becomes � i

�� i �

Qi ��i �d�i + Pi Qi − C�Qi �

(5)

96


where �i is the weight of user i. With this social-welfare function, and still considering the budget constraint in Equation (2), the optimal pricing rule Equation (3) changes to � � �D � + 1 − �i �i � P i = C + Qi (6) + �Qi 1+� �i Morrison then asked the following question: what set of weights is implied by actual airport charges? To uncover the weights, he followed Ross (1984) and solved for the weights �i in Equation (6). Using actual data, those weights can be obtained up to a multiplicative constant. Morrison’s main result was that when the airport is uncongested, weight-based landing fees imply welfare weights (the �i ) that are very similar. But when congestion increases, the dispersion in the weights also increases, implying that the weight-based landing fees would be less appropriate when there is congestion. He argued that this happens because, though weight is a reasonable proxy for elasticity of demand, it is a poor proxy for congestion costs.

2.2 Lumpy Capacity and Cost Recovery Oum and Zhang (1990) and Zhang and Zhang (2001) were interested in how budget adequacy would be affected if capacity can be increased only in discrete lumps. The conjecture was that the lumpy nature of capacity expansions would make social marginal congestion pricing lead to alternating periods of airport surplus and deficits. Oum and Zhang (1990) incorporated a positive time trend to the airport’s demand to capture the fact that the aviation demand would increase with the overall economy. By considering lumpy capacity expansions – that is, K can be increased only by a minimum amount �K – they focused on the timing of capacity expansions rather than the capacity investment in a steady state as discussed above (budget constraint was not considered, however). They concluded that, when capacity is indivisible, the optimal congestion pricing – given by Equation (3) with � = 0 – and optimal capacity expansion would lead to alternating periods of excess capacity and capacity shortage. During capacity shortage, the congestion toll would exceed annualized capacity costs but during excess capacity, the congestion toll would fall short of annualized capacity costs. This implies that budget adequacy would depend entirely on the number of shortage/excess capacity periods between capacity expansions. And the number of periods in each case depends on the pattern of traffic growth. Oum and Zhang (1990) concluded that when capacity is indivisible, the cost recovery status of an airport cannot be predicted without reference to the time path of the traffic growth and, therefore, the cost recovery theorem for investment in transportation infrastructure would not hold. This important theorem states that (see, e.g., Mohring, 1976) when operational costs are separable from capacity costs, the latter exhibit constant returns to scale, and the delay function is homogenous of degree one in the traffic to capacity ratio, optimal congestion pricing and capacity provision leads to exact cost recovery of capacity investments and operational costs. This is not the only way in which the cost recovery theorem would fail for airports though. Even if capacity is divisible, as in the basic model shown in Equations (1) and (2), Zhang and Zhang (1997) showed that, without a budget constraint, social-marginal-cost pricing would always give rise to


97

a financial deficit to the airport because the delay function D would not be homogenous of degree one in the traffic to capacity ratio (Lave and De Salvo, 1968; US Federal Aviation Administration, 1969; see Horonjeff and McKelvey, 1983). Furthermore, the deficit would increase with congested at the airport. Given all this, Zhang and Zhang (2001) were interested in the case where delays are non-homogenous of degree one, capacity is indivisible, traffic grows over time, but airports are required to recover their costs from both operations and capacity investments. The question they asked was – Should public airports be asked to break even in the short run, or in the long run, which may involve taking losses in early years of a capacity investment but surplus in later years? For this, they modified the airport’s problem (1)–(2), so as to consider that the airport would now maximize social welfare over a period of time S, while achieving cost recovery over the entire period. Capacity was assumed to be fixed during the period, owing to its indivisibility. The new long-run problem faced by the public airport is � � �S �� Q�� s�d� + PQ − C�Q� − rK e−rs ds max P�K 0

s�t�

�

�S

(7) �PQ�� s� − C�Q� − rK�e−rs ds = 0

0

Now, the airport’s demand increases with time, that is, �Q/�s > 0, and future revenues are discounted using the cost of capital, r. The short-run problem is as in Equations (1)–(2). Not surprisingly, Zhang and Zhang found that the short-run financial break-even constraint leads to a lower level of social welfare than a long-run break-even constraint. This increase in welfare is expected, since short-run budget adequacy implies long-run budget adequacy but not vice versa. In fact, Zhang and Zhang showed that the two will be equal only when the airport’s demand remains constant over time, that is, �Q/�s = 0. This directly speaks of the importance of the time path of the traffic growth, as pointed out by Oum and Zhang (1990): To maximize social welfare, airports should be allowed to take losses or make profits at different times, seeking cost recovery only in the long run. What is perhaps more interesting in Zhang and Zhang (2001)’s finding is that under the short-term cost recovery, airport charges are high when the demand is low and there is excess capacity. However, when the demand is high, and there is congestion, airport charges would be low. This seems to be undesirable. On the other hand, under the long-term cost recovery, airport charges grow together with the demand.

2.3 Airport Concessions and Pricing Effects: Public and Private Airports Given the increasing pressure on public airports to self-finance their operations, airports have been increasingly depending on revenues generated by non-aeronautical businesses,


98

such as airport parking, in-airport stores and so on.4 The demand for these concession services is complementary to the demand for aeronautical services, in that the more people there are using the airport, the higher the concession revenues. Zhang and Zhang (1997) wanted to analyze what would be the socially optimal balance between aeronautical revenues and concession revenues given the cost recovery constraint, and how the associated pricing practices would look like. For this, they modified the public airport’s problem Equations (1)–(2) by incorporating the fact that concession demand is complementary to aeronautical demand: � � �� max Q��d� + PQ − C�Q� − rK + Q X�p�dp + pX − c�X� P�K�p � p (8) s�t�

PQ − C�Q� − rK + Q �pX − c�X�� = 0

In Equation (8), p represents the price for concession goods or non-aeronautical services provided in the airport, X�p� is the demand for concession services per flight, and c�X� are the costs of providing the concession services, which are assumed to feature constant returns to scale. There are two important things to note in the above setup. First, the complementarity between the demands is unidirectional, that is, consumers’ decision to fly or not is based on the full price of the aeronautical service; they do not take into account the price of the concessions in their travel decisions. Only after arrival at the airport, passengers observe concession prices and make purchasing decisions. Second, note that the budget constraint in Equation (8) includes the revenues from both aeronautical and concession services, which effectively enables cross-subsidies between the two services. Without the budget constraint, the (first best) optimal solution obviously involves marginal cost pricing on the concessions side, i.e., p = c� �X�. On the aeronautical side, the social-marginal-cost pricing of Equation (3) would have an additional markdown; this happens because, now, a smaller aeronautical charge increases the demand for both aeronautical services and concessions services. Hence, the optimal aeronautical charge is smaller. This would, however, lead to deficits if the delay function is non-homogenous of degree one in the traffic to capacity ratio, as discussed above. With the budget constraint, and assuming that the delay function is non-homogenous of degree one, Zhang and Zhang showed that at the (second best) optimal solution of problem (8), the price of concession services would be such that p > c� �X�, showing that profits would be made in concession services. Therefore, concession operations would subsidize aeronautical operations. If the airport were not allowed to make profits from its concessions, but was

4

For the last two decades, concession revenues have grown faster than aeronautical revenues; as a result, they have become the main income source for many airports. At medium to large US airports, for instance, commercial business represents 75–80% of the total airport revenue (Doganis 1992). Furthermore, concession revenues have grown faster than aeronautical revenues. For example, in 1979, Hong Kong International Airport generated similar amounts of revenue from its aeronautical and non-aeronautical (mostly concession) operations. In the late 1980s and 1990s, however, its concession revenue accounted for 66–70% of total revenue (Zhang and Zhang, 1997). More importantly, concession operations tend to be more profitable than aeronautical operations (see e.g., Jones et al., 1993; Starkie, 2001).


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still asked to self-finance its operations, then this would obviously lead to a smaller level of social welfare. Furthermore, Zhang and Zhang showed that the cross subsidy from concessions does not in general restore social-marginal-cost pricing on the aeronautical side – Equation (2) – unless the demands and costs fulfill a very particular condition. The attention to concession revenues, however, does not stop at the pricing and costrecovery issues of public airports. It has also been suggested that the complementary nature of the concessions demand would give incentives for private airports to reduce the price they charge for aeronautical services in order to maximize the number of travelers in the airport using the concessions. This may imply that ex ante price regulations may be unnecessary (see, e.g., Condie, 2000; Starkie, 2001). In order to assess whether the argument holds, Zhang and Zhang (2003) and Oum et al. (2004) used Zhang and Zhang (1997)’s model to look at the decisions a private unregulated airport would make. The profit-maximization problem faced by a private unregulated airport is max PQ − C�Q� − rK + Q �pX − c�X�� P�K�p

(9)

Zhang and Zhang (2003) and Oum et al. (2004) found that, while airside private prices diminish as it was conjectured by Condie (2000) and Starkie (2001), they decrease less than the prices in a public airport that also has concessions, and that this is the case for both the first-best pricing (unconstrained public airport) and second best-pricing (budget-constrained public airport). Therefore, concession revenues would not be a valid argument for de-regulation once an airport is privatized. The intuition of the result is simple: a private airport would care about the extra profits it can make from concession activities; a public airport maximizing social welfare, however, would care about concession profits but also about the consumer surplus induced. Consequently, the decrease in the aeronautical charge would be larger in the public case: concession revenues would actually increase the gap between private and public airside charges. As for the effects of privatization on capacity decisions, Oum et al. (2004) obtained that the capacity investment rule of the private airport would be the same as the one a public airport follows, as in Equation (4). Hence, they argued that, if the capacity can be adjusted continuously, the capacity investment decision of the private unregulated airport would be efficient from a social viewpoint. However, since the price and capacity decisions are jointly determined, and the pricing rules of the two airport types are different, so will be the actual levels of traffic and capacity. In fact, since a private airport charges more, its actual capacity would be smaller. But, their main point is that, conditional on traffic level Q, the capacity K determined by Equation (4) would be efficient because marginal benefit equals marginal cost. In line with the actual capacity of private airports being smaller when capacity can be adjusted continuously, Zhang and Zhang (2003) found that, when capacity is indivisible, a private airport would make the (lumpy) addition of capacity later than a public airport. Note that none of these two results imply anything about the level of actual delays, because traffic levels will be different as well. Czerny (2006) also looked at the effects of concession revenues on airside charges. There are two important differences between his and Oum et al.’s model (2004): First, he considers an airport that is non-congestible and has spare capacity, making the reasons for cross-subsidization discussed above vanish. Second, in Oum et al. (2004) the number of actual flyers would depend only on the full price � and not on the price for concession


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services. The price of concession services would only determine how many of those who are already flying buy concession services. Czerny (2006), however, considered that both airport and concession charges affect the number of flyers, and that the complementarity arises because only people who are actually flying will be able to purchase concession goods. Hence, in Czerny’s setting it may happen that the airport charge is higher than a consumer’s willingness to pay for flying, but that negative payoff is compensated by positive benefits arising from consumption of commercial services. These differences are material. Czerny showed that in this setting, the monopoly charge for aeronautical activities is actually higher with concession revenues than without concession revenues, thus rejecting the conjecture of Condie (2000) and Starkie (2001). The intuition is as follows: when the airport has concession services, and since these influence the number of flyers, the airport may increase its revenues in two ways. It may increase the price for aeronautical services, using a low concessions charge to mitigate the decrease in demand, or it may decrease its aeronautical charge, hoping to make revenues on the concessions side. But since only passengers can buy commercial services, the demand for the latter is a subset of the demand for flights. Therefore, an increase in aeronautical charges increases revenue more than an increase in the concession services charge.

2.4 Efficiency Implications of Alternative Forms of Regulation Traditionally airports have been owned by governments (national or local). Privatization of major airports started in the late 1980s, and airport privatization has now become an important phenomenon around the world.5 Most of the privatized airports have been regulated out of the market-power concern given the monopoly nature of airports. Oum et al. (2004), Lu and Pagliari (2004) and Czerny (2006) analyze the effects of alternative mechanisms of regulation on the performance of private airports, with a particular focus on how revenues from concession services should be dealt with. Oum et al. (2004) have considered four different regulation mechanisms: single-till rate of return (ROR), dual-till ROR, single-till price cap and dual-till price cap. Under the single-till ROR, airport charges (for both airside and concession operations) are set for cost recovery plus a fair return on the invested capital. If u is the allowed ROR, then the new problem the private airport solves is max PQ − C�Q� − rK + Q �pX − c�X�� P�K�p

s�t� PQ − C�Q� + Q �pX − c�X�� = uK

(10)

The well-known problem with ROR is that, if the allowed return is greater than the cost of capital, i.e., u > r, the airport has an incentive to over-invest in capital, a problem known as the Averch–Johnson effect. However, if the regulators get the allowed return 5 In 1987, the British government privatized the BAA, which owned and operated the three London airports (Heathrow, Gatwick, and Stansted), among other airports in the UK. Since then, many airports around the world have been or are in the process of being privatized. The majority stakes of Copenhagen airport, Vienna airport, Rome’s Leonardo Da Vinci Airport and 49% of Schiphol airport have been sold to private sector owners. Many other European airports are in the process of being privatized. Major airports in Australia and New Zealand have been privatized as well. As a way to partially privatize airports, six Chinese airport companies including seven airports have been listed on stock exchanges.


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right, the problem vanishes. It has been argued though that, even if the allowed return is chosen correctly, the single-till ROR would still misplace the incentives on terms of the productive efficiency, because it is essentially a cost-based mechanism. While the argument is sensible and has been detected empirically in several industries, it does not flow analytically from model (10). Under the dual-till ROR, the allowed return applies only to aeronautical operations. If the regulators get the allowed rate right, the new restriction is PQ − C�Q� = rK. In this case, the airport would make no profits in airside operations and, therefore, would try to maximize Q�pX − c�X��, the profits coming from concession operations. Given the complementary nature of the concessions demand, the airport will, in fact, try to maximize traffic, which is equivalent to minimize the full price �. Hence, this regulation mechanism would lead to a capacity rule as in the public case, that is Equation (4), and to average cost pricing, that is P = �C�Q� + rK�/Q. Note, however, that if u > r, the Averch–Johnson effect re-appears. We now turn to the price-cap regulation, a mechanism in which the regulator sets a ceiling for the aeronautical charge, that is P ≤ P ∗ . Theoretically, the cap is set to limit the airport’s market power, while ensuring its financial viability (this may include a fair rate of return on capital investment). The difference between the single-till and dual-till price-cap regulations is, again, related to whether concession revenues will be lumped together with airside revenues or not; to be perfectly clear, the debate is not about regulating concession activities. Under the single-till price-cap regulation, the cap P ∗ will be set considering that the airport will likely make profits from concession activities. This would imply, according to Oum et al. (2004), a cross-subsidy, just as in the case of a public airport subject to budget constraint (Zhang and Zhang, 1997). However, a problem is that the more profit the airport makes from concessions, the smaller the allowed aeronautical charge would be in future revisions of the cap, even if traffic grows and congestion builds. Because of this, the single-till cap regulation for the case of congested airports has been criticized (e.g., Starkie, 2001): the airport charge would not be a useful signal to users regarding congestion. Moreover, Oum et al. (2004) also showed that a price cap (either single-till or dual-till) induces underinvestment in capacity, worsening the problem. Here, the airport is unable to recoup fully from its investment in capacity – which reduces congestion and hence increases the users’ willingness to pay – because the price is capped. Under the price-cap regulation, therefore, while the market-power distortion is alleviated, the service-quality provision is sub-optimal, suggesting an interesting trade-off between with and without the regulation. This result is in fact very robust. Spence (1975) showed that if a monopolist who initially can choose both price and quality of its product is constrained to charge below some price ceiling, the quality it chooses will be always below what is socially optimal for that price. It is noted that under the dual-till price cap, that is, when concessions revenues are not considered in establishing the cap, Oum et al. (2004) showed that the cap would not be set as low as in the single-till, something that seems desirable. Hence, overall, Oum et al. (2004) concluded that the presence of the concession rev enues make the dual-till ROR approach a quite interesting mechanism as it would induce the airport to invest optimally in capacity, while minimizing its costs and congestions delays, since it would try to minimize the full-price. Indeed, Spence (1975) suggested that ROR has nice properties when regulating both quantity and quality.

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Like Oum et al. (2004) and Lu and Pagliari (2004) have looked at the effects of singletill and dual-till price cap regulations. They used a social-welfare function as the one maximized in Equation (1), but considered that more traffic caused no congestion, that is D = 0. The difference is that in a model with a delay function being non-homogenous of degree one, congestion is essentially a cost. And given that the cost increases more pronouncedly as the traffic gets closer to capacity, equilibrium levels of traffic would never surpass capacity (e.g., when D�Q� K� = Q�K�K − Q��−1 , delays approach infinity when output approaches capacity). In Lu and Pagliari’s case, however, if the aeronautical charge is too low, demand may well exceed capacity, particularly because in their model, capacity is assumed to be fixed. Lu and Pagliari found that a single-till price cap would be appropriate when the average cost of the airport is greater than the market clearing price (for the given capacity), because cross-subsidies from concession revenues would be needed to reduce the airside charge and restore full capacity use. In other cases, however, they found that a dual-till price cap would be better: under the single-till the price cap may be set “too low,” owing to the cross subsidy from concessions, and hence dead-weight losses would occur because of excess demand. Czerny (2006) also compared the single-till and dual-till price-cap regulations. As discussed previously, he examined an airport that is non-congestible and has spare capacity, and considered that both airport and concession charges affect the number of flyers. Under these conditions, he found that the single-till dominates the dual-till in terms of social welfare, a result similar to what Lu and Pagliari found when the airport does not suffer from excess demand. The intuition is that with the single-till price cap, the regulator has better control of the overall profits of the airport, which is not the case with the dual-till regulation. Thus, the single-till helps to limit market power. Hence, overall, when the airports are not congested, a single-till price cap seems like a reasonable approach to control market power. However if congestion actually occurs, the single-till would induce incorrect signals regarding congestion, while the dual-till would distort capacity investments. Furthermore, if there are delays as traffic levels approach capacity (as in the original setup), the socially optimal pricing structure would require cross-subsidization (Zhang and Zhang, 1997), but this is precluded in the dualtill. Hence, in congested airports, the dual-till ROR regulation may be a better option: the incentives for capacity investments would be well placed, while the regulated airport would pursue average cost pricing.

2.5 Airport Pricing Considering Environmental Costs Carlsson (2003) developed a model of airport pricing that, in addition to congestion, also includes environmental damages (noise, emissions).6 For this, he modified the social-welfare function in Equation (1) to include environmental costs, as follows:

6 Air travel is considered a rapidly growing source of greenhouse gases (GHGs), something that has sparked concern. The problem is that, while airport delays result in aircraft’s holding/circling in the air waiting for landing and hence cost to airlines, the circling also burns extra fuel increasing GHG emissions. Furthermore, the possibility of being held up induce airlines to carry extra fuel in their aircrafts, which increases the aircraft’s weight and, consequently, its consumption of fuel and GHG emissions (see Economist, 2006).


�� max P

Q��d� + PQ − C�Q� − rK − QE �D�Q� K��

103

(11)

�

where E is the average environmental cost per flight. It depends on the level of conges tion because, for example, the delay increases fuel consumption and hence emissions. Carlsson considered many periods throughout the day and allowed the environmental costs to vary according to the type of aircraft. For simplicity we do not do so here; the intuition of the results remains unchanged. The optimal pricing obtained has two more terms than the congestion-only social-marginal-cost pricing in Equation (3) when � = 0. He gets P = C� + Q

�D �E �D +E+Q �Q �D �Q

(12)

The last two terms in the RHS of (12) represent the marginal environmental cost: In addition to the airport’s marginal cost and the marginal cost of congestion, each aircraft would have to pay the environmental cost it produces, plus another sum owing to the fact that the extra delay a new flight imposes on existing flights, increases the average environmental cost of all flights.7 These last two terms are obviously positive, which shows that, when environmental costs are considered, the airside charge is higher. Carlsson then pointed out that, if the proceeds from the environmental charge accrue to the airport, then cost recovery may be feasible. Whether this is the case or not, however is an empirical matter, as it depends heavily on the shapes of the delay function and the average environmental cost. As for the capacity decision, although Carlsson did not look into it, it is fairly evident the direction in which it would change with the added environmental costs. Since now more capacity is beneficial not only because smaller delays decrease the full price, but also because smaller delays reduce average environmental costs, the socially efficient capacity investment rule would induce a larger investment in capacity.

3 THE VERTICAL STRUCTURE APPROACH TO AIRPORT PRICING The vertical structure approach is newer and, hence, there are fewer papers. Here we review Brueckner (2002), Pels and Verhoef (2004), Raffarin (2004), Basso (2005) and Zhang and Zhang (2006). In this approach, the airline market is formally modeled as an oligopoly, which takes airport charges and congestion taxes as given. Airports, however, are not always considered integrally; in some cases, only airport authorities, who need to

7

The optimal charge is differentiated between types of aircraft and times of the day when these are differentiated.

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set a tax to be paid in addition to the airport charge – implicitly assumed to be marginal cost – are considered. In these cases, airport profits do not enter the social-welfare function. This airport–airlines approach to airport pricing was driven by the policy need to respond to an increasing level of delays at hubs throughout the world. An important characteristic of hub airports is that usually a few major airlines dominate the airports: these are not atomistic carriers and hence they are not price takers. The focus of the approach has mainly been on the characterization of optimal (public) runway pricing under congestion and airline market power, as can be see from Table 2. Thus, the idea has been to highlight the differences between the airport congestion pricing and the road congestion pricing, where decision makers (individual drivers) are atomistic. Until most recently, capacity was assumed to be fixed, and hence was not a decision variable of the airport or the airport authority, in the vertical structure approach. Brueckner (2002) should undoubtedly be credited for starting this stream of literature. In this very influential paper, he considers N airlines that are seen as homogenous by consumers and that compete in a Cournot fashion. He allows for peak and off-peak demands, which are interrelated, and where the peak period consists of a set of relatively short time intervals containing the daily most desirable travel times. Only the peak is congested. From this setup, it would seem that the peak and off-peak travel are vertically differentiated in that, other considerations such as income and congestion levels being absent, consumers would prefer traveling in the peak period to traveling in the off-peak period. In fact, Brueckner does not directly assume downward sloping demands, but starts with a continuum of consumers who would decide to use the peak or the off-peak periods (or not traveling by air at all) depending on the full prices they face: airfare, plus congestion costs caused by delays at the airports. However, Brueckner also adds a “tendency to fly in business,” which correlates to travel in the peak, as a device that would enable simpler (non-corner) solutions. The problem with this is that it actually imposes that in terms of pure utility, with no income or congestion effect whatsoever, some consumers would prefer traveling in the off-peak period. This seems to contradict the idea of the peak period being “the most desirable travel times.” The airlines, observing the demands and understanding how consumers’ decisions are made, choose their quantities in the output market. An important aspect here is that congestion also affects airlines: There are externalities in production in that, the more a rival produces, the higher a firm’s marginal and average costs will be. The delay function is not necessarily linear in traffic. In equilibrium then, the sorting of consumers towards peak and off-peak occurs through the airlines’ quantity decisions (for given airport charge and capacity). Brueckner then looks at what should be the optimal additional tax that should be charged to airlines in the peak period, in order to adequately account for the congestion externality. Since the off-peak period is assumed to be non-congested, no congestion toll would be needed. Thus, he looks at the regulator case in the sense that the airport is not formally incorporated into the analysis: its profits do not enter the social-welfare function, which is composed of only consumer surplus and airlines’ profits, and there is no consideration of cost recovery, something that has drawn important attention within the traditional approach (see Section 2). Brueckner’s main conclusion – the one that has since driven research in the area – is that with Cournot oligopoly, each airline will internalize the congestion imposed on its flights

Table 2 Summary of Papers Using the Vertical Structure Approach Author

Goal of the Paper

Oligopoly model

Objective Function and airport modeling

Observations

Brueckner (2002)

Optimal tax (additional to airport charges) to account for congestion

N airlines in homogenous Cournot

Max SW = CS + � No formal modeling of the airport, only a regulator

There are peak and off-peak periods (peak-load pricing). Sorting to periods is endogenous through airlines decisions. Only the peak is congested Congestion is a non-linear function of traffic and affects both airlines and passengers

Pels and Verhoef (2004)

Optimal tax (additional to airport charges) to account for congestion and market power

Duopoly in homogenous Cournot

Two airports not formally modeled, only two regulators. Max SW = CS + � Also analyze Individual Max SW

One period (congestion pricing). Delay is a linear function of traffic and affects both airlines and passengers

Raffarin (2004)

Efficient congestion pricing

Differentiated duopoly competing in prices and frequencies

Max SW = CS + � + �− congestion costs. Single airport.

One period (congestion pricing). Three stage game: airport pricing, frequencies, prices. Congestion does not affect airlines nor demand. They are only an external social cost. Delay is a linear function of traffic (Continued )

Table 2 Summary of Papers Using the Vertical Structure Approach—Cont’d Author

Goal of the Paper

Oligopoly model

Objective Function and airport modeling

Observations

Basso (2005)

Effects of ownership on prices and capacity

N airlines in differentiated Cournot

Two airports (round trips) Max SW = CS + � + � Max airports’ profits Max airport–airlines joint profits Max SW st BC Max individual airport profits

One period (congestion pricing). Congestion is a non-linear function of traffic and affects both airlines and passengers. Consumers are also affected by schedule delay cost


Optimal pricing to account for congestion and market power when there are N airlines and capacity is variable

N airlines in homogenous Cournot

Max SW = CS + � + � Max airports’ profits Max SW st BC

One period (congestion pricing). Congestion is a non-linear function of traffic affecting only the passengers. The demand function is general

SW: social welfare; CS: consumer surplus; �: airlines’ profits (industry wide); �: airport profits; BC: Budget constraint.


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(and passengers) while ignoring the congestion externality imposed on other airlines’ flights, which enables a limited role for congestion pricing by the airport authority.8 In a “symmetric airlines” case, the optimal toll that should be charged during congested periods is equal to the congestion cost from an extra flight times one minus a carrier’s share. In particular, a monopoly airline would perfectly internalize all the congestion it produces and hence there would be no room for congestion pricing. This shows the difference with the road case: with market power, the degree of internalized congestion is usually sizeable. Pels and Verhoef (2004) attempted to expand Brueckner’s work in two directions: first, they explicitly considered the market power distortion and its effect on the optimal congestion toll. Second, they addressed the issue that, at an origin–destination (OD) pair, the airports may not collaborate to maximize overall social welfare; instead, each airport may maximize a local measure of welfare. Their model is as follows. Consider an OD pair in which the airports decide charges prior to airline competition. The capacities of the airports are assumed to be fixed. In this OD pair, two homogenous and symmetric airlines compete in Cournot fashion, taking airport charges and taxes as given when they choose their quantities (frequencies). Congestion delays affect airlines costs; the delay function is a linear function of total traffic at an airport. Passengers choose airlines based on a generalized cost which is the sum of the air ticket and congestion delay costs, and their demand for air travel is roundtrip-based. The model is solved by backward induction to obtain sub-game perfect equilibrium. Hence, the first step is to solve the airlines’ oligopoly, in order to obtain a sub-game equilibrium which will be parametrically dependent on the congestion tolls charged at each airport. With that sub-game equilibrium at hand, the authors looked for the optimal taxes that should be charged at each airport in order to adequately account for congestion. Initially, they consider that a single authority handles both airports and, consequently, maximizes the sum of consumer surplus and airlines’ profits. Hence, like Brueckner (2002), Pels and Verhoef looked at the regulator case, in that the airports’ profits do not enter the social-welfare function. Their main result indicates that the optimal toll would have two components: a congestion effect (which is positive) and a market power effect (which is negative). The first part is the one identified by Brueckner: since airlines only internalize the congestion they imposed on themselves, the uninternalized congestion should be charged. The second term, which decreases the toll, arises because of the market power at the airline level. What happens is that the regulator, in maximizing social welfare, would need to subsidize the airlines to induce them to produce more. The sign of the optimal toll is therefore undetermined; in particular, when the market-power effect exceeds the congestion effect, a subsidy would be the result. The toll would be positive if the congestion effect dominates. They pointed out, for example, that this would undoubtedly be the case for a monopoly airline.

8

As indicated above, Brueckner obtained the result by developing a model that explicitly recognizes the congestion’s effect on airfares. It is noted that Daniel (1995) first raised the internalization issue and developed a detailed simulation model to analyze carriers’ self-internalization and calculate congestion tolls that exclude the internalized congestion.

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Pels and Verhoef compared their toll to the pure congestion toll suggested by Brueckner (2002). They found that, when the market-power effect is strong, a pure congestion toll may actually be harmful for social welfare, since airlines are charged with a tax when in fact they should be receiving a subsidy. Brueckner did acknowledge this, though, by stating in his proposition that, “since congestion pricing corrects one distortion but leaves the residual market-power effect in place, tolls are guaranteed to be welfare improving only if that effect is sufficiently small. Otherwise, a negative welfare effect is possible” (p. 1367). Pels and Verhoef argued that, if a negative toll (subsidy) is optimal but unfeasible (for example for political reasons) the regulator should charge a zero toll. As indicated above, Pels and Verhoef also considered the case in which, at each airport, different regulators only maximize consumer surplus of passengers that live in the airport’s region, plus the profits of the home airline. The non-cooperative behavior of airports obviously implies that the result will be inferior to the single-regulator case. In fact, the authors showed, both numerically and analytically, that in the non-cooperation case, tolls at each of the two airports would always be positive. Raffarin (2004), like Brueckner (2002) and Pels and Verhoef (2004), was interested in the optimal airport toll. But rather than considering a two-stage model, she considered a three-stage model. In the first stage, the airport chooses its price. But then, conditional on the airport charge, duopoly airlines sequentially decide frequencies and then prices. The difference with Brueckner and Pels and Verhoef is that, in their case, airlines only decided frequencies; the price is determined in equilibrium by the Cournot assumption. Raffarin, however, has a system of differentiated demands (obtained from a representa tive consumer framework) such that an airline’s demand increases when its frequency increases or price decreases, and decreases when its rival’s frequency increases or price decreases. Raffarin’s model has three key assumptions that determine her results: first, she assumes that, even though frequencies are airlines’ decisions, any demand will always be fulfilled. And this is not ensured by the airlines’ choice of aircraft size, k, because k is an exogenous parameter in the model (i.e., equilibrium results will be dependent on k). Hence, there is no real connection between the number of passengers and the number of flights, other than the assumption that there will be enough space. Both Brueckner (2002) and Pels and Verhoef (2004) made a “fixed proportions” assumption, by which the number of passengers in a flight is a fixed constant. This assumption makes it easier, yet transparent, to transform the demand in terms of passengers, into an airport’s demand in terms of flights. The second assumption is that congestion delays – which as in Pels and Verhoef (2004) increase linearly with total traffic – do not affect consumers’ or airlines’ decisions. Instead, congestion costs are subtracted in the social-welfare function, which, interestingly, explicitly includes the airport’s profits. Hence, in this case, airlines do not internalize any of the congestion they cause because it does not directly affect them (it is not a cost to them), and passengers do not care about congestion either. Finally, the third important assumption is that an airline’s operational cost per flight, z, depends on the aircraft size in an increasing fashion, that is dz�k�/dk > 0. Hence, even though using larger aircraft means fewer flights, which saves on costs, each of those flights will be individually more costly. Aircraft size, however, is not a decision variable


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but a parameter. Hence, the implication is that, for given airport charges, equilibrium frequencies increase as the aircraft size diminishes. Rafffarin then maximizes social welfare – which is the sum of the airport’s profits, airlines’ profits and consumer surplus, minus congestion costs – in order to find what the optimal frequencies are, that is, the optimal level of airport’s demand. The optimal airport charge is then obtained as the price that would induce the optimal frequencies. The optimal charge she obtained has three components (which she did not recognize): the airport’s marginal cost, plus the cost of congestion (recall that airlines do not internalize any fraction of congestion in this model), plus a third term. This third term is negative, and could be assimilated to Pels and Verhoef’s market-power effect. The interesting twist, however, is that this term depends on the aircraft size, k, and diminishes the higher k. That is, the airport charge should be larger for smaller aircraft. And since aircraft size and weight are positively correlated, this implies that the airport charge should decrease with the aircraft weight, rather than increase as it is usually the case. The airport would reward airlines that use larger aircrafts because that implies smaller frequencies and hence smaller congestion costs. The choice of k, however, is not endogenous for the airlines in the model. The three papers we have reviewed so far have in common two important features: they all consider maximization of social welfare and in all the three cases, the airport capacities are fixed. In closely related but independent work, Basso (2005) and Zhang and Zhang (2006) generalized these two aspects. Both papers considered that the airport decides on price and capacity in the first stage, and in the second stage N airlines choose quantities (frequencies) in the output market. The airlines have identical cost functions; they are insensitive to congestion costs in Zhang and Zhang (2006) while they do bear extra costs owing to congestion in Basso (2005). Passengers, as usual, are sensitive to the full price of travel, that is, the airline ticket plus congestion delay costs.9 Both used congestion delay functions that are not homogenous of degree one in the traffic to capacity ratio, that is, congestion increases more than linearly with total traffic (for a given level of capacity). Other differences between the two papers are Zhang and Zhang considered that airlines are homogenous in the eyes of the consumers, while Basso allowed them to be horizontally differentiated (in a “non-address” fashion). Basso also considered in the full price perceived by the passengers another time cost, namely, schedule delay cost. This time cost arises because flights do not depart at a consumer’s will but have a schedule. Hence, schedule delay costs are a sort of waiting time, which decreases with higher airline frequencies. On the other hand, Zhang and Zhang considered a general demand function (of the full price) while Basso considered a more restrictive system of demands: linear in the full-prices of airlines. Both Basso (2005) and Zhang and Zhang (2006) solved the airport–airlines game by backward induction, characterizing the shape of the derived demand for the air port through comparative statics. Then, they both considered three different objective functions (Basso considered two more which are discussed later): unregulated profit

9 This last point is enough for the internalization of own congestion by an airline to arise in oligopoly, as discussed earlier. It is not needed for both, airlines and consumers, to be sensitive to congestion costs in order to derive the result.

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maximization, unconstrained social-welfare maximization, and social-welfare maximiza tion subject to cost recovery. Let us first discuss the pricing rules they obtained. In the case of unconstrained maximization of social welfare, they both considered a welfare function in which the airport’s profit is included. They found that, in their more general settings, Pels and Verhoef’s insight goes through: the optimal pricing rule is the sum of airport’s marginal cost, plus a congestion effect (positive) and a market-power effect (negative). When capacity is fixed, this pricing rule shows that with large values of N , the congestion effect is large while the market-power effect is weakened. Smaller values of N , on the other hand, imply a weaker congestion effect but a stronger market-power effect. With this pricing rule, the airport manages to obtain a “first best” outcome (subject to the market structure of the airline market which may be of monopoly or oligopoly) in the airline market. Note that, in this setting, rather than a regulator setting the toll, it is the airport that would distort marginal cost pricing to account for both uninternalized congestion and market power. Since the optimal airport charge may be below marginal cost and even below zero, the airport may run a deficit. In the case of unregulated profit maximization, Basso (2005) and Zhang and Zhang (2006) clearly found, in the pricing rule of the airport, the “double marginalization” problem that affects an uncoordinated vertical structure of airport and airlines. For a given capacity, the airport charge will decrease with the number of airlines downstream. On the other hand, and in a somewhat expectable result, an airport that maximizes social welfare subject to cost recovery will have a charge that is in between the unconstrained welfare-maximizing charge and the profit-maximizing charge. The balance will be given by the severity of the budget constraint. Turning to capacity decisions, Basso (2005) and Zhang and Zhang (2006) found that an unconstrained welfare-maximizing airport will provide capacity until the marginal cost of capacity equates the marginal benefits in reducing delays (to airlines and passengers in the case of Basso, to passengers only in the case of Zhang and Zhang). Interestingly, Zhang and Zhang (2006) proved that when both price and capacity are decision variables, in their setting, the market structure (i.e., N ) has no impact on airport’s actual demand and capacity. Consequently, delay levels will be independent of market structure. This however does not hold in Basso’s setting, in which airlines are differentiated and/or passengers care about schedule delay cost. The explanation has to do with the “preferred N ” of a welfare-maximizing airport. Basso showed that there are two opposing effects. With the congestion and market power effects being controlled, as it is the case here, fewer airlines in oligopoly would provide – each of them – higher frequencies than more airlines, thus delivering smaller schedule delay costs which increases social welfare. Smaller N would be preferable. On the other hand, differentiation brings about new demand when N increases, so a larger N is preferable. An unregulated private airport, however, would increase its capacity until the marginal revenue of doing so equates its marginal cost. Clearly, this capacity rule is different from the previous one. Basso (2005) noted then, that this is different than what happened in the traditional approach (e.g., Oum et al., 2004), in which the capacity rules of unregulated private airports and unconstrained public airports were the same. However, when N goes to infinity, i.e., airlines become perfectly competitive, the capacity rules become the same. The explanation for this is given in the next section. Further, Zhang and Zhang, and Basso, showed that conditional on the level of traffic, a private airport


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would over-supply capacity. However, that capacity would most likely be too small in a second-best sense. That is, a public airport that is forced to charge using the private airport pricing rule, would most likely supply more capacity than the actual capacity offered by the private airport (Basso, 2005). As with price, a budget constrained airport would, conditional on the level of traffic, choose a level of capacity that is in between the private capacity and the unconstrained public capacity. Basso looked at two other types of ownership as well. First, he investigated the case in which airports and airlines vertically integrate. The reason to look at this is because it has often been argued that more strategic collaboration between airlines and airports would solve incentive problems, particularly regarding capacity expansions. Basso found that the airport charge would include marginal cost and a term equal to the uninternalized congestion cost of each carrier, but would also include a third term, which is positive. This mark-up is put in place to fight against the business-stealing effect, a horizontal externality typical of oligopoly: a firm does not take into account profits lost by competitors when expanding its output. By increasing the airlines’ marginal cost with a higher airport charge, the airport would be able to induce a profitable (for the combined vertical structure) contraction of total output. In fact, the final outcome is indeed that of cooperation between competitors in the airline market. The intuition is that airlines would “capture” an input provider to run the cartel for them, given that they are unable to collude on their own. As for capacity, the vertically integrated structure would have the same capacity rule as the unconstrained public airport. The actual capacity however would be below the second-best capacity (i.e., a public airport that is forced to charge using the vertical integration pricing rule would supply more capacity). Basso also showed that, depending on how differentiated airlines are, and how strong schedule delay effects are, profits may be higher when the airports integrate with a single airline. A non-integrated private airport though will always prefer a larger N .10 Basso (2005) also looked at the case in which two distant airports are privatized separately. Social-welfare wise, the results worsen because the airports’ demands are perfect complements: in his setup with only two airports, a trip that starts at one airport necessarily ends at the other. Therefore “competition” between the airports induces a horizontal double-marginalization problem. This horizontal double marginalization arises in both the unintegrated and integrated vertical structures.

4 RELATIONSHIP BETWEEN APPROACHES It is clear that the questions examined in the two approaches – which we have called the traditional approach and the vertical structure approach – have not perfectly over lapped, and the two approaches appear rather different. This raises questions about the transferability of results, something that seems quite important to clarify if one is to apply to policy making what has been learned from analytical models of airport pricing.

10

Both Brueckner (2002) and Zhang and Zhang (2006) had N airlines downstream. However, public airports and vertically integrated airports would have no particular preference for N in their settings, because airlines are homogenous and there are no schedule delay effects.

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We address the issue of the connection between the two approaches in this section, based on results and discussions in Basso (2005). In the traditional approach, the airline market is not formally modeled, under the assumption that the airport charge would be completely passed to consumers, and that airline tickets and other charges would be exogenous to the airport. Oum et al. (2004) argue that this would be the case under perfect competition. In the vertical structure approach, on the other hand, it is recognized that airports provide an essential service that is required by airlines to move passengers; therefore, airports are viewed as providing a necessary input for the production of an output: travel. In fact, some authors using the vertical structure approach have been somewhat critical of the traditional approach on the grounds that it does not properly consider all the actors involved. For example, Raffarin (2004) said that it is rather strange that the pricing rules obtained from the traditional approach do not consider passengers’ utility. However, this is not completely accurate. Passengers are indeed somehow considered in the approach, as delay costs affect them as well, something that Raffarin missed.11 On the other hand, a view of the problem that recognizes that (i) airlines may have market power and (ii) airports provide an input for the production of an output sold at another market, appears more complete. Using the notations of Section 2, what the papers in the vertical structure approach have shown is that for any given airport charge, P, and airport capacity, K, the airline market – the downstream market – will reach some equilibrium. This equilibrium is constituted not only by equilibrium traffic but also by equilibrium delays and air ticket prices. By stressing this fact, three things become apparent. First, as far as the airport is concerned, its demand will be some direct function of P� K and of the (exogenous) airline market structure, which in most papers is represented by the number of airlines N . Hence, the airport’s derived demand would be Q�P� K� N�. Delays enter the picture through the equilibrium of the downstream market. How this demand faced by the airport responds to changes in P and K is something that a formal analysis of the airline market can unveil. Second, how airport charges and airlines’ delay costs are passed to consumers is built inside the demand faced by the airport and hence depends in general on the nature of the equilibrium reached in the airline market. In this sense, it would seem that a full price model pertains more to the airline-market stage than the airport-market stage. And third, other airline charges may not be exogenous to the airport because the downstream equilibrium – that is, the airport demand – depends on P and K, which are decided by the airport. Airport managers with foresight will take this into account and decide user charges and capacity investment accordingly. Thus, we can go back to the traditional approach and contrast its basic setting with what we have described above. Two important questions arise: 1. Is it reasonable to use the full-price idea at the airport level, rather than at the airlinemarket level? That is, under what conditions would it be legitimate to assume that the airport demand can be written as Q�� – with � = P + D�Q� K� – rather than as Q�P� K� N�?

11

The problem might lie in that Morrison (1987) states that the final consumers of airports services are airlines, even though in his model congestion explicitly affects passengers. In Oum et al. (2004), passengers are said to be the final consumers.


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2. If under some conditions the airport demand can reasonably be written as Q��, would its integration give a correct measure of consumer surplus? We have learned that the consumers of airports are both airlines and passengers. Hence, a socialwelfare function should include both airlines’ profits and passenger surplus. This is in fact what is explicitly done in the vertical structure approach when analyzing the maximization of social welfare. In the traditional approach, however, consumer surplus has been obtained through integration of the airport demand function with respect to a full price. Under what conditions does the derived demand for the airport carry enough information about the downstream market so that its integration gives a correct measure of airlines’ profits and passenger surplus? In short, these two questions attempt to clarify how the two approaches are related to each other. Basso (2005) analyzed this by using a vertical structure model to derive the demand for the airport. Details of his modeling were presented in Section 3 but, in short, he considered an airline oligopoly featuring N symmetric airlines, facing (linear) differentiated demands, which are dependent on the vector of full prices. These full prices are the sum of the airfare plus congestion delay costs. The important thing to note here is that, as opposed to the traditional approach case, the full-price is used at the airline market level rather than at the airport market level. Solving the airline subgame, Basso found an equation which implicitly defined the airport’s derived demand function Q�P� K� N�. Examination of the equation allowed Basso to show that, in general, Q would depend not only on � = P + D�Q� K� but also on DQ ≡ �D/�Q and N . That is, in general, Q ≡ Q�� DQ � N�. However, in the “perfect competition” case, i.e. when N → � under the Cournot conjecture, it is true that Q�� DQ � N → �� ≡ Q��. Thus, the answer to the first question above is: Under perfect competition, a full price as defined by � can in fact be used directly at the airport-market level. It does summarize well the equilibrium of the downstream market. Now we turn to the second question: If we assume that there is perfect competition, would the integration of Q�� correspond to the sum of airlines’ profits and passenger surplus? This question is relevant because, if it is not the case, then even under perfect competition the traditional approach would be maximizing a function that is not total social welfare. This second question is related to the more general subject of the relation between input and output market surplus measures (Jacobsen, 1979; Quirmbach, 1984; Basso, 2006). Results from that literature, however, do not apply directly to this case because, in the traditional approach, the integration of the airport’s demand is with respect to the full price �, rather than the airport charge P. To answer the question, Basso (2005) computed, in subgame equilibrium, the surpluses of airlines and passengers. He then showed that, when N → �, and therefore one can reasonably write the airport demand as Q��, the integration of the airport demand with respect to � would give ��

Q��d� = � + PS

(13)

�

where � is the aggregate airlines’ profits, and PS is passenger surplus. Therefore, the answer to the second question would be this: When there is perfect competition, such


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that using Q�� is justified, the integration of the airport demand with respect to the full price � will deliver a correct measure of consumer surplus, i.e., airlines’ profits plus passenger surplus. Perfect competition in the airline market was in fact the maintained assumption of Oum et al. (2004). Hence, Basso (2005) provided a theoretical support for their claim. But he also provided boundaries for the use of the traditional approach: it would be reasonable to use it only if market power at the airline level is absent.12 If airlines have market power, modeling the demand for the airport as Q�� would be incorrect. Furthermore, Basso (2005) showed that its integration with respect to � would actually fall short of giving the sum of airlines’ profits and passenger surplus. In this case, a full model that formally considers the airline market, as in the vertical structure approach, would be necessary. Lastly, since Q�� cannot be used when there is market power downstream, one may wonder whether by using the demand function Q�P� K� N� – which may be estimated empirically for instance – and by integrating it with respect to P, one can adequately capture airlines’ profits plus passenger surplus. This is not the case, unfortunately. Using results in Basso (2006) it can be shown that the integration of the airport demand with respect to P would give: �� P

N −1 �N − 1� � �Q Q�P� K� N�dP = � + PS − Q DQ dP N N �P �

(14)

P

Thus, there is no value of N for which the integral of the airport demand with respect to P would be equal to airlines’ profits plus passenger surplus (not even if N is very large).

5 PRICING OF AIRPORT NETWORKS The papers we have reviewed, in both the traditional and vertical structure approaches, do not really deal with airport networks. In most cases they deal with an airport in isolation. The exceptions, so far, have been Pels and Verhoef (2004) and Basso (2005) who consider a “network” of two airports. Yet, real air networks are obviously more complex than that, and it is fairly clear that in these real airport networks other issues arise. We review here three papers – namely, Oum et al. (1996), Brueckner (2005), and Pels et al. (1997) – that have dealt with a network of airports, that is, three or more airports. Oum et al. (1996) argue that in hub and spoke (HS) networks, airports’ demands are complementary because any take-off at a spoke airport will generate a landing at the hub. This complementarity is of different nature than the complementarity that arises in

12 An important qualification here is that these results hold for the specific set-up that Basso (2005) used which, for example, featured linear demands, Cournot competition and symmetric airlines with constant operational marginal costs. An open research question is how these findings change under more general demand and/or cost specifications, and other types of airline competition.


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two-airports networks because the presence of a hub introduces asymmetries. As in the two-airport cases, failure to consider the complementarities when looking for optimal pricing policies will result in social welfare losses. But in a HS network, congestion at the hub will build up more rapidly than at spoke airports. And when budget adequacy is an issue, this may imply the need for cross subsidizations between airports. Depending on the type of ownership however, cross subsidies may be unfeasible. Oum et al. study how ownership and cost recovery constraints affect airport pricing in a HS network and, consequently, social welfare. More specifically, Oum et al. (1996) consider n airports in a HS system: n-1 airports are spoke airports and there is one hub. All the airports have constant operational marginal costs and fixed capacity, but their capacity maintenance costs are positive. The demands for these airports depend on the charges at both the hub and spoke airports. All the airports are congestible, but congestion is an external cost that the airport authority will include in the social-welfare function; it does not affect the demands (as in Raffarin, 2004; see Section 3). This setup shows two things: First, the spoke airports’ demands are indeed complementary with the hub’s demand, but the demands are not directly complementary among the spoke airports. Second, that this paper is ascribable to the traditional approach, since the airline market is not for mally included. Indeed, consumer surplus is measured as the integrals of the airports’ demand. Oum et al. first analyze the case in which all the airports are publicly owned and under the control of a single authority: this is the “federal” case. The authority will maximize the airports’ profits plus consumer surplus – the sum of the integrals of airports’ demands – minus external congestion costs. The optimal pricing policy would have all the airports charging SMC, that is, the operational marginal cost plus the external costs of congestion. Since the hub is more likely to be heavily utilized, congestion will be greater there than at the spoke airports. Hence, they assume that SMC pricing would lead to cost recovery at the hub but to deficits at the spoke airports. The first-best federal case then would require cross subsidies from the hub to the less utilized spoke airports. If a budget constraint is set in place, the question becomes whether the hub makes enough profits to cover for the spoke airports’ deficits. If it does, we are back in the first-best case. If it does not, then Ramsey pricing is called for: the charge at the hub will increase. Cross subsidization will be, obviously, still needed and this alternative will be welfare inferior to SMC pricing. They then look at the case in which each airport is under the control of a different authority who, subject to cost recovery, maximizes its local social welfare, that is, the integral of own demand plus own profits, minus congestion costs. This is the “de-federalized” or “local government” case. Given the assumption about SMC not covering costs in spoke airports, in this case, the hub will price at SMC, but the spoke airports would charge average costs to ensure cost recovery. Since individual cost recovery implies overall cost recovery, this case will be inferior, social-welfare wise, to the previous Ramsey pricing case. In general, in the federal case, and independent of whether SMC or Ramsey prices are used, charges at the hub will be larger and charges at the spoke airports will be smaller than in the local government case. Oum et al. (1996) conclude that de-federalization of airports may imply social welfare losses: by not jointly pricing the airports, the local airport authorities will not take into account


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that demands are complementary and cross-subsidies will likely become unfeasible. The welfare losses, though, would have to be balanced against possible X-inefficiencies gains that de-federalization may bring about.

5.1 Network Airport Pricing with Airline Competition Recall, however, that the conclusion of Section 4 was that a traditional approach would be justified only when air carriers are atomistic. What would happen if carriers have market power? In this case, we would need a vertical structure type of approach. This is what Brueckner (2005) analyzes. The main point here has to do with the meaning of market power. One of the conclusions in Section 3 was that congestion tolls would decrease in an airline’s share of flights at the airport, because an airline only internalizes the congestion caused on own flights. Since in that section, only one or two airports were considered, the share of flights at the airport was identical to the share of flights at the city-pair market level. However, when one considers even a simple network of airports in which airline competition exists, it is no longer true that the share of flights at the airports will necessarily be equal to the share of flights at the city-pair market level. Hence, the relevant question becomes – what is the relevant flight share for congestion internalization? Brueckner considers the following network in which two airlines compete. In this network, airport H is airline 1’s hub, while airport K is airlines 2’s hub. Airline 1 serves four city-pair markets (depicted by the solid lines in Figure 1): AH, KH, BH, and AB (two legs). Airline 2 also serves four city-pair markets (dashed lines). The airlines compete in two markets, KH and AB, while each is a monopolist in its two other markets. It can be easily recognized – for example under full symmetry – that airline 1’s share of departures and take-offs at its hub H is larger than airline 2’s share. Similarly, airline 2 dominates hub K in terms of departures and take-offs. However, in the two markets where the airlines compete, they would both have a 50% share of flights under symmetry. This nicely shows the difference between the shares of flights at airports and the share of flights in city-pair markets, which justify the research question.

H

A

B

K

Airline 1 Airline 2

Figure 1 Network Structure and Airline Competition (Brueckner, 2005).


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To analyze what would be the optimal congestion toll, Brueckner uses a setup which essentially is the same as in his single-airport paper (Brueckner 2002; see Section 3 for a description) but considers each of the various markets. Airports are assumed to have a fixed exogenous capacity with only the hubs being prone to con gestion. The derivation of optimal congestion tolls is quite involved so it is omitted here, but the conclusion is simple and important: Regardless of the degree of market power that an airline has in the city-pair markets it serves, the amount of conges tion it internalizes depends only on its flight share at the congested airport. Hence, “the appropriate airport congestion tolls are carrier-specific and equal to the conges tion damage from an extra flight times one minus the carrier’s airport flight share” (Brueckner, 2005, Proposition 1, p. 612). An important final point that Brueckner (2005) raised has to do with the marketpower effect we discussed in Section 3. There, we saw that, while a congestion toll is justified when carriers are oligopolistic, from a first-best point of view a subsidy was also justified as a means to fight against market power at the airline level and hence reduce allocative inefficiencies.13 In the simple settings of one or two airports, both the congestion effect and the market-power effect depended on a carrier’s flight share. But in that case the airport share and the city-pair market share were the same. Brueckner (2005) showed that, in a network setting, whilst the congestion tolls are airport-specific, the subsidies required are city-pair specific. Hence, an airport regulator would need to calculate appropriate airport-specific congestion tolls together with city-pair specific subsides to obtain, finally, the optimal charge, which would be positive if the congestion effect dominates the market-power effect. Brueckner argues that, since market-level subsides are impractical to implement, only airport congestion tolls would be used, an approach that would be welfare improving, yet not first-best, if congestion effects dominate.

5.2 Network Airport Pricing with Variable Route Structure Now, both Oum et al. (1996) and Brueckner (2005) have assumed that the route structure of airlines, that is, the way airlines move passengers between origins and destinations, remain unchanged and is independent of the pricing practices of airports. But, what would happen in the long run if the route structure is be changed? For example, it has been often argued that economies of density drive the adoption of HS networks. But if congestion at hubs is too important, airlines may decide to by-pass them, offering direct connections in some city-pair markets.14 Would congestion pricing affect the timing of such a decision? May airports use their pricing practices as a way to compete for connecting passengers, that is, may they compete to become hubs? A model including all these elements would be indeed very complicated and has, as far as we know, not yet been proposed. However, there is one paper that, even though in a context of non-congestible airports and a monopoly airline, does look at how airport pricing and

13

On the other hand, we do not normally think of solving the market-power problem by subsidizing the firms,

for several good reasons. The subsidy may alternatively be interpreted as an imperfect proxy for some kind

of antitrust policy in its effect on price reduction.

14 For a paper related to this issue, see Basso and Jara-Diaz (2006).


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B

Fully connected Network (FC)

Hub and Spoke Route Structure (HS)

A

C

Figure 2 Possible Route Structures.

airline’s choice of route structure are related. Specifically, Pels et al. (1997) consider a model with three non-congestible public airports (hence three OD city-pair markets) and a monopoly airline. Airport charges are directly made to passengers. Thus, the demands for airports and for the airline depend on both airfares and airport charges. The airports and the monopoly airline play a simultaneous game in which each airport chooses its per-passenger charge, while the airline chooses a route structure and its airfares. The objective function of the airports is to maximize own social welfare (as in the de-federalized case of Oum et al., 1996), which is measured as the integral of the airport’s demand, subject to a budget constraint. The airline seeks to maximize its profit. There are some key assumptions in the model, which are more easily explained using Figure 2. First, it is assumed that node (airport) A has more passenger generating capacity. That is, if airports’ and airline charges were zero, the demands in the AB and AC pairs would be �, while in the BC pair it would be ��, where � < 1. Second, consumers only care about the monetary charges (from the airports and the airline) but would not care about travel times (which are higher in a HS route structure) or whether they have to make connections or not. Third, the marginal cost of carrying a passenger is constant and equal across links; hence, in a HS route structure, a passenger traveling from B to C would cost the airline 2c whilst with a FC route it would cost only c. Finally, if a link is used, it has a fixed cost c0 . Hence, a HS route structure is cheaper in terms of fixed costs, as it only uses two links (vs. three links in a FC structure), but is more expensive in term of operational costs. Pels et al. (1997) show that, in this setup, if the airport charges are zero (or, if they are equal but are chosen non-strategically, i.e., without considering what the airline does) a HS route structure will be preferred by the monopoly airline if � < �, i.e. the demand in the BC market is much smaller than the demands in the AB and AC markets. The limit � increases in both c and c0 , and decreases in �. Further, they show that the airline will always choose to place its hub at the node with the highest level of demand, in this case, node A.15 When the airports choose their prices simultaneously with the airline’s choice of route structure and airfares, Pels et al. show that the airport charges will increase in fares, but the fares will decrease in airport charges. The “dynamics” of equilibrium would be:

15 For more discussions on the choice of route structure, see, e.g., Oum et al. (1995), Hendricks et al. (1999), Pels et al. (2000) and Jara-Diaz and Basso (2003).


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The monopoly airline, which is a profit maximizer, would increase its prices depressing demands. Since the public airport must break even, it would raise its own charges, but that would induce the airline to decrease its prices. This in turn would increase demand, inducing a decrease in the airports’ charge, which in turn would induce the airlines to increase price. Eventually, this loop may reach an equilibrium, although Pels et al. show that non-existence of equilibrium is a possible outcome. Since analytical solution of the equilibrium is unfeasible, they rely on a numerical simulation to extract more conclusions. They found that, only if � is small enough, the airline would choose a HS route structure. The higher the �, however, the better for the hub. More importantly, price competition between the airports seems to have little effect on the airline’s choice of a hub; the choice would still be made based on passenger generating capacity. Obviously, one can foresee that the actual geographic position of the airports would be important as well. A hub would not be placed really far away from all its spoke airports. But in this model, distances, that is the topology of the network, does not play a role. This is reasonable under the assumption that all airports are located fairly close or equidistant from each other.

6 CONCLUSIONS AND FURTHER RESEARCH Airport pricing has been widely analyzed in the economics literature. In this survey paper, we have focused on analytical models of airport pricing from 1987 on. We have grouped the models in the literature into two broad approaches. Roughly, the traditional approach has used a classical partial equilibrium model where the demand for airports depends on airport charges and on congestion costs of both passengers and airlines; the airline market is not formally modeled, in several cases under the assumption that airline competition is perfect and hence airport charges and delay costs are completely passed to passengers. The vertical structure approach was motivated initially by the increasing and acute congestion at major hub airports in the United States and around the world. Since hub airports usually have only a few dominant airlines, the airline market there is better characterized as oligopoly: air carriers may possess market power. Thus, the airline market was considered in the analysis of airport pricing. Furthermore, the vertical structure approach has recognized that airports provide an input for the airline market – which is modeled as a rather simple oligopoly – and that it is the equilibrium of this downstream market that determines the airports’ demand: the demand for airports is therefore a derived demand. The questions investigated with the two approaches have not perfectly overlapped. The traditional approach has been used to analyze a variety of issues such as optimal capac ity investments, effect of concession revenues, privatization, efficiency of alternative regulation mechanisms, cost recovery when capacity cannot be increased continuously, and efficiency of weight-based airport charges. On the other hand, the vertical structure approach has focused mainly on calculating the additional toll that airlines should be charged to attain maximization of social welfare. It is only recently that vertical structure models have been used to assess such issues as optimal capacity levels, or the effects of privatization on airport charges. Drawing from results in Basso (2005), we indicated here that abstracting from the airline market, as is done in the traditional approach, is a

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reasonable approximation only when airlines behave competitively, but it is not when airlines have market power. In the latter case, the derived demand for the airport would not be dependent only on its full price, as it is assumed in the traditional approach. As a result, the integration of the airport demand with respect to the full price, which is said to capture consumer surplus, would not adequately capture the surpluses of passengers and airlines because market power and congestion effects preclude it. Therefore, in that case, the function that is maximized in the first-best scenario would not correspond to total social welfare.16 The fact that the airline market cannot be ignored if airlines have market power implies, on one hand, that future research would need to use vertical structure models if the airline market structure is an important factor for the issues to be investigated. This may include re-examination of some of the questions that have been addressed only with the traditional approach, including, for example, the effect of concession revenues on airport charges, the efficiency of regulation mechanisms for congested hub airports, and congestion pricing with lumpy airport capacity. But on the practical side, the fact that the airline market has to be included in the models is also bad news for managers of public airports and regulators: to implement optimal decisions, the amount of information required would be massive even in simple settings, which undoubtedly complicates the problem. In the models we have reviewed in this survey, authors have resorted to a number of simplifications, which was the price to pay to preserve analytical tractability. In the airline market of vertical structure models, two usual simplifications are the assumption of fixed proportions and the assumption of symmetric airlines. The former was made when the authors assumed, as constant, the product between aircraft size and load factor (or both). Yet, it has been widely accepted that airlines enjoy what is called “economies of traffic density” – decreasing average cost on nonstop connections – owing largely to the economies of aircraft size. These economies are not considered under the fixedproportions assumption (which precludes the endogenous choice of aircraft types by airlines). A variable-proportions case would arise because, if the charge per flight is too high, airlines would have an incentive to change to larger airplanes, independently of existing or exhausted economies of airplane size. So, with privatization for example, not only capacities and traffic levels would be distorted downwards, but aircraft size would be distorted as well. Modeling this effect is an interesting area of future research albeit a complex one, as larger aircrafts imply smaller frequencies, which directly affects congestion and demand through schedule delay costs.17 Regarding the assumption of asymmetric airlines, certainly insights would be gained if the analysis could be extended to the case of asymmetric airlines, as the model would depict a more realistic case. Brueckner (2002, p. 1368) stated that “cost differences

16 This result in fact applies not only to airports but to any other types of transport terminal, or even railroad tracks, since the situation is essentially the same. 17 Note that Raffarin (2004) is not an analysis of variable proportions case because, although she did considered different aircraft sizes, the airlines where not free to decide about their preferred aircraft size. Rather, the aircraft size was exogenously given through a parameter, which thus showed up in the final pricing rules of the airport. Also, in her model congestion did not directly affect passengers or airlines but was an external cost to be minimized by the airport authority and capacity was fixed.


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across firms may not be a useful source of asymmetry, however, because a planner would not allow high-cost firms to operate at the social optimum.” In Basso (2005) and Zhang and Zhang (2006), however, there was no social planner but rather managers of public airports maximizing social welfare, who probably would not have the power to preclude less efficient airlines to operate. But they did not consider asymmetries. It seems, to us, that characterizing the properties for the case of asymmetric airlines would be unfeasible analytically; instead, numerical simulations would be required. Pels and Verhoef (2004) did present some numerical simulation results for the case of an asymmetric duopoly (see Table 2 for a description of their setting). The papers in Section 3 have looked at either a single airport in isolation or, at most, round-trip travel between two airports. In the latter case, the airports have complementary demands; consequently, public airports that are priced independently would not achieve a first-best outcome (Pels and Verhoef, 2004), and separate private airports would end up with a horizontal double marginalization (Basso, 2005). However, airport networks are more complex than that; and on this subject, the papers presented in Section 5 represent good progress in understanding the main issues. Nevertheless, we believe that there is still much work to do. In Oum et al. (1996) and Brueckner (2005) there were no route structure decisions on the part of airlines, but it is through route structure decisions that airports may actually compete: they would be competing for connecting passengers. On the other hand, although considering route structure decisions, Pels et al. (1997) do not include congestion, capacity choices, or airline competition. Further work on the pricing of network airports – including effects of privatization and regulation mechanisms – is, in our view, a clear line of future work. A related aspect is geographic competition: airports competing for costumers in the same origin, i.e., with overlapping catchment areas, as in the case of New York and San Francisco Bay Area. There has been some empirical work on this issue (e.g., Ishii et al., 2005, and the references cited there), but not too much work on the analytical side. Some papers have looked at competition between congestible Bertrand facilities (e.g., De Borger and Van Dender, 2006) but they overlooked the intermediate carrier market in vertical structures discussed above. A simple model of geographic competition between two airport-airline structures is Gillen and Morrison (2003). But they considered only the case of one airline per airport and the joint airport–airline profit maximization, and they did not consider the issues of airport congestion and airport capacity choices. We think that competition in multiple-airport regions with congestion is another interesting area of future research.18 Another important aspect is the issue of peak-load pricing, in addition to just con gestion pricing. Most of the models we have reviewed are about congestion pricing rather than peak-load pricing, in the sense that even if there is more than one period in those models, the demands between periods are not interdependent. Hence, the only way to fight against excess usage is to dampen the demands. When the periods are interdependent, however, pricing can be used not only to dampen the demands, but also to redistribute consumers and flights across different periods, “flattening” the demand

18

As this survey was being completed, a paper dealing with the specific issue of geographic competition was accepted for publication. Time precluded the presentation of the main results in this review. For details see Basso and Zhang (2007).

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curve – the case of peak-load pricing. Brueckner (2002) allowed for endogenous sorting to peak and off-peak periods, but the sorting was done mainly through airlines’ decisions. If the airlines use peak-load pricing, then that would deliver a different demand pattern to the airport, which would probably also have peak and off-peak periods. The airport would then have an incentive to choose prices for its own peak and off-peak periods, probably using peak-load pricing as well, in order to maximize its objective function. The objective function would be dependent on the type of ownership and regulation. Hence, we would be in a situation of sequential peak-load pricing, which represents particularly well the case of airports and airlines (Basso and Zhang, 2006). We have highlighted some of the issues that we think should be examined in the future, but perhaps one of the most important aspects of future research has to do with actual policies. It is seldom true that airports are priced as in a system, and it is seldom true that airport managers have access to all the information that they would need to do what is best. Hence, how should public airports be priced when they are not in a system, and when information is incomplete? And given this, what are the costs and gains of airport privatization, and what would be a good and feasible regulation mechanism for privatized airports? Investigating these questions will advance our understanding of the subject and produce useful guidance to policy formulations.

REFERENCES Basso, L.J. (2005) Airport ownership: Effects on pricing and capacity. Working Paper, Sauder

School of Business, The University of British Columbia (http://ssrn.com/abstract=849584).

Basso, L.J. (2006) On input markets surplus and its relation to the downstream market game.

Working Paper, Sauder School of Business, The University of British Columbia. Basso, L.J. and Jara-Diaz, S.R. (2006) Distinguishing multiproduct economies of scale from economies of density on a fixed-size transport network. Networks and Spatial Economics, 6, 149–162. Basso, L.J. and Zhang, A.M. (2007) Congestible facility rivalry in vertical structures. Journal of Urban Economics, 61, 218–237. Basso, L.J. and Zhang, A.M. (2006) Sequential peak-load pricing: The case of airports and airlines. Working Paper, Sauder School of Business, The University of British Columbia. Brueckner, J.K. (2002) Airport congestion when carriers have market power. American Economic Review, 92(5), 1357–1375. Brueckner, J.K. (2005) Internalization of airport congestion: A network analysis. International Journal of Industrial Organization, 23(7–8), 599–614. Carlin, A. and Park, R.E. (1970) Marginal cost pricing of airport runway capacity. American Economic Review, 60, 310–319. Carlsson, F. (2003) Airport marginal cost pricing: Discussion and an application to Swedish airports. International Journal of Transport Economics, 30, 283–303. Condie, S. (2000) Whither airport regulation? In: Smith, H.L. and Bradshaw, W. (Eds.), Privati zation and Deregulation of Transport, St. Martin’s Press, Inc., New York, 364–393. Czerny, A.I. (2006) Price-cap regulation of airports: Single-till versus dual-till. Journal of Regu latory Economics, 30, 85–97. Daniel, J.I. (1995) Congestion pricing and capacity of large hub airports: A bottleneck model with stochastic queues. Econometrica, 63, 327–370.


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De Borger, B. and Van Dender, K. (2006) Prices, capacities and service quality in a congestible Bertrand duopoly. Journal of Urban Economics, 60, 264–283. Doganis, R. (1992) The Airport Business, Routledge, London. Economist (2006) Global warming, The Economist, 8 June 2006, Economist Intelligence Unit. Forsyth, P. (2000) Models of airport performance, In: Hensher, D.A. and Button, K.J. (Eds.), Handbooks in Transport, Vol. 1, Pergamon, Amsterdam, 597–608. Gillen, D.W. and Morrison, W.G. (2003) Bundling, integration and the delivered price of air travel: Are low cost carriers full service competitors? Journal of Air transport Management, 9, 15–23. Hendricks, K., Piccione, M., and Tan, G.F. (1999) Equilibria in networks. Econometrica, 67(6), 1407–1434. Horonjeff, R. and McKelvey, F.X. (1983) Planning and Design of Airports. McGraw-Hill. Ishii, J., K. Van Dender and S. Jun (2005) Air travel choices in multi-airport markets, Working Paper, Department of Economics, University of California at Irvine. Jacobsen, S.E. (1979) Equivalence of input and output market Marshallian surplus measures. American Economic Review, 69(3), 423–428. Jara-Diaz, S.R. and Basso, L.J. (2003) Transport cost functions, network expansion and economies of scope. Transportation Research Part E-Logistics and Transportation Review, 39(4), 271–288. Jones, I., Viehoff, I. and Marks, I. (1993) The economics of airport slots. Fiscal Studies, 14, 37–57. Lave, L.B. and De Salvo, J.S. (1968) Congestion, tolls and the economic capacity of a waterway. Journal of Political Economy, 76, 375–391. Levine, M.E. (1969) Landing fees and the airport congestion problem. Journal of Law and Economics, 12, 79–108. Lu, C.C. and Pagliari, R.I. (2004) Evaluating the potential impact of alternative airport pricing approaches on social welfare. Transportation Research Part E-Logistics and Transportation Review, 40(1), 1–17. Mohring, H. (1976) Transportation Economics. Ballinger, Cambridge MA. Morrison, S.A. (1983) Estimation of long-run prices and investment levels for airport runways. Research in Transportation Economics, 1, 103–130. Morrison, S.A. (1987) The equity and efficiency of runway pricing. Journal of Public Economics, 34(1), 45–60. Morrison, S.A. and Winston, C. (1989) Enhancing the performance of the deregulated air trans portation system. Brookings Papers on Economic Activity, 61–112. Oum, T.H. and Zhang, Y.M. (1990) Airport pricing – Congestion tolls, lumpy investment, and cost recovery. Journal of Public Economics, 43(3), 353–374. Oum, T.H., Zhang, A.M., and Zhang, Y.M. (1995) Airline network rivalry. Canadian Journal of Economics, 28, 836–857. Oum, T.H., Zhang, A.M., and Zhang, Y.M. (1996) A note on optimal airport pricing in a huband-spoke system. Transportation Research Part B-Methodological, 30(1), 11–18. Oum, T.H., Zhang, A.M., and Zhang, Y.M. (2004) Alternative forms of economic regulation and their efficiency implications for airports. Journal of Transport Economics and Policy, 38(2), 217–246. Pels, E., Nijkamp, P., and Rietveld, P. (1997) Substitution and complementarity in aviation: Airports vs. airlines. Transportation Research Part E-Logistics and Transportation Review, 33(4), 275–286. Pels, E., Nijkamp, P., and Rietveld, P. (2000) A note on the optimality of airline networks. Economics Letters, 69(3), 429–434. Pels, E. and Verhoef, E.T. (2004) The economics of airport congestion pricing. Journal of Urban Economics, 55(2), 257–277.

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Quirmbach, H.C. (1984) Input market surplus – The case of imperfect competition. Economics Letters, 16(3–4), 357–362. Raffarin, M. (2004) Congestion in European airspace – A pricing solution? Journal of Transport Economics and Policy, 38, 109–125. Ross, T.W. (1984) Uncovering regulators social-welfare weights. Rand Journal of Economics, 15(1), 152–155. Spence, A.M. (1975) Monopoly, quality, and regulation. Bell Journal of Economics, 6(2), 417–429. Starkie, D. (2001) Reforming UK airport regulation. Journal of Transport Economics and Policy, 35, 119–135. US Department of Transportation (2006) National Strategy to Reduce Congestion on America’s Transportation Network, May 2006, Washington DC. US Federal Aviation Administration (1969) Airport Capacity handbook. Government Printing Office, Washington DC. Zhang, A.M. and Zhang, Y.M. (1997) Concession revenue and optimal airport pricing. Trans portation Research Part E-Logistics and Transportation Review, 33(4), 287–296. Zhang, A.M. and Zhang, Y.M. (2001) Airport charges, economic growth and cost recovery. Transportation Research Part E-Logistics and Transportation Review, 37, 25–33. Zhang, A.M. and Zhang, Y.M. (2003) Airport charges and capacity expansion: Effects of conces sions and privatization. Journal of Urban Economics, 53, 54–75. Zhang, A.M. and Zhang, Y.M. (2006) Airport capacity and congestion when carriers have market power. Journal of Urban Economics, 60, 229–247.


5 What if the European Airline Industry had Deregulated in 1979?: A Counterfactual Dynamic Simulation∗ Purvez F. Captain† , David H. Good‡ , Robin C. Sickles§ , and Ashok Ayyar¶

ABSTRACT Studies in industrial organization predict rapid consolidation following deregulation to seize economies of scale. The European airlines, while witnessing some strategic movement, have remained remarkably stable in the wake of deregulation. By contrast, the US industry underwent deregulation beginning in late 1978 and experienced a vigorous shakeout. This begs the question: if Europe had deregulated in 1979 alongside the US, how would have the European industry fared without the American experience in hindsight? We developed a dynamic industry model to answer this question, simulating for optimal levels of operational variables, namely level of employment, network size, and fleet size for the period 1979–1990. The study reveals which European airlines were operating most inefficiently by comparing the simulation results with the actual numbers. Our findings point to several sources of forgone profits, in particular to the need for the European carriers to adopt policies which allow them to take advantage of returns to density by network reconfigurations brought about by code-sharing arrangements.

∗ The findings and interpretations reflected in this article do not reflect in any way those of Ernst and Young, LLP, Houston, Texas. † Ernst & Young, LLP, Houston, TX ‡ Indiana University, Bloomington, IN

§ Corresponding author. Rice University, Houston, TX, 6100 Main St Houston TX 77005. e-mail:

[email protected].

¶ Chicago Partners, LLC, New York

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1 INTRODUCTION The European airline industry was traditionally sheltered from competition due to its state-owned national carriers and inflexible bilateral agreements. Consequently, the mar ket structure developed brought with it market distortions and inefficiencies. The airfares proved it – fares were consistently higher than those charged for equidistant routes in the US. Case in point: When the Federation of European Consumers planned a conference in 1984, they calculated it would be cheaper to fly all their delegates to Washington, DC than to convene anywhere in Europe (Sampson, 1984). The liberalization movement, achieved in three reform packages between 1987 and 1992, successively eased the airline industry’s straight jacket, creating a competitive mar ketplace centered on a profit-maximizing business model rather than the old rent-seeking one. History has shown us that rapid consolidation follows on the heels of deregulation, as firms exploit economies of scale (Bannerman, 2002). Yet, while witnessing some strategic movement, the European industry has remained remarkably stable in the wake of deregulation. By contrast, the US industry underwent deregulation beginning in late 1978 and experienced a vigorous shakeout. This begs the question: if Europe had dereg ulated in 1979 alongside the United States, how would have the European industry fared without the American experience in hindsight? We developed a dynamic model of the industry in response, simulating for optimal levels of operational variables, namely employment, network size, and fleet size for the period after the US deregulatory initiatives took hold and before the European deregulatory transition began, the period from 1979 to 1990. The study reveals which European airlines were operating most inefficiently by comparing the simulation results with the actual levels of input use. A number of dynamic industry models have been proposed and estimated. Early work by Jovanovic (1982) modeled a perfect foresight equilibrium industry structure in which efficient firms grow and survive, while the inefficient firms decline and exit the industry. In this model, firms learn about their efficiency as they operate in the industry. Firms decide to enter or exit the industry based on a comparison of the value of staying in the industry and behaving optimally with the discounted present value of the opportunity cost associated with the firm’s fixed factor, such as managerial ability or advantageous location. The latter example of a fixed factor is clearly applicable to the European airline industry, where congestion at most major airports has made gates and landing slots coveted fixed factors. Research on industrial evolution has since focused on the relationship between firm size and growth (Evans, 1987a,b; Hall, 1987), endogenous learning (Pakes and Ericson, 1998), and in endogenizing firm strategies (Berry, 1992). This chapter’s approach builds on the intertemporally nonseparable model introduced by Hotz et al. (1988) and utilized and extended Sickles and Yazbeck (1998) and Sickles and Williams (2006). It is organized as follows. Section 2 gives an international regula tory history, for the relevant years of the study. Section 3 outlines the dynamic model and discusses the specification and estimation of its relevant components: demand, produc tion, and cost. Section 4 discusses the data sources; Section 5 interprets the simulation results and section 6 concludes.

A COUNTERFACTUAL DYNAMIC SIMULATION

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2 INTERNATIONAL REGULATORY HISTORY The Paris Convention of 1919 first gave rise to the regulation of international aviation. There it was decreed that states have the sovereign rights over the air space of their territory, which immediately involved national governments in the regulation of the industry. Fifty-two countries met at the Chicago conference of 1944 to spar over Five Freedoms of Air, the fundamental set of rights in airline economics. The First Freedom gave the right to fly over a third country’s airspace while on an agreed service and the Second Freedom permitted the airline to land in a third country for fuel and maintenance but not pick up or discharge traffic. The Third Freedom allowed an airline to carry traffic from its own country to a second country in a bilateral. The Fourth Freedom permitted an airline to carry traffic back from that country to its own country. The Fifth Freedom permitted the transportation of traffic by the first country’s airline between the second country and a third country not party to a bilateral (Taneja, 1988). The key parties at the conference, the US and the UK, were at opposite ends of the economic spectrum. The US, whose civil aviation industry emerged from World War II unscathed, sought operating freedom for its airlines under a multilateral “open skies” agreement. Smaller European countries like the Netherlands and Sweden flanked this policy because they would depend heavily on Fifth Freedom traffic. The UK and other large European countries, devastated by the war, proposed the formation of an international authority, which would regulate capacity and fares on routes, thereby giving their aviation industries a chance to rebuild. These opposing views could not be reconciled at the conference, and the convention ended with concordance only on the first two Freedoms. The US and the UK met in Bermuda in 1946 in an effort to resolve differences on the next three freedoms. The two countries agreed to these freedoms in a bilateral agreement (Bermuda I) on flights to and from the US and the UK. This bilateral became a model for the other countries and their respective aviation partners. It also assured that the aviation industry would be heavily regulated and quagmire in political uncertainty (Williams, 1994). Meanwhile, the other participants of the Chicago conference created the International Air Transport Association (IATA) in Havana in 1945. The proposed plan was to fix fares jointly and submit it to governments for approval, instead of either multilateral or unilateral government imposition of fares on airlines. These fares required a unanimous vote from all members and were binding to all of these members. The US Civil Aeronau tics Board (CAB) reluctantly agreed to this fare-setting environment, which remained an international fixture for the next 30 years. The system worked fairly smoothly in Europe. The airlines were government-owned and strongly opposed to any form of competition; the fare submission procedure amounted to little more than a formality. The CAB was never comfortable with this arrangement and often protested fare structures set by IATA. In the late 1970s, frustrated by its efforts to liberalize the structure through IATA, the CAB actively began its attempt to liberalize the transatlantic market by forming bilateral agreements with European nations. CAB’s strategy of penetrating one national market at a time and then forcing liberal agreements on others through the threat of traffic diversion was successful in opening the transatlantic market. The level of competition increased substantially with the entry of new airlines into the market.

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While the CAB pried the transatlantic market open, the internal European market remained strictly protected until the mid-1980s. The European airlines were mostly public airlines or majority government-owned; they enjoyed the duopolistic situation created by the bilateral agreements and prevented new entry in the intra-European market. Pooling revenue and sharing capacity, the airlines eliminated any competition among themselves in the internal market. The European Commission (EC) recommended opening aviation to competition as early as 1972, but strong objections from the European governments tabled discussions until 1979 when the EC published Civil Aviation Memorandum Number l. The memo recommended that (1) airlines offer cheaper fares; (2) there was a need to develop new cross-frontier services connecting regional centers within the community; (3) a clear universal policy on government subsidies was required; and (4) full freedom of access to all markets was desirable. The transportation ministers adopted these measures in limited form in the early 1980s, which did marginally improve competition and lower fares (Balassa, 1985). The larger European nations, however, were very reluctant through the mid-1980s to abandon the protected status of their national carriers by advocating more liberal competition policies. These governments directly or indirectly subsidized their carriers, the extent of which varied from country to country. Financial assistance was provided to (l) compensate airlines for the imposition of a public service obligation; (2) develop and operate domestic services; (3) provide service to economically underdeveloped regions; (4) encourage the acquisition and operation of specific airplanes (Airbus); or (5) simply cover an airline’s operating loss (Taneja, 1988). EC commissioner Peter Sutherland provided the catalyst for change, threatening to take the airlines to the European Court in 1987 for violation of the competition rules of the Treaty of Rome. The European transport ministers met thereafter in Brussels to negotiate for flexibility in setting fares. The deal allowed airlines to offer discount fares – ranging between 65 and 90 per cent of the economy class fares – provided this was accepted by the member states. It also allowed for an increase in capacity shares on a route provided that the shares split between two countries were not outside the range of 55 to 45 per cent up to 1 October 1989, and 60–40 per cent thereafter. The next round of liberalization talks ended in 1992 in Luxembourg where after 10 years of hard negotiations, the European Union finally agreed on issues that would establish a more competitive environment in European skies. The five major provisions in the deal were the following: 1. Fares: Airlines would be able to set their own prices, subject to two major controls. Brussels was empowered to limit excessive prices from being charged, following notification from national aviation authorities. It would also be able to set a baseline under fares on a specific route if prices free-fall, foisting losses on all carriers. These mechanisms were designed to obviate predatory pricing. 2. Routes: Consecutive cabotage rights to add a domestic leg onto a flight originating from a carrier’s home base to a foreign destination, provided that the load factor on the domestic leg did not exceed 50 per cent of the total on the main flight. Thus, a KLM flight from Amsterdam to Paris could pick up passengers in Paris and fly to Nice provided that the 50 per cent rule was satisfied.


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3. Flights: Agreement to the Sixth Freedom (which had been in dispute since the Chicago Convention) where airlines could fly passengers to two destinations while stopping at a third country, which was the airline’s base. With this in place, Air France, on a flight from Rome to London, could stop in Paris en route and pick up passengers. The Seventh Freedom was introduced, whereby any carrier could fly between any two EC states without the need to start or end in the home country. For example, British Airways could fly between Paris and Frankfurt, with the flight originating and ending at the two destinations. 4. Domestic services: Starting on 1 April l997, any carrier from any EC country could operate internal flights in any of the 12 member states. 5. Licensing: Common rules governing safety and financial requirements on capital adequacy for new entrants to the market. Once satisfied, they would be able to fly on any EC route under the above package (Schipper et al., 2002). The final accord of 1992 established a beachhead in the gradual deregulation of the airline industry. Conducting reform in gradual packages was Europe’s attempt to avert the “big bang” of US reform (Button and Johnson, 1998). Our dynamic industry model attempts to explain how European airline firms would have operated from 1979 to 1990 had they transitioned to deregulation in 1979, as did the US airlines.1

3 THE DYNAMIC INDUSTRY MODEL Our dynamic model analyzes the long-run strategies of the firms and simulates the optimal profit-maximizing levels of the operational variables for different scenarios. We assume that the airline chooses the level of employment (L), network size (N ) and capital (K) to maximize the flow of expected profits Max Et

T �

−t t Lt Nt Kt

t=

subject to a per-period asset accumulation constraint At+1 = t At + Pt Qt − wt Lt − rt It where Qt = FKt Lt Nt The output price is set by the inverse demand equation that is specified below. At are the firm’s real assets in the beginning of period t, is the discount factor, t = 1 + rt where rt is the real interest rate, Pt is the price of output, and It is the level of investment. Other inputs such as materials are assumed to be state variables in our simulations and

1

For an extensive study of airline deregulation in Europe, see Button (1990, 2003).


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are thus not directly introduced through the production function. We assume that T is finite and Qt = 0 when the firm exits the industry. Capital accumulation is written in terms of a perpetual inventory model: Kt = It + at where the law of motion for at is at = 1 − at−1 + Kt−1 Here measures the rate of depreciation of past levels of capital stock to its current level, while is the constant capital depreciation rate. Temporal nonseparability in the dynamic optimization problem comes in through the distributed lag of current and past investment decisions. The dynamic programming problem is characterized by the value function at time t: Vt At at Pt wt rt = MaxLNK t Lt Nt Kt + Et Vt+1 At+1 at+1 Pt+1 The use of standard solution techniques for maximizing the value function with respect to the control variables labor (L), network size (N ), and fleet size (K) provides us with a set of three highly nonlinear equations – Euler equations. The first-order conditions expressed in the Euler equations are L t − t Et L t + 1 wt + Lt wL t − Pt QL t − Qt PQ t QL t/ wt+1 + Lt+1 wL t + 1 − Pt+1 QL t + 1 − Qt+1 PQ t + 1 QL t + 1 = 0

(1)

N t + L t Pt QN + Qt PQ t QL t/wt + Lt wL t − Pt QL t − Qt PQ t QL t = 0

(2)

k t − L trt + Kt rK t − Pt QK t − Qt PQ t QK t/wt + Lt wL t − Pt QL t − Qt PQ t QL t + Et K t + 1 + 1 − + × Et rt+1 + Kt+1 rK t + 1 − Pt+1 QK t + 1 − Qt+1 PQ t + 1 QK t + 1/ wt+1 + Lt+1 wL t + 1 − Pt+1 QL t + 1 − Qt+1 PQ t + 1 QL t + 1 × Et L t + 1 − Et K t + 1 = 0

(3)

The production function is specified as a Cobb–Douglas stochastic frontier (Cornwell et al., 1990) of the form: ln Qkt = ln Xkt + ln Zk + ln Wkt K + kt K = 0 + ukt


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where the subscripts k = 1 N and t = 1 T refer to firm and time, respectively. Xkt is a vector of inputs, Wkt is a vector of other firm characteristics, and Zk is a vector of explanatory variables, which have different effects for different firms. The unobservable effects, k , can be correlated with other explanatory variables and can interact with selected slope and intercept terms. This allows for the endogeneity of variables such as load factor and network size with respect to the firm specific statistical error. The disturbance term ukt is assumed to be an independent and identically distributed (i.i.d.) zero mean random vector with covariance matrix u . The disturbances kt are taken to be i.i.d. with zero mean, constant variance 2 , and uncorrelated with both the regressors and ukt . Total revenues can then be calculated at time t by specifying the factor market demand equation while total profits at time t can be obtained by specifying a total cost function. To close our dynamic model, we must specify the demand and cost equations. We use the approach adopted by Captain and Sickles (1997). For an alternative dynamic two-stage game for the European industry, see Roeller and Sickles (2000). First, consider the cost function. Suppose an industry in which N firms produce a differentiated output, q, using n inputs, x = x1 xn . The market demand function facing firm k at time t is of the form2 : qkt = qk pt pmt Yt edt where pmt is an index of all the other firms’ prices, Yt are the other variables (measured on the country level) shifting demand, are unknown parameters of the demand function and edt are the disturbances. Perceived marginal revenue is PMR = pt + D1 qkt The cost function facing firm k is Ckt = Ck qkt Wlt Zt ect where Wlt is the vector of factor prices paid by firm k at time t Zt are the other industry variables shifting cost, are unknown parameters of the cost function, and where D1 = pkt /qkt . Marginal cost is written as: MC = C1 qkt Wt Zt The firm chooses optimal output where MC is equal to perceived marginal revenue in an oligopolistic industry (PMR = p in a perfectly competitive setting). Thus, the quantity-setting condition is C1 qkt Wt Zt = pt + D1 pkt pmt Yt edt qit The parameter is an index of the competitive nature of the firm. If = 0, price equals marginal cost and the industry is perfectly competitive, while = 1 is consistent with 2

For different forms of this model, see Bresnahan (1989).


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Nash behavior. In a price-setting game, the first-order conditions for profit maximization imply q qkt pt + qkt − Ckt kt = 0 qkt pkt pkt Summing over the N firms, we have Qt = k qkt and thus � Ckt qkt Qt p + Qt − =0 q p pt t k kt kt Q pt = Ckt − t Qt qkt pt The market demand function is specified as semilogarithmic, ln q = d0 + d1 P + d2 Pindex + d3 GDP + D4 GASP + d5 GCONS + d6 PRAIL + ed where q is the output of firm k P is the price of firm k Pindex is an index of the other N − 1 firms’ prices, GDP is Gross Domestic Product, GASP is the retail price of gasoline (inclusive of taxes) and PRAIL is the price of rail travel. The behavioral equation which identifies the degree of competition is P = MC − /D1 + eB . The costs are specified using the translog cost function: ln Cp q = ln a0 +

� i

ai lnpi +

1 �� b lnpi lnpj + bq lnq 2 i j ij

1� 1 + bqq lnq2 + b lnqlnpi + + ec 2 2 i qi Here, the inputs are capital (K), labor (L), and materials (M). The prices of the inputs are PK PL , and PM , respectively. The term contains heterogeneity controls for service and capital characteristics, which are added linearly and include the (natural logarithm) ln(average stage length), ln(network size), ln(load factor), percentage of planes that are wide-bodied, and percentage of planes that are turbo prop. Applying Shephard’s Lemma, the factor share equations are linear functions in the parameters. Since the sum of the cost shares over all equations always equals 1, and only two of the three share equations are linearly independent, for each observation the sum of the disturbances across equations must always equal zero. Linear homogeneity and symmetry are imposed parametrically. The system of five equations – translog cost, labor share, capital share, demand and behavior – are estimated by iterative nonlinear three-stage least squares, treating output price and quantity (p q), cost (C), labor share, capital share, and the price of labor (pL )


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as endogenous and all others as exogenous (the standard panel data firm fixed effects has been specified in the cost equation). Endogeneity of the labor’s price is due to the strong national carrier status of the European carriers over the sample period and the use of the national carriers to pursue macroeconomic employment stabilization policies. Based on the parameter estimates obtained from these production, cost, and demand equations, the Euler equations were simulated with the Gauss–Newton algorithm in the SAS system, for optimal levels of labor, network, and fleet. Data sources are discussed in the next section.

4 DATA This study uses a panel of seven European carriers with their ticket codes: Air France (AF), Alitalia (AZ), British Airways (BA), Iberia (IB), Royal Dutch Airline, KLM (KL), Lufthansa (LH), Scandinavian Airlines System, SAS (SK), and Sabena (SN), with annual data from 1976 to 1990. The series follows these carriers during the period just following the deregulation of airlines in the US and prior to the beginning of deregulation in Europe. Network alliances in Europe were just beginning to take shape in 1989 and 1990 (e.g., the Northwest Airlines KLM alliance). These alliances have become a standard in the international airline industry (see Table 1). Our measures for system size based solely on the carrier’s physical network begins to lose validity as the alliance provides benefits of network size (passenger feed) without the accounting for the resources necessary to produce it.

Table 1 Airline Alliances in 2006 oneworld

SkyTeam

Star Alliance

Aer Lingus American Airlines British Airways Cathay Pacific Finnair Iberia LAN Chile Qantas

AeroFlot AeroMexico Air France KLM Alitalia Continental CSA Czech Airlines Delta Korean Air Northwest Airlines

Air Canada Air New Zealand Asiana Austrian bmi British Midland LOT Polish Airlines Lufthansa SAS Scandanavian Airlines Singapore Airlines South African Airlines Spanair SWISS TAPPortugal Thai US Airways United

Source: oneworld, Sky Team, Star Alliance websites May 31, 2006

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The primary source for the input, output, expense, and revenue data was the Digest of Statistics from the International Civil Aviation Organization (ICAO). This was aug mented using output characteristic data from IATA World Air Transport Statistics, asset valuation data from the Avmark Newsletter, purchasing power parity information from the Penn World Table, and demand data from the Organization for Economic Cooperation and Development (OECD) publication Historical Statistics. The data is sketched in this section with readers interested in reconstructing or extending this series directed to Good et al. (1993a). The data can be organized into three broad cate gories: inputs and expenses, outputs and their characteristics, and demand side market conditions.

4.1 Input and Expense Data The primary source for the input data was the Digest of Statistics from the ICAO. It is important to note that ICAO data is voluntarily reported rather than being an artifact of international regulatory requirement. When carriers decline to submit their information, we obtained data from alternative sources, often carrier annual reports. The model assumes airline production is a function of three inputs: labor, materials, and aircraft fleet. The labor input is an aggregate of five separate categories of employment used in the production of air travel. Included in these categories are all cockpit crew, flight attendants, mechanics, sales and promotional personnel, and other employees including general administration and aircraft and passenger handlers. Expenses for these categories included fringe benefits in addition to salaries. Quantity and implicit price indices, L and PL, were constructed based on these five subcomponents using a Divisia multilateral index number procedure (Caves et al., 1982). So that our simulations are more interpretable as number of employees, these indices have been rescaled so that the average quantity index is equal to the average number of employees. We are primarily interested in the portion of capital that comprises the carrier’s fleet. Ground-based capital is incorporated into the aggregate materials indices described later. The number of aircraft by type is obtained from the Digest of Statistics for the beginning and end of year. Our quantity measure is the average of these two values. An effective rental price for this fleet is constructed by valuing each type of aircraft at its used equipment price (the average for each year of the Avmark Newsletter), and using the Jorgenson–Hall user price formula, the carrier’s home country’s short-term commercial paper interest rate, and a declining balance depreciation schedule with a remaining asset life of 20 years. In addition, two characteristics that summarize the potential productivity of the fleet are provided: the per cent of the fleet, which is wide bodied, and the per cent using turboprop propulsion. The proportion of fleet that is wide-bodied, PWIDEB, provides a crude measure of average equipment size. We define wide-bodied aircraft as those having two aisles. It is generally accepted that there are economies of equipment size as resources for flight crews, passenger and aircraft handlers, landing slots, and so on do not increase proportionately. The per cent turboprops, PTURBO, provides another measure of the mix of capital available to the carrier. Together, our three capital variables describe both the quantity of capital and the kinds of missions they are suited to serve: turboprop aircraft are ideal for low-density short haul routes, wide-bodied aircraft ideal for high-density long haul routes, and narrow-body jets are ideal for medium-haul


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routes. We should note that by the beginning of our time frame, long-haul narrow-bodied jets (1950s vintage aircraft like the Boeing 707, Douglas DC-8, SUD Caravelle and de Havilland Comets) were in the process of being phased out, and regional jets had not yet been widely adopted (the smallest jets in our sample being the BAC-111 and Fokker F28). The purchase of equipment over the study period was dominated by strong brand loyalty: SAS, Iberia, and Alitalia continued to purchase mostly Douglas aircraft while Air France, British Air, KLM, and Lufthansa continued to purchase predominately equipment from Boeing. It is important to note that Airbus was essentially a one aircraft type manufacturer (the A300) over the bulk of our study period. The A310 introduced in 1985 was essentially a modified version of the same plane. In that regard, Airbus was much more like Lockheed than it was like Douglas or Boeing. It was not until the mid-1990s with the introduction of the A320, A330, and A340 families of equipment that they spanned the range of small narrow bodied to large wide-bodied equipment and became the across the board competitors that they now are. Even given this severe limitation, they made significant inroads in European fleets. When one considers all acquisitions (purchases or leases) compared to retirements (sales, retirement, or returns to the leasing company), Airbus was able to add 127 aircraft to the fleets of these eight carriers (155–28). At the same time, Boeing was able to add net 206 aircraft (547–341). Douglas added only 6 aircraft (269–263), while there was a loss of 27 from all other manufacturers (185–212). The materials component is summarized as price and quantity indices that aggre gate several subcomponents. The source for expense information is ICAO’s Digest of Statistics, Financial Data. This is supplemented with either physical quantity or price information from another source to identify price quantity pairs for each material’s sub component at each year for each carrier. The largest component of materials is aviation fuel with price information provided by ICAO’s Regional Differences in Fares and Costs Report, under the presumption that a carrier will purchase fuel at many differ ent countries in the European region. Expenses for landing fees and en route traffic control facilities are paired with aircraft departures from ICAO’s Commercial Airline Traffic Series. The resulting prices can be considered rental expenses for this publicly owned capital. Expenses for carrier owned ground-based capital services are based on a Jorgensen–Hall user price using depreciated book value, for nonflight capital from ICAO’s Digest of Statistics, Financial Data, a seven per cent annual depreciation rate, and the individual carrier’s interest rate on long-term debt. The remaining materials and services including passenger food, maintenance materials, and outside services including commissions and other services are pooled into a residual materials category using the carrier’s home country purchasing power parity (Summers and Heston, 1991) from the Penn World Table Mark 5.2 as a price deflator. The price index for materials, PM, is normalized to one for the sample average and consequently the implicit quantity index, M, is normalized for average materials expenditures.

4.2 Output, Revenue, and Output Characteristics The airline services actually sold (revenue output) are based on three subcomponents: scheduled passenger and excess baggage, scheduled freight and mail, and nonscheduled


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services. Sources for revenue and physical output are based on ICAO’s Digest of Statistics, Financial Data and Commercial Airline Traffic Series. Unfortunately, data availability leaves us with aggregate revenues for small amounts of cargo services (e.g., excess baggage or charter cargo) with passenger traffic for some carriers. This aggre gation is carried out under the widely used convention that one revenue passenger kilometer is equivalent to 0.090 t km (or one passenger and standard baggage averages approximately 200 lbs). This has the effect of combining the three subcomponents into the same physical units, which are then aggregated using a multilateral index process normalized to an average price of 1 across the sample. Three characteristics of output are also used in our analysis. The load factor, LOADF, is the ratio of passenger output sold to total passenger output produced. In the American context, low load factors are a traditional indication the level of service is too high. Since the structure of European competition is more collusive, one might expect that load factors might be higher than optimal and that the price is too high and level of service is too low. As Figure 1 points out, trends for load factor among European carriers closely follow that for their American counter parts. Among US carriers, load factor increased from approximately 52 per cent in the beginning of our study period to roughly 67 per cent in 1990. This is as one would expect given that the European system had no competition on inter-European routes with revenue sharing, resulting in, few flights, high fares, and relatively full planes. Stage length, STAGEL, is the ratio of aircraft miles flown to aircraft departures. Typically, longer routes require fewer resources per amount of output produced. Finally, a measure of overall network size, NETSIZE, is the number of route kilometers and is provided by the International Air Transport Association (IATA) World Air Transport Statistics. NETSIZE is the only systematic measure across carriers and over time that

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we access from publicly available data sources. The measure is the sum of the distances for all unique routes in the carriers network. When used in an estimated equation that incorporates both lnQ and lnNETSIZE, it has the implicit effect of including network density in the model.

4.3 Demand Data Data important for describing the demand for travel was collected for the home countries of each of our carriers. A weighted sum of the three Scandinavian countries, Denmark, Sweden, and Norway, was used to represent the home country of SAS with GDP used to form the weights. The Gross Domestic Product, GDP, was obtained from the Main Economic Indi cators publication of the Economics and Statistics Department of the Organization for Economic Co-Operation and Development (OECD) and provides an overall scale for economic activity in the demand equation. They were reported for the above countries in billions of dollars. The OECD Economic Outlook publication Histori cal Statistics was the source of the growth in private consumption expenditure data. They are reported as an implicit price index with year-to-year percentage changes. The annual short-term interest rates, INTRATES, were also obtained from this publi cation. The rates are reported by the respective countries on the basis of the follow ing financial instruments: Belgium (3-month Treasury certificates), Denmark (3-month interbank rate), France (3-month Pibor), Germany (3-month Fibor), Italy (interbank sight deposits), Netherlands (3-month Aibor), Norway (3-month Nibor), Spain (3-month interbank loans), Sweden (3-month Treasury discount notes), and the UK (3-month interbank loans). The European airline industry differs from the US industry in that the continent’s small size makes autos and rail a feasible alternative to air travel (Captain and Sickles, 1997).3 Jane’s World Railways was the source of the rail data. The rail price, PRAIL, was cal culated as the ratio of passenger (and baggage) revenue to passenger tonne-kilometers. The retail gasoline price (prices plus taxes), PGASP, was obtained from the International Energy Agency’s publication, Energy Prices and Taxes. Finally, to capture the effects of competition from other airlines, an index of the “other” airlines’ prices was com puted by weighting the individual prices their respective revenue shares in the market, PINDEX. Summary statistics for different carriers/countries are provided in Table 2.

5 SIMULATION RESULTS The results of the dynamic simulation are presented in graphical form in Figures 2a–c. The simulations were run with two values for (constant capital depreciation rate), 0.12 and 0.08, (discount factor) of 0.95, and (rate of depreciation of past levels of capital stock to its current level) of 0.08 to solve for optimal levels of operational 3 For a discussion of the history of US airline competition and the industry’s response to deregulation see Morrison and Winston (1990) and Borenstein (1992).

Table 2 Carrier Specific Sample Mean Values for Model Variables Air France AF Inputs: L PL (000) M (000000) PM K PWIDEB PTURBO Outputs: Q (000000) P LOADF NETSIZE (000) Demand: PRAIL PINDEX GASP GDP INTRATES

34877000 21266

Alitalia AZ 18974000 29480

British Air BA

Iberia IB

KLM KL

Lufthansa LH

SAS SK

Sabena SN

45725000 17160

25127000 19666

20238000 27266

34013000 26253

17761000 31953

8971000 23253

19012 09718

7606 08738

26317 09419

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11005 09930

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8066 11821

5868 09388

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76667 02612 00275

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52800 04628 00381

109533 03206 00155

91467 01418 00365

27200 02771 00217

256766 10992 06586 748210

126944 11777 06143 332511

356325 11037 06641 621877

143613 10693 06351 350562

181102 09152 06444 370913

253433 12503 06185 509879

109533 14942 06390 225556

74675 10982 06302 215300

00474 11645 06901 653549 01044

00367 11517 07995 495572 01459

00742 11696 05575 527681 01155

00254 11621 06067 224405 01348

00461 11789 06459 162287 00744

00517 11322 05474 819314 00624

00689 11169 06558 259728 00972

00369 10192 06292 108503 01035


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variables during the time period 1979–1990.4 The chosen parameters were consistent with industry estimates. Solid lines indicate sample observations, small dashed lines indicate simulations for = 0.12, and large dashed lines for = 0.08. The simulation exposes Sabena, Alitalia, and Iberia as the carriers least primed for a deregulated airline market. Both Iberia and Alitalia have recently flirted with bankruptcy. Moreover, Iberia has also had a recent spate of what would appear to be predatory pricing, pushing partners like Viasa into bankruptcy. Sabena sold a large minority position to Air France in 1993. But shortly thereafter Air France, itself struggling mightily, divested its interest, and Swiss Air bought a 49 per cent interest in Sabena in 1995. Swissair liquidated in 2001 partially because it was unable to halt Sabena’s trail of red ink.5 Iberia struggled with poor management and financial performance until it privatized by selling 49 per cent, including a 9 per cent stake to British Airways in 1999. Alitalia foundered in the twenty-first century, undergoing major restructuring despite compacting with Air France–KLM (itself an agreed-upon acquisition by Air France, creating the world’s largest airline by revenues). It remains to be seen if Alitalia can return to profitability; more broadly, if smaller, state-owned carriers can survive in a unified European market. To analyze the results of the simulation in-depth, the airline market in Europe should be divided according to scale of operation. Air France, British Airways, and Lufthansa were larger with similar scales of operation, while Alitalia, Iberia, Sabena, and SAS were smaller. The airlines with levels closest to the simulation results were best prepared for the competitive milieu ahead. The main stylized fact from the simulation was that the larger carriers were better prepared for deregulation than the smaller ones. All airlines, excepting Lufthansa, employed too few workers. At first blush, grow ing the workforce hardly seems the way to maximize profits. A possible justification relates to powerful labor unions negotiating wages above competitive levels reducing employment below optimal levels (Captain and Sickles, 1997; Good et al., 1993b). The McGowan and Seabright (1989) study evinced this phenomenon, finding labor costs for many European carriers to have been more than double the US rates.6 The simulation solution for fleet size suggested Air France, British Airways, Lufthansa, and SAS possessed a sizeable fleet relative to the optimal solutions, at times even exceeding the values. Conversely, Iberia and Sabena purchased few or no planes during the period studied, but should have purchased more. As for network size, Lufthansa operated at levels close to optimal. However, for all other airlines, networks were suboptimal because they were too small over much of the sample period. Increasing the size of the network, ceteris paribus, lowers the total

4

A note about the solutions: the solutions predict optimal levels of the operational variables with the assumptions that planes, people, and networks can be increased and decreased without costs. 5 See http://www.sabena.com/EN/Historique_FR.htm 6 As pointed out by a referee, staffing of flight personnel is based on regulatory requirements for particular aircraft types. To address this further institutional fact, we could have allowed labor also to be quasi-fixed but this would add substantial complexity to an already complex modeling scenario. Our labor input is an aggregate of five separate categories of employment used in the production of air travel. Our finding that there is generally understaffing is consistent with the need for European carriers to expand their operations and thus their labor requirements in general. Our model is not detailed enough to point to specific classes of labor that should expand nor is it detailed enough to allow differentiation of demand for own and outsourced labor and/or endogenous wage outcomes of union/firm negotiations.


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cost of the airline. This is the sine qua non of operating a viable airline, for the following reasons: Hub-and-spoke operations allow airlines to concentrate traffic on certain routes, allowing both larger, more efficient planes and more frequent service. In addition, hub-and-spoke operation allows for a greater range of destinations and city-pair combinations to be served, including city-pair combinations, which would not normally generate enough traffic to justify a regular service. The addition of a new spoke to a hub-and-spoke network signif icantly increases the city-pair combinations served by the network, at minimal additional cost (OECD, 2000).

Achieving scale economies has to be through alliances because outright acquisition is largely proscribed by further restrictions on foreign ownership (Staniland, 1996). Integrating networks through alliances offers efficiency gains from passenger pooling agreements and fungible airport gate and slot rights. Large networks also exploit cost advantages, as airlines discard linear route systems in favor of the hub and spoke network configuration. This adjustment derives economies of density, and higher load factors on spoke routes radiating from the hub (OECD, 1988). Without alliances, deregulation in Europe has the effect of reducing load factors drastically, as it did in the US failing an acquisition or alliance, and deregulated markets can sink an airline, for example, Pan-Am (Brueckner, 2003; Brueckner and Whalen, 2000; Levine, 1987).78 As an example of Europe’s first intercontinental alliance, in December 1986, British Airways, with its equity wiped out by a debt burden reaching over £1 billion at one time, was sold to the private sector, thus joining Swissair as the only privately owned airlines at the time. To stave off its declining profitability, BA signed an alliance with United Airlines. The agreement integrated United’s flight schedules and networks in America with BA’s transatlantic services to American cities. The agreement enabled the airlines to share passengers and increased the quality of service for time conscious (and high margin) business travelers. As noted in the simulation, 1988 was a watershed year for British Airways, as privatization quickly resuscitated the airline. Other airlines followed suit and formed alliances to brace themselves for the onset of competition, learning from the experience of American deregulation. Despite deregulating, barriers remain in the aviation sector. The march towards com plete deregulation in both the US and Europe is hindered by three factors: (1) limitations to existing “open sky” agreements, (2) ownership restrictions, and (3) and barriers to entry. While “open skies” means increased international competition, domestic markets

7 For further research on US Domestic codesharing that closely parallels the experiences of intra-European codesharing, see Ito and Lee (2005) and Bamberger et al. (2004). 8 Substantial variation in the dynamic simulations occurs because the Euler equations are highly nonlinear. We didn’t feel “adjustment factors,” such as those commonly used in dynamic nonlinear forecasts from large macro models (e.g., the WEFA Quarterly Forecasts), were appropriate since they are difficult to justify on any other than ad hoc grounds. That said our results make economic sense because they point out that most European airlines suffered in their ability to maximize the present value of discounted profits because their networks and operational capacity were too limited during the period we studied. European airline networks (excluding those for carriers that exited the industry) expanded substantially after accelerating industry reforms that began around 1990. Lost profits for many of the European airlines in our sample appeared to be most pronounced during the early and middle part of our sample period and by in large were trending toward equilibrium at the end of the 1990s.

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remain off-limits to foreign carriers. In other words, British Airways cannot fly from New York to Los Angeles, even as a continuing flight from London (Staniland, 1996). US law dictates that foreign citizens may not own more than 25 per cent of voting stock, and Europe permits no more than 49 per cent foreign ownership (Economist, 2005). Lastly, landing rights and gates at airports often are not traded freely, preventing access for new entrants (Captain, 1993). Further liberalization in these areas is needed to attain more perfect competition (Postert and Sickles, 1998). The expressed concern during the early liberalization talks was that the rush to acquire and ally could lead to the development of mega-carriers that would dominate the market – a reversion to oligopoly, without the stability needed from a vital transportation service. Nearly 10 years removed from 1997, the three factors – “open skies” or lack thereof, ownership restrictions, and barriers to entry – still impede full deregulation. Taken together with firm anti-trust laws in Europe, a reversion to oligopoly is an improbable outcome.

6 CONCLUSIONS, LIMITATIONS AND FUTURE RESEARCH This chapter has focused on an integrated dynamic model of the European airline industry. We use the dynamic structural model to examine the extent to which the European industry allocated its factor inputs during the period 1979–1990, beginning with US airline deregulation and ending with the period of transition to deregulation of carriers in the European Union in keeping with a goal of long-run profitability. We have allowed for a fairly rich menu of strategic decision-making among the carriers and for relatively general production and cost structures. Our findings point to several sources of forgone profits, in particular, the need for European carriers to adopt policies for expansion of their networks. This would allow them to take advantage of returns to density by expanding and reconfiguring their networks and were realized in the years subsequent to our after the sample period, in part by forming the alliances summarized in Table 1. Interestingly, just these sorts of changes characterized the competitive policies undertaken by European carriers in their code-sharing agreements and in their oftenbitter union confrontations as the carriers transitioned from national flag carriers to competitive international companies. This chapter presented a methodology and modeling approach that can be used in other settings to better understand the potential impacts of regulatory changes in an industry. As with any such new approach to study such an issue, our model does have limitations. For example, the use of relatively simple functional forms such as the Cobb–Douglas imposes a degree of substitutability that might exaggerate the swings in our dynamic and may be a reason for such temporal patterns in our simulations. Another limitation is that we applied this model in the European context where there are data limitations and inconsistencies in reporting protocols across time. These are more severe than with US data from the Department of Transportation. Future work could focus on utilizing our methodology and modeling approach for US, Canadian or Australian carriers where prior regulation made for more extensive and consistent data. To that end, one might be


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able to use better measures of network size, such as cities served, or measures of network structure. Our methodology also places an increasing burden of complexity for adding more details – adding more control variables implies adding more Euler equations.

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Hotz, J.V., F. E. Kydland, and G. L. Sedlacek (1988). “Intertemporal preferences and labor supply,” Econometrica, 56, 335–360. International Air Transport Association (various years). World Air Transport Statistics Montreal: IATA. International Civil Aviation Organization (various years). Digest of Statistics, Montreal: ICAO Ito, H., and D. Lee (2005). “The impact of domestic codesharing on market airfares: Evidence from the U.S.,” in Advances in Airline Economics, Volume 1, Competition Policy and Antitrust, edited by Darin Lee, Amsterdam: Elsevier. Jovanovic, B. (1982). “Selection and the evolution of industry,” Econometrica, 50(3), 649–70. Levine, M. E. (1987). “Airline competition in deregulated markets: Theory, firm strategy, and public policy,” Yale Journal on Regulation, 4, 434–36. McGowan, F. and P. Seabright (1989). “Deregulating European airlines,” Economic Policy, 9, 284–343. Morrison, S. and C. Winston (1990) “The dynamics of airline pricing and competition,” American Economic Review Papers and Proceedings, 80, 389–393. OECD (1988). Deregulation and Airline Competition, Paris: OECD. OECD (2000). “Airline mergers and alliances,” OECD Journal of Competition Law and Policy, 2(2), 122–220. Pakes, A. and R. Ericson (1998). “Empirical implications of alternative models of firm dynamics,” Journal of Economic Theory, 79, 1–46. Postert, A. and R.C. Sickles (1998). “Air liberalization: the record in Europe,” in Taking Stock of Air Liberalization, edited by M. Gaudry and R. Mayes, Boston: Kluwer Academic, 39–59. Roeller, L-H., and R. C. Sickles (2000). “Capacity and product market competition: Measuring market power in a ‘puppy-dog’ industry,” International Journal of Industrial Organization, 18, 845–865. Sampson, A. (1984). Empires of the Sky (The Politics, Contests and Cartels of World Airlines). London: Hodder and Stoughton. Schipper, Y., P. Rietveld, and P. Nijkamp. (2002) “European airline reform,” Journal of Transport Economics and Policy, 36, 189–209. Sickles, R. C. and Williams, J. (2006) “A intertemporal model of rational criminal choice, panel data econometrics: Theoretical contributions and Empirical Applications,” edited by Badi Baltagi, Elsevier Science, Amsterdam, 135–166. Sickles, R. C. and A. Yazbeck (1998) “On the dynamics of demand for leisure and production of health: Evidence from the retirement history survey,” Journal of Business and Economic Statistics, 16, 187–197. Staniland, M. (1996) “Open skies – fewer planes?: Public policy and corporate strategy in EU–US Aviation Relations, European Policy Papers #3, European Union Center, University Center for International Studies, University of Pittsburgh. Summers, R. and A. Heston (1991). “The Penn World Table (Mark 5): An expanded set of international comparisons, 1950–1988,” Quarterly Journal of Economics, 106(2), 327–368. Taneja, N. (1988). The International Airline Industry: Trends, Issues and Challenges. Lexington, MA: Lexington Books. Williams, G. (1994). The Airline Industry and the Impact of Deregulation, 2nd Edition, Avebury Aviation Ashgate Publishing Limited, UK: Aldershot.


6 State Aid to European Airlines

A critical Analysis of the Framework and its Application∗

Pietro Crocioni† and Chris Newton‡

ABSTRACT This chapter provides a critical assessment of European state aid policy as applied to the airline sector. Within the policy framework, competitive distortions and negative spillovers between Member States are typically presumed to result from the granting of aid rather than being the subject of analysis. Whilst such an approach might be justified where the central concern of state aid policy is to prevent national governments from favoring their own flag carrier airlines, it is less likely to be appropriate in relation to the types of state aid case that have begun to emerge in the sector in recent years. The application of state aid rules in the Charleroi decision illustrates the potential weaknesses in the current approach.

1 INTRODUCTION European airline markets were gradually opened up to competition during the 1990s by allowing entry and competition on intra-European Union (EU) and domestic routes. Competition on many routes has increased and liberalization would appear to have had generally beneficial effects on fares, service quality, and choice. Market entry, especially from low cost airlines, has also resulted in new services being created and increased use of secondary or regional airports. With liberalization, competition (antitrust under the US terminology) law has been increasingly applied to the airline sector. Whilst the mainstay of antitrust analysis is the ∗

We wish to thank Darin Lee and Claudio Piga for useful comments. However, the content of this article reflects only the opinion of the authors, who are solely responsible for any remaining errors. † Senior Economist, Chief Economist Team, Office of Communications (Ofcom), UK; e-mail: [email protected]. ‡ Director, Frontier Economics, UK; e-mail: [email protected].

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competitive distortions that can arise from mergers or the conduct of firms with market power, the granting of subsidies by national Governments to specific firms can also raise significant concerns. In the light of this, the European Commission is given the responsibility to control subsidies (termed state aids) granted by EU Member States and ensure that such subsidies do not serve to distort competition. Such subsidies have been a particular concern in the airline industry given the prominent position of flag carriers and the potential incentive on the part of Member States to promote the interest of their own flag carrier. This contribution provides a critical assessment of the state aid framework in the Treaties of the European Communities and the European Commission’s state aid policy in the airline sector, examining the rationale for supranational control of state aid and identifying a number of possible concerns with the existing approach. In particular, we argue that, whilst a primary justification for supranational control is the potential for state aid to generate negative externalities or distort competition across Member States, under the current approach little emphasis is placed on identifying whether an aid is in fact likely to distort competition or generate such negative externalities. In order to highlight these issues and concerns, we provide an overview of state aid decisions by the European Commission in the airline sector. We consider the state aid cases to failing airlines in the 1990s and also focus on the more recent Charleroi decision and briefly examine its implications. This decision is of particular interest because it concerned an alleged subsidy to an entrant airline rather than a state-owned incumbent.

2 AIR TRANSPORT SECTOR AND STATE AID IN EUROPE Until the mid 1980s, air transport was effectively exempt from the application of EU competition law including the state aid rules (Adkins, 1994; Starkie, 2002). Following three packages of measures implemented in 1988, 1990, and 1993, the EU airline industry gradually moved away from the system of bilateral agreements that still regulates most international airline markets. It is only as this process of deregulation progressed that the European Commission (henceforth Commission) started to apply competition policy and the state aid rules to the sector. Prior to deregulation, international routes within the EU were served by one carrier designated by each of the two Member States at each end of the route. This meant that each route was served by a maximum of two flag carriers with airfares being regulated by bilateral agreements. Domestic routes were also often the sole preserve of the flag carrier. This is in stark contrast with the current situation where fares, capacity, route access, designation, and licensing of airlines are all, to a great extent, deregulated – with full deregulation having come into force in 1997. In response to deregulation, flag carriers reorganized themselves into hub-and-spoke networks. At the same time, new point-to-point low cost carriers emerged whose oper ations were based on the business model used by Southwest Airlines in the US. These carriers achieved cost savings by simplifying their organizations and logistics, using secondary airports (with lower taxes and landing and handling fees), cutting out travel agent commissions by, for example, distributing via the Internet and avoiding some of the “legacy costs” (e.g., high manpower costs) faced by flag carriers.

STATE AID TO EUROPEAN AIRLINES

149

Low cost carriers first emerged in the early 1990s in the UK and Ireland with carriers like Ryanair (set up in 1985 but relaunched in 1991), Easyjet (founded in 1995), Go and Buzz. These initially established themselves at secondary UK and Irish airports before expanding, together with other carriers, into airports in continental Europe in recent years. The impact of new entry and increased competition has been particularly evident in the UK where the market has expanded significantly (Gil-Molto and Piga, 2005). Figure 1 shows how UK all passenger growth has been higher in the 1990s than previously (the fall in 1991 was due to the first Gulf War and that in 2001–2002 to the 9/11 terrorist attacks). In particular, while between 1982 and 1990 air passengers have increased on average by just less that 5.5 million a year, and this grew to 9.2 million a year between 1991 and 2000. State aid to European carriers reached its highest point in the mid-1990s and has remained relatively low since. Figure 2 shows that total state aid across all sectors has been declining over the 1990s and has followed a trend different to that followed by the levels of aid to the airline sector. The increase in state aid to airlines in 1994–1997 was largely due to the combined effects of a drop in air traffic following the first Gulf War and the restructuring process that most flag carriers went through in response to or ahead of deregulation. The high levels of state aid that were seen in the mid-1990s were, however, unlikely to have led to significant distortions to competition (although they may have impacted on economic efficiency) since, at this time, the recipient flag carriers faced no or only limited competition and entry was in most cases not allowed in the routes where they operated. The growing number of carriers active in each route and the more intense competition that has emerged in recent years mean that the provision of state aid (granted to either flag carriers or new entrants) now has substantially greater potential to distort competition – even if the actual level of aid granted is lower.

200 180 160

(Million)

140 120 100 80 60 40 20 54 56 19 58 19 60 19 62 19 64 19 66 19 68 19 70 19 72 19 74 19 76 19 78 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02 19

19

19

52

0

Source: Department for Transport.

Domestic passengers are counted both at airport of departure and arrival.

Figure 1 Terminal Passengers UK Airports (All flights).


150

Air Transport

Total

3,000

80,000 70,000

Total Aid

2,500

60,000 2,000 50,000 1,500

40,000 30,000

1,000

Aid to Air Transport 20,000

500 10,000 0

0 1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

Source: European Commission, DG Competition.

Figure 2 State Aid in the European Union (million E).

3 STATE AID POLICY IN THE EUROPEAN UNION 3.1 The Framework The original Treaty of the European Communities contains among its competition law provisions not only general antitrust rules but also a set of rules specifically aimed at limiting the amount of subsidies and assistance granted by Member States to their national firms. These provisions arose from fears that the European Community could witness subsidy competition between Member States reminiscent of the beggar-thy neighbor industrial policies that afflicted Europe in the 1930s. The Commission was therefore assigned a supervisory role over the decisions by Member States to grant state aids. Article 87(1) of the Treaty provides a general prohibition on state aid. This apparently very strict policy does, however, in practice allow state assistance to be provided to firms. Firstly, a measure is only defined as state aid if it satisfies a number of criteria. It must confer a benefit or an advantage to one or more firms – i.e., be selective1 – and be granted by a state or through state resources. Furthermore, only state aid that “distorts or threatens to distort competition ( ) insofar as it affects trade between Member States” is prohibited. In the practical application of the rules, where measures are found to meet the definitional criteria – i.e., are selective and granted through state resources – there is generally a presumption that they distort competition and affect trade. Secondly, under Articles 86, 87(2), and 87(3), there is scope for aid to be declared “compatible with the common market” where it is aimed at achieving a number of

1

General measures, such as general tax exemptions, are not classified as state aids.


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economic and, more often, social objectives. For example, Article 86 provides scope for exemption for firms that provide “services of general economic interest” (SGEI), and this has often been used to exempt aid to firms entrusted with public services obligations (PSO) – subject to a number of conditions being met. Articles 87(2) and (3) list further cases where aid is or could be deemed compatible. The Commission has issued a number of guidelines that set out the types of aid that in principle may be exempt from this general prohibition and the circumstances under which such exemptions are likely to apply. Guidelines cover three broad categories of state aid: horizontal (Research and Development (R&D), environmental protection, small- and medium-sized enterprises (SMEs), training, employment programs, rescue and restructuring, risk capital and undertakings operating in deprived urban areas), sectoral (steel, car, shipbuilding and synthetic fibers), and regional. The Commission generally takes a negative view of granting state aid to ailing firms, given the perverse incentives that this generates in terms of dynamic efficiency and the higher likelihood of generating competitive distortions. However, the Commission is willing to approve aid to ailing firms in certain circumstances – either for social or for economic reasons – as long as (i) distortions are limited, (ii) the aid measures form part of a coherent restructuring plan aimed at restoring firms to financial health, and (iii) the level of aid does not go beyond that needed to achieve this objective.2 In the past, concerns have arisen in relation to hidden or implicit state aid granted to state-owned firms. As a result, the “Market Economy Investor Principle” (MEIP) was introduced and originally confined to state-owned undertakings, though more recently its application has been extended beyond this. The MEIP holds that if a government were to invest on the same basis as the private sector would, under the same circumstances, this would not amount to state aid. This has often been criticized.3

3.2 The Economics of State Aid State aid can be used as an effective tool for remedying market failures and, for example, ensuring the provision of public goods or correcting externalities. For example, firms’ decisions on where to locate generate external benefits and costs which might differ across locations, but the firms’ private decision might fail to reflect these.4 However, even in those circumstances when aid appears justified on such grounds, it can nevertheless generate negative outcomes due to the potential to create significant distortions to competition. The fact that the provision of aid can have both positive and negative effects is implicitly recognized in the framework of the Treaty that involves a general prohibition on aid combined with exemptions when aid is targeted at meeting particular objectives.

2

European Commission, Community guidelines on State aid for rescuing and restructuring firms in difficulty,

OJ C 244, 01.10.2004, pp. 2–17 (Rescue & Restructuring Aid Guidelines henceforth).

3 Nicolaides and Bilal (1999) claim that it is wrong to expect that a government should obtain a financial

return similar to that of any private investor. If this was the case, there would be no reason to grant a subsidy

as private investors would supply capital. On the other hand, if the measure corrects a market failure, returns

can be expected to be lower because of the resulting welfare benefits.

4 There could be production externalities where firms fail to appropriate all the benefits of their production,

for example, with R&D. There could also be agglomeration externalities which might arise when physical

proximity increases the efficiency of all firms in a particular market.

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It should be borne in mind, however, that although the presence of market failure may be viewed as a necessary condition for justifying state aid, it is not a sufficient condition. State aid can often be a relatively indirect way of addressing market failure and, as such, may not be the most efficient way of addressing it (Nicolaides and Bilal, 1999, p. 104). Ideally, the first best policy is to address market failure directly, and only when it is not feasible to do so, state aid could be considered as the second best. First best policies are very specific and therefore generate minimal distortion. For example, there are negative externalities from congestions at major airports. Airports and airlines might not take into account the negative externalities (noise and pollution), which affect residents in surrounding areas. The Commission policy for addressing congestion concerns at main airports has among its tools the use of subsidies to attract airlines to smaller regional airports. In this case, state aid is unlikely to be a first best policy tool. The most effective way to address that is by internalizing it – i.e., through a surcharge on airport landing charges in congested airports. There are also a number of “non-economic” justifications for state aid, reflecting social or public policy concerns rather than market failures in an economic sense. For example, state aid may be used to redistribute income or for providing universal services.5 In the case of airlines, state aid could, at least in principle, be granted in order to enable services to be run on “thin” routes that would otherwise not be economic to serve. This might be justified on the grounds of market failure – i.e., the airlines could fail to internalize the benefits to the local economy – and/or social grounds – i.e., geographically marginal areas should not be left isolated.6 Despite the presence of potential justifications, state aid can harm efficiency and distort competition. State aid tends to reduce dynamic efficiency because it softens the recipient’s budget constraint as firms that could reasonably expect to receive state aid will have reduced incentives to achieve productive efficiency. It could also provide incentives for firms to invest in wasteful rent seeking rather than invest in productive activities. There are also well-known risks in terms of potential distortion of competition. One can distinguish between two main types of distortionary effects that might coexist, as recognized by Article 87 itself, which is concerned with any state aid scheme that distorts competition “insofar as it affects trade between Member States.” A state aid could first distort competition in the country where it is granted. Therefore, state aid could generate serious inefficiencies for the economy as a whole and if granted to a firm or firms with market power it might also distort competition in the market(s) in which the firm(s) operate(s). Second, when state aid granted by one government distorts competition beyond its national borders – i.e., the market is wider than national – it could generate negative spillovers affecting countries other than the one where the aid was granted. This is a critical consideration and justification for a supranational system of state aid control, as discussed in the next section. 5 However, as in the case of aid aiming at correcting market failure, state aid might not be the most efficient or optimal way even if the purpose is not an economic one. For example, in order to ensure that a service is universally available, it might be more efficient to grant a subsidy to consumers that otherwise would not be supplied and that can therefore select their provider, rather than granting aid to a specific firm. 6 This is, however, potentially prone to abuse and be used to create legal entry barriers. This was allegedly the case of the Italian government’s recent decision to impose PSO on routes between Sarninia and the mainland that some argue are commercially viable.


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3.3 The Rationale for a Supranational Control State aid might lead to two types of inefficiencies, often but not always coexisting. It might distort competition in the country of the recipient firm, and in some cases, this distortion could also extend to other countries. Both could justify the need for regulatory oversight; however, there is a significant difference between the two. In the case of a domestic-only distortion, there is an implicit assumption of regulatory failure at the national or local government level. This could arise because the government fails to internalize the distortion of competition when granting a state aid. This could happen, for example, because the government is captured by interest groups or because of political economy considerations.7 The critical question in this case is whether the national government or a supranational authority would be better placed to avoid this type of regulatory failure.8 The case for a supranational control is not clear-cut. The latter could perhaps, but not necessarily, be less influenced by interest groups but at the same time might have reduced information about the existence or extent of national or local market failure that the state aid is meant to address. Therefore, national government might still be better placed at addressing national or local externalities and at selecting the optimal tool.9 A stronger rationale for a supranational control of state aid is the presence of negative externalities which national government could fail to internalize because they negatively affect consumers in foreign countries. However, there is an even more serious concern based on a stream of economic literature known as “Strategic Trade” which claims that countries might have an interest to grant aid in order to appropriate rents that arise in imperfectly competitive markets. While this might be in the “private” interest of individual countries, it might not be in the “public” interest of the EU as this aid is expected to lower overall welfare because it imposes negative externalities on other countries.10 This literature concludes that each government has an incentive to grant subsidies to firms located in their jurisdiction when the market is imperfectly competitive potentially leading to a subsidy war/race with all countries being worse-off as a result.

7 A state aid confers a large benefit to the recipient(s) who therefore have a strong interest in the decision. However, the state aid might have to be financed by a (distortionary) tax and therefore have a negative impact on all consumers. While the benefits from the aid are concentrated, the negative impact on consumers is usually diffused. Therefore, even if overall the costs outweighed the benefits, the former might not be large for each consumer who therefore has a reduced incentive in influencing the state aid decision. 8 This question was also recently raised by the former Commission Chief Economist Röller, see Friederiszick et al. (2006). 9 Besley and Seabright (1999) argue that the ability to cast a sceptical eye on Member States’ unrealistic judgments on how to use public funds should not be lightly dismissed. Besley and Seabright (pp. 16–18), also refer to economic geography as providing further justification for national or local government granting subsidies to correct local market failures. Governments compete to attract firms because their decision might have important external effects in the country where they locate. The magnitude of these externalities depends not just on the type of activity but also on where it occurs however, unless government intervened firms would fail to internalize these effects. The basis for government intervention is based on efficiency, but it could also have an equity justification. 10 The main model on which this strand of literature is based on is Brander and Spencer (1985). See also a review and criticism by Corden (1990). The conclusions of the strategic trade literature are not strong to changes in assumptions. For example, if firms play Bertrand with differentiated products rather than Cournot, domestic welfare is increased by the government imposing an export tax rather than subsidy.

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The implication is that a strict control on state aid is desirable. The important insight is that the distortive impact of state aid can only be assumed when there is evidence pointing to the aid inflicting a strong negative externality on other countries because markets are imperfectly competitive and their geographic scope spans beyond national boundaries. The basic setting of the “Strategic Trade” literature has firms located in separate countries engaging in Cournot competition in a supranational market. Governments compete with each other, shifting rents that arise in imperfectly competitive markets. The tool used to compete is the granting of an export subsidy.11 The type of subsidy assumed has the important consequence that an action by a government is assumed to produce no net benefit in terms of productive efficiency to its domestic consumers – i.e., no increase in domestic output. However, it inflicts a negative externality on other countries and therefore has a negative impact on overall welfare. An export subsidy allows the recipient to capture a greater share of a slightly smaller total industry profit and reduces overall welfare but it also alters its distribution in favor of the recipient of the aid. Recent work (Collie, 2003) extends the conclusions of the “Strategic Trade” literature to the case of a production rather than export subsidy. This is a more benevolent measure as it also expands domestic output of the recipient firms, thus offsetting the domestic distortion from imperfect competition.

3.4 Problems with Current Framework The above discussion shows that in some circumstances national governments should be left with the freedom to grant state aid not only for social or equity but also for economic reasons. The key question for a supranational authority such as the Commission is under which circumstances it should intervene. A supranational authority could either ban state aids that generate substantial cross-border negative spillovers or only do so when such a spillover is larger than any benefits from remedying a domestic market failure.12 At present, state aid policy operates a number of presumptions in order to assess whether competition is likely to be distorted and/or a negative spillover can be expected. This, however, is an imperfect substitute for the rigor, which is required by other provision of competition law, namely those applied to firms rather than Member States. The differ ences in approach between state aid and competition law are particularly important in three areas: market definition, distortion of competition and assessment of effect on trade. In principle, in order to assess the potential distortion of competition that a state aid measure might generate, it could be sensible to adopt a similar approach to that followed in abuse of dominance or merger cases. This would require an analysis of the relevant market. State aid can distort competition in one or more markets – either final or input products markets where the recipient of the aid operates. Logically, it would appear useful to define the relevant product and geographic markets. However, for state aid,

11

An export subsidy is a direct or indirect compensation provided by government to private commercial firms to promote exports of domestic products. It makes foreign competitors react less aggressively. 12 This has led some commentators to propose a system based on a welfare assessment whereby state aid should perhaps be allowed when the effect on domestic welfare is expected to be positive and outweigh the negative spillover effect (Nicolaides and Bilal, 1999, p. 102).


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this is currently not the case, as markets are identified not on the basis of economic analysis but on product classification used for statistical purposes and covering implicitly the whole EU or the European Economic Area (EEA).13 The extent of the geographic market appears an especially critical first step in assessing the impact on trade. Limited or no market or competitive analysis is undertaken, and the likely effects of the subsidies on the position of the firm(s) are rarely analyzed. This would be critical to assess the degree of market power and, hence, the potential impact of the state aid. The impact in turn will depend on the type of state aid. The current policy of the Commission rests heavily on the distinction between generic (general measures) and ad hoc state aids, which selectively favors some firms. This is based on the presumption that generic aids are more likely to be targeted at genuine market failures rather than consist of attempts to strategically shift rents from other countries. Indeed, a generic aid scheme, because it allows all firms to be eligible if they meet the preset conditions, is an ineffective and expensive instrument to shift rents from other countries.14 A full market or competitive analysis would lead to better analysis and policy decisions. State aid granted to firms in a competitive market is unlikely to significantly distort competition. However, in imperfectly competitive markets, state aid can be distortionary. First, the more concentrated a market, the more likely a selective state aid is to affect a larger proportion of output (Garcia and Neven, 2004). Second, when the recipient has market power, state aid could facilitate anticompetitive abuse. The competition distortion also depends on the type of state aid. State aid that affects the firm’s marginal or variable cost and therefore its pricing is most likely to distort competition.15 This is recognized by the current practice of prohibiting aid that affects operating costs. However, state aid may affect or harm competitors even when it does not affect pricing directly (Möellgaard, 2004). The harm could arise because the recipient could use the aid to invest, for example, in R&D and become able to provide a higher quality product. Competing firms will be harmed and forced to reduce their price, output and investment. These considerations are important as most state aids do not directly affect marginal costs. Furthermore, state aid might affect entry and exit decision by both recipients and competitors. One would expect the analysis of the effect on trade between Member States to be central in the Commission’s state aid decisions. However, this is not the case as a negative spillover is presumed when there is even very limited or no trade. The presence of trade does not necessarily mean that a negative spillover will occur as a result of the granting of a state aid. State aid could bring about a negative spillover if the geographic market is wider than national – or encompasses an area which covers at least two Member States. Therefore, both geographic market definition (Fingleton et al., 1999) and market analysis are critical. Even when the market is defined to cover two or more Member States, the granting of state aid might not necessarily result in a

13

The EA consists of the European Union and EFTA (Iceland, Liechtenstein and Norway) Member States. Ad hoc aid may also be looked at suspiciously because they might increase the firms’ ex post bargaining power vis-à-vis the government. However, in this case, state aid control would not be a means to control the negative externalities imposed on other countries, but a way for governments to overcome their own weak bargaining position, once state aid has been granted. 15 In practice, in some cases, it could be difficult to establish whether state aid is likely to affect variable costs and if so for which products. 14

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negative spillover. Only where markets are imperfectly competitive, a concern arises as aid might be used to capture rents that only exist if the market is not competitive. The extent or existence of a negative profit-shifting effect as a result of a subsidy depends on the degree of product differentiation (Collie, 2003). Suppose that products produced by the domestic and foreign firms are differentiated but not to such an extent to make them part of different product markets. When products are close substitutes, the impact of a subsidy to a domestic firm on foreign firms is maximum. Conversely, at the other extreme (very high product differentiation), a production subsidy is beneficial to other countries because they can now obtain the product cheaper but has no effect on the profit of their domestic firms (as in this case would be in a separate market). This means that when products are relatively homogeneous, state aid is likely to be most harmful. The Commission has recently attempted to partly counter this criticism introducing the Significant Impact Tests (SIT) which attempt to screen those state aids that merit a deeper analysis. The SIT includes the Lesser Amounts of State Aid test (the LASA test), a type of de minimis rule, and the Limited Effect on intra-Community trade Test (the LET test). The LET is a way to identify state aid that is unlikely to raise significant concerns about negative spillovers and which therefore should not be a cause of concern at Community level. The Commission in its Communication summarizes the Community courts’ jurisprudence, which interprets broadly the concept of effect on intra-Community trade. Therefore, if the other elements of state aid exist, then the measure will most likely be considered to affect trade between Member States and thus qualify as state aid under Article 87(1) EC Treaty. Nevertheless, the Community courts have recognized that in particular economic sectors that are not exposed to such intense competition at Community level, a small amount of aid to an undertaking over a given period would not affect trade between Member States. The Commission, on the basis of “economic rationale,” concluded that LET should only apply to a limited number of activities that, by their nature, do not produce significant cross-border effects or do not appear to be characterized by high concentration and barriers to entry. More recently, the Commission has undertaken a wider process of reform of state aid.16 However, because of the constraint of legal precedents, one should not expect radical changes in the Commission’s practice, unless the Treaty itself is modified.

4 STATE AID POLICY IN THE AIRLINE SECTOR The major state aid cases in the air transport sector since the 1990s have involved direct financial interventions by national governments aimed at the rescue or restructuring of state-owned flag carriers. In other words, these measures amounted to subsidies to ailing airlines. The main concerns of the Commission in relation to these cases were (i) whether the financial interventions in fact constituted state aid – i.e., they would not be under taken by a private investor according to the MEIP test – and, if so, (ii) to ensure measures

16 The European Commission has recently issued a consultation document entitled State Aid Action Plan, 7 June 2005, which highlights a number of potential reforms in the approach to state aid policy (available at http://europa.eu.int/comm/competition/state_aid/others/action_plan/saap_en.pdf). See also Friederiszick et al. (2006).


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were in place to limit the amount of aid to that strictly necessary to achieve restructuring objectives and to minimize any potential distortions to competition arising from the aid. Close scrutiny of these measures was particularly warranted, given that the develop ment of competition between the flag carriers and other carriers was during the 1990s in its infancy and the measures were selective and aimed at maintaining ailing firms in business. At the same time, the Commission saw this period as an opportunity for the flag carriers to get their houses in order before full liberalization. The desire of the Commission to take a tough line on state aid whilst recognizing the need for restructuring led to the single aid principle policy for restructuring (i.e., “one time, last time” rule). This was a clear statement of the Commission’s position that restructuring was accept able, and perhaps (politically) necessary, but wanted to avoid repeated restructuring and rescue aid measures. Although rescue and restructuring measures continued to be a feature of the sector into the latter part of the1990s, the “one time, last time” principle was in most but not all cases (the exception being Air France) largely abided by. This ensured that major restructuring was completed by the time airline markets were fully opened up to competition. Given the Commission’s policy position, the rescue and restructuring measures that have so dominated state aid, the airline sector in the 1990s are likely to be very much a thing of the past. The Commission’s recent Charleroi decision involving aid to Ryanair to set up at Charleroi airport raised entirely different issues.17 In contrast to the state aid decisions of the past, it involves a low-cost entrant rather than an incumbent flag carrier. Moreover, the aid did not involve a flow of capital from a national government to its national airline. Rather, the case involved indirect assistance by a regional government and a publicly owned regional airport to a foreign-based and/or owned airline. Although, so far, an isolated case, the policy questions raised are in many ways as fundamental as those relating to the restructuring of the flag carriers. As such, the Charleroi decision may provide a good indication of the type of issues that will arise in the sector in the future. Below, we highlight the potential deficiencies in the Commission’s approach to the analysis of state aid using the rescue and restructuring state aid cases and, in particular, the Charleroi decision. The latter would appear to have potential implications for the commercial strategies that can be pursued by regional airports within Europe (the vast majority of which are public undertakings) in attracting carriers.

4.1 Aid to Flag Carriers in the 1990s Prior to the 1990s, there were only a few minor state aid cases relating to the aviation sector. However, when demand in the sector fell significantly at the beginning of the 1990s, many airlines sought to restructure and looked to public funds to help them do so. Table 1 provides a summary of the main state aid cases to ailing flag carriers, for which

17 European Commission, Commission Decision of 12 February 2004 concerning advantages granted by the Walloon Region and Brussels South Charleroi Airport to the airline Ryanair in connection with its establishment at Charleroi (notified in Number C(2004) 516), (Charleroi decision henceforth), 2004/393/EC. The decision is currently under appeal by Ryanair.

Table 1 Main Rescue and Restructuring State Aid to European Airlines Case

Member State

Amount of assistance provided

Type of assistance

Undertakings and compensatory measures

Sabena, 1991 (OJ No L300/48, 31.10.91)

Belgium

c. Euro 1,600 million

Capital injections and cancellation of equity and debt

Approved subject to undertakings relating to (i) implementation of an agreed restructuring plan; (ii) ensuring no further direct or indirect state support including privileged access to slots or airport services

Air France, 1991 and 1992 (Commission press releases IP/91/1024 and IP/92/587)

France

c. Euro 900 million

Capital injections

Capital injections determined not be aid upon application of the MEIP

Air France, 1994 (OJ No L254/73, 30.9.94)

France


Capital injection and bond subscription (the latter by CDC a state-owned company)

Aid relating to CDC bond subscription to be repaid. Capital injection approved subject a range of commitments including: (i) implementation of a restructuring plan and meeting of performance targets; (ii) ring-fencing of the aid; (iii) limitations on size of fleet, number of route and services operated, and level of fares; (iv) non-preferential treatment in respect of air traffic rights

Iberia, 1992 and 1996 (Commission press release IP/92/606 and OJ No L104/25, 27.4.96)

Spain


Two waves of capital injection

First capital injection approved subject to commitments regarding the ring-fencing of the aid and absence of further assistance in the future. Second capital injection determined not to be aid following a reduction in amount to be granted

Aer Lingus, 1994 (OJ No L54/30, 25.2.94)

Ireland

c. Euro 200 million

Capital injection

Approved subject to wide ranging commitments including (i) implementation of restructuring plan and meeting of performance targets; (ii) ring-fencing of the aid; (iii) limitations on size of fleet and services operated; (iv) no acquisitions of other carriers within the Community (Continued)

Table 1 Main Rescue and Restructuring State Aid to European Airlines—(Cont’d) Case

Member State

Amount of assistance provided

Type of assistance

Undertakings and compensatory measures

TAP, 1994 (Commission press release IP/94/609)

Portugal


Capital injection, loan guarantees and tax exemptions

Approved subject to conditions including (i) payment of aid conditional on meeting financial targets; (ii) ring-fencing of the aid; (iii) limitations on expansion of services operated

Olympic Airways, 1994, 1998 and 2005 (Commission press releases IP/94/700 and IP/05/1139, and OJ No L128/1, 21.5.99)

Greece


Capital injection, loan guarantees, conversion of debt to equity an debt write-off

Originally approved subject to undertakings regarding: (i) meeting agreed restructuring plan; (ii) limitations on expansion of services; (iii) ending of exclusive rights to scheduled services to Greek islands. Following subsequent investigation by the Commission, a proportion of the aid was ordered to be repaid in light of certain undertakings not having been met

Alitalia, 1997 (OJ No L322/44, 25.11.97)

Italy


Capital injection

Approved subject to undertakings including (i) implementation of agreed restructuring plan; (ii) absence of further aid; (iii) ring-fencing of aid; (iv) non-discrimination in favor of Alitalia in respect of traffic rights, slotting and access to airport services; (v) limitation on fare reductions.

Source: Relevant Commission’s decisions. This is unlikely to be complete as it is based on publicly available information, while sometimes state aid cases are closed informally if a Member State modifies the state aid measure. No significant state aid concerns arose in the sector until the terrorist attack of 11 September 2001. The Commission stressed that these events should not be used to justify substantial increases in aid in the sector. However, compensation to airlines for closure of US airspace and assistance in relation to insurance was permitted under state aid rules in order to make good damage caused by an exceptional occurrence.

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information is publicly available, and the types of remedies imposed by the Commission to approve the measures. All the examples in Table 1 involve subsidies to ailing flag carriers which come under the label of rescue and restructuring aid. The Commission is aware of the problems and inefficiencies raised by this type of aid.18 Benefits are difficult to frame in terms of either market failure or social benefits. Competitive distortions can be substantial and reductions in incentives for productive efficiency can arise as a result of the softening of the firm’s budget constraint. These effects are more likely to be greater and wider in scope where the recipient firm has market power which was often the case for flag carriers. Furthermore, there might be legitimate reasons for smoothing the social impact of closure, but the same funds might be more efficiently used in other ways (e.g., to retrain unemployed workers). The recent Rescue & Restructuring Aid Guidelines explicitly recognize that aid to ailing firms is potentially very distortive.19 However, they conclude that there might be some economic and social justifications for granting state aid to ailing firms. The former are justified on the basis of social or regional considerations and other policy considerations.20 The Rescue & Restructuring Aid Guidelines also suggest that there might be an economic justification for avoiding bankruptcy and exit by claiming that there is a need to maintain a “competitive market structure when the demise of firms could lead to a monopoly or a tight oligopolistic situation.”21 This is, however, contentious as firms might fail, but this may not necessarily mean that this per se will lead to exit or to a reduction in the number of firms in the market, other than perhaps in the short term. The assets of the failed firm could remain in the market and therefore no reduction in competition might occur, if taken over by an entrant. This was the case of Swissair which went bankrupt in October 2001. Its assets remained in the market as the company was bailed out, although the latter was largely led by the Swiss government. Another perhaps more pertinent example is that of Sabena which was dragged into bankruptcy as well by the collapse of its major shareholder Swissair. Most of its assets were purchased by a group of investors under the brand name of SN Brussels. Therefore, the Commission’s approach seems based on a static view of competition, whereas new entry could occur following exit. Although in some cases it might be argued that state aid to ailing firms could prevent a reduction of competition in a particular market, this has to be based on a case-by-case analysis. For example, state aid might be justified

18

See for example Friederiszick et al. (2006). They recognize that “the exit of inefficient firms is a normal part of the market. It cannot be the norm that a company which gets into difficulties is rescued by the State. Aid for rescue and restructuring operations has given rise to some of the most controversial State aid cases in the past and is among the most distortive types of State aid. Hence, the general principle of the prohibition of State aid as laid down in the Treaty should remain the rule and derogation from the rule should be limited.” Furthermore, they mention that restructuring aid could “shift and unfair share of the burden of structural adjustment and the attendant social and economic problems onto other producers who are managing without aid.” Rescue & Restructuring Aid Guidelines, paras 4 and 31. 20 Rescue & Restructuring Aid Guidelines, para 8. Aid might be thought as legitimate if it does not distort trade and this could be “where the aid is necessary to correct disparities caused by market failures or to ensure economic and social cohesion” (para 19). 21 Rescue & Restructuring Aid Guidelines, para 8. 19


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where there are significant barriers to entry or when markets exhibit characteristics that might lead to tipping after the ailing firm exited. These, however, seem to be the exception rather than the rule and not particularly relevant in the case of aid to airlines in the 1990s. The Commission, when it considered state aid as justified but had concerns that it may have led to competitive distortions, has often imposed compensatory measures to limit such distortion. During the 1990s, these included among others output restrictions affecting fleet size, routes served, and even prices (Table 1). The range of compensatory measures contemplated in the Rescue & Restructuring Aid Guidelines also includes asset divest ments, capacity reductions, or reduction or removal of entry barriers.22 However, some of these compensatory measures are not necessarily pro-competitive. For example, impos ing a reduction of capacity might exacerbate rather than reduce the anticompetitive effects of state aid. These measures are defined as an attempt to maintain the status quo which, however, should not be maintained if the measure aims at correcting a market failure. There is another potentially relevant consideration in relation to aid to ailing airlines. In the period in which this aid was granted and largely approved by the Commission, competition on most intra-EU routes was limited. Therefore, the recipients were likely to have market power. As argued earlier, when this is the case, the risk that competition will be distorted is more acute and correspondingly the justification for the state aid weaker. Conversely, because of the nature of this type of aid, the potential and precise impact on the market(s) is often difficult to predict – i.e., how is the aid likely to be used and in which routes?

4.2 The Charleroi Decision 4.2.1 Main Facts In 2004, the Commission ruled against what it determined to be state aid provided to Ryanair, a low-cost carrier, by the Walloon Region and the Brussels Charleroi Airport (BSCA). It concluded that, in part, this aid could be compatible with the common market – in particular, subject to certain conditions, aid to support the launch of new routes. However, it did not authorize other forms of aid received by Ryanair and consequently repayment was required. The measures that were the subject of the decision were contained in two contracts. The first was between Ryanair and the Walloon Region (the owner of the airport infrastructure) and signed in November 2001. Under this contract, Ryanair received a reduction in airport landing charges amounting to approximately a 50% discount against published rates.23 Under a second contract with BSCA (a public company managing the airport under a long-term concession agreement), Ryanair received discounts on fees for ground-handling services (at approximately 10% of the published rates), contributions to promotional and marketing activities, and financial incentives relating to the opening of new routes. In return, Ryanair made guarantees to base its aircrafts at Charleroi and to operate a minimum number of flights over a period of 15 years. These conditions

22

Rescue & Restructuring Aid Guidelines, paras 39–40.

As part of this contract, the Walloon Region also committed to pay compensation should Ryanair suffer

losses as a result of regulatory changes regarding airport taxes and opening hours.

23

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were only granted as part of the private commercial contract with Ryanair as a departure from the conditions generally available to airlines at Charleroi. The Commission, there fore, concluded that Ryanair was the only actual and potential airline to receive these benefits. 4.2.2 Was It State Aid? Following its standard approach, the Commission assessed whether a transfer of state resources took place and conferred an advantage. The former was assessed by applying the MEIP test, whilst the latter was based on the selectivity criterion according to the Commission’s standard practice. The Commission distinguished between Ryanair’s contractual arrangements with the Walloon Region and those with BSCA. The Commission maintained that the Walloon Region is, in effect, a public undertaking that acts as the regulator of airport charges for the Walloon airports. It found that the determination of landing charges “falls within the legislative and regulatory competence of the Walloon Region and that the principle of private investor in a market economy is not applicable in these circumstances.”24 It argued that as the Walloon Region acts as a regulator rather than a company in relation to the setting of these charges,25 it would be inappropriate to apply the MEIP test in this case. In reaching an agreement with Ryanair, the Walloon Region had deviated from the framework of rules it had itself laid down for the determination of airport charges. Since the reductions to landing charges were provided on a selective basis to Ryanair, conferring an advantage in terms of reduced operating costs, they must be considered as state aid. The Commission seems to argue that because of the nature of the economic relationship between the Walloon Region and Charleroi airport, the decision to offer Ryanair reductions on landing charges could not be viewed as acceptable on the basis that it was motivated by normal commercial considerations. In challenging the Commission’s conclusions, Ryanair argued strongly that it was common practice to negotiate terms with airports and that the terms that it had secured at Charleroi were no more favorable than those it had achieved in normal commercial negotiations with a number of private airports across Europe. Moreover, it argued that the Commission had mischaracterized the nature of the relationship between the Walloon Region and Charleroi. In its view, in deciding to reach an agreement with Ryanair, the Walloon Region (the airport owner and main shareholder in BSCA) was acting as economic agent, not as a regulator. Given this, the MEIP test should be applied. The Commission rejected this line of argument. Although it seems to accept that the agreement may have been reached out of a “commercial need” to attract Ryanair (and indeed any other airline) to Charleroi – i.e., the Walloon Region’s behavior may have been motivated, as claimed by Ryanair, by its role as airport owner and shareholder in BSCA – the Commission argued that this was irrelevant. As long as the Walloon Region

24

Charleroi decision, para 144.

The Commission also notes that the income derived from the airport charges was split between BSCA and

an environmental fund, suggesting that the Walloon Region has no (direct) interest of a commercial nature in

the level of airport charges.

25


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acts as an airport charges regulator, whatever its motivation, a decision to step outside its normal framework and offer selective discounts to a carrier must constitute state aid. Indeed, the Commission’s key concern was that the Walloon Region had “placed itself in a situation of confusion of powers.” Irrespective of whether or not this was a “confusion of powers” the Wallon region was an “investor” in BSCA and, therefore, could in principle have acted in an economically rational way – i.e., according to the MEIP test – in deciding to grant state aid to Ryanair. Regarding the agreement with BSCA, the Commission determined that it was appropri ate to apply the MEIP and consider whether a private operator in the same circumstances would have offered these terms to Ryanair. It argued that the evidence put forward by Ryanair comparing the terms offered by Charleroi with those that Ryanair had agreed with a number of European private airports was of limited relevance. The differences in circumstances and/or the potential presence of an element public subsidy at other airports limit the validity of such comparisons. Instead, the Commission relied on an analysis of the business plans and assumptions underlying the agreement with Ryanair. It concluded that the business case underlying the agreement did not take account of relevant costs and was based on what the Commission believed to be inappropriate assumptions. Moreover, according to the Commission, the agreement involved commer cial risks for BSCA of a magnitude that would not have been acceptable to a private operator.26 As a result, the Commission concluded that the terms of the agreement with Ryanair failed the MEIP test and both sets of measures were state aid. While the decision is largely based on a formalistic approach on whether a measure is state aid, there might be some additional considerations which will be more fully explored in the next sections. It might be that in the absence of the state aid no airline would have settled at Charleroi. As a consequence, the only one which was open to such option – i.e., Ryanair – could act as monopsonist and extract all the rent. Had Charleroi been privately owned, this could have forced airport charges down to marginal cost. Because Charleroi was state owned, charges could have been forced below marginal costs as the Commission claims. If the Walloon Region agreed to this in order to correct market failure, then the measures could be justified. Lastly, it is unclear whether competition and/or trade were distorted. Airports compete in the provision of ground and landing services to attract airlines. As discussed below, however, competition between airports could only occur if they are sufficiently close to each other that the airlines consider them close substitutes. This is because the demand for airport services is a derived demand from passenger air transport services and passengers demand is for route-specific services – i.e., a flight from Charleroi to Prague is not a substitute for one on the Charleroi–Madrid route. Therefore, it is at least debatable that the function of the aid was to attract airline demand that otherwise would have benefited airports elsewhere in Europe. If this was the case, no distortion of competition would arise.

26

It argued (para 237) that the “BSCA’s financial structure is based on that of the Walloon region, and that without the implicit guarantee and assurance that the Region procures for its public sector companies [ ] and because of the commercial hazards inherent in the business plan, BSCA would never have committed itself to Ryanair.”

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4.2.3 Was Competition Distorted? Under current practice for a measure to constitute state aid, it must both distort compe tition and affect trade between Member States. The Commission’s analysis of the extent of any advantage conferred on Ryanair by the agreements with the Walloon Region and BSCA relies essentially on a presumption that the selective nature of agreements must imply Ryanair had secured an advantage. Ryanair argued that the agreements were not exclusive, and similar reductions to charges could be offered to other users of the airport who wished to enter into comparable arrangements. The Commission argued that because the agreements were made privately, similar terms could not be considered automati cally available to other users and this was sufficient for the agreements to be considered selective. While the confidential nature of the agreement might be an important legal consideration, it is at least doubtful whether it had any practical consequences. Indeed, the same (selective) effect could be achieved by structuring the charges Ryanair was offered as conditional to reaching the same traffic volumes that Ryanair guaranteed to Charleroi. Furthermore, because of the large fixed costs in running airports, it is efficient to recover them by charging based on the demand price elasticity of each airline.27 As in all state aid cases, once the financial transfer and the selectivity have been established, the distortion of competition is currently presumed. Nonetheless, Ryanair and the Belgian State argued that the aid could not have an impact on competition in the relevant market because there were no direct competitors on the routes served by Ryanair out of Charleroi.28 Ryanair stressed that its services were not in direct competition with those of other users of Charleroi – i.e., charter carriers operating a limited number of flights mainly in the summer months. Ryanair flights out of Charleroi amounted to about 90% of all flights (including charter flights). Ryanair also pointed out that its direct low-cost rivals – Virgin Express and EasyJet – had refused to operate from Charleroi. As a result, to the extent that Ryanair competed with these operators’ services from other airports, it should not be assumed that the reductions in charges it had achieved at Charleroi placed it at a competitive advantage. There were competitive advantages associated with operating from other airports, and in Ryanair’s view, the reductions it achieved at Charleroi served simply to offset the disadvantages of operating from what, in their absence, would be a relatively unattractive airport. Initially, the Commission appeared to suggest that a detailed analysis of the compet itive effects of the measures was required.29 However, the final decision contains very

27

The Commission recognizes that differences in charges are potentially justifiable as established in its Manchester Airport decision. 28 Charleroi decision, paras 70–72 and 247. 29 In its initial assessment in its decision to initiate proceedings, the Commission had concluded: “the granting by the Walloon Region of a reduction in airport taxes to one airline company only, on all its for a period of fifteen years, in a bilateral agreement that was given no publicity and deviates from the stipulations of the law, amounts to giving a tax exemption to the company. This places the company at a more advantageous position than competitors flying out of Charleroi” (para 13). With regard to the agreement with BSCA it similarly concluded: “the bearing by BSCA of certain air service costs also had the effect of putting Ryanair in a more advantageous situation than its competitors, whether they were companies operating out of Charleroi or other companies operating out of other airports” (para 14).


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limited reasoning either on which markets could be affected or the potentially distor tionary effects of the measure. Indeed, the Commission made its view clear that “the analysis of the impact of competition in the State aid sector is not the one applied when the Commission examines and alliance or concentration between airlines. Extending the definition of the relevant geographic market, which is governed by competition law, to the State aid sector would involve ignoring specific nature of these two separate areas of Community economic law.”30 While there might be some justification as to why the approach to market definition might differ under state aid law, the Commission did not elaborate further as to why this is the case. What is striking in this case is that the Commission appears to put forward two implicit markets that might be affected which are very different from those normally defined in the sector under competition law. First, the Commission implicitly argued that airlines compete in a potential market for “air transport services”31 or more precisely “the advantage granted through the bearing by the State of operating costs normally borne by an airline does not only distort competition on one or more routes and on a particular market segment. The advantage gained by the airline strengthens its economic position on its network as a whole in relation to competing companies, whether these are traditional low-cost, charter or regional compa nies.”32 Under competition law, the traditional view for short haul (and point-to-point) services such as those provided by Ryanair at Charleroi is that potentially there are as many relevant markets as the routes or city pairs served by the airline (depending on the substitutability of airports that are not too far away from each other (Crocioni, 2000)).33 The second implicitly defined market is that for the provision of airport services to airlines.34 The Commission appears to put forward the notion that regional airports such as Charleroi do not offer the same services as national airport, and evidence shows that “when an airline sets up at a secondary airport, the passenger traffic will not necessarily be diverted from the main airport to the secondary airport.” Therefore, secondary airports such as Charleroi according to the Commission are implicitly in a separate market from traditional national airports. The issue of whether all regional airports or only those that are closely located are in the same market was left open.35 While this second potential market appears sensible at first sight, it is in contrast to the fact that the aid was granted not to the airport but to the airline, given that according to the Commission Charleroi airport would be at an economic disadvantage as a result of inducing Ryanair to establish a hub at its airport. The Commission appears to conclude that Charleroi airport was in a better financial position prior than after the aid. Indeed, it concluded that if BSCA was a private investor it would have not offered such terms to Ryanair. However, one could examine airport services as being an input market affected, instead. The aid is still

30



32 Charleroi decision, para 249. This wide definition could be somewhat relevant for rescue and restructuring

aid where the effects of generic measures of state aid could not be easy to determine on a route-by-route basis.

33 For long haul air transport services, markets are defined more widely. This is for two reasons. First, the

relative dis-benefit of traveling to airports which are further away is likely to decline with the distance or

duration of the flight. More airports at both departure and arrival could be part of the same market. Second,

flights which involve an intermediate stop might also be in the same market as non-stop flights.

34 Charleroi decision, para 299–301.

35 Charleroi decision, para 301.

31

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granted to Ryanair but because it is conditional to the airline committing to Charleroi, the latter benefits from increased demand from its services. The decision contains no analysis of the potentially distortionary impact of the state aid on competition. This case appears different from those of aid to ailing flag carriers. In the cases in Table 1, aid was not tied to specific services, and therefore, this made it difficult to identify the potential specific effects. In the Charleroi decision, most of the measures that were deemed to be state aid were route or flight specific and affected Ryanair’s marginal costs – discounts on landing charges, contribution to the opening of new routes, etc. – and their effect on pricing and route entry decisions could in principle be properly assessed. Because of the nature of the aid measures, a direct impact on fares could be presumed or deemed likely. Yet, the Commission does not seem to reply directly to Ryanair’s argument that because the relevant markets are the routes out of Charleroi where it was the sole provider of scheduled passenger services, there could be no impact on competition. Despite the lack of formal market definition, implicitly the decision concluded that all the routes out of Charleroi are in separate markets than those out of the closest airport, Brussels Zaventem, although the two are only about 30 miles apart.36 If they were not, competition could have been affected. In this case, an analysis of the city pairs served by Ryanair out of Charleroi – including all possible airports at either end – shows that in the 11 routes served by Ryanair, there could have been between zero and five actual competitors (Barbot, 2004).37 When aid is granted to the sole company currently active in the market, it could still distort potential rather than actual competition. For example, potential entrants in the route could be discouraged from entering because the incumbent’s services are subsidized. This raises an important consideration. State aid analysis is necessarily forward-looking as in most cases, the exception being aid which was not notified and later discovered, the Commission does have to assess whether the measure, if allowed, is likely to distort competition. In this case, it appears difficult to claim that this would have been the case. The airport struggled to attract airlines as other low-cost carriers had responded negatively to offers by the BSCA to set up a hub at Charleroi in the past. 4.2.4 Was There a Negative Spillover? As argued above, in the presence of negative spillovers there is a stronger case for a supranational control of state aid. This is reflected by the law that in principle bans only state aid that affects trade between Member States. We argued that, contrary to the current practice based on presumptions, this should be interpreted as whether the aid generates a negative externality on other Member States. The Charleroi decision did

36 In two merger decisions involving the Belgian national carrier Sabena, the Commission appears to have concluded that the merger would have affected city pairs from Brussels. While this appears to suggest that the Commission concluded that airports in the same urban area are in the same market, these decisions relate to a period when in Brussels there was effectively only one national airport. See European Commission, Case No. IV/M.616, Swissair/Sabena, 20 July 1995 and Case No. IV/M.157, Air France/Sabena, 05 October 1992. 37 However, some of the airports of these city pairs are at a considerable distance from each other – i.e., Glasgow Prestwick and Edinburgh or Pisa and Florence are about 60 miles apart – raising some questions as to whether these could be seen as close substitutes by consumers. Barbot also shows that Ryanair’s fares are not influenced by the presence in the same city pair of another low-cost airline – i.e. a competitor offering services which are closest to those of Ryanair.


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not investigate whether a negative spillover might arise. While airline services across the EU and especially those originating in a small Member State such as Belgium have an international dimension this does not necessarily mean that a negative externality will arise from subsidizing such services. Using the implicitly defined product markets one could start drawing some conclusions. First, let’s consider the provision of airline passenger services. If the relevant market is the route, while all routes out of Charleroi are international it appears difficult to argue that there is a negative externality as the production of the services appears not “based” in Belgium but on both Member States at either end of the route. Second, assume that the relevant market is that for the provision of airport services to airlines. We discussed above that it is difficult to argue that one of the affected markets is that for the provision of airport services when the supposed aid would make the recipient (BSCA) worse off. However, assuming that the aid was granted to Charleroi airport rather than to Ryanair one could assess whether a negative externality could arise. This would require that airports located in different Member States compete with each other in offering services to airlines. This is alluded to in the Charleroi decision which mentions the example of Ryanair taking advantage of competition between the two closely related airports of Tarbes and Pau in France and concluded that it could also occur “between airports located in separate Member States”.38 Whether this is the case it is at least debatable and a question largely and ultimately depending on whether a sufficient proportion of consumers (and therefore airlines) viewed two destinations far from each other as substitutable. Moreover, in this case it seems unlikely that a negative externality could arise in the absence of substitutability between airports located in different Member States. If Charleroi airport received a subsidy and this allowed it to attract airlines such as Ryanair to use it as a base, airports at the end of each route out of Charleroi would also benefit by the increase in traffic in the form of increased demand. This is a positive rather than negative externality. In other words, airports at both ends of a “Charleroi” route are complements rather than substitutes. 4.2.5 Was There a Market Failure or Social Justification? The Commission found that the measures in question could not be exempted under Article 87(2) and 87(3) of the Treaty. However, the Commission recognized the growing role that regional airports may have to play in promoting the economic development of regions (the subject of Article 87(3)(c)). The Commission concluded: operational aid measures intended to help the launch of new airlines or strengthen certain frequencies may be a necessary tool for the development of small regional airports. The measures may indeed persuade the interested companies to take the risk of investing in new routes. However, in order to declare such aid compatible on the basis of Article 87(3)(c) of the Treaty, it should be determined whether this aid is necessary and in proportion to the objective sought, and whether it affects trade to an extent that is contrary to the common interest.39

38 39

Charleroi decision, para 301. Charleroi decision, para 279.

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Although both the concessions made by the Walloon Region and BSCA were found to constitute aid, the Commission determined that certain elements of this aid were compatible with the common market to the extent that they foster the development of and use of underutilized secondary airport infrastructure. This included aid relating to “one-shot incentives” to develop routes (including BSCA’s contribution to promotion and publicity and sums received over the 2001 to 2003 period).40 Nevertheless, for this aid to be declared compatible the Commission required a number of conditions to be met, namely that (i) the aid is necessary for opening of new routes and is proportional to meeting this objective; (ii) principles of transparency and nondiscrimination between operators are followed; (iii) there are appropriate penalties for carriers who fail to meet commitments; and (iv) the aid is of limited duration (5 years), applying only to genuinely new, rather than replacement, routes. The Commission found the other elements of aid incompatible with the common market.41 In determining that the start-up aid (i.e., intended to promote the development of new routes) provided to Ryanair could be deemed to be permissible, the Commission clearly had accepted that such aid could be justified on either social grounds or on the basis of the existence of a market failure. The Commission’s decision, however, is not entirely explicit regarding the precise nature of the justification for the aid. Two possible types of justifications could be relevant. First, to the extent that the development and growth of a regional airport may have spill-over effects – for example, through the creation of employment – which benefit the wider regional economy, start-up aid might be viewed as having a social justification, especially in less developed areas of the EU. Alternatively, such aid could equally be viewed as addressing a market failure by helping internalize the positive externalities that users of the regional airport may confer on the local economy but that they would not consider in making private decisions. The Commission does not provide evidence of a link between the development of regional airport infrastructure and regional economic development. Second, the Commission makes reference to underutilized capacity at secondary airports. Given the extent of congestion that exists at many major airports, encouraging airlines to use secondary airport infrastructure may generate positive externalities for other users by reducing congestion costs. Although this could provide a market failure justification of the type of assistance provided to Ryanair, it is unlikely to be a first best. Above we argued that a more efficient measure could be a tax on the use of congested airport. 4.2.6 Promoting the Development of Regional Airports? The Commission has argued that its decision provides guidance and clarity regarding the financial incentives that can be offered to attract carriers by airports that are under

40

This accounted for approximately three-quarters of the aid the Commission had identified. In particular, the Commission required aid to be recovered in relation to (i) the reduced airport charges agreed with the Walloon Region – that could only be permissible if granted in a non-discriminatory manner and were time limited; (ii) the reduced ground handing charges agreed with BSCA – the Commission determined that such reduction are unlikely to be compatible in any circumstances; (iii) one-shot incentives to develop new routes which do not reflect the costs of doing and/or that are not tied to meeting this objectives; and (iv) aid relating the Ryanair’s Dublin-Charleroi – this route had been opened in 1997 and therefore in the Commission’s view could not be considered as a ‘new route’. 41


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public ownership or control. It also claimed that the decision will serve to promote the activities of low-cost airlines and the development of regional airports whilst ensuring a level playing field for competition.42 The decision undoubtedly provides clarity regarding the measures the Commission is likely to view as acceptable for airports to attract carriers. It is clear that Commission considers that such measures should be limited to the development of new routes and should not relate to existing routes. In line with its state aid policy in other areas, the Commission has also placed great emphasis on factors including the need for a coherent set of objectives for the aid, the requirement for long-term profitability and the presence of time limits on the duration of any aid, transparency and nondiscrimination. However, whether the decision will serve to promote the activities of low-cost carriers and regional airports is less clear. The decision would appear to limit significantly the scope of agreements that can be reached between low-cost carriers and regional airports. Agreements of a similar nature elsewhere in the sector may not meet the criteria set out by the Commission in Charleroi. Moreover, it is unclear whether the business model developed by Ryanair and other low-cost operators – or at least further growth of this model – would be a viable proposition if the incentives that can be offered by airports cannot go beyond those set out in Charleroi. It is arguable that the Commission’s decision places a significant regulatory burden on publicly owned or controlled airports wishing to offer carriers start-up incentives. It would appear that, at least in principle, an airport offering such incentives must be in position to demonstrate clear and direct benefits and that the aid is necessary and does not go beyond that needed to achieve these objectives. The stringent nature of the tests to apply to these types of assistance and the potential penalties that may be faced if the Commission deems these criteria are not met and the aid is incompatible, may serve to deter airports and carriers from agreeing even financial incentives that are limited in scope.

5 CONCLUSIONS We have critically reviewed the Commission state aid policy and highlighted the prob lems with the current system which is based on a set of presumptions rather than based on the effects, and in particular the distortions, that state aid can bring about. We used state aid decisions in the airline sector to illustrate some of the problems caused by the current approach to state aid. State aid to ailing flag carriers was frequently granted in the 1990s. This type of state aid is one of the most problematic from an economic efficiency point of view and it is equally difficult to justify as pursuing social objectives. While the Commission was successful in largely confining this type of aid to the period of transition to liberalization, it approved most of the state aid measures. We also argued that some of the compensatory conditions imposed and mentioned in the recent Rescue & Restructuring Aid Guidelines could exacerbate rather than reduce the distortionary effects of state aid.

42

Commission press release IP 04/157.

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The Charleroi decision is of a different nature as it involved a new entrant rather than an incumbent. It highlights the problems caused by the lack of a clear identification of the markets affected by the measure, whether the measure could distort actual and potential competition, whether it generates negative spillovers (and therefore justifies a supra-national control), and when it could be justified in spite of the distortions and spillovers brought about. We argue that a better supranational system that aims at controlling subsidies granted by EU Member States should be based on a more rigorous economic approach and analysis looking at the likely effects of state aid measures.

REFERENCES Adkins B. (1994), Air Transport and EC Competition Law, Sweet & Maxwell, London. Barbot C. (2004), “Low cost carriers, secondary airports and State aid: an economic assessment of the Charleroi affair”, FEP Working Papers No. 159. Besley T. and Seabright P. (1999), “The Effects and Policy Implications of State Aids to Industry: An Economic Analysis”, Report to DG-III of the Commission, mimeo, available at http://europa.eu.int/comm/enterprise/library/lib-competition/libr-competition.html. Brander J. and Spencer B. (1985), “Export Subsidies and International Market Share Rivalry”. Journal of International Economics, 18, 83–100. Collie D. (2003), “Prohibiting State Aid in an Integrated market: Cournot and Bertrand Oligopolies with Differentiated Products”, Journal of Industry, Competition and Trade, 2, 215–231. Corden M. (1990), “Strategic Trade Policy. How New? How Sensible?”, World Band Working Papers, WPS 396. Crocioni P. (2000), “Defining Airline Markets: A Comparison of the U.S. and EU Experiences”, Antitrust Bulletin, 45 (spring), 1–45. Fingleton J., Ruane F. and Ryan V. (1999), “Market Definition and State Aid Control”, mimeo, available at http://europa.eu.int/comm/images/language/lang_en3.gif. Friederiszick H.W., Röller L.H. and Verouden V. (2006), “European State Aid Control: An Economic Framework”, forthcoming in Buccirossi P. (ed), Advances in the Economics of Competition Law. Garcia J.A. and Neven D.J. (2004), “Identification of sensitive sectors in which State aids may have significant distorting effects”, Report to HM Treasury. Gil-Molto M.J. and Piga C.A. (2005), “Entry and exit in a liberalised market”, Discussion Paper Series, Loughborough University Economics Department, available at http://papers.ssrn.com/ sol3/papers.cfm?abstract_id=916505. Möellgaard P. (2004), “Competitive Effects of State Aid in Oligopoly”, mimeo, available at www.econ.ku.dk/cie/Seminars/pdf%20%20seminar/stateaid.pdf. Nicolaides P. and Bilal S. (1999), “An Appraisal of the State Aid Rules of the European Com munity – Do they Promote Efficiency?”, Journal of World Trade, 33(2), 97–124. Starkie D. (2002), “Airport Regulation and Competition”, Journal of Air Transport Management, 8, 62–72.


7 The Implications of the Commercialization of Air Transport Infrastructure Kenneth Button∗

ABSTRACT Following the on-going liberalization of airline markets from the 1970s, there has begun a movement to inject more commercialization into the provision and operation of airports and air navigation systems. These latter developments have been gradual and taken a variety of forms. The perception of success in these endeavors depends on the particular objective of each case. In some situations, such as those of South American airports, the aim has been to retain state ownership while injecting private capital and expertise into systems. In countries such as the UK, the privatization of most airport capacity and the establishment of a private/public enterprise that runs the air navigation system have been influenced more by a quest for economic efficiency irrespective of ownership. The overall conclusion is that, unlike airlines where the flexibility of the industry allows for relatively rapid responses to institutional change, the reforms to air transportation infrastructure will take time to work there way through, especially with continual interruptions to the process as policy continually redefines itself in the light of such things as new security considerations.

1 INTRODUCTION Globally, air transport has traditionally been heavily regulated. The rationale for this has differed somewhat over time and between countries. In the early years there were generic legal constraints on the sector that applied across industries more generally – the Wright Brothers, for example, held patents on some aspects of airplane design. From the 1920s many nations began to appreciate the role that air transport can play in economic and political integration. The US subsidized domestic airmail services and the UK fostered its longer haul services as a means of Imperial integration. Concerns about market

∗ University Professor and Director of the Aerospace Policy Research Center, School of Public Policy, George Mason University, Fairfax, Virginia. E-mail: [email protected]

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stability, and in some cases potential monopoly power, led to nations imposing specific controls over market entry and fares, and nationalization was common. The potency of air power as a military instrument added to the interest of governments to control their own industries. Wider economic regulation was initiated after the Second World War as international air transportation was seen as a potential and strategically important growth sector and the United Nations, at the 1944 Chicago Convention, set out ground rules for countries to negotiate bilateral agreements in the provision of services. Overriding these market interventions for economic reasons have been the long-standing social regulations designed to meet safety, environmental and strategic needs that recently have included a particular focus on security. Since the late 1970s there have been major shifts in the regulatory environment under which civil air transport services are provided. There has been a move towards what is known as deregulation in the US and market liberalization in much of the rest of the world1 . This has seen governments allowing market forces exert a greater influence in the determination of airlines fares, the services that can be offered, and the carriers that can offer them. The results have been a general lowering of fares, an increase in the number of airlines, the initiation of new types of service, and a significant increase in both passenger and cargo traffic (Morisson and Winston, 1995; Button and Stough, 2000). These developments, however, initially almost exclusively involved changes in the airline services market and there has been much less and a much slower liberalization of air transport infrastructure (Table 1). Only 2% of the world’s commercial airports, for example, are fully managed or owned by the private sector, although where this has taken place the results seem to have been sufficiently encouraging to stimulate further interest by the private sector. Similarly, air navigation services (ANSs) have been regulated, with the majority being state owned, with changes coming slowly. One might add to this though, that the organization and management structure of many airports and ANSs that remain in public control has changed significantly with moves away from them being treated as public utilities (DeNuefville and Odon, 2003). This particular situation, with institutional changes affecting the users of air transport infrastructure preceding that of the infrastructure providers themselves is not unique to the air sector; it can be seen in many countries with regard to railways and maritime transport and is particularly pronounced in road transportation where public ownership and operation of infrastructure remains the norm despite widespread liberalization of the trucking and bus industries. The pattern is also to be found in the energy and telecommunications sectors. Nevertheless, despite the tardiness of change in the way air transport infrastructure is provided and regulated, there has been change in many countries; and gradually evidences of its effects are beginning to emerge. Unlike airlines, where rapid changes were seen relatively, it takes time for reforms in airport and air navigation systems (ANSPs) to be felt, and anything approaching a long-term equilibrium, because of the longevity of the hardware, may not emerge for many years. Infrastructure is also less immediately visible and thus less prone to come under the scrutiny of the public.

1

The variation in jargon is partly due to the different meaning of “liberalization” on either side of the Atlantic. Traditionally, in the US liberalization means more government involvement whereas in Europe it means less. We use the terms interchangeably here.

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Table 1 Major Air Transportation Liberalization Initiatives Year

Action

Airlines/infrastructure

1944 1977 1978 1979 1984 1987 1987 1989 1989 1992 1992 1995 1996 1997 1999 2001 2001

Chicago Convention US Domestic cargo deregulation US Domestic passenger deregulation Term “Open Skies” used UK-Netherlands liberal ASA bilateral EU’s “First Package” UK Airports Act (privatization) EU’s “Second Package” Northwest-KLM strategic alliance EU’s “Third Package” US–Netherlands Open Skies Agreement GATS NAV Canada established Banjul Accord “Single European Skies” initiative MALIAT NATS UK established

Airlines/infrastructure Airlines Airlines Airlines Airlines Airlines Infrastructure Airlines Airlines Airlines Airlines Airlines Infrastructure Airlines Infrastructure Airlines Infrastructure

Note: GATS: General Agreement on Trade in Services; MALIAT: Multilateral Agreement on the Liberalization of International Air Transportation.

2 PRESSURE FOR COMMERCIALIZATION Commercialization is a somewhat vague term. Dictionary definitions largely focus on the seeking of profits, but in many cases it is more generally taken to mean the introduction of some notion, often equally vaguely defined, of market forces, whilst in other narrower contexts, it is seen more as forcing an institution to meet the demands of the user more closely, in particular in terms of allocating facilities according to consumer’s willingnessto-pay. A common feature is seen to be a general tightening of the link between the costs and revenues of an undertaking so that outside finance is reduced and users are made more aware of the opportunity costs of their actions. Many tie commercialization directly to privatization2 , but this need not be the case if a public entity has to be self-sustaining financially and has any monopoly power it may enjoy constrained by countervailing powers or institutional control. The notion of commercialization can also have diverse connotations. At one extreme it is a derogatory term indicating that something, often a service that was previously provided as a social activity, is now sold on the market to the detriment of its quality and the numbers who have access to it. Alternatively, others see commercialization as taking an activity out of the hands of state bureaucrats and allowing its provision at an economic price by

2

The term privatization is itself open to many interpretations. In its broadest sense, some interpret it to mean no state involvement at all in the market (DeNuefville, 1999). Here it is taken to mean the non-state ownership of assets; a more widely used definition.

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individuals and private firms that fosters more efficient use of resources and opens wider avenues for investment funding. We make no firm judgment here, other than to consider any move that increases economic efficiency as beneficial, and, taking the Robbins (1932) line, if this results in a socially undesirable distributional impact then it is up to politicians to initiate remedies through taxes and subsidies. We take a neutral view of commercialization in the sense that per se it is neither seen as a good or bad thing and look at it from the perspective of it being an institutional mechanism for achieving particular objectives. In most cases this has involved the introduction of greater market power into decision making either through the relaxation of public regulation or through the reduction in the direct involvement of government in the ownership of air transport infrastructure.3 The commercialization of airline markets came about through a combination of eco nomics and political factors. The changes began in the mid-1970s in the US domestic market where a mounting body of empirical academic evidence comparing regulated inter-state routes manifestly demonstrated higher fare levels than comparable unregu lated, intra-state fares (Levine, 1965). These coincided with the emergence of new ideas of how competition may influence firms’ behavior, and in particular how ultra-free entry to and exit from a market will reduce the potential for monopoly exploitation even when there is only one supplier; contestable market theory. It was also at a time when the nature of regulation itself began to be challenged and some economists, particularly from the University of Chicago, started questioning whether economic regulation served the pubic interest or the interests of those being regulated and the regulators themselves; capture theory. Overriding these largely academic debates was the macro-issue of the day; rising prices and unemployment (“Stagflation”). Deregulation was seen as a way of reducing prices and thus easing the cost-push pressures linked to Stagflation. It was this macro concern that was the catalyst for bringing about reform at that particular time. The pressures for change in the airline market within the Europe, and notably the European Union (EU)4 , have been somewhat different. The European air transport market, because of the lengths of domestic routes, is primarily international in its nature and thus bound by international agreements, such as those established by the 1944 Chicago Convention, that make regulatory reform more difficult. In addition most of the major airlines within Europe in the 1970s were state owned and often subsidized, in part to facilitate the reaching of international agreements, but also in many cases for doctrinal reasons; countries like France favoring the “Continental Philosophy” of regulation whereby the onus is to demonstrate intervention failure before resorting to the market rather than giving the market primacy.5 Again while there was considerable academic evidence of the failings in the European regulatory structure, highlighted following the use of new powerful statistical and programming techniques showing the

3 Some moves to privatize transportation infrastructure have actually led to the introduction of new economic regulations such as price-capping in the case of BAA (the company owning the main airports) and NATS (the ANSP in the UK). But these regulations are less stringent than those when the assets were state owned. 4 The European Union has enjoyed several titles during its existence but EU will be used throughout for convenience. 5 Additionally, while the founding Treaty of Rome had a Common Transport Policy (CTP) as one its two cornerstones, air transport was explicitly excluded.


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positive effects of reform in the US, it was a macro issue that really galvanize reform In this case the move to a Single European Market following legislation in 1987. The Single European Act initiated a general, phased removal of government regulation across most sectors of the European economy, including airlines. By 1997 the intra-European airline market had, in some ways, less residual economic regulation than the US domestic market regarding, for example, foreign ownership rules. Air transport infrastructure was almost universally, however, largely left out of this liberalization process. Most of it was government owned, either by the national authority, or in the case of some airports by local authorities. The rationale for this varied. In some cases it was simply a legacy effect; the facility had been initiated by a state agency, perhaps for local economic development reasons, and had remained in its hands subsequently. In some cases, and most notably in countries of South America and Africa, airports and air traffic control were seen as of strategic importance and came under the control of the military. Governments also often saw air transport as a political and social integration mechanism and wanted to ensure adequate access even if maintaining particular airports was not commercially viable. There were also arguments, albeit with a rather thin veneer of rigor, with an economic content put forward for public ownership. Some maintained that efficient airport and air traffic control services required large, periodic lump-sum investment that could not be guaranteed by the private sector. Invoking, generally implicitly, one of Adam Smith’s justifications for public ownership, the argument was that state financing, and with it direct control, was needed to meet the strategic investments of large pieces of air transport infrastructure. In some cases it has also been argued that airports and air traffic control services should be allocated on the basis of “need” rather than effective demand to counteract the poor access enjoyed by remoter parts of a country. But perhaps more strongly, there were concerns that airports and ANSPs are natural monopolies and that intervention was needed to prevent them exercising their market power. In itself, this is not an argument for state ownership; many public utilities have this feature and have been directed through regulation rather than ownership.6 Other arguments, such as that air transport infrastructure is a “public good,” are found in debates, both academic and political, but can hardly be taken seriously because it is clear that it is neither non-excludable nor non-rival; the necessary conditions for publicness. The very success of the deregulation and, in many parts of the world, privatization of airlines and other industries has been one of the reasons for the current interest in fostering more commercialization in airport and ANS provision. Demonstration effects can be strong, but more practically the world’s air traffic has been growing rapidly since regulator reforms of airlines were initiated and with this has come pressure on the capacity of infrastructure. There has been an increased appreciation that it has not been provided or used to its best effect and that there are mounting capacity problems (Button and Reynolds-Feighan, 1999). The existing, state dominated systems finding it difficult to manage existing facilities and to finance new ones at a time when tax increases have become politically unpopular.

6

Indeed, the United Nations’ International Civil Aviation Organization has used fare setting and other regulations since its inception in the 1940s to control international air transport.

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The pressure for change has also come as part of a wider move for more commercial ization in the provisions of many forms of infrastructure. This generic push has neither, however, been even across countries nor sectors. Intellectually, new analysis of how to best handle infrastructure where there is potentially monopoly power and, often at the same time, the perception of public need for its services has been somewhat slower to be assimilated than developments more germane to competitive and contestable situations. For example, there has been renewed interest involving “competition-for-the-market,” rather than just “competition-in-the-market,” that has involved ideas of bidding for tem porally limited monopoly rights to provide and/or operate air transport infrastructure – build, own, operate, and transfer (BOOT) schemes and concessions being examples. This is designed to attract the most efficient suppliers and to extract excess economic rent from these limited monopolies that can then be used by government for transfer purposes. Where regulation of a private monopoly is seen as still needed, lighter handed approaches have been developed, most noticeably price-cap regulations. The challenge in these cases is to establish mechanisms that meet the objectives set – auctions of monopoly rights, for example, can take a variety of forms as can concessionary contracts. There are also stronger and more concentrated vested interests involved in infrastructure provision than in airlines that can stymie immediate reform and institutional structures have to be devised to counter these. From a more direct public policy perspective, infrastructure always tends to be seen as more remote and of less immediate interest to the electorate and thus actions may be delayed. This is particularly true of maintenance and up-grading where there is little political capital to be earned. Many of the problems in the public provision of air transport infrastructure are associated with its efficient use, but the impact of changing institutional structures to embody more commercially oriented stimuli are slow to materialize and less immediately transparent to users of the system. In some cases, the move towards more commercial provision of air transport infras tructure service provision has been a logical continuation of developments in the airline and other transport markets. This has effectively been the situation in the UK where the airline, airport, and ANS industries have all largely been moved into the private sector, albeit in some cases with concomitant sets of economic regulations largely to limit any abuse of monopoly power. But in other cases, different and peculiar arrangements have been favored that have left the facilities in state hands but involved mechanisms to pass operations and development to the private sector.

3 NATURE OF COMMERCIALIZATION To understand the exact nature of commercialization of air transport infrastructure and national variations, it is helpful to review some recent developments in economic thinking about institutional structures. There has been a recent up-surge of interest in New Institutional Economics (NIE) that considers economic outcomes within the broader informal and formal structures within which they take place7 . This type of approach

7

See Williamson (2000) for a review of the new institutional economics.


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provides a useful basis for exploring the nature of some of the changes that have taken place regarding air transport. In particular, the NIE places emphasis not only on the shortterm market outcome, which is seen as embodying conventional neo-classical market clearing concepts such as the pricing of landing slots in the airport context, but also on the informal environment in which these contracts are reached – embodying such things as local transactions costs, methods of bargaining, degree of trust, and the de facto interpretation of commercial laws – but also the longer term formal legal constraints that set the boundaries for deal-making that change relatively infrequently. Overshadowing all of this are the norms of the society involved – for example, the Muslim approach to banking is considerably different to that found in western economies and this influences the way that undertakings such as airports are financed and operated, but even within what are normally seen as market economies there are differences in the ways that various countries view private ownership of large scale assets. This latter, long-term, cultural effect is one factor that has led to a relatively faster move towards commercialization of air transport infrastructure in many western societies than in large parts of South America or Asia. Even where commercialization and privatization have taken place there are variations. Whilst many western style economies such a the UK, Germany, Canada, and Australia have engaged in various programs of divestiture of assets to the private sector, sometimes as profit-oriented entities and sometimes as not-for-profits, South American and Sub-Saharan countries have preferred concessions with the state retaining ownership of the air transport infrastructure. Other countries, such as the US that otherwise has a moderately strong market ethos, prefer to operate large parts of their air transport infrastructure in a manner almost akin to the former Soviet Union with state ownership of, for example, its ANS, with finance coming from taxation and rationing by queues rather than price.8 This cultural effect thus influences the degree to which commercialization has taken place and the channels trough which it as been introduced.

3.1 Airports The national approaches aimed at injecting more commercial pressures into the provision of airport services have varied. The complete privatization of airports, or at least the vast majority of their components, is the norm in most countries. Much of the interest that is now emerging is either the privatization of some aspects of airport activity or engaging the private sector in some partnership arrangement with the state. In part this is because an airport is effectively a composite entity comprising of units offering a variety of services – land access, parking, concessions, terminals, runways, ground handling, fire and response units, security, etc. Commercialization does not have to be applied to all these activities, and may be pursued in a piece-meal way if politics or economics dictate. Approaches often differ, for example, according to the state of the local air trans port market which is in turn often linked to the stage in economic development of the

8

The FAA has recently begun moving away from this approach in terms of tower control whereby some facilities have been outsourced to private providers.

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178

Traffic

Growth

Simple economic regulation

Developing countries • Increased capacity of the airport system • Large share of revenues from airside charges

Developed countries

Complex

economic

regulation

• Maximum revenue base with limited passenger growth • Large share of revenues from commercial services

Share of Commercial Revenues

Figure 1 A Generalization of Airport Trends in Developing and Developed Countries. Source: Adopted from Juan (1995).

country concerned. For example, airports can vary in terms of their potential revenue flow from different sources and this can affect the degree of privatization or deregu lation that is possible and the form it is most likely to take. Figure 1 offers a fairly simply representation of what seems to be going on regarding developed and developing countries. Much depends on the state of the regional air transport market. The forecasts of relatively slow longer term growth in air traffic in and between the developed countries (e.g., estimated at about 3.6% a year to 2005 within North America, 3.4% within Europe, and 4.5% between North America and Europe by Boeing Commercial Airplane) means that their major airports will increasingly become dependent on commercial or nonaeronautical revenues to enhance their revenue stream.9 This in turn can pose problems in terms of regulation as has, for instance, already been seen in the debates over the imposition of the price-capping regime used in the UK. While still relatively small, the protected growth of many air markets involving developing countries (e.g., 6.9% within Latin America, 8.8% between Latin America and the Asia-Pacific region, and 8.7% between Latin America and Africa) offers the potential for increased airside revenue in situations where there are potentially fewer social constraints involving such things as noise and land-take on building additional capacity or where there is already adequate capacity. The scope for raising significant commercial income is much less, however, because of the lower initial traffic base.10 It also suggests, though, that the regulatory regime overseeing a privatized airport system needs to be less sophisticated because it only has to deal with airside issues. The potential for various forms of regulatory capture, a phenomenon not unknown in many developing countries, is thus smaller.

9 Additionally, there are capacity issues in many developed markets that are unlikely, for a variety of reasons,

including environmental concerns, to be resolved through the provision of additional facilities.

10 Many large international airports generate up to 60% of the income from non-aviation activities.


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The problem for many of the poorest developing countries, however, is that even though their air traffic flows may in aggregate be growing, this is from a low base and they still seldom generate sufficient revenue to cover the full costs of operations – airports are essentially decreasing cost entities where cost recovery can be difficult especially in a situation where there is competition from other airports. This makes pure privatization options less tenable and the need for outside assistance from aid agencies or from government more relevant. Private/public partnerships offer another alternative. The wide variety of circumstances around the world has led to a diversity of approaches to commercialization of airports. Some have involved complete divestiture of former state assets to the private sector, albeit normally with some continuing oversight of how the airport is operated, but in other instances the withdrawal of the state has been less complete. Table 2 provides some insights into the various options that are available and gives examples of changes in governance that have occurred. The management contract approach retains government control but contracts out air port activities for periods, normally by some form of auction, specified elements of airport services; parking, hotels, retail concessions, etc. The system is very much in line with the notion of “competition for the market.” Long-term contracting involves giving over, following a tendering process, the operational side of an airport, sometimes including investment commitments in additional capacity, for an extended period with the authorities retaining a degree of strategic control. The degree of financing required normally entails bringing specialized international companies with the expertise to man age an airport, or system of airports, together with financial houses that can provide Table 2 Types of Airport Governance Form of governance Control device

Management contract Periodic tendering

Long-term contracting Rate-of-return regulation

Rate-of-return regulation plus market for corporate control

Management responsi bility Time frame

Operational

Operational and financial

Operational, financial, and strategic

5–10 years

15 plus years

Examples

Management concessions • Burbank (5 years) • Indianapolis (10 years) • Westchester, New York (10 years)

Build-operate-transfer • Toronto Terminal 3 • Ataturk Long-term lease • Bolivia (3 airports for 25 years) • Argentina (33 airports for 30 years) • JFK New York Termi nal 4 (30 years) • Macao (33 years)

99 year lease or indefinite Initial public offerings (IPOs) • UK – BAA (100%) • Vienna (27%) • Copenhagen (25%) Trade sales • Sydney (100%) • Auckland (25%) • Naples (30%)

Source: Carney and Mew (2003).

Full/part privatization

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the necessary support for large scale service activities. These types of concessions are widespread in South America where local expertise and finance is limited but there is a reluctance for the state to divest itself of aviation assets. Many developed countries have also pursued similar philosophies when expanding the involvement of private enterprise, but falling short of the complete divestiture favored by the UK. Many US airports have adopted various concessionary schemes – for example, Boston, Pittsburgh, and Reagan National Airport, Washington have entered into con cessionaire agreements, for the entire operations at Pittsburgh and for specific terminal buildings at the other airports. At Chicago O’Hare airport, parking has been contracted out, and the Port Authority of New York and New Jersey that own a number of airports have a variety of agreements covering such things as the operation of terminal buildings and the supply of heating and cooling at some of its facilities. US airports in general also practice considerable unbundling of activities and there is, for example, a tradition of significant airline involvement in providing check-in facilities and baggage systems. Complete privatization of major airports is uncommon, although some of the larger facilities are now in private hands. In most cases there is concern that a privately owned airport will exercise its monopoly power to extract rent from customers and thus regulatory controls. The challenges are to device and operationalize appropriate regulatory regimes to monitor and direct these large companies in the public interest – often price-capping is deployed.11 The on-going debates about full privatization concern such things as whether single airports, or as with the UK’s BAA, systems of airports, should be privatized and when they are privatized what should be regulated; should it be all airport activities or just those directly aviation related? In their overview of these various governance options, Carney and Mew (2003) focus correctly on the government being involved in both seeking to improve the efficiency of their airports but at the same time trying to direct the gains to particular groups rather than leaving management with full autonomy in their actions.12 This involves complexities that, while common to businesses in developed countries, are unfamiliar in many parts of the world. As a result, this has added to the growth in international firms specializing in airport management, including ownership, to allow the development of common, best-practice methods of operation while at the same time being innovative in creating bespoke models for different circumstances.13

11

For expositional reasons, a more general discussion of the theory behind regulation of monopoly infras tructure suppliers is reserved until we deal with ANSP commercialization. The evidence regarding airports is that rate-of-return regulation has not proved successful in Germany (Kunz and Niemeier, 2000), while the price-capping regime is seen as inappropriate for London (Beesley, 1999). A particular issue in the UK is whether the price-cap should be applied to the entire set of activities of the BAA (the “one-till approach”) or whether airside activities should be separated out and be regulated (the “two-till approach”). For details see Starkie (2001). 12 The authors do not, however, spend much time on situations where state-controlled activity of an existing activity is retained but is opened up to private sector competition – for example, the requirement in the EU for airport ground handling to be open to competition. Nor do they consider situations where a large state system, such as that former found in Canada, is divided up between smaller units, largely municipalities in the Canadian case with competition allowed to develop between them. 13 Freathy (2004) offers a similar type of breakdown but focuses more on the role of commercial activities at airports in his analysis.


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3.2 Air Navigation Systems Provision The majority of the world’s ANSPs have traditionally been state owned and operated with objectives akin to those of public utilities; safety, common carrier obligations, allocation by need, etc. Recent trends from the mid-1990s have seen moves to engender more commercial approaches to the supply of ANSs (Charles and Newman, 1995). Table 3 provides details of the existing ownership structures of 11 major ANSPs together with some information of when structures have been created and modified. The economic institutional structures in which they operate vary by form of ownership and by the nature of prevailing rate controls – see Button and MacDougall (2006) for more details. From a financial risk-taking perspective, there are also differences as to whether State Table 3 Basic Features of Selected Air Navigation Service Providers Country

ANSP Name

Ownership

Rate Regulation#

Australia1

Airservices Australia

Government corporation

Commission oversight

Canada∗

NAV CANADA

Not-for-profit private corporation

Legislated principles/appeals

France∗∗

Direction des services de la navigation Aérienne (DSNA)

State department

Approved by transport ministry

Germanyç

Deutsche Flugsicherung Government GmbH (DFS) corporation

Approved by transport ministry

Ireland§

Irish Aviation Authority

Government corporation

Regulatory commission

Netherlands¶

Luchtverkeersleiding Nederland (LVNL)

Not-for-profit Approved by transport government corporation ministry

New Zealandy

Airways Corporation of Corporation New Zealand

Self-regulating/appeals

South Africa

Air Traffic and Navigation Services Ltd

Not-for-profit joint-stock corporation

Transport ministry committee

Switzerland¥

Skyguide

Not-for-profit Approved by transport government corporation ministry

United Kingdom� National Air traffic System, Ltd

Public/private partnership

Price capping

United States

State department

Financing from taxation

FAA’s Air Traffic Organization

Corporatized in 1988; ∗ Corporatized in 1996; ∗∗ Consolidated in 2003; ç Established in 1993 and was to be privatized in 2006 but since aborted; § Corporatized in 1993; ¶ Corporatized in 1993; yCorporatized in 1987; ¥ Incorporated in 2001, predecessor established in 1921 � Public/private partnership in 2001; # Excluding national, generic anti-trust and similar regulations. ALL ANSPs are financed by user fees except for the US Federal Aviation Administration that is funded by taxation. Source: Button and Dougall (2006). 1

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debt guarantees are offered; they are not except in the cases of Australia, France and Switzerland – the issue is not applicable in for the US where taxes are the current mode for finance. There has been a gradual but perceptible shift away from state ownership with a variety of institutional structures emerging. Ownership is clearly, from the political economic perspective, not seen as a neutral matter (Button and McDougall, 2006). Corporatization has become a popular option to distance government from the operations of ASNPs and their financing, although the formulation varies; in some case it involves a the creation of a free-standing entity whereas in others the undertaking is linked to the state. This can be seen as a reflection of wider national approaches to the topic with some countries having a tradition of preferring particular types of corporate entities and have experiences of their workings. In some cases there are explicit rate-of-return conditions – namely non-profitability – built into the terms under which the corporation is established. Rate-of-return regulation in various guises was a characteristic of US industrial policy and that of many other countries until the 1980s. It largely became discredited because of manifest evidence of X-inefficiency when it has been applied and the longer terms effects of over capitalization that accompanied it – the so-called Averch–Johnson effect.14 The X-inefficiency arises largely because of the ability of the regulated enterprise to capture the system through control over information flows about costs and allowed them to enjoy significant inert areas without the pressure for full cost efficiency. The Averch–Johnson effect comes about because rate-of-return regulation creates a bias that leads to excessive capital intensity. Nevertheless, a number of countries now practice an explicit form of rate-of-return regulation (e.g., Canada, Netherlands, South Africa, and Switzerland) over their ANSPs by adopting either private or public “not-for-profit” regulation. New Zealand also practice rate-of-return regulation whereby the ANSP returns money to users once costs have been recovered and an agreed “profit” has been paid to the government. Price-capping, as developed in the UK by Littlechild (1983) for the newly priva tized telecommunications sector has been preferred more recently because of its lower informational needs and because it is directly aimed at minimizing X-inefficiency, both static and dynamic. It entails the setting of a maximum average price across a bundle of outputs that is related to changes in general price levels. In the transport context it is the preferred method for regulating the BAA in the UK, and is now to be applied to the privatized NATS (Goodliffe, 2002; Majundar and Ochieng, 2003) and was to be used as the tool to regulate, the now aborted public-privatization of the German ANSP provider, (Classen, 2007). Whether price-capping is appropriate for regulating ANSPs (or for that matter airports) depends on a number of factors. The simplicity of price-capping diminishes as X-inefficiency is driven from the system; as this occurs it effectively converges on a rate-of-return regulation. But it is also most effective when supply is highly flexible. If there are shortages, as does occur at airports and in air-space because of invisibilities or other rigidities in supply, price should be used as a “con gestion” charge. A price-cap regime to bring down the cost of use over time is not the instrument to use in these conditions and its rigidity reduces the ability to allocate scarce

14

In the particular context of its use for airports, Tretheway (2001) also points to its complexity, high administration costs, and lack of responsiveness.


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supply effectively. Indeed, most of the early advocates of price-capping seem to have viewed it as a short-term expedience where there was rapidly expanding capacity and while genuine competition built up; hence its use in telecommunications and energy. Other countries have adopted less structured forms for regulating their ANSPs. Some have commissions that monitor the rates that are levied; a government ministry fulfills this role in a number of cases. In the case of Canada, there are appeals procedures that effectively lead to regulation by a judicial process that can review changes in the rates levied by ANSPs to assess whether they violate a set of specific charging principles. The Australian Competition and Consumer Commission that regulates the prices of Airservices Australia does not have powers of price-capping, but only of giving opinions as to the appropriateness of the price increases. In South Africa the ANSP is prohibited from levying or increasing an air traffic service charge unless it has permission from the Economic Regulatory Committee. New Zealand and Ireland largely leave it to the market. Financing investment in expanding and modernizing ATC systems also takes a variety of forms. The US’s Federal Aviation Administration (FAA) is largely funded from a variety of taxes, notably the federal ticket tax and the federal flight-segment tax, with no explicit user charges being levied. It has no access to the private capital market.15 The French ANSP provider operates in a more commercial way by levying user charges and by having recourse to the private capital market, although there is oversight as to investment levels. NATS, DFS, NAV Canada, and Airservices Australia, for example, borrow extensively in the market.

4 IMPACTS OF COMMERCIALIZATION The extent of commercialization of air transportation infrastructure, albeit in a variety of ways, has been seen to be growing but it is still limited in many countries. Perhaps more of a problem from an analytical perspective is that most of the change is relatively recent, and economic data to study it is sparse and not always of prime quality.16 Unlike airline markets it takes time for changes in infrastructure institutions to have their full effects felt; there is thus a need for fairly long and consistent sets of data. There has also been a lot of experimentation that where initial problems have arisen, it has resulted in further institutional reforms being initiated. Separating out the effects of individual elements of such iterative actions is challenging. And overriding all of this, the air transportation market has, or at least one hopes it has, not been typical in recent times due to the unprecedented collapse in demand after the events in the US of September 2001.

15

Gloaszewaki (2002) outlines the nature of the US ANS and also gives a comparative analysis of the interactions between ANSP and airport regulations in the US and Europe. 16 Although privatization often forces providers to adopt standard accountancy conventions, rather than the ad hoc systems used by public entities, commercial confidentiality generally means that companies release less data. Some databases are being developed. For example the Air Transport Research Society does a worldwide survey of airports but participation is far from complete and the data itself poses problems – for example, there are erratic changes in the ranking of airports.

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4.1 Airports The diverse ways in which commercialization has been introduced to airport activities, and the numerous objectives motivating them, combined with the large number of elements that make up airport services makes it difficult to come to firm conclusions about the success of recent changes. Added to this, there has always been considerable variation in the levels of efficiency even among the state owned airports and in their reported financial positions. The subject of the relative efficiency of different governance models has, however, attracted quite a lot of recent interest from academics and policymakers, in part because economic data, albeit not always completely sound, are now becoming available for analysis and because techniques for looking at relative efficiency of multi-product undertakings, such as data envelopment analysis (DEA), are now much easier to apply with the advent of appropriate computer software suites. Table 4 provides brief details of some of the main academic work that has been done looking at various efficiency aspects of airport commercialization around the world. It is not an exhaustive listing, there is inevitably a large gray literature on the subject in the hands of the financial and management interests participating in the commercialization process, and the brief table inevitably does not do justice to the various studies that are reported. Most of the work focuses on privatization, either in a time-series context of before-and-after analysis or in a cross-sectional framework comparing privatized with state-owned airports. Much less work has been done on changes in regulatory regimes, outsourcing of some airport activities, or on the transitional effects of moving to a more commercialized governance structure. While the quality of the analysis inevitably varies because of data constraints (airports use a diversity of methods for cost accounting), the statistical or programming method ology adopted, the detailed nature of the commercialization measures, and the simple quality of scholarship applied, the general picture that emerges is that commercialization often does lead to the more efficient provision of airport services, albeit with a range of caveats. In many cases, for example, changes in governance are important but are overshadowed by other changes that are taking place such as increased traffic levels and the amount of traffic hubbing at an airport.17 Taking a conservative position, what the studies do show is that the introduction of commercial pressures, almost irrespective of their nature, certainly does not decrease the efficiency of airports and would, on average, seem to act to increase it. What perhaps this type of table misses are the nuances of individual situations; as the saying goes “The devil often lies in the detail.” The privatization of the UK’s main airports, and especially those around London, for example, seems to have met the main criteria of generating revenues for capacity enhancement, but issues remain about the role of regulation (whether it should continue to only cover air operations charges) and over the single authority ownership of three large airports in the area. Concessions, in their diverse forms, are now a popular form of injecting private finance into airports and of stimulating a more commercial approach to their management. They

17

From a commercialization perspective, findings regarding the underlying economic nature of airports should not be discounted. Studies, for example, do indicate economies of scale exist and this, in itself, is important to public authorities seeking the appropriate way to structure a commercialization strategy.


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Table 4 Studies of the Impacts of Airport Institutional Reforms Study

Case

Topic

Findings

Juan (1995)

10 airport case studies

Institutional comparison of approaches being adopted towards privatization including 6 lower income countries

Privatization is more efficient that corporatization; the need for different approaches to profitable and unprofitable airports; the specification of concession contracts needs to be carefully thought through

US General Accounting Office (1996)

Airports in 50 countries

Looking for lessons for US privatization

Limited evidence regarding performance although privatized facilities generated more revenue

Parker (1999)

BAA

Pre- and postprivatization DEA analysis

Found privatization had no impact on technical efficiency

Serebrisky and Presso (2002)

Argentinian airports

Considered the vertical integration between airport and airline in a concession arrangement

Vertical integration can lead to market distortions as there are not appropriate regulations to control monopoly powers

Hooper (2002)

Asian airports

Financial aspects of privatization

There is a need for an appropriate set of controls to be established before airports are privatized

Forsyth (2002)

Australia and New Zealand airports

Institutional analysis of reforms

Australia: Problems of handling investment decisions when there is price capping. New Zealand: Despite lack of regulation acting as if there were rate-of-return controls

Niemeier (2002)

Hamburg airport

Examination of efficiency of regulatory reforms

Price-capping is superior to rate-of-return regulation

Bosch and García-Montalvo (2003)

Latin America airports

Review of issues of nondiscriminatory access to airports using secondary sources

The problems of Latin American airports are ultimately similar to many of those being encountered in the European Union

Forsyth (2003)

Australian airports

Replacement of price caps by price monitoring

Unclear as to the effects on long-term changes

Holvad and Graham (2003)

UK airports

DEA of relative efficiency of privatization

Privatization increased efficiency

(Continued)

KENNETH BUTTON

186

Table 4 Studies of the Impacts of Airport Institutional Reforms—Cont’d Study

Case

Topic

Findings

Hanaoka and Phomma (2004)

Airports in Thailand

Comparison of fully state owned and partially privatized airports

No clear-cut difference in productivity due to ownership

Oum et al. (2004)

Airports from around the world

Assessment of economic regulation regimes using factor productivity analysis

Rate-of-return regulation leads to excess capacity; price-capping leads to under investment

Pacheco et al. (2006)

Brazilian airports DEA to look at efficiency of managerial changes in the lead-up to privatization

The performance of Ifraero improved as it prepared for privatization

Lin and Hong (2006)

20 large airports from around the world

DEA analysis to examine importance of ownership on efficiency

Ownership has little impact on an airport’s efficiency

Andrew and Dochia (2006)

Global privatization initiatives

Statistical analysis of airport privatization in low and medium income countries

The preferred institutional structure involves concessions rather than divestiture

Vogel (2006)

European airports

Analysis of cost efficiency and financial performance of privatized airports

Generally, privatized airports are more cost efficient but do not earn a higher return

Vogel and Graham (2006)

31 European airports

Examination of factors affecting performance using DEA analysis

Ownership status affects economic performance

Oum et al. (2006)

Large airport around the world

Regression analysis to look at productivity differences

Evidence that airports with majority government ownership leads to less efficiency

Lipovich (2007)

Argentinean airports

Concession issues

Difficulties emerged in the concession allocation process that led to an unrealistic financial structure

Low and Tang (2006)

Asian airports

Degree of factor substitution as outsourcing takes place

Outsourcing has allowed airports to become more adaptive to cost changes


187

have generated different types of challenges that have been the subject not only of qualitative analysis as seen in Table 4, but also of wider institutional work. The number of different forms that concessions take make generalizing problematic; not only are they for different time periods but they may allow or disallow for public sector or foreign participation, may be for a single or for a group of airports, may involve commitments for investment, etc. Nevertheless, experiences do provide insights. There are often problems in meeting the terms of concessions. In 1998, for example, Argentina gave a 30-year concession, with a possible 10 extension, to a single consor tium, Aeropuertos Argentinia 2000 to run 32 of its main airports. A commitment to major investments in the system was part of the agreement but also was a large annual payment ($171.121 million in 1998 prices and up-dated periodically for inflation) that has proved difficult to meet at approved fee levels. This has led to renegotiations and suggestions that the initial concession arrangements were flawed and expectations were unrealistic. There is also significant political risk in some cases. In Venezuela, the responsibility for airports has been transferred from central to state governments and the latter that have then engaged in trying to bring in private finance. In 1992 three airports in Zulia state were privatized but then subsequently taken back by the governor after a change in the state government.

4.2 Air Navigation Service Providers Compared to airports, there have been relatively few attempts at full privatization of ANSPs, although efforts to make them more commercially accountable are more widespread. The experiment in the UK with the NATS public–private partnership is too recent to pass substantive comments on, although the need to refinance it almost imme diately after its initiation following the September 11 attacks does suggest that quite high levels of capitalization may be required to avoid major, unexpected financial “hits.”18 The same problems arise with the various efforts to corporatize airports as not-for-profit entities; essentially a form of government or private sector business subject to zero rate of return regulation. The main ones are relatively new and found it difficult to balance their books after 2001 when with very limited reserves they were confronted with falling traffic but significant fixed costs to recover. Recent political and academic interest in making ANSPs more commercially oriented has come largely from the US, where the system under FAA control has met with criticism and is, in 2007, due for review, and from the European Union, where there are policies to bring together the disparate national providers within a more structured framework – a Single European Skies. The main concern in EU and its associates has only marginally involved commercialization issues – there are more basic challenges in developing a coordinated ANS currently embracing 34 ANPS. Indeed, this focus is reflected in the detailed benchmarking done by EUROCONTROL (2006) that involves considerable analysis of the complexities confronting various ANSs and provides a four

18

NATS initially had a 115% debt gearing.

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level ranking of cost-effectiveness but makes no comment on the implications of the various forms of governance covering the different systems. Much of the quantitative work on ANSP commercialization has been cross-sectional in approach – there is simply not enough long-term data to conduct time series analysis. It has also tended to lack any real statistical rigor because of data constraints. Studies of five ANSPs by the US Government Accountability Office (2005a,b) suggests that commercialization was particularly effective in allowing systems to finance and carry through modernization programs. Findings supported in a larger study of 11 systems from around the world by Button and McDougall (2006). Indeed, it was this need for financing modernization that motivated the formation of the NATS public–private partnership structure in the UK (UK House of Commons Committee of Public Accounts, 2002/3); the state owned undertaking could only cover about half of its investment needs from operating revenues. One reason for this improved financing is the greater flexibility non-state owned can enjoy in gaining funds but still at a relatively low cost – privatized and corporatized systems typically enjoy very high credit ratings, although often less than for state owned entities going to the capital market. Government debt guarantees can reduce the costs of borrowing for privatized and corporatized ANSPs (Magdalena, 2005). DFS the German provider and Airservice Australia, for example, have their debt guaranteed and enjoy exceptionally high credit ratings (although they do also have very conservative financial portfolios).19 The impact of commercialization on costs incurred by the ANSPs and, subsequently on users of the systems, provides the ultimate test for economic efficiency. There is, however, little rigorous econometric analysis exploring links between governance structure and the fees paid for ANSs. Button and McDougal, albeit limited to basic data analysis, find some evidence suggesting that there is less “gold-plating” when there is commercial pressure on suppliers, with investment tending to be reigned in. As seen in Figure 2, the pattern of rates charged over time by various ANSP providers reveals falling generally rates until 2001 when rates rose to permit fixed cost recovery from a considerably reduced traffic volume.20 There is little consistency in the patterns that emerge for the various types of governance regime; perhaps an inevitable situation over has been a relatively short and volatile time period. Other indicators of performance suggest that commercialization has not led to any deterioration in service quality. All the providers examined by the US Government Accountability Office and by Button and McDougall significantly increased the traffic that they handled in the early years of the twenty-first century, and in the case of the commercialized entities, without any increase in air traffic management induced delays; indeed the state owned FAA seems to have encountered the biggest problems in this area since traffic has picked up in the aftermath of the events of September 11th and the SARS fears.

19

Strong and Oster (2007) looking at the US’s FAA, NATS, and NAV Canada, and find that although the governance models are very different they all “appear to have more sustainable business models and organizational structures to meet the challenges of air traffic management in coming years.” 20 This, of course, goes against what one wants in these circumstances when there is a need to counteract falling demand with lower input prices to the air transportation market.


189

140 130 SkyGuide

120

Airservices Australia

110

Airways NZ

100

DFS

90

NATS U.K.

80

Irish Aviation DSNA

70

LVNL

60 50 1997

1998

1999

2000

2001

2002

2003

2004

Year Note: All data based on 1997 except for NATS UK 2001 = 100. (a) En route unit rates 180 160 SkyGuide

140

Irish Aviation

120

LVNL Airservices Australia

100 80

DFS

60 40 1997

1998

1999

2000

2001

2002

2003

2004

Year Note: Initials as defined in Table 3. (b) Terminal unit rates

Figure 2 Charges for En route and Terminal Services in Constant 2004 Prices.

5 CONCLUSIONS Air transport is now an important mode for the international and, in many countries, domestic carriage of people and cargo. Reforms in the airline services market, to inject more commercial vitality into the sector, have largely proved beneficial; but devel opments regarding airports and ANSs have been slower to materialize, piece-meal in nature, and often only partial in their coverage. This is not atypical in the sense that in many other sectors where commercialization has been fostered, the infrastructure elements have been the last to be reformed. As we have seen, changes are now taking place and they have taken a variety of forms. One may see this as experimentation but

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equally, it may be seen as tailoring institutional structures to local politico-economic realities. Studies are still not conclusive as to the verdict offered on the reforms. Infrastructure is by its nature fixed and changing the way it is provided and operated inevitably has limited short-term impacts. The airport experiences suggest that there are numerous ways to make providers more commercially oriented, and that this may be done in a bigbang approach by throwing the entire enterprise directly into the market or piece-meal and gradually by unbundling services over time and allowing these to be subjected to market in turn. The network nature of ANSs makes this more difficult, although some countries do employ concessionary arrangements for putting commercial pressures on the provision of tower services and the supply of equipment. Perhaps one last point to make is that much of the public and political debate about commercialization of air transportation, both airlines and infrastructure, has focused on the potential safety implications of relaxing economic regulation or of privatization. The one solid thing that has emerged from a wide range of studies is that safety has not been adversely affected by any of the institutional changes – the privatized and corporatized systems have no worse safety record than those in government ownership. Indeed, by most measures air transportation has become safer over time because of improved technology and any recent commercialization initiatives do not seem to have affected this trend. One reason for this has been parallel initiatives to improve safety oversight and to initiate the introduction of new, safer technologies as they have come on-line. The policy-makers seem to have been very successful in separating the impacts of economic reforms from those of a more social nature. Another factor is that privatized or commercialized providers have market incentives to ensure safety standards are met; any accident will almost inevitably affects their financial returns.

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Pacheco, R.R., Peixoto de Sequeire Santos, M. and Fernades, E. (2007) The performance of Brazilian airports based on management style, Journal of Air Transport Management (forthcoming). Parker, D. (1999) The performance of BAA before and after privatization: a DEA study, Journal of Transport Economics and Policy, 33, 133–146. Pels, E., Nijkamp, P. and Rietveld, P. (2003) Inefficiencies and scale economies of European airport operations, Transportation Research E, 39, 341–361. Poole, R. (2005) Commercializing air traffic control: a new window of opportunity to solve and old problem, Regulation, 20, 1–12. Robbins, L. 1932, An Essay on the Nature and Significance of Economic Science, Macmillan, London. Serebrisky, T. and Presso, P. (2002) An Incomplete Regulatory Framework? Vertical Integration in Argentine Airports. 37th Meeting of the Argentine Political Economy Association. Starkie, D. (2001) Reforming UK airport regulation, Journal of Transport Economics and Policy, 35, 119–135. Strong, J. and Oster, C (2007) Air Traffic Management under Stress: The Performance of Air Navigation Providers in Canada, Britain, and the United States, paper to the 11th World Con ference on Transport Research, Berkeley. Tretheway, M.W. (2001) Airport Ownership Management and Price Regulation, Report to the Canadian Transportation review Committee, Ottawa. UK House of Commons Committee of Public Accounts (2002/3) The Public Private partnership for National Air Traffic Services Ltd, The printing Office, London. US General Accounting Office (1996) Airport Privatization: Issues Related to the Sale or Lease of US Commercial Airports, GAO/T-RCED-96-82 GAO, Washington DC. US Government Accountability Office (2005a) Air Traffic Control: Preliminary Observations on Commercialized Air Navigation Service Providers, GAO-05-542T, GAO, Washington DC. US Government Accountability Office (2005b) Air Traffic Control: Characteristics and Perfor mance of Selected International Air Navigation Service Providers and Lessons Learned from their Commercialization, GAO-05-769, GAO, Washington DC. Vogel, H.-A. (2006) Airport privatization: ownership structure and financial performance of European commercial airports, Competition and Regulation in Network Industries, 2, 139–162. Vogel, H.-A. and Graham, A. (2006) A comparison of alternative airport performance measurement techniques: a European case study, Journal of Airport Management, 1, 59074. Williamson, O. (2000) The New Institutional Economics: taking stock, looking ahead, Journal of Economic Literature, 38, 595–613.


8 The Role of Regional Airlines in the US Airline Industry Silke Januszewski Forbes∗ , Mara Lederman†

ABSTRACT We describe the role of regional or commuter airlines in the US airline industry. Most major carriers subcontract service on low-density short and medium-haul routes to regional airlines which operate as separate companies. We describe the history of these regional airlines and their growing role for passenger traffic in the last decade. We explore the organizational relationships between majors and regionals and the contribution of the regional jet to the growth of regional airline service.

1 INTRODUCTION In 2005, US regional airlines – carriers which operate aircraft with fewer than 90 seats – carried almost 135 million passengers or approximately one in five domestic travelers. They completed over 14,000 daily departures and had a combined fleet of over 2,700 aircraft. Regional airline service has increased steadily over the past decade and there are no indications that this trend is likely to slow. Yet, despite the increasingly important role played by regional airlines, this segment of the industry has received surprisingly little attention from airline economists. Indeed, the academic literature has traditionally focused on the roles of large network carriers and, more recently, the so-called “low-cost carriers”, leaving regional airlines virtually untouched. This chapter documents the role

∗

Department of Economics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 0508, USA. E-mail: [email protected] † Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario, Canada, M5S 3E6. E-mail: [email protected]

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and extent of regional air service in the US commercial aviation industry and introduces some of the key economic issues that affect regional airlines. The organization of the chapter is as follows. In Section 2, we discuss the role of regional airlines and document the extent of regional airline participation in the industry. In Section 3, we discuss the history of regional airlines, tracing their origins to the small, unregulated air taxi operations that served small communities during the pre-deregulation era. Section 4 discusses the nature of the relationship between regionals and the major car riers with which they partner and highlights some of the organizational economics issues that these relationships raise. Section 5 describes the emergence and diffusion of the regional jet (RJ). A final section briefly speculates on the future role of regional airlines.

2 THE ROLE OF REGIONAL AIRLINES In the United States, regional airlines operate short- and medium-haul scheduled airline service, often connecting smaller communities with larger cities. Almost all regional airlines operate under codeshare agreements with one or more major carriers.1 Under these agreements, the regional operates flights on behalf of the major carrier, who markets and tickets these flights under its own two-letter flight designator code. Typically, no tickets are sold under the regional’s own code. In addition to using the major’s code, the regional’s flights also share the major’s brand. For example, the regional’s planes are painted in the major’s color schemes, the regional’s flight attendants wear the uniforms of the major, passengers traveling on the regional earn the major’s frequent flyer points, and the regional uses the logos, trademarks and even the name of the major (e.g., regional airline Comair operates for Delta under the name Delta Connection).2 To facilitate passenger connections between the regional and the major, the schedules of the regional and its partner are coordinated – in fact the regional carrier’s schedule is often dictated by the major carrier. Check-in and baggage handling are also coordinated so that passengers need only check-in and check their luggage once, at the start of their trip. Majors subcontract service to regional airlines because regionals have a cost advantage on the types of routes that they serve. Table 1 compares several characteristics of routes served by majors themselves with characteristics of routes served by majors via their regional partners. We only use routes under 1,500 miles for this comparison because the type of aircraft flown by regionals have shorter ranges than the type of aircraft flown by majors. As the data in the table suggest, majors tend to use regionals to serve routes that involve at least one very small endpoint, measured either by the number of flights the major operates from the endpoint or by the population of that endpoint. In addition, majors tend to use regionals on low-density routes. Indeed, the average number of passengers flying a regional’s route in a quarter is about one-fifth of the average number flying a major’s route. Finally, even limiting the sample to routes less than

1

In 2003, 99% of regional airline passengers traveled on flights that were codeshared with a major carrier. Note that this is different from the type of codeshare arrangement typically negotiated between two major carriers, such as United Airlines and Lufthansa. Under that type of agreement, both carriers will sell tickets under their own codes for a given flight and the flight carries the identity of the operating carrier. 2

THE ROLE OF REGIONAL AIRLINES IN THE US AIRLINE INDUSTRY

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Table 1 Characteristics of Routes (

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