Financial markets, credit constraints, and investment in rural Romania, Volumes 23-499 issue 499

WORLD BANK TECHNICAL PAPER NO. 499 Europe and Central Asia Environmentally and Socially Sustainable Development Series...

Author: Rodrigo Chaves | World Bank

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WORLD BANK TECHNICAL PAPER NO. 499

Europe and Central Asia Environmentally and Socially Sustainable Development Series

Financial Markets, Credit Constraints, and Investment in Rural Romania

Rodrigo A. Chaves Susana Sanchez Saul Schor Emil Tesliuc The World Bank Washington, D.C.

Copyright © 2001 The International Bank for Reconstruction and Development/THE WORLD BANK 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. All rights reserved Manufactured in the United States of America First printing April 2001 1 2 3 4 04 03 02 01 Technical Papers are published to communicate the results of the Bank's work to the development community with the least possible delay. The typescript of this paper therefore has not been prepared in accordance with the procedures appropriate to formal printed texts, and the World Bank accepts no responsibility for errors. Some sources cited in this paper may be informal documents that are not readily available. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) and should not be attributed in any manner to the World Bank, to its affiliated organizations, or to members of its Board of Executive Directors or the countries they represent. The World Bank does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The boundaries, colors, denominations, and other information shown on any map in this volume do not imply on the part of the World Bank Group any judgment on the legal status of any territory or the endorsement or acceptance of such boundaries. The material in this publication is copyrighted. The World Bank encourages dissemination of its work and will normally grant permission promptly. Permission to photocopy items for internal or personal use, for the internal or personal use of specific clients, or for educational classroom use, is granted by the World Bank, provided that the appropriate fee is paid directly to Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, U.S.A., telephone 978-750-8400, fax 978-750-4470. Please contact the Copyright Clearance Center before photocopying items. For permission to reprint individual articles or chapters, please fax your request with complete information to the Republication Department, Copyright Clearance Center, fax 978-750-4470. All other queries on rights and licenses should be addressed to the World Bank at the address above or faxed to 202-522-2422. ISBN: 0-8213-4928-7 ISSN: 0253-7494 Rodrigo A. Chaves is a lead financial economist in the Europe and Central Asia Region at the World Bank. Susana Sanchez is a financial specialist in the Latin America and the Caribbean Region at the World Bank. Saul Schor is an operations analyst in the Europe and Central Asia Region at the World Bank. Emil Tesliuc is an economist in the Europe and Central Asia Region at the World Bank. Library of Congress Cataloging-in-Publication Data . Financial markets, credit constraints, and investment in rural Romania / Rodrigo Chaves --- [et al.] p. cm. — (World Bank technical paper ; no. 499. Europe and Central Asia environmentally and socially sustainable development series) Includes bibliographical references. ISBN 0-8213-4928-7 1. Rural credit—Romania. 2. Financial institutions—Romania. 3. Investments—Romania. I. Chaves, Rodrigo, 1961- II. World Bank. III. World Bank technical paper. Europe and Central Asia environmentally and socially sustainable rural development series. HG3729.R62 F56 2001 332.7’0948’091734—dc21 2001023605 CIP

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Contents Foreword..................................................................................................................................vi Abstract...................................................................................................................................vii Acknowledgements ................................................................................................................viii Currency Equivalents..............................................................................................................ix Abbreviations and Acronyms..................................................................................................ix Executive Summary and Introduction..................................................................................... x A. Executive Summary .......................................................................................................... x B. Specific Objectives, Methodology, and Data ................................................................ xxxi C. Organization of the Study ........................................................................................... xxxiv Chapter I: The Rural Economy and its Economic Agents ..................................................... 1 A. B. C. D. E.

The Rural Economy within the Aggregate Economy ......................................................... 1 Agricultural Sector Policies During the Transition............................................................. 3 Rural Employment ............................................................................................................ 4 Rural Households and their Economic Activities ............................................................... 5 Rural Enterprises ............................................................................................................... 8

Chapter II: Rural Financial Intermediaries, Market Shares, Credit Products, and Deposit Services.................................................................................................................................... 13 A. The Financial Sector........................................................................................................ 13 B. The Banking Sub-Sector.................................................................................................. 14 C. Mutual Rural Financial Intermediaries............................................................................. 18 D. Distribution Network of Financial Services ..................................................................... 19 E. Market Shares in Rural Financial Markets ....................................................................... 23 F. Distribution of the Flow of Credit Among Borrowers and Lender Preferences ................. 25 G. Characteristics of Credit Products.................................................................................... 26 H. Participation of Rural Enterprises and Households in Financial Markets as Depositors and Savers ................................................................................................................................... 32 Chapter III: Limited Access to Loans: Weak Supply of and Weak Demand for Loans..... 35 A. Participation of Economic Agents in the Market for Loans.............................................. 35 B. Weak Supply of Credit .................................................................................................... 36 C. The Demand for Loans: An Econometric Model............................................................. 48 Chapter IV: Credit Constraints and Rural Investment ....................................................... 55 A. The Extent of Credit Constraints in the Rural Sector ....................................................... 55 B. Credit Constraints at the Level of Rural Households........................................................ 57

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C. Credit Constraints at the Level of Rural Enterprises......................................................... 58 D. Investment Levels: Is It Where You Are and What You Have or What You Do With It? 64 Chapter V: Policy Options and Possible World Bank Support ........................................... 78 A. B. C. D. E. F. G. H.

General Strategy and Emphasis ....................................................................................... 78 Government Credit Lines ................................................................................................ 79 Improving the Legal and Institutional Environment for Financial Transactions................ 82 Improving the Legal and Institutional Environment for Using Land as Collateral ............ 84 Retail Lending ................................................................................................................. 86 Regulatory Concerns Regarding Chartered Non-Bank Mutual Financial Intermediaries ... 88 Market Development, Balanced Rural Development, and Privatization ........................... 92 Policy Coordination ........................................................................................................ 92

References ............................................................................................................................... 95 List of Tables Table 1 Consolidated Financial Performance of Rural Enterprises in 1997............................... 11 Table 2 Consolidated Financial Performance of Rural Enterprises in 1997 (Adjusted by Inflation)................................................................................................................................... 12 Table 3 Composition of the Romanian Banking Sector, 1996-2000.......................................... 16 Table 4 Non-performing Loans, Provisions, and Capital Adequacy Ratio (1996-2000) ............ 17 Table 5 Consolidated Loans, Deposits, and Loan-to-Deposit Ratios by Agro-region and Population ................................................................................................................................ 22 Table 6 Market Shares of Credit Products ................................................................................ 23 Table 7 Distribution of Loan Amount Disbursed to Rural Enterprises by Type of Lender ........ 25 Table 8 Use of Loans by Type of Lender and Borrower ........................................................... 27 Table 9 Collateral Use by Type of Lender (% of Amount Lent to Households and Enterprises)28 Table 10 Shares of Savings Accounts of Rural Households by Type of Instrument .................. 33 Table 11 Average Amount and Maturity of Deposit Instruments of Rural Households ............. 34 Table 12 Participation in the Market for Cash Loans................................................................ 36 Table 13 Structure of Effective Nominal Interest Rates on Loans for Different Agricultural Activities according to the 1998 Ordinance on Providing Finance for Crop Planting, Maintenance, and Harvesting, and for Livestock Raising and Feeding ...................................... 39 Table 14 Demand for Loans by Rural Households (Probit Model) ........................................... 50 Table 15 Demand for Loans by Rural Enterprises (Probit Model) ............................................ 52 Table 16 The Extent of Credit Constraints ............................................................................... 56 Table 17 Rural Households: Credit Constraints (Ordered Probit Model) .................................. 69 Table 18 Rural Households: Supply of Loans by Type of Lender (Multinomial Logit Model).. 70 Table 19 Rural Enterprises: Supply of Loans (Ordered Probit Model)...................................... 71 Table 20 Rural Households: Investment Decision and Investment Outlays............................... 72 Table 21 Rural Households: Effect of Removing Credit Constraints on Investment Decisions and Investment Opportunities ................................................................................................... 73 Table 22 Rural Households: Investment Decisions for Borrowing and Non-Borrowing Households ............................................................................................................................... 74 Table 23 Decomposition of Investment Decisions between Borrowing and Non-Borrowing Rural Households ..................................................................................................................... 74

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Table 24 Rural Enterprises: Investment Opportunities and Investment Levels.......................... 75 Table 25 Rural Enterprises: Estimated Effect of Removing Credit Constraints on Investment Decisions and Investment Levels .............................................................................................. 76 Table 26 Rural Enterprises: Investment Decisions for Borrowing and Non-Borrowing Enterprises................................................................................................................................ 77 Table 27 Rural Enterprises: Decomposition of Investment Decisions between Borrowing and Non-Borrowing Enterprises ...................................................................................................... 77 Table 28 Romania: Summary Matrix for a Proposed Transitional Directed Credit Program for the Rural Sector (2000-2003).................................................................................................... 81 List of Figures Figure 1 Change in GDP and Agricultural GVA ........................................................................ 1 Figure 2 GDP and Agricultural GVA Growth Rate .................................................................... 2 Figure 3 Rural Households by Farm Size ................................................................................... 7 Figure 4 Credit from Deposit-taking Banks to the Private Sector, 1998 (as percent of GDP) .... 13 Figure 5 Credit to the Private Sector: Transition Economies and Rest of the World, 1998 (as percent of GDP)........................................................................................................................ 15 Figure 6 Population per Bank Branch....................................................................................... 20 Figure 7 Percentage of Localities with Financial Outlets across Population Brackets ............... 20 Figure 8 Average Speed of Disbursement of Loans by Lender Type ........................................ 29 Figure 9 Repayment Problems on Cash Loans ......................................................................... 30 Figure 10 Percentage of Households with Savings Accounts by Per Capita Income Quartile.... 32 Figure 11 Commercial Lending Interest Rate vs. T-Bill Rate vs. Inflation................................ 37 Figure 12 Investment Decisions by Credit Constraints ............................................................. 60 Figure 13 Romania by Agro-Region ........................................................................................ 94 List of Annexes (Annexes available upon request) Annex 1 Annex 2 Annex 3 Annex 4 Annex 5

The Rural Economy in Romania and the Characteristics of Financial Products Credit Constraints and Investment Behavior of Households and Enterprises in Romania’s Rural Areas: An Empirical Analysis The Institutional Framework for Secured Transactions The Profitability of Financial Services in Rural Areas Sampling Design of the Households and Enterprise Surveys

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Foreword Romanian policy makers are justifiably concerned with the performance of financial markets in rural areas because these markets have an important impact on rural growth and poverty. In the absence of sufficient investment capital, the rural economy has experienced difficulty in adjusting to the major policy reforms of recent years, the aftermath of the exchange rate crisis of early 1997, and the strong depreciation of the Leu that has occurred since early 1999. These events require rural enterprises and households to adjust factor proportions, modify output mixes, change their scale of operations, and invest in new technologies. Their success in this endeavor, which depends on the performance of all factor markets, has been hindered by the observed poor performance of financial markets. This report is intended to assist Romanian policy makers as they seek to formulate and implement a market-based rural sector strategy that aims to render rural areas internationally competitive with significantly less incidence of poverty through the establishment of effective private financial markets and intermediaries which will provide access to investment capital and safe deposit services to all segments of the rural population, especially individual farmers, rural microentrepreneurs, and small and medium businesses. The report is the latest addition to a long and growing series of World Bank publications on the former socialist countries of Europe and Central Asia. The unique features of all these publications is their reliance on first-hand empirical information collected through extensive surveys of rural constituencies. Analysis of survey findings enables the World Bank to base its policy dialogue with governments in the region on empirical fact, rendering the Bank’s recommendations more credible and relevant. The new findings for Romanian rural financial markets contained in this report will provide a solid platform for policy discussions with the Government of Romania and supply the many international donors active in the country with essential information for the design of their strategic programs.

Laura Tuck Sector Manager Environmentally and Socially Sustainable Development Eastern Europe and Central Asia Region

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Abstract This report assesses the performance of financial markets in rural areas of Romania based on three (rural household, rural enterprise, and financial intermediary) surveys carried out in 1998, and on other official statistical data covering 1997. The study finds that rural financial markets perform rather poorly in three key dimensions, namely: (a) the degree of access to financial services by rural economic agents (enterprises and households) is very limited; (b) this limited access hinders the ability of these agents to take advantage of the investment opportunities available in rural areas; and (c) these markets failed to allocate (very scarce) flows of credit to those agents with the most profitable investment opportunities. This poor performance is caused by an unfortunate combination of short term circumstances (including high and volatile inflation rates), structural factors (such as an inadequate legal and institutional framework), and government policies and interventions (such as subsidized credit programs for agriculture). In particular, the degree of access to credit services by rural agents is very low because several factors have combined to weaken both the supply of and demand for rural credit. The report presents empirical evidence indicating that this constrained access to credit markets negatively influences the investment behavior of households and enterprises. The report suggests a detailed government strategy to correct the observed shortcomings of rural financial markets and identifies new challenges likely to appear. In particular, the Government could assist in increasing the availability in rural areas of viable, competitively priced, and untargeted credit (and deposits) by improving: (a) its own policies and interventions in financial markets; (b) the legal and institutional environment for financial transactions; and (c) the ability of the financial sector to provide retail financial services.

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Acknowledgements This report was written by Rodrigo Chaves (Lead Financial Economist, ECSSD), Susana M. Sánchez (Financial Economist, LCSFP), Saul Schor (Operations Analyst, ECSSD), and Emil D. Tesliuc (Economist, ECSPF) on the basis of background papers written by Rodrigo Chaves, Heywood Fleisig (consultant), José Pagán (consultant), Nuria de la Peña (consultant), Susana M. Sánchez, Saul Schor, and Emil D. Tesliuc. Peer reviewers of this report were J. Luis Guasch (Sector Manager, LCSFR), Paul Holden (Principal Economist, on leave from the LAC Region), and Jacob Yaron (Senior Advisor, RDV). The report benefited greatly from the comments of Marcelo Bueno (consultant), Kevin Cleaver (Sector Director, ECSSD), Farid Dhanji (Lead Economist, ECSPE), Henry Gordon (Senior Sector Economist, ECSSD), John Kendall (consultant), Kaled Sheriff (Lead Country Economist, ECSPF), Laura Tuck (Sector Manager, ECSSD), and Andrew Vorkink (Country Director, ECC05). The National Commission for Statistics (NCS) contributed significantly to the sample design of the surveys and to the collection of data used in the report.

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Currency Equivalents Currency Unit = Leu US$1 = 8,477 Lei (May 1998) US$1 = 26,160 Lei (January 2001)

Abbreviations and Acronyms BIR CAR CC CENTROCOOP CREDITCOOP FEDERALCOOP MOAFF MFI MOPF NBR NCS SAPARD SFI SRB SREFS SRHFS TFI UNCAR

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International Bank of Religion Casa de Ajutor Reciproc Credit Cooperative National Cooperative Union House of Credit Cooperatives National Federation of Cooperatives Ministry of Agriculture, Food and Forestry Mutual Financial Intermediary Ministry of Public Finance National Bank of Romania National Commission of Statistics Special Accession Program for Rural Development Survey of Financial Intermediaries Small Regional Bank Survey of Rural Enterprises and Financial Services Survey of Rural Households and Financial Services Technology of Financial Intermediation Uniunea Nationala a Caselor de Ajutor Reciproc

Executive Summary and Introduction A. EXECUTIVE SUMMARY The Key Findings This study assesses the performance of financial markets in rural areas of Romania based on three (rural household, rural enterprise, and financial intermediary) surveys carried out in 1998, and on other official statistical data covering 1997.1 The performance of these markets is evaluated in the following dimensions: (a) the degree of access to financial services by rural economic agents (enterprises and households); (b) the influence of this access (or lack thereof) on the ability of these agents to take advantage of the investment opportunities available in rural areas; and (c) the effectiveness of financial markets in allocating (very scarce) flows of credit to those agents with the most profitable investment opportunities. The study finds that rural financial markets perform rather poorly in each of these dimensions and that this poor performance is caused by an unfortunate combination of short term circumstances (including high and volatile inflation rates), structural factors (such as an inadequate legal and institutional framework), and government policies and interventions (such as subsidized credit programs for agriculture). In particular, the degree of access to credit services by rural agents is very low because several factors have combined to weaken both the supply of and demand for rural credit. Lenders avoid rural credit and comparatively few rural agents demand credit (Chapter III). The net result was that about 80 percent of rural enterprises and 80 percent of rural households did not incur any form of debt (loans or suppliers’ credit) from formal or informal lenders during the period covered by the surveys which form the basis of this study (see page xxxi for a description of these surveys). The incidence of borrowing from the banking sector was particularly low as only one percent of households and 14 percent of enterprises borrowed from commercial banks. These enterprises and households operated in all sub-sectors of the rural economy, including agriculture, industry, trade, and services. The study presents empirical evidence indicating that constrained access to credit markets negatively influences the investment behavior of households and enterprises. The presence of 1 The definition of “rural” used in this study corresponds to the legal definition used in Romania, which is an administrative definition. In this sense, the rural areas are comprised of all localities which have not attained the status of “urban.” A law is required to grant urban status to a locality. This somewhat arbitrary convention implies that it is possible to find urban localities with, say, 10,000 inhabitants while some rural localities have up to 80,000 inhabitants. In practice, rural areas are comprised of the entire country minus 200 (mostly large) localities which have been granted urban status by legislative action. References throughout the report to households and enterprises should be understood as rural households and rural enterprises. The report’s empirical findings are based on statistically representative surveys of rural households and enterprises conducted in late spring of 1998 as well as on disaggregated data on the country’s banking sector covering 1997. Thus, the figures contained in the report correspond to those years, unless otherwise indicated. The data sources are fully described below.

Finanacial Markets, Credit Constraints, and Investment in Rural Romania

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such constraints reduces both the number of agents that invested and the amounts they invested. The effect is especially negative at the enterprise level. The bottom line is that profitable investment opportunities are not pursued because of limited access to credit markets. This situation is detrimental because these forgone investment opportunities are among the very few available in rural Romania, an environment not particularly conducive to productive investments anyway. Financial markets fail to allocate credit to the best alternative uses within the rural economy. Lenders allocate significant portions of rural credit to enterprises (as opposed to households) which experience negative net incomes (losses) and which have negative gross cash flows. About a third of all credit went to enterprises with negative profits and about 40 percent to enterprises with negative cash flows during the period covered by the surveys. A related and worrisome finding is that rural enterprises that borrow are not able, in the aggregate, to service their existing debt (see chapter III section B). Moreover, the agricultural and services subsectors need to incur additional debt to service interest payments and amortize the principal amount of their outstanding loans. State-owned enterprises contribute most to this situation in that the negative balances on their consolidated cash flow is large enough to wipe out the net cash surplus generated by the private sector. Romanian policy makers are justifiably concerned with this poor performance of rural financial markets because it has had a negative impact on rural growth and poverty. In the absence of sufficient investment capital, the rural economy has experienced difficulty in adjusting to the major policy reforms of recent years, the aftermath of the exchange rate crisis of early 1997, and the strong depreciation of the Leu that has occurred since early 1999. These events require rural enterprises to adjust factor proportions, modify output mixes, change their scale of operations, and invest in new technologies. Their success in this endeavor, which depends on the performance of all factor markets, has been hindered by the observed poor performance of financial markets. Finally, Romanian rural agents have been, and will continue to be, at a disadvantage when competing with counterparts in European Union countries and the United States where rural enterprises and households have much better access to far superior financial services. Clearly, these problems are not limited to the rural economy. All sectors are likely suffering similar problems because the impediments to efficient financial intermediation identified in this study are common to all financial transactions, regardless of economic sector. The study suggests a detailed government strategy to correct the observed shortcomings of rural financial markets and identifies new challenges likely to appear (Chapter V). In particular, the Government could assist in increasing the availability in rural areas of viable, competitively priced, and untargeted credit (and deposits) by improving: (a) its own policies and interventions in financial markets; (b) the legal and institutional environment for financial transactions; and (c) the ability of the financial sector to provide retail financial services. These three elements should be the core of the short term strategy because they would augment the supply of credit by reducing credit risk and the transaction costs of rural lending. The empirical findings of the study provide strong support for policies aimed at: (a) integrating households into markets and allowing consolidation of land holdings; (b) formulating

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Executive Summary and Introduction

balanced rural development policies (in contrast to focussing on agriculture only); (c) privatizing state enterprises; and (d) privatizing state banks. These findings show that household investment opportunities are positively associated with the degree of connection to markets. Further, enterprises more likely to invest are, everything else the same, in sectors other than agriculture and are totally private. Finally, private banks are more amenable to financing productive investments than are their state-owned counterparts. The next generation of public policy relevant issues on rural finance will likely include two additional elements. (Chapter V provides detailed policy recommendations to deal with them.) The first element will be a likely reduction of the network of bank branches. This reduction may result from the expected privatization or divestiture of the state banks which owned 87 percent of all bank branches. The presence of a network of retail finance will be required to allow for the large redeployment of resources that need to occur for the rural economy to adjust to the policy reforms of the recent years. The second element will be the provision of an appropriate regulatory framework for the estimated 1,400 independent mutual financial intermediaries registered under Law 109/1996. A majority of these intermediaries are domiciled in rural areas. The reasons for concern are that the Government may have assumed important contingent liabilities by chartering them, and that they may constitute a regulatory hazard because they can be used to profitably avoid banking sector prudential regulations. The vacuum that may be left by a retiring state banking sector introduces the risk that these unregulated intermediaries will increase their share of deposits. The three state-owned banks expected to be privatized soon held 80 percent of the deposits of the rural population during the period covered by the surveys. The remainder of this executive summary puts rural financial markets in the context of the rural economy and provides the empirical evidence supporting the above conclusions. The summary follows the same sequence of the five chapters included in the main body of the study. The last two sections of the Executive Summary and Introduction describe the statistical and econometric analyses of the data collected in the three surveys conducted specifically for the study. Chapter I examines the Romanian rural economy and provides a profile of economic agents in rural areas and the context in which rural financial intermediaries operate. Chapter II describes financial intermediaries, their market shares, and their financial products in rural areas. Chapter III examines the roles of demand and supply factors in explaining the limited use of credit services. Chapter IV measures empirically the influence of credit constraints on the investment strategies of households and enterprises. Finally, Chapter V draws conclusions and specific policy recommendations to improve the performance of financial markets in rural areas. The Rural Economy and its Economic Agents Rural areas are important within the Romanian economy. More than half of total employment and roughly a fifth of all incorporated business are domiciled there. The sector is a dual economy in that a formal sector coexists with a large informal economy. The formal sector consists of about 80,000 incorporated businesses, most of which were created after the fall of the centrally planned regime. The informal sector consists mainly of small-scale, subsistence-based farm households which conduct a handful of other informal business activities. The economy of


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these rural households is highly autarchic, is based on low-input production technology, and is largely directed towards self-consumption. Rural households. Most rural households operate with limited integration into market activities and primarily engage in agricultural activities. About 61 percent of rural households were self-sufficient farm households, during the period covered by the surveys, in that they did not: (a) sell any outputs; (b) buy any inputs; (c) hire labor; or (d) rent or buy fixed assets. Seventeen (17) percent had some marginal involvement in markets (less than US$20 of monthly sales), 12 percent had substantial market involvement, five percent had non-farm entrepreneurial activities, and the remaining five percent relied entirely on wages and pension benefits. Farm households. Most farms are small and fragmented. The average farm had 2.1 hectares during the period covered by the surveys, and was subdivided into 3 or 4 plots. In fact, 35 percent of households operated more than four farming plots. About a fifth of all households operated a portion of their landholdings through family associations (17 percent) and very few through agricultural associations (4 percent). Non-farm households. Non-farm entrepreneurial activities are very limited among rural households. Only five percent of households had members who were entrepreneurs outside agriculture during the period covered by the surveys. These members accounted for about two percent of the economically active rural population. Non-farm entrepreneurs had (mostly very small) businesses in all economic sectors (25 percent in trade, 23 percent in the processing industry, 21 percent in transportation, 15 percent in construction, and 10 percent in services). Their business activities tend to be small and informal. In fact: (a) 75 percent employ one or no workers at all; (b) 75 percent had an endowment of assets in their business of less than US$1,775; (c) their average monthly income was US$139, which was higher, nevertheless, than farm entrepreneurs; (d) 40 percent were not registered nor had licenses; and (e) only 27 percent kept formal accounting records of their activities. The formal enterprise sector. The rural economy contained about 80,000 enterprises during the period covered by the surveys.2 The large majority of them were engaged in trade and commerce (62 percent). Agriculture was the main activity for six percent of them. The remaining enterprises were evenly divided between the service sector (15 percent) and in industry and construction (16 percent). Agriculture was the sub-sector which had the majority of assets (57 percent by book value). Trade and industry followed with 21 and 18 percent of assets, respectively. The services sub-sector was the smallest and had the remaining three percent of the consolidated book value of enterprise assets. The large majority of rural enterprises (98 percent of them) were in the private sector and were totally private. These private enterprises were basically small and medium size businesses. 2 This figure includes businesses legally incorporated and which are domiciled in rural areas. It excludes all: (a) enterprises with operations in rural areas but with headquarters in urban areas and Regies Autonomes; (b) enterprises not legally incorporated; (c) branch offices of financial institutions, public administration offices; (d) educational institutions; and (e) health care units. Therefore, some large enterprises which have operations in rural areas but are domiciled in urban localities were not included in the sampling universe for the study.

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In fact, the average private enterprise had US$11,900 of assets at book value and 80 percent of them had less than 5 employees. The participation of the state in terms of the value of enterprise assets was very significant, however, as the two percent of enterprises that had some degree of state ownership controlled more than half of the aggregate book value of the assets of all rural enterprises. This large incidence of state ownership is due mostly to the fact that the state partly owned about a fifth of agricultural businesses and that these agricultural state enterprises were particularly large. Agricultural state enterprises accounted for about one percent of all rural enterprises but controlled about 43 percent of their assets. The aggregate profitability indicators of rural enterprises are rather weak. The aggregate return on equity (ROE) and return on assets (ROA) of Romania’s rural enterprises in 1997 were much lower than inflation (18 percent and 9 percent, respectively, against an annual inflation rate of 155 percent). This poor aggregate performance was mostly caused by the state-owned enterprises which had a negative ROE of 9 percent and of which 53 percent reported losses. In contrast, the consolidated ROE of private enterprises was 69 percent and the share of them which reported losses was 29 percent.3 By sector, agricultural enterprises reported losses while the remaining sectors generated aggregate profits. The trade sub-sector was by far the most profitable in terms of ROE. Cash flow analysis confirms that rural enterprises have, in the aggregate, a profitability problem. The value of the sales (products and services), during the period covered by the surveys, of the entire rural enterprise sector was not sufficient to cover production costs and operational expenses. The state-owned enterprises contributed most to this situation, as their negative cash flow balances were large enough to wipe out the net cash surpluses generated by the private sector. A worrisome implication is that rural enterprises are not able, in the aggregate, to service their existing debts. Moreover, the agricultural and services sub-sectors need to incur additional debt to service interest payments and amortize the principal amount of their outstanding debts. Indeed, banks lent 45 percent of all new credit flows to state enterprises with negative cash flows during the period covered by the surveys. Again, state enterprises were the primary cause of this situation. A likely outcome of lending to state enterprises with negative cash flows is that these loans will have to be assumed by the Government or the banking system. The likelihood of these enterprises returning to a positive cash flow under state ownership is minimal, and privatizing them will be difficult while they have a large debt overhang. Rural Financial Intermediaries and their Market Shares The banking sub-sector. As of 1998, there were 45 banks licensed by the National Bank of Romania, of which 35 were open to the public and operating normally, three had their operations 3 The consolidated financial statements of enterprises were adjusted according to International Accounting Standard (IAS) No. 29 to account for high inflation in the period under analysis. The adjusted financial statements indicate that the consolidated ROE for rural enterprises was 2.4 percent. Private sector enterprises had a consolidated ROE of 16 percent while their state-owned counterparts had a ROE of negative six percent.


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effectively suspended by the regulatory authorities pending reorganization or liquidation, and seven (mostly foreign-owned) were preparing to initiate operations. These banks had about US$ 14 billion in assets (123,744 billion lei). The system was dominated by state banks which accounted for 71 percent of total banking assets and 81 percent of total bank deposits in national currency. Mutual financial intermediaries. As of 1998, there were 840 credit cooperatives that were members of the National Cooperative Union (CENTROCOOP), which operated at the comuna level with a membership of about 1.8 million farmers, professionals, and self-employed individuals. These credit cooperatives had about US$92 million in assets (1,000 billion Lei) and were comparatively small financial intermediaries. The average credit cooperative in Romania had assets of US$110,000 and 3.5 employees. There were also about 4,600 Casa de Ajutor Reciprocs (CARs), of which 400 were in rural areas. These are mutual financial organizations that primarily serve employees of rural enterprises, commercial societies, and state-owned companies. Finally, it is estimated that there were about 600 independent mutual financial intermediaries (Banca Populara) for which information was not available. The distribution network of financial services. Romania possesses an extensive network of retail financial outlets in both rural and urban areas. As of the period covered by the surveys, there were 4,076 retail outlets, 3,156 bank branches, and 840 credit cooperatives for which data were available. this network was also dominated by the state-owned banks, which owned 87 percent of all bank branches in the country. The ownership of the private branches was also highly concentrated in that two banks owned 86 percent of them. Who gave rural credit? Financial markets in rural areas are basically segmented. Friends, relatives, and the semi-formal sector serve households, while the formal financial sector and suppliers of inputs give credit to rural enterprises. Cash-loan transactions are the most important credit product available. For households, these loans accounted for 88 percent of the number of transactions and for 85 percent of the total amount of credit during the period covered by the surveys. For enterprises, cash loans accounted for 48 percent the of number of transactions and for 50 percent of the amount. Romanian rural households rely significantly less than their counterparts in other developing countries on the informal sector. Commercial credit transactions and forward sales are a comparatively small source of credit, accounting for 13 percent and 2 percent of the volume of credit disbursed, respectively during the period covered by the surveys. This scarcity of commercial credit and forward sales is consistent with households’ low levels of market activity and lack of linkages with traders. Commercial and supplier credit played an important role among rural enterprises, accounting for 41 percent of the amount disbursed and 40 percent of the number of credit transactions. The banking sector had a three percent share of the number, and a 16 percent share of the amount, of the transactions involving households during the period covered by the surveys. The banking sector’s share of credit to enterprises was significantly larger. Banks were the lenders in 31 percent of the number of transactions and allocated 50 percent of the amounts of credit received by enterprises. State banks allocated five times more credit to rural enterprises than private banks.

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Who obtained the rural credit actually available? The agricultural sector received 61 percent of the total amount allocated during the period covered by the surveys, while the service sector received 3 percent. Industry and trade received, respectively, 19 and 16 percent. This allocation of credit tracked very closely the shares of these sectors in the aggregate book value of assets owned by rural enterprises. Contrary to the generalized perception in Romania, private banks did not discriminate against agriculture. Indeed, 65 percent of their disbursements went to agriculture − slightly higher than the share of credit that public banks allocated to agriculture (62 percent). Agriculture was also the sector which received the largest share of subsidized credit, obtaining 90 percent of all preferential lending. The private sector received 57 percent of all credit and 45 percent of subsidized loans. State enterprises received the difference, namely, 43 percent of all credit and 55 percent of subsidized loans. Characteristics of the Credit Services Available Amounts. By source of credit, banks provided the largest loans in rural credit markets during the period covered by the surveys. The average bank loan to enterprises (US$17,875) was almost 16 times larger than the average loan disbursed by the informal sector (US$1,137). A similar situation occurred with the credit allocated to households. The average bank loan to households (US$797) was eight times larger than the average loan allocated by friends and relatives (US$173) and about seven times larger than the average loan disbursed by credit cooperatives and CARs (US$99). Maturity of cash loans. The large majority of loans received by rural borrowers were shortterm loans. In fact, 93 percent of the loan transactions entered into by households had to be repaid in less than a year. The corresponding percentage for enterprises was 85 percent. Bank loans had the longest average term to repayment at 16 months. This average increased to 20 months when weighted by amount, as larger bank loans tended to have longer terms. Use of loan proceeds. Most of the enterprise loans were reported to have financed working capital (87 percent) and most of the household loans were reported to have financed consumption and household durable assets (53 percent). By amount, 29 percent of the loans received by enterprises were used to finance investments, while the equivalent percentage of the loans received by households was 17 percent. Collateral and guarantees. Romanian rural financial markets rely significantly on real assets as collateral for loans. Naturally, there is a large number of small loans guaranteed only by fiduciary contracts and verbal promises. These loans accounted for about a third of the aggregate amount and were granted by the informal and semi-formal sectors during the period covered by the surveys. The remaining two thirds of the value of rural loans were secured with tangible assets by pledges on movable assets, mortgages on real state, or both. Indeed, about half of the amount of secured loans was guaranteed by a pledge on movables and a mortgage simultaneously. When tangible assets are used as collateral for loans, the ratio of the market value of the pledged assets to the amount of the loans (collateral/loan) is very high. The average value of


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these assets was four times the amount borrowed during the period covered by the surveys. This seemingly excessive protection of loans was due in part to the costly and lengthy processes involved in repossessing assets pledged as collateral and to the lack of liquidity of rural real estate. The use of farm land to secure loans is also extremely low. The use of land as collateral was impossible during the period covered by the surveys because, until late 1998, transactions with restituted agricultural land were prohibited. More than 90 percent of the country’s land was under this regime. Recently, there has been an increase in land transactions − mostly in land leases however. Thin farm land markets combined with the structural features of land ownership (fragmentation, incomplete titling, poor registration) make land mortgages risky collateral. Limited mortgage lending should not be surprising, therefore. Repayment problems of cash loans. The number of enterprise loans that fell in arrears (15 percent) was almost three times that of households (5 percent) during the period covered by the surveys. The loans that enterprises reported in arrears were very large. These loans accounted for 43 percent of the aggregate amount received by the sector. In contrast, delinquent household loans were slightly below the average size and delayed payments represented 4 percent of the aggregate amount. There is a significantly higher incidence of arrears on the loans received by state enterprises relative to the loans received by their private counterparts. About 52 percent of the amount of loans to public enterprises fell in arrears during the period covered by the surveys, while the equivalent percentage for private enterprises was 12 percent. The incidence of arrears was very similar when measured by number of transactions (as opposed to amounts) as 59 and 12 percent of the number of loans obtained by public and private enterprises, respectively, fell in arrears. Arrears are a more serious problem for state-owned banks than for private banks. Sixty percent of the amount of the loans disbursed by state banks fell in arrears during the survey period − more than twice the arrears of private banks (25 percent). Delinquency on subsidized government credit lines was significant when state banks were the lenders (about 35 percent of the amount disbursed). In contrast, when private banks allocated subsidized credit, the delinquency reported was about 3 percent. Commercial credit. Credit received in kind, such as commercial and supplier credit, represents a significant source of financing for the rural economy. It accounted for 9 percent of all credit transactions and for about 20 percent of the flow of credit to rural households and enterprises during the period covered by the survey. Commercial credit was particularly important for enterprises. It was a source of financing for about 9 percent of them, accounted for 40 percent of the number of their credit transactions, and represented 23 percent of the total amount they borrowed in the period, including all other forms of credit. The 2 percent of enterprises owned by the state received 34 percent of the aggregate amount of credit disbursed under this modality. Households, on the other hand, used commercial credit less often and mostly to purchase durable goods and appliances. This type of credit was a source of financing for 2 percent of households, accounted for 7 percent of

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household credit transactions, and represented 13 percent of the total amount borrowed by households. Deposits and Savings Rural enterprises make intense use of the banking sector to manage their cash and to make and collect payments. Virtually all rural enterprises had sight deposits and/or checking accounts during the period covered by the surveys. About 80 percent of these accounts were in state banks while the remaining 20 percent were in private banks. Less than one percent of these enterprises had certificates of deposit or similar financial instruments. About 36 percent of rural households had financial savings during the period covered by the surveys. The highest incidence of households that save is among the well-off. While only 11 percent of the households belonging to the poorest income quartile save, the participation rate approaches one half for households in the two richest quartiles. Savings accounts are the most common deposit instrument held by rural entrepreneurs. They represented 69 percent of the number of accounts and 64 of the amounts deposited. Three state-owned banks – Savings Bank, Banca Agricola, and Banca Comercial_ Român_ – held more than 80 percent of the savings of rural inhabitants. Limited Access to Loans: Weak Supply of and Weak Demand for Loans Overall access to loans by rural households and enterprises is limited. In fact, the percentage of households and enterprises that used loans to finance consumption, working capital, or investments was only 20 percent during the period covered by the surveys. This observed scarcity of credit transactions in rural areas is caused by numerous factors which have weakened both the supply and demand for rural credit. Lenders avoid rural credit and few rural agents demand credit. Worse, the supply and demand do not match in that those agents which demand credit do not correspond to those to which lenders want to lend. Most likely, the other sectors in the economy also suffer from limited access to credit because the majority of these problems are common to all financial transactions in Romania. Weak supply of rural credit. The financial sector, especially the banking industry, supplies very limited amounts of loans to the productive sectors of the economy. This weak supply results not from lack of liquidity, but from an unfortunate combination of the short-term circumstances and structural factors analyzed below. These factors combine to make the returns to rural lending (adjusted by risk and transaction costs) unattractive relative to alternative investments available to lenders. Government macroeconomic policies. The Government is crowding out the enterprise sector from bank lending portfolios. For significant periods over the last few years, it has been more profitable and less risky for banks to invest their liquidity in inter-bank lending and government securities than in credit to enterprises or individuals. Treasury bill yields have been consistently above the rates on commercial loans. In January 1998, the yield on treasury bills was about 4,400 basis points above the rate at which banks reported lending to their prime borrowers.


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Government policies and participation in rural financial markets. The Government is also crowding out private lenders from rural credit markets and hinders the private supply of rural credit. Private lenders have not been in a position to compete with a poorly run government bank which was not subject to a budget constraint (Banca Agricola), and with numerous directed credit lines that financed rural loans at subsidized rates with a high probability of debtforgiveness. Debt forgiveness programs (implicit or explicit) have promoted strategic defaults and created obvious credibility problems for all rural entrepreneurs as viable borrowers. The institutional and legal framework for financial transactions. Some of the features of the legal and institutional framework have made credit transactions riskier and more costly than necessary, diminishing, therefore, the inclination of lenders to lend to all applicants, especially small and medium businesses and informal entrepreneurs. First, the majority of assets in the sector could not be effectively pledged as collateral for loans during the period covered by the surveys. Land and buildings accounted for 42 percent of the aggregate book value of the assets owned by rural enterprises and were by far the single most important component of the wealth endowments of rural households (57 percent). Nonetheless, agricultural land was not acceptable as collateral because transactions involving restituted agricultural land remained prohibited until late 1998. More than 90 percent of the country’s land is under this regime. Land markets have remained thin, in part due to lack of viable long term financing. Thin markets combined with the negative structural characteristics of land ownership such as fragmentation, incomplete titling, and poor registration make land too risky as collateral. Second, movable assets (equipment, machinery, inventories, livestock, and accounts receivable) had very limited capacity to carry debt during the period covered by the surveys because of imperfections in the legal regime.4 These assets represented about 48 percent of the aggregate book value of assets of rural enterprises. The legal regime for securing transactions with movables: (a) limited the creation of security interests on inventory, accounts receivable, leases, fixtures, and chattel paper; (b) did not provide a unified and easily accessible system for publicly registering and ranking the priority of a lender to collect against the property of a debtor; and (c) implied that repossession and sale of goods in which a lender had a security interest simply took too long (sometimes years), exceeding the economic life of an important portion of movable property. The net result was that moveable property as collateral was not valued, and borrowers offering movable property as collateral got no better terms than did those who offered nothing, nor were they more likely to be given credit. When real estate and movable assets were used to secure debts, the ratios of collateral value to loan amount were extremely high to protect lenders against the above imperfections. For the average bank loan, the assets securing repayment were four times more valuable than the amount borrowed. Hence, the real estate and movable assets in the hands of the enterprise sector 4

The Government of Romania passed Law No. 99 of 26 May 1999, published in Monitorul Oficial 236 of 27 May 1999 "Law Regarding Some Steps to Speed Up Economic Reform, TITLE VI. The Legal Status of the Security Interests in Personal Property." Shortly thereafter the Government issued the regulations for this Law. Preparation of the law and regulations was supported by the World Bank, which is also supporting the creation of an electronic filing archive for security interests. This archive will stand among the most modern in the world. The archive is presently under development and should begin operating during first quarter 2001. It is expected that this new framework will correct the deficiencies mentioned above.

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(90 percent of the aggregate book value of assets) could be used to secure credit transactions worth about 22 percent of the value of such assets. In countries with well-functioning collateral systems, assets carry about four times more debt than in Romania. For instance, in the United States loans guaranteed by mortgages normally finance up to 90 percent of the value of the real estate pledged while loans secured with movables normally finance up to 95 percent of the goods pledged. Third, other financing instruments such as warehouse receipts and leasing are, and continue to be, unavailable. The legal environment for warehouse receipts is inappropriate in that the rights, liabilities, and duties of each party to a warehouse receipt (e.g., producer, bank, warehouse) are not clearly defined or enforceable. In practice, receipts are not freely transferable by delivery or endorsement. In addition, potential lenders have no way to determine if there are competing claims on a given stock of commodities. There are no performance guarantees for warehouses. Farmers and traders are reluctant to store crops and banks are not willing to accept receipts as collateral because there is significant uncertainty as to whether the goods exist in the quantities specified by the receipt or whether the quality is the same or worse than that noted on the receipt. Lack of performance guarantees is worsened by the lack of independent inspection and licensing of warehouses. The storage industry is not competitive and remains dominated by the state. The excessive prices charged by elevators and the probability of receiving different amounts and qualities of commodities than originally stored make it unattractive for farmers and traders to store their products. Leasing has been rendered an unprofitable business by uncertainty and inappropriate rules on depreciation, accounting, and taxation of fixed assets. The law does not provide clear definitions for financial and operational forms of leasing and is unclear on: (a) the differing tax and accounting treatments accorded to each of these two arrangements; (b) how leased goods must be treated in the balance sheets; and (c) who (lessor or lessee) can claim credit on depreciation and rental payments under each type of leasing. Also, there is enforcement uncertainty because the law does not assign priority to lessors over leased assets in the case of the bankruptcy or reorganization of the lessee and because recovery of leased assets upon default by the lessee involves complicated, expensive, and time-consuming judicial procedures. The depreciation schedules allowed by law on fixed assets are too long compared with the normal life of a leasing contract. When such long depreciation schedules are applied to equipment leases, the lessor has to report artificially-high net taxable profits because current period costs are not being matched with current period expenditures. The Government is taxing the difference between the historical value of assets and their current replacement cost (in nominal Lei). Also, according to Romanian accounting law, all assets must be booked at their historical value and their revaluation is not allowed. This rule implies that, in the presence of inflation, depreciation expenditures are underestimated causing, again, artificially high taxable profits and low equity ratios for firms. The net effect is equivalent to a tax on investment in capital goods. Romanian law does not permit tax payers to deduct from their taxable income losses incurred when selling assets below their book value. Book value losses are unavoidable for Romanian leasing companies because of the very long depreciation schedules imposed by law


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and the comparatively short leasing periods, typically 3 to 4 years. In most cases, this combination causes the market value of fixed assets to be below their book value. Losses occur, therefore, when leased assets are sold. This practice gives leasing companies an unduly large tax burden. The customs duties and value added tax (VAT) on equipment leased from a foreign leasing company are deferred until the end of the lease period and are calculated on the residual value of the assets. These practices favor cross-border leasing and make it difficult to lease Romanianmade assets. In fact, the Romanian leasing association estimates that 99 percent of outstanding leasing contracts in the country are cross-border leasing. The practice also makes leasing a comparatively easy mechanism to avoid custom duties and the VAT on imported assets. Industrial companies could profit from establishing wholly owned leasing companies in foreign countries for the sole purpose of leasing their fixed assets from these companies and reduce, thereby, the amounts paid on custom duties and VAT. Retail lending capacity. Another factor contributing to the weak supply of credit is that the country’s banking industry does not have the interest or the capacity to serve retail clients as evidenced by an almost negligible share of loans to households and to small businesses in the portfolios of banks. Successful financing of rural areas will require the ability of the financial sector to supply retail and micro-finance services profitably because the large majority of potential clients are small. Small and medium businesses are predominant in the enterprise sector. The average rural private enterprise had US$11,900 of assets while 80 percent of them had less than 5 employees. Households, on the other hand, were even smaller clients as their average monthly income was US$67 per month and the average value of their assets was US$1,564. Several elements suggest that the financial sector will continue to be reticent about retail and micro-finance in the medium term. First, the methods or technologies of financial intermediation used by the country’s banks render retail lending unprofitable because: (a) they imply high fixed costs (expensive physical infrastructure, numerous employees) that could not be supported by the comparatively small volume of operations in retail and rural markets; and (b) the methods used to screen loan applicants imply costs that render small loans non-economical. The second factor that may weaken retail lending even more is that the network of bank branches may shrink significantly after the expected privatization or divestiture of state banks. In this case, a retail network would be required to lend to small and medium businesses and farmers because small credit transactions are highly elastic with respect to transaction costs, which are large in the absence of a point of sale in the locality of residence of borrowers. The network of bank branches may shrink because it is likely that struggling state banks will downsize by closing branches and that large state commercial banks will close many existing branches after privatization as they adopt strategies focussed on the corporate portion of the market. This tendency, which characterizes the behavior of the banking sector in most countries in Central and Eastern Europe, is already occurring in Romania where, for instance, Banca Agricola closed the majority of its branches during the process leading to its planned privatization. Privatized banks may also close existing branches as macroeconomic stability reduces the profitability of “deposit-only” branches. These branches have been used to arbitrage

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on the lack of access of the population to government securities. Banks have enjoyed disproportionately high margins from collecting retail deposits to finance portfolios of government securities which, under macroeconomic stability, will produce much lower yields than those obtained over the last few years. A reduction of the yields on government securities will render many “deposit-only” branches unprofitable. The weak demand for rural credit. The empirical findings of this study dispute the commonly held belief that the unwillingness of the banking sector to lend to rural agents is the (only) factor contributing to insufficient credit flows to rural areas. A weak demand for loans is a very important determinant of the limited participation of rural agents in credit markets. Only 31 percent of households with farm and other entrepreneurial activities, and about 50 percent of all rural enterprises, reported having a demand for loans during the period covered by the surveys. The demand for loans at the household level is associated with highly inelastic consumption needs, rather than with investment opportunities. Households that have access to: (a) bigger endowments of assets and wealth, including larger landholdings; and (b) sources of liquidity, including bank deposits and sales revenues, were more likely to report that they had no demand for loans during the period covered by the surveys. Indeed, 44% of the households which reported no demand for loans belonged to the top quartile in terms of the value of assets owned. It is reasonable to conclude, therefore, that households preferred internal sources of funding over external borrowing. One consequence of the very high observed collateral requirements is that the demand for loans decreases as large numbers of otherwise creditworthy borrowers opt out of credit markets. Peculiar collateral requirements, together with the shortcomings of the legal framework, could make borrowers' cost of defaulting disproportionate to the amount borrowed. Rural areas have no functioning mechanisms with which to auction property given as collateral and to ensure that any amount remaining after lenders have been fully compensated will be returned to the borrower. Hence, those potential borrowers that would be required to pledge collateral may face an artificially skewed risk-return distribution for their investments. Indeed, 27 percent of rural entrepreneurs and 8 percent of rural enterprises did not request loans during the period covered by the surveys because they considered borrowing too risky for this reason. There are also underlying profitability problems in the rural sector which imply low values for sector-specific assets, notably land. These low values restrict the demand for credit. As mentioned above, the profitability indicators of the enterprise sector were rather weak during the period covered by the surveys. In addition, the sector’s demand for credit was also weak because limited investment took place during the period. Investment outlays tended to be lumpy and required liquid resources. Thus, access to external credit may assist households and enterprises to take advantage of profitable investment opportunities. Availability of internal financing was not necessarily synchronized with investment opportunities. A comparatively limited number of rural households and enterprises made investments in capital goods. Only 28 percent of rural households and 26 of enterprises made some type of investments. Macroeconomic uncertainty is a significant concern of potential rural borrowers. Most borrowers must borrow at variable rates of interest, as 87 and 75 percent of all bank loans granted to enterprises and households, respectively, during the period covered by the surveys had


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rates of interest adjustable with respect to some market index. Borrowers can go bankrupt when interest costs rise relative to their enterprise earnings, especially for households which have very limited access to markets or enterprises in non-tradable sectors, because of difficulties in hedging against devaluation of the Lei. Another related factor that weakens the effective demand for credit is the high levels of ex-ante real interest rates on loans − whether denominated in Lei or in hard currency (taking into account expected devaluation). High real rates require investments to have very high marginal productivity. Smaller enterprises with low capital/labor ratios are more willing, everything else equal, to borrow at the prevailing high real rates, while larger and more capital intensive businesses cannot afford such rates. In Romania there may be an unfortunate mismatch in which smaller businesses which demand credit even at high rates are not being served by banks, while larger enterprises which banks are willing to serve are not demanding credit at high (real) rates. Credit Constraints and Rural Investment This study answers two key questions resulting from the empirical evidence of weak supply of, and demand for, credit, namely: Does the limited supply of loans relative to existing demand result in significant numbers of households and enterprises not taking advantage of the profitable investment opportunities that may be present in rural areas because of constrained access to credit markets? And if so, how much larger would rural investment be in the absence of credit constraints? Answering these questions required determining whether the agents which have a positive demand for loans are able to borrow the amounts they desire, that is, whether rural agents are credit constrained. Being “credit constrained” is necessarily a relative concept resulting from the comparison of an agent’s demand with the supply of credit to which it has access. An agent which does not have a demand for credit could not be credit constrained by definition. In terms of credit constraints, every agent must, therefore, belong to one and only one of the following four groups: (a) agents which do not have loans because they do not demand loans may be called unconstrained non-borrowers; (b) agents which do not get loans although they demanded credit correspond to totally constrained non-borrowers; (c) agents which receive loans for exactly the amount they request may be called unconstrained borrowers; and (d) agents who receive loans for less than the amount they want to borrow. This last group represents constrained borrowers. Only 6 percent of households and 8 percent of enterprises were able to borrow the amounts that they wanted to borrow during the period covered by the surveys. Enterprises reported that they were totally credit constrained three times more often than households. This greater incidence among enterprises results because they had a stronger demand for loans. Among households, 10 percent reported being totally credit constrained and 14 percent were partially credit constrained. Among enterprises, 29 percent reported being totally constrained while 12 percent reported that they were partially constrained. Credit constraints at the household level. Unconstrained and partially constrained households (i.e., those which borrowed) were similar among themselves, but tended to be very different from their totally credit constrained counterparts. After controlling for numerous other variables, totally credit constrained households were more likely (with statistical significance)

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than their borrowing counterparts to: (a) be headed by unmarried individuals; (b) be less educated; (c) have more members; (d) have less members working in the non-agricultural sector; (e) have smaller endowments of non-financial movable assets; (f) receive smaller amounts of fixed incomes such as salaries and pensions; (g) have smaller real estate holdings; (h) live in localities where there are more farmers relative to total population; and (h) live in localities where there are more branches of state-owned banks. The study also estimated, as a function of observable variables, the probability of a household being: (a) totally credit constrained; (b) a borrower from the informal sector; or (c) a borrower from the formal sector. The results indicated that there was a matching of borrowers and lenders in that (among those who had borrowed) the better-off individuals with access to financial markets obtained their loans from the formal sector, while worse-off and economically isolated individuals resorted to borrowing mostly from friends and relatives. Regression results confirmed that one reason why few Romanian rural households participated in credit markets is because there was a limited coincidence between those which wanted loans (the aggregate demand) and the willingness of all potential lenders to lend to them (the aggregate supply). In fact, a majority of characteristics that made households more likely to demand loans also made lenders less willing to grant loans to them. Credit constraints at the rural enterprise level. The enterprises that were partially credit constrained or unconstrained were statistically similar and, as a group, differed significantly from their totally unconstrained counterparts. In a sense, lenders to rural enterprises based their decisions to allocate any amount of credit (the amount actually requested or less) on basically the same criteria. Lenders were more likely, everything else the same, to have received and to have approved credit applications from enterprises which: (a) were managed by older and less educated individuals; (b) were operating in sectors other than industry and were incorporated as stock corporations; (c) were large in terms of the value of their gross sales and the value of their assets; (d) were very large enterprises in the agricultural sector; and (e) were domiciled in localities in which there were many branches of state-owned banks. That is, enterprises with these characteristics were less likely to be totally credit constrained and more likely to be either unconstrained borrowers or constrained borrowers. The bottom line effect of credit constraints on rural investment. The study finds strong empirical evidence that credit constraints influence negatively the investment behavior of households and enterprises. In particular, such constraints reduce the number of agents that invest and the amounts they invest. The effect is especially negative at the enterprise level. Thus, profitable investment opportunities are not pursued as a result of limited access to credit markets. This situation is very negative for rural Romania because there are few such opportunities relative to the size of the sector. Investments. The study examines the investments made by households and enterprises. Investments are defined as the expenditures incurred in acquiring capital goods including buildings, equipment, tools, machinery, vehicles, livestock, and land. A comparatively limited number of rural households and enterprises made investments during the period covered by the surveys. About 27 percent of rural households and about 26 percent of enterprises made some


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type of investment. The amounts actually invested were small relative to the income of rural enterprises and households. In the aggregate they invested 4 and 6.5 percent of their gross annual incomes, respectively. The value of physical investment as a percentage of GDP in the EU and the OECD was 22 and 25 percent, respectively. Although the Romanian, EU, and OECD statistics are not directly comparable because of measuring methodologies, the absolute differences in magnitude are sufficient to indicate low levels of investment relative to income in rural Romania. Investment opportunities and the effects of removing credit constraints. The study estimated how much more investment would have occurred in rural Romania during the period covered by the surveys had credit constraints been removed − that is, how many more agents would have invested, and how much more they would have invested, had they been able to borrow as much as they wanted under the prevailing conditions during the period. The results follow. Investments by households. Investment opportunities at the household level: (a) were negatively related to the age of the household head; (b) increased with the number of household members who were pensioners, mostly because of stability of cash flows; (c) were basically in consumer goods; (d) were positively related to the number of household members; (e) were more likely for households which hold bank deposits; (f) were more frequent for households with larger housing units, again associated with durable consumer goods; (g) were positively associated with the degree of connection to markets as proxied by the share of the value of agricultural sales in total household income − in fact, 45 percent of farm households with substantial market involvement made investments during the period covered by the surveys, compared to only 24 percent of farm households which consumed their production; and (h) varied significantly by region in that there were more frequent opportunities in Moldova de Podis, Subcarpati de Sud, and Oltenia de Sud, and less frequent opportunities in Campia Dunarii de Jos and Campia Romana Centrala. A significant portion of the investments made were in consumer durables. The amounts invested by households that perceived profitable opportunities tended to be larger for households: (a) headed by younger, female, and less educated individuals; and (b) with more pensioners. Some of the characteristics of the entrepreneurial activities influenced the amounts invested as well. The households which invested larger amounts had: (a) more fragmented landholdings; and (b) more market involvement as indicated by the shares of their income originated in labor and output markets (farm and non-farm). Finally, households in: (a) agrarian localities, as proxied by the ratio of farmers to population; and (b) Subcarpatii de Sud and Oltenia de Sud, tended to invest lower amounts. Removing credit constraints at the household level. The key policy issues regarding the relationship between investment and access to credit at the household level are: (a) the set of investment opportunities available to rural households is rather limited; (b) lack of financing (debt or equity) under the conditions prevailing during the period covered by the surveys was not a bottleneck to investment in the sense that most of the households which had investment opportunities actually took advantage of them; (c) mitigating credit constraints by providing additional credit at the prevailing conditions would have a limited impact on the number of households which would have invested and on the aggregate amount of household investments

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In terms of numbers of households, had there been no credit constraints for households during the period covered by the surveys, 29 percent of households would have invested. This is an increase of only 2 percent from the 27 percent of households which actually made investments. The aggregate amount invested by households in the absence of credit constraints would have been 10 percent above the amount actually invested. This increase would have placed household investment levels at about 7.2 percent of their aggregate income instead of the 6.5 percent actually observed. Investments by enterprises. Everything else the same, the enterprises more likely to invest during the period covered by the surveys: (a) had younger managers; (b) were in sectors other than agriculture with the exception of large agriculture enterprises which were also more likely to invest; (c) were private in that the state had no participation in their ownership; (d) had high volumes of sales; (f) were those which did not have large numbers of owners managing the enterprise nor working in it, as measured by the share of members in the total work force; and (g) were located in more densely populated regions. Enterprises in the regions of Moldova Deal and SAI were less likely to invest. The amounts invested by enterprises were statistically independent of economic sectors, legal status of incorporation, ownership, and economic conditions of the locality where the enterprises were located. The amounts invested were higher for enterprises with more: (a) assets; (b) gross value of sales; and (c) leverage, as measured by their debt-to-asset ratios. The amounts invested by enterprises in the regions of Subcarpatii de Sud and Moldova de Podis tended to be smaller. Lack of financing represented a significant impediment for rural enterprises to take advantage of the investment opportunities available in that a considerably larger number of them would have made investments had credit constraints not been present. In particular, the econometric analysis estimated that, in the absence of credit constraints, about 37 percent of enterprises would have invested versus the 26 percent that actually did invest (an increase of 41 percent) during the period covered by the survey. The aggregate amount invested in the absence of credit constraints would have been about 57 percent greater than the amount actually invested. Policy Options General strategy and emphasis. Deepening financial markets in rural areas and increasing their outreach requires stronger credit supply and demand. While the problem must be tackled simultaneously from both sides (supply and demand), efforts to shift the supply curve of rural credit to the right would probably yield results faster than interventions in the demand side. Significant increases in the demand for credit to finance investments will occur only after the full implementation of appropriate policies (privatization of state enterprises, land titling) and the development of infrastructure (warehousing system) in rural areas.5 5

An important exogenous factor that may increase the demand for private investments and for rural credit is the Special Accession Program for Agriculture and Rural Development (SAPARD). This program will be financed by the European Union. SAPARD will allocate a significant portion of _ 150 million per year during the period 20002006 in grants to finance eligible private sector investments in rural areas. These grants will finance up to 50 percent of eligible investments. The remaining 50 percent of the value of these investments will need to be financed by


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The core of the short term strategy should, therefore, be to augment the supply of credit by increasing the returns to rural lending, adjusted by risk and transaction costs. An increased supply of credit would translate into lower total cost of borrowing, including lower and less volatile effective rates of interest, transaction costs of borrowing, and collateral requirements. Better conditions on credit would be followed by an increase in the amount of credit demanded in the form of a movement along the existing demand curve (as opposed to a shift in the demand curve). In practice, this challenge requires: (a) removing the unfair competition between the state and the private sector for (i) controlling productive rural assets, (ii) collecting savings from the public, and (iii) allocating credit; (b) improving contract enforcement; and (c) increasing competition in the supply of deposit services and funding to private rural clients of which the large majority are farmers and micro, small, and medium enterprises. The following is a summary of the options available to the Government to implement a program aimed at meeting the above challenge.6 Some of these policies have already been adopted by the Romanian authorities, as indicated below. Government credit lines. The government has realized that directing and subsidizing credit in the face of existing high costs, risks, and distortions will only perpetuate the existing problems by crowding out private lenders. The Ministries of Agriculture and Finance have agreed to the dissolution of all subsidized credit programs and all government funds financing rural and agricultural credit, including Ordinance 36/99 (Support for Farm Equipment Purchases) and Ordinance 165/98 (Ordinance for Providing Finance for Crop Planting). It is expected that the Government will issue this Ordinance at the end of 2000. The elimination of directed subsidized credit to the sector constitutes one of the conditions for a proposed World Bank loan, which will finance the implementation of a project to develop rural financial markets in Romania. Improving the legal and institutional environment for using movable assets to secure transactions. There has been significant progress in passing legislation that will allow for greater and more effective use of movable assets as collateral most notably, farm equipment, inventories, accounts receivable, and consumer goods. In particular, the Government passed Law No. 99 of 26 May 1999, published in Monitorul Oficial 236 of 27 May 1999, "Law Regarding Some Steps to Accelerate Economic Reform, TITLE VI. The Legal Status of the Security Interests in Personal Property." Preparation of the law and its regulations was supported by the World Bank as preparation for the above-mentioned rural finance project. The Romanian authorities are

beneficiaries either with their own resources or with debt. There may be, therefore, a “step” increase in the demand for rural credit from the private sector to finance the counterpart funding requirements to obtain SAPARD grants. Clearly, financial rates of return on private investments will increase because of the grants. 6

The benefits for the development of financial markets of conducive macroeconomic conditions in the form of low and predictable inflation rates and exchange rate stability are obvious. It should suffice to mention, as an example, that an improved fiscal balance would allow the government not to crowd out the private sector in financial markets. Policy recommendations to achieve macro stability are, however, beyond the scope of this study. While recognizing that such stability is a necessary (albeit not sufficient) condition for the development of rural financial markets, this chapter focuses on possible government interventions that may be required to achieve other necessary conditions for the improved performance of these markets.

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creating, with World Bank support, an electronic filing archive for interests interest secured with movable assets. It is expected that the archive will begin operations before the end of 2000. The legal environment for warehouse receipts will improve when Law 99 above becomes effective with the launching of the archive. This law clarified and defined clearly the rights, liabilities, and duties in each party to a warehouse receipt (e.g., producer, bank, warehouse) by making receipts freely transferable by delivery or endorsement. In addition, potential lenders will be able to use the new security interest electronic archive to determine if there are competing claims on a given stock of commodities. Three actions are still required to develop a fully effective warehousing framework. First, independent inspection and licensing of warehouses should be established. Second, a system of performance guarantees for warehouses should be developed, including establishing an indemnity fund and/or requiring mandatory insurance among licensed warehouses. Third, more competition should be introduced in the storage industry which remains dominated by the state. There has been important progress in establishing a western-style leasing system with the “Law on Amending Ordinance No. 51/1997.” Nonetheless, the problems in the accounting and fiscal treatment of leasing and, more generally, of depreciable fixed assets, remain. Leasing should not be expected to grow because investment in the types of assets that are typically leased is taxed excessively. Specific recommendations include: (a) allow for shorter depreciation schedules on fixed assets; (b) allow reasonable revaluation of assets over their historical book values to compensate for inflation; (c) allow tax payers to deduct from their taxable income losses incurred when selling assets below their book value; (d) finish leveling the playing field between domestic and cross border lessors in terms of the value added tax (VAT) on equipment leased; and (e) eliminate the customs duties incentives on assets to be leased, namely, total exemption of import tariffs, duties, and customs guarantees because these incentives have only increased inter-company leasing as a means of avoiding customs duties, and not the growth of real leasing transactions. Improving the legal and institutional environment for using land as collateral. There are obvious benefits for rural finance of well-defined property rights and secure title to real estate, namely, the ability to use land as collateral which both enhances financial market development and promotes greater investment. In particular, titled land which has secure registration generally has a much higher market value. While this is not sufficient for a well functioning financial system, insecure property rights unambiguously reduce the development of financial markets, especially in rural areas where farm land represents an important portion of all assets. The following are recommendations for a successful titling and registration system: (a) do not use titling and registration programs to collect additional taxes; (b) invest in making property rights and property boundaries clearly recognizable and easily definable; (c) hire and train qualified survey and registry staff to ensure their suitable competence; (d) improve the ability of the court system to enforce and protect property rights; (e) decrease the degree of regulation of land sales and make zoning regulations more transparent while the procedures for zoning changes should be simpler and less expensive; (f) reduce the statutory costs of property transactions, as well as those related to the transfer and registration of title.


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Retail lending. Successful financing of rural areas will require the ability of the financial sector to supply retail and micro-finance services profitably because the large majority of potential clients are small. Section B of Chapter III argues, however, that the supply of retail and micro-finance services is likely to remain weak. Government support may be justified to provide technical assistance to private lenders to accelerate their understanding of the rural sector, of how to evaluate business plans from new private farms and rural businesses, of how to use and value rural assets that might be pledged as security, of how to dispose of such assets, and so forth. Financial and technical assistance should also be provided to non-profit organizations to support the provision of micro-credit to the poorest segments of the rural population, i.e., those which will not be reached by the banking sector. The Government could also assist in the development and introduction of technologies and institutional arrangements that could reduce costs and risks of retail banking and micro-credit in the rural areas (e.g., character based lending, credit bureaus). Government support for these activities is justified from a public policy point of view.7 The development of sustainable technologies for delivering financial services to retail and micro rural clients requires extensive local experimentation. The problem is that the investment in experimentation may be inadequate unless the Government provides the necessary stimulus. Since no single lender can capture a significant portion of the social value of improved lending, the rational strategy is to wait for someone else to assume the risks and costs of experimentation and, in the case that the technologies are successful, to copy them. It is also justifiable for the Government to invest in this experimentation because past government interventions in financial markets have been extremely costly. Any future mistakes are likely to also be expensive. Hence, limited support to private intermediaries that will avoid future direct involvement by the Government may be a good policy. Micro-finance, on the other hand, has proven to be a cost effective and sometimes sustainable instrument to deal with the rural poor. Regulatory concerns regarding chartered non-bank mutual financial intermediaries. As argued in section F of Chapter V, the stability of the overall financial sector and the protection of the savings of the population may be threatened by the operations of an estimated 1,400 independent mutual financial intermediaries (MFIs) registered under Law 109/1996 and of which a majority are domiciled in rural areas. The elimination or management of the risks imposed by MFIs will not be a simple task. The authorities have taken the important initial step of suspending the licensing of new MFIs. The challenge of what to do with the existing ones remains, however. Two options have been proposed in Romania, namely: (a) bring the system under the supervision of the NBR; or (b) introduce self-regulation by requiring individual MFIs to join second-tier groups such as federations of credit cooperatives, which would supervise their members. Neither option may be suitable, however. The first may strain the supervisory capacity of the NBR as it would increase the number of intermediaries it currently supervises from 45 commercial banks to more than 1,400 in one single step. The second option has significant shortcomings, including: (a) the federations (the supervising entities) would be owned and controlled by MFIs (the supervised entities) − the managers of more tightly-run federations could be replaced by laxer management 7 Chapter V: Policy Options and Possible World Bank Support provides an outline of an operationally feasible way for the Government to support these efforts.

xxx


teams; and (b) federations and MFIs would be private entities, allowing MFIs to choose to exercise their constitutional right of free association by either moving from tightly-run federations to lax federations or to no federation at all – the Government may not be able to condition the existence or functioning of a MFI on belonging to a federation. A third option seems to be required. The following sequence of actions may represent a viable option to ameliorate the risks entailed in the operations of MFIs: (a) maintain the status quo, leaving existing MFIs outside NBR’s regulatory authority and supervisory responsibility; (b) pass legislation, possibly by amending Law 109/1996, so that (i) MFIs are no longer allowed to use the word “bank” in their names (e.g., Banca Populare), (ii) MFIs are obliged to register with the NBR with the (sole) purpose of establishing a complete inventory of them, (iii) NBR has the authority to request some basic financial data on MFI performance, including external audits for MFIs above certain asset thresholds, (iv) NBR has the authority to regulate the “act” of financial intermediation rather than specific financial intermediaries (e.g., bank charter only), allowing NBR to take discretionary actions with respect to selected MFIs without acquiring the obligation of supervising all MFIs; (c) pass new, or amend existing, legislation that would allow for the creation of a totally new financial intermediary charter such as a “small regional bank” (SRB) charter which would be subject to a complete regulatory framework (see details in Chapter V); (d) NBR would undertake immediate efforts to develop its capacity to enforce SRB compliance with the above prudential norms, including a well staffed unit devoted to this purpose, an early-warning system based on data reported by SRBs, and on-site supervision necessary to undertake inspections that, because of their nature, cannot be performed by an offsite analysis; (e) existing MFIs would be eligible to be licensed under the new regulations under a “fast track” procedure for a period of, say, 12-18 months; (f) MFIs that would opt to comply with the new regulations and get licensed under the new framework would be provided technical assistance to meet the new regulatory standards; and (g) existing MFIs that refuse to migrate to the new charter and to comply with the new regulatory framework would remain unregulated informal financial intermediaries and the NBR may consider the possibility of making the public aware of the risks involved in maintaining deposits in such intermediaries by publicizing their status. Market development, balanced rural development, and privatization. The empirical findings of the study provide strong empirical support to the claim that the following actions would contribute to increased investment in rural areas: (a) Integrating households into markets and allowing concentration of land holdings. Household investment opportunities are positively associated with the degree of connection to markets as proxied by the share of the value of agricultural sales in total household income and negatively associated with the age of the heads of households. In fact, 45 percent of farm households with substantial market involvement made investments during the period covered by the surveys, in contrast with only 24 percent of the farm households which consumed their production. In turn, market involvement requires eliminating the restrictions for exiting agriculture faced by the large numbers of elderly landowners who have small-scale operations and lack agriculture equipment. These farmers created by the land reform process will remain engaged in subsistence farming and will remain disconnected from markets.


xxxi

(b) Formulating balanced rural development policies (in contrast to focussing on agriculture only) and privatizing state enterprises. The enterprises more likely to invest were, everything else the same, in sectors other than agriculture and were private in that the state had no participation in their ownership. Everything else the same, the probability that an enterprise in the industry, trade, and service sectors had a demand for loans was, respectively, 36, 32, and 30 percentage points higher than the probability of an agricultural enterprise reporting a demand for loans. (c) Privatizing state banks. Private banks were more amenable to financing investments than their state-owned counterparts. Private banks allocated 80 percent of their loans to borrowers who reported having made investments in the period in which they received the loan, while the equivalent share allocated by state banks was 55 percent. Policy coordination. Rural finance in Romania is a very complex multi-sector subject with important policy and political implications. It is an issue with multiple influences on the economy ranging from macroeconomic stability to impact on rural poverty. A consistent set of policies towards rural financial markets is a vital concern, therefore. A steering committee should coordinate general policies and, maybe, guide the reform of specialized government institutions and programs. This committee should consist of representatives from the government agencies involved, including the Ministry of Agriculture, Food and Forestry, the Ministry of Public Finance, and the National Bank of Romania. B. SPECIFIC OBJECTIVES, METHODOLOGY, AND DATA The objective of this study is to address public policy questions relevant to rural finance. What is the impact of the widely perceived limited access to credit on growth, efficiency, and poverty in rural areas? What are the roles of demand and supply factors in explaining limited access to rural credit? Does access to credit influence the investment strategies of rural entrepreneurs and rural enterprises? What determines the extensive geographical coverage of the banking sector? Is this coverage efficient, especially in the case of public banks? What would be the profitability of rural bank branches if they not only collected deposits but also allocated credit to rural households and enterprises? What should be the government strategy to increase the availability of financial services, especially credit, in rural areas? Who would be the winners and losers of reforming the sector? In short, the study provides the data and analytical tools needed to design rural financial markets polices and to support the dialogue between the Government of Romania and the World Bank. The study provides an empirical basis for a government strategy to increase the availability of financial services in rural areas and for the World Bank to fine tune its possible support in the endeavor. The approach used was to: (a) assess the performance of the markets; (b) identify the causes of any identified deficiencies in performance; and (c) design the minimum-cost policy instruments to bring about improvement. The research focuses on entrepreneurs and enterprises and the financial transactions and capital investments in which these agents participated. Entrepreneurs and enterprises are defined as any physical or legally incorporated persons engaged in an economic activity and whose

xxxii


earnings depend on the differences between uncertain incomes and contractual costs. The agents under study are, therefore, the residual claimants of the cash flows of an economic activity. Three kinds of credit products or services are considered in this study, namely: (a) cash loans, which are credit transactions disbursed and repaid in cash; (b) commercial credit, which includes all credit provided in kind and paid back in cash; and (c) forward sales or sales with a down payment, which consist of payments received by the borrower in exchange for the future delivery of products and services. Deposits in financial institutions and investments in securities are also considered. All types of lenders and their services are also considered. Lenders are classified as formal, semi-formal, or informal, according to whether they have a government-granted license to provide financial services or operate under the auspices of specific legislation. The formal sector includes commercial banks or deposit-taking institutions supervised by the National Bank of Romania. The semi-formal sector includes chartered non-bank financial intermediaries and other registered institutions providing credit products − mostly credit cooperatives and Mutual Aid Intermediaries (CARs).8 Informal lenders consist of: (a) moneylenders, who provide cash loans in exchange for explicit interest payments; (b) friends and relatives, who provide cash loans without explicit pecuniary compensation; and (c) traders, merchants, and processors, who engage in commercial credit or sales with a down payment as defined above. The analysis in this study relies intensively on statistical and econometric analysis of the data collected in three surveys conducted specifically for the study.9 A brief description of these surveys follows. Survey of Rural Households and Financial Services (SRHFS) This survey was conducted in Spring of 1998. The sampling universe corresponded to households located in Romania’s rural areas, as defined by the National Commission of Statistics (NCS). A total of 2,420 households were selected using a two-stage selection scheme. The first stage used the Master Sample of Census Tracts (referred to by its Romanian acronym, EMZOT) to select 242 census tracts.10 In the second stage, a total of 2,420 households were randomly

8

There are few Non-Governmental Organizations providing financial services in rural areas. The scale of their operations is very small and of limited geographical scope. 9 The technical aspects of this study are presented in detail in each of the annexes to the study. Annex 5 presents the complete sample design of the household and enterprise surveys. These annexes are available on request through Rodrigo Chaves or Saul Schor. 10

NCS uses a master sample of census tracts to carry out all of its household surveys. This master sample of census tracts, which was built using the 1992 population and housing censuses, contains 242 census tracts and 107,662 dwellings according to the latest update in 1995. These 242 census tracts were selected using a spiraling selection scheme from a total of 93,037 census tracts in the Romanian territory.


xxxiii

selected from the pool of households that had not been selected for other NCS surveys.11 Data were collected on a total of 7,098 individuals belonging to sampled rural households. The household survey provided data on individual labor market decisions, household demographic characteristics, and basic socio-economic data on household members. In addition, the survey collected detailed information on agricultural and non-agricultural activities undertaken by the household. The data set provides previously unavailable information regarding the use of credit and savings products, investment activities, and the extent of credit constraints. The survey considered three kinds of credit products: cash-loans, trade-credit, and sales with advances. Survey of Rural Enterprises and Financial Services (SREFS) This survey was also conducted during Spring of 1998. The sampling universe corresponded to enterprises domiciled in rural areas. The survey excluded, therefore, all enterprises with operations in rural areas but with headquarters in urban areas and Regies Autonomes, enterprises not legally incorporated, branch offices of financial institutions, public administration offices, educational institutions, and health care units. The sampling frame was constructed using a farm enterprise survey conducted in 1997 and the REGIS registry.12 The frame included 4,238 agricultural enterprises and 75,516 non-agricultural enterprises. A total of 900 rural enterprises of which 390 were agricultural enterprises were sampled using stratified sampling. Four strata were constructed on the basis of the value of annual sales. The enterprise survey provided data on financial statements, financial transactions, characteristics of enterprise managers, investments, and problems affecting the enterprise. The survey is unique in its collection of rarely available data – namely, the characteristics of loan and savings products and the extent of credit constraints. Survey of Financial Intermediaries (SFI) This survey was conducted in 1998 and gathered information at the locality level on the number of financial outlets, amount of deposits and loans outstanding and number of employees per branch. Responses were obtained from 5 state-owned banks and 11 private banks. Aggregate data for all individual credit cooperatives was also obtained. The surveyed banks accounted for more than 70 percent of the assets in the banking sector at time.13

11

This procedure does not introduce a bias in the selection of the SRHFS because a random process was used to select the households for the other surveys. To account for non-responses, a total of 14 households per census tract were sampled, but only 10 were actually surveyed.

12

The REGIS registry is the most comprehensive list of enterprises in Romania. It is updated monthly with entries from the Trade Registry, the Fiscal Registry, and the National Commission for Statistics.

13

The banks which responded to the survey were Banca Internationala a Religiilor (International Bank of Religions), Bankcoop, Banca Turco-Romana (Turkish-Romanian Bank), Banca Franco-Romana (French-Romanian Bank), Casa de Economii si Consemnatiuni (Savings Bank), Banca Romaneasca, RoBank, ABN AMRO Bank, Daewoo Bank, Demir Bank, Ion Tiriac Bank, Bucharest Bank, BancPost, and Banca Agricola.

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Additional Data The survey data are complemented with information collected by the National Commission of Statistics (NCS) on Romanian localities for the year 1997. This NCS locality database contains information regarding numerous variables disaggregated at the locality level, including employment, population demographics, and educational enrollment. C. ORGANIZATION OF THE STUDY This study is organized in five chapters that summarize the findings and analysis of five detailed annexes to the study. These annexes are available upon request at the World Bank through Rodrigo Chaves or Saul Schor. Chapter I examines the Romanian rural economy to illustrate the profile of economic agents in rural areas and the context in which rural financial intermediaries operate. Chapter II describes the financial intermediaries existing in Romania’s rural areas, their market shares, and their financial products. Chapter III examines the roles of demand and supply factors in explaining the limited use of credit services. Chapter IV illustrates the influence of credit constraints on the investment strategies of households and enterprises. Finally, Chapter V draws some conclusions and policy recommendations to improve the performance of financial markets in rural areas, before closing with a look at the challenges forthcoming in the future.

Chapter I: The Rural Economy and its Economic Agents The focus of this report is the performance of Romania’s rural financial markets, which are intrinsically connected with the performance of product, input, and others factor markets. The first part of the chapter (sections A and B) introduce the reader to the main features of rural Romania, describing the characteristics and policies that affect its economic activity.14 Section A establishes that Romania has a large and diverse rural economy, predominantly agricultural, with a low-educated and aging labor force. The major “reforms” implemented during the transition period that dramatically modified the rural economic landscape are presented in section B: (a) the land reform in 1991; (b) the interventionist agriculture and agricultural credit policies implemented during 1993-96; and (c) the hesitant reforms of 1997-98. Section C summarizes the characteristics of rural employment. The second part of this chapter (sections D and E) examines rural entrepreneurs and enterprises. Section D presents the characteristics of rural entrepreneurs. Most are farmers who emerged as a result of the 1991 land reform, but whose potential was stifled by almost a decade of inappropriate policies. The section describes the diversity of farm entrepreneurs, including non-agricultural entrepreneurs, who run informal family-owned businesses. Finally, section E describes the main characteristics of the formal rural enterprise sector. A. THE RURAL ECONOMY WITHIN THE AGGREGATE ECONOMY Romania ranks as a mid-sized European country, with a population of 22.5 million, an area of 238,391 km2 , and a GDP of US$31.8 billion (1997). Romania Figure 1 Change in GDP and Agricultural GVA belongs to the group of lower 160.0 middle-income countries, with a 140.0 GDP per capita of US$1,410 120.0 (US$4,270 at purchasing power 100.0 parity). 80.0 60.0 40.0 20.0 1990

1991

1992

1993

Change in GDP

1994

1996

Change in Agricultural GVA

Source: National Commission of Statistics.

14

1995

1997

1998

Transition to a market economy has occurred gradually and the results of the transition have been less than encouraging. In 1993, GDP had contracted to 76 percent of its 1989 level. State intervention briefly restored some GDP growth at the cost of serious

This chapter provides required background to the study’s empirical findings on rural financial markets. The chapter attempts to provide the most succinct possible information. Hence, readers familiar with the sector may skip some sections accordingly, while those totally unfamiliar with the subject may benefit from reading Annex 1 which contains more complete and detailed information on Romania’s aggregate and rural economy.

2

Chapter One:

macroeconomic imbalances. These imbalances triggered a new period of recession from 1997 through 1999, when GDP declined back to its 1993 level. In contrast, agricultural gross value added (GVA) was higher than its 1989 level throughout the transition period. Poverty is a widespread and severe problem in Romania. In 1998, roughly 44.5 percent of Romanians were living on less than $4 of purchasing power parity (1996 PPP) a day with per capita consumption falling 25 percent short of the poverty line (World Bank, 2000). Poverty is greater and deeper among the approximately 10 million people who live in rural areas (45 percent of population).

Annual Growth Rate (%)

The definition of “rural” used in this study corresponds to the legal and administrative definition used in Romania, which is an administrative definition. Under this definition, rural areas are comprised of all localities which have not Figure 2 GDP and Agricultural GVA Growth Rate achieved the status of “urban”. This status 30 requires a law. This 25 20 somewhat arbitrary 15 custom implies that it is 10 possible to find urban 5 towns with, say, 10,000 inhabitants, while some 1991 1992 1993 1994 1995 1996 1997 1998 (5)1990 rural villages may have, (10) say, 20,000 inhabitants. (15) In practice, therefore, (20) rural areas are comprised GDP Growth Rate Agricultural GVA Growth Rate of the entire country Source: National Commission of Statistics. minus 200 (mostly large) localities which have been granted urban status by legislative action. More than half of total employment is located in rural areas (52 percent in 1997), and roughly a fifth of all incorporated business are headquartered in rural areas. Rural inhabitants are spread out among 2,686 communes (the smallest administrative unit), which contain 13 thousand villages spread over 89 percent of the country’s surface. Population density is comparatively high. Primary productive activities prevail in rural areas. The typical occupations are farming, forestry, fishing, and extractive industries, and most of the economically active population in rural areas are self-employed farmers. The educational level in rural areas is lower than in urban regions. Individuals over 15 years of age with no formal schooling or only primary education make up 27.6 percent of rural inhabitants. The same group corresponds to 2.6 percent in urban locations, while 90 percent of high school graduates are concentrated in urban areas.

The Rural Economy and its Economic Agents

3

Rural areas are heterogeneous, made up of both small human settlements and larger communities, densely populated areas and isolated villages and hamlets, and rich and poor communities. Some large rural communities are comparable in size to towns (up to 30 thousand inhabitants), while smaller communities may have a little over one hundred residents. Three main trends have shaped rural Romania and its villages over the past 30 years (Chirca and Tesliuc, 1999). First, population decreased by almost 20 percent due to a combination of migration, low birth rate, and high mortality. Those leaving the villages for towns were basically young high-school graduates. The out-migration of rural youth caused the aging of the rural population and contributed to increasing the educational differences between rural and urban areas. The beginning of the transition found an aged rural population occupied mostly in the agriculture sector, which was totally dominated by the State and collectivization B. AGRICULTURAL SECTOR POLICIES DURING THE TRANSITION There were three phases of agricultural sector reforms with the greatest impact on rural markets during the transition period: (a) a period of heavy structural changes between 1990-91, triggered by the land reform; (b) a period of heavy interventionist agricultural policies between 1992 and 1996; and (c) a recent period of hesitant liberalization of rural markets. A common feature of these policies was their “stop-and-go” nature, with liberalization followed by measures aimed at counteracting their perceived negative effects. Land Reform In 1991, the Government undertook a land reform program that dramatically changed rural areas. The land reform restituted 9.25 million hectares of land to private agents.15 This land accounted for 73 percent of total arable land or 63 percent of total agricultural land in the country. Consequently, the share of private land increased from 12 percent in 1989 to 70 percent in 1992. Second, peasant farms and small informal and formal associations of farmers replaced the traditional state and cooperative farms that existed during the communist era. By design, the land reform created the largest class of entrepreneurs in Romania – the farmer. These new entrepreneurs, however, are elderly and uneducated landowners who have small-scale operations and lack agriculture equipment. They engage mainly in subsistence farming disconnected from markets. To date, one in five farmers does not possess legal title to their land due to delays in the implementation of land titling. Moreover, the Government banned sales of restituted land until August 1998 when the restrictions were removed. These two events have had serious consequences for the development of land markets needed to consolidate private farms and provide farmers with incentives to invest. The lack of an effective rural land market in Romania has posed a significant constraint on the access of farmers to credit (see below).

15

Land was restituted to those individuals that were forced to put their land under collective control during 19491962.

4

Chapter One:

The new land ownership and tenure did not match the previous arrangements for input procurement or output marketing, requiring adjustments across all segments of the chain. Changes in land tenure made established distribution channels in input and product marketing unsuitable for a very small and dispersed clientele. A rapid organizational solution was needed in response to these changes in order to re-establish marketing and credit chains for small farmers and family associations. The Government, however, failed to recognize this, and opted instead to maintain the status quo. The immediate effect was a severe drop in input use, followed by a notable reduction in output 1992-1993 − the largest in two decades. The Heavy Hand of the State Faced with a substantial reduction in agricultural output in 1991-92, the authorities decided to replace the “invisible hand” of market forces with the “heavy hand” of the State in agriculture, which delayed the adjustment to a market economy and created open ended large public liabilities. The agricultural policy implemented between 1992 to 1996 had two pillars: (a) to use the financial sector to allocate subsidies to agriculture in which bankers were dictated to whom to lend and at what rates; and (b) to use the procurement, marketing, and credit arrangements of the communist era to implement administratively set prices for the inputs and outputs of main agricultural products, namely (i) ROMCEREAL, a parastatal controlling the country’s entire silo capacity under a single management and (ii) the network of state-owned animal breeding facilities. These massive interventions have been extremely costly for the Government (about 20 percent of agriculture value added) and have had negative consequences for the development of financial markets. State farms, storage and marketing agents (ROMCEREAL and later NAAP), and the processing industry, which accounted for 20 percent of the gross agricultural output, received 80 percent of agricultural-directed subsidies during 1992-1996. Private lenders have been crowded out from rural credit markets, while lenders with no access to cheap resources to subsidize their loans and permit arrears were out-competed. The repayment culture was shattered, and as a consequence of the misallocation of resources, growth potential in rural areas has ultimately been hampered. Recent Liberalization in Agriculture In 1997, the Government adopted an agricultural reform strategy supported by a structural adjustment loan financed by the World Bank. The strategy covered four areas: (a) agricultural incentives and credit; (b) operation of land and grain markets; (c) privatization of state-owned farms and storage operators; and (d) adoption of a new mandate of the agricultural administration. Although the reform was originally scheduled to be implemented over the period of May 1997 to June 1998, there were significant delays, and full implementation was still uncertain as of Fall 2000. C. RURAL EMPLOYMENT The rural labor market is virtually mono-sectoral with more than 70 percent of the labor force in agriculture and mono-occupational and 65 percent of employment in farming. Rural


5

areas have a dual economy in which a commercial sector coexists with a large informal sector. The commercial sector consists of about 80 thousand incorporated business, most of which were created after the fall of the centrally planned regime. The informal sector consists, in large part, of small-scale farms and a handful of other businesses, and is dominated by small-scale, subsistence-based farms. The economy of these rural households is highly autarchic, is based on low-input production technology, and is largely directed toward self-consumption. With a working age population exceeding 8.2 million, the household survey shows that 72 percent of adults (15 years or older) were economically active, compared to 59.3 percent in urban areas during the period covered by the survey. The age-labor force participation profile is concave and peaks for the group of individuals in their forties. About 24 percent of adults were wage earners, 27 percent were entrepreneurs (self-employed or employers), and 21 percent were non-paid family labor. The majority of entrepreneurs (about 92 percent) were engaged in farm activities and, compared to western economies, the extent of non-farm entrepreneurial activities is minimal. Gender differences in labor force participation are significant but small, with 75 percent of males employed and only 67 percent of females holding any type of job during the period covered by the surveys. However, the survey shows substantial differences in the types of jobs between the genders. For example, 29 percent of males were employed as farm entrepreneurs, compared to 20 percent of females. Moreover, family labor was more predominant among females (29 percent) than among males (11 percent). Labor markets show some differences among agro-regions. Farm entrepreneurs accounted for 36 percent of adults in Moldova de Podis, but for only 14 percent in SAI. The proportion of pensioners, which is only 5 percent in Moldova de Podis, is as high as 23 percent in Campia Romana Centrala. D. RURAL HOUSEHOLDS AND THEIR ECONOMIC ACTIVITIES Most rural households operate with limited integration into market activities and primarily engage in agricultural activities. About 61 percent of rural households were self-sufficient farm households, according to the survey data, in that they did not: (a) sell any outputs; (b) buy any inputs; (c) hire labor; or (d) rent or buy fixed assets. Seventeen (17) percent had some marginal involvement in markets (less than US$20 of monthly sales), 12 percent had substantial market involvement, 5 percent had non-farm entrepreneurial activities, and the remaining 5 percent relied strictly on wages and pension benefits. This limited market integration may reflect the comparative isolation of households from large towns and market centers. About 52 percent of surveyed households lived 27 kilometers or more from a town and 42 percent lived 11 kilometers or more from a railway station. Rural households are headed by older men. Almost half of household heads were 60 years old and older, and about three-quarters (74 percent) of them were males.

6

Chapter One:

Household Income Average per capita monthly income of households was US$67 (567,980 lei) during the period covered by the survey, which was about 60 percent of monthly per capita GDP and 50 percent of the average net wages at the national level. Household income was computed in four categories: sales of agricultural products, sales of non-agricultural products, imputed value of monthly self-consumption, and periodic income, such as wages and pension benefits.16 For the average household, wages and pension benefits were the most important sources of household income (58 percent), while agricultural and non-agricultural sales represented the least significant sources, 6 percent and 5 percent, respectively. The imputed value of self-consumption accounted for 30 percent of income. The distribution of monthly per capita income is skewed, as 52 percent of income went to the top quartile of households. The bottom quartile of the distribution earned 9 percent of the total. In this way, households in the richest per capita income quartile earned six times more than those in the poorest income quartile. Household Wealth The per capita wealth endowment of households had a market value of US$1,564 (13,261,300 lei) during the period covered by the survey.17 Agricultural land and housing constituted the main assets of rural households for 25 percent and 32 percent of household wealth, respectively. The household survey shows that the distribution of wealth endowments is a bit more skewed than that of income. About 59 percent of aggregate total wealth was owned by the top wealth quartile. Moreover, households in the lowest wealth quartile had 12 times fewer assets than households in the richest quartile. Farm Households Most farms are small and fragmented. The average farm had 2.1 hectares, and was subdivided into 3 or 4 plots. In fact, 35 percent of households operate more than four farming plots. About a fifth (17 percent) of all households operate a portion of their landholdings through family associations and a very few (4 percent) in agricultural associations. Almost all farms are for self-subsistence production (68 percent during the period covered by the survey), are based on the labor input of household members (99 percent during the period covered by the survey), and use very simple technologies. The typical farm is one where two adults work and occasionally hire one paid worker during the peak planting or harvesting season. Most farmers use their own seeds to grow grains and their own livestock to raise animals. About 16

This last category includes wages, pensions, social aid and other protection benefits, plus annual incomes from land leased, dividends, and asset rentals.

17

Household wealth includes the imputed value of buildings, agricultural land, houses, equipment, livestock, and agricultural stock. Annex 1 provides a detailed description of the method used to estimate the value of these assets.


7

half of farmers utilize fertilizers but only a small percentage apply pesticides or other intensive inputs. Most farmers rent machinery or animal-traction to plough and harvest. Larger farms are the exception. Less than 17 percent of farms earned an income higher than the economy-wide average wage during the period covered by the survey. Only one percent of farms had one or more permanent paid worker and only 8 percent operated more than 5 hectares. There are significant regional differences in the size of farms. Farms located in Transylvania, Western Plain and Southern Sub-Carpathia earn Figure 3 Rural Households by Farm Size higher incomes and are wealthier. These areas are also 5 Has or more Landless the ones where farm (8%) (12%) entrepreneurs hire permanent workers and where there is a 2 - 5 Has higher incidence of seasonal (28%) workers. Farms located in Transylvania are the largest and < 1 Ha (30%) are more fragmented on average. Although GDP declined dramatically in 1997, most farm households perceived that their activities were the same in 1996 Source: Survey of Rural Households and Financial Services, 1998. as in 1997 (42 percent). Only 21 percent considered that economic conditions declined in 1997, while the remaining 34 percent reported that 1997 was better than 1996. Among those farm households reporting 1997 as their worst year, 90 percent attributed their situation to low income levels resulting from such causes as low levels of production. 1- 2 Has (22%)

Non-Farm Households Non-farm entrepreneurial activities are very limited among rural households. Only 5 percent of households had members who were entrepreneurs outside agriculture during the period covered by the surveys. These members accounted for about two percent of the economically active rural population. Non-farm entrepreneurs had (mostly small) businesses in all economic sectors with 25 percent in (mostly small) trade, 23 percent in the processing industry, 21 percent in transportation, 15 percent in construction, and 10 percent in services. Whether measured by number of employees, value of assets, non-farm income, or accounting practices, the business activities carried out by non-farm households tend to be small and informal. In fact: (a) 75 percent employed one or no workers at all during the period covered by the survey; (b) 75 percent had an endowment of assets in their business of less than US$1,775; (c) their average monthly income was US$139, which was higher than farm entrepreneurs, nevertheless; (d) 40 percent were not registered nor had licenses; and (e) only 27 percent kept formal accounting records of their activities. These small and micro rural businesses were comparatively young and depended mostly on local markets. More than half had been in

8

Chapter One:

business for less than five years, while only about a tenth of them sold their products or services outside their immediate community. E. RURAL ENTERPRISES As of 1997, the Romanian rural economy contained about 80,000 rural enterprises.18 The large majority of them were engaged in trade and commerce (62 percent). Agriculture was the main activity for 6 percent of them. The remaining enterprises were evenly divided between the service sector (15 percent) and industry and construction (16 percent). Private sector enterprises dominate the sector in terms of number of enterprises (98 percent were totally private during the period covered by the survey). However, the participation of the state in terms of the value of assets was very significant and disproportionately large. The two percent of enterprises that had some degree of state ownership controlled more than half of the aggregate book value of the assets of all rural enterprises. The incidence of state ownership is highest in agriculture, where about a fifth of agricultural businesses were owned partly by the state during the period covered by the survey. These state enterprises in agriculture were particularly large. They accounted for about one percent of all rural enterprises, but controlled about 43 percent of their assets. The private enterprise sector is basically composed of small and medium size businesses. In fact, the average private enterprise had US$11,900 of assets at book value, and 80 percent had less than 5 employees during the period covered by the survey. Most firms are owned by few individuals, as 93.2 percent had less than five partners or shareholders during the period covered by the survey. In agriculture, however, the situation is reversed as 74 percent of businesses had more than 5 partners or shareholders. The average age and years of experience of managers of agricultural-related businesses is higher than the average for the rural sector (48 years of age with 15.4 years of experience in the case of agricultural managers, and 42 years of age with 8 years of experience for the whole sector during the period covered by the survey). About half of the managers of private sector enterprises were under 40 years of age, while less than 20 percent of state enterprises had managers under 40. Table 1 presents the consolidated balance sheet for the rural enterprise sector in 1997. The sector was dominated by agriculture in terms of activity and by the state in terms of ownership. Agriculture accounted for 57 percent of total assets while the state controlled about half of all assets. Dominance of agriculture resulted because the book value of land and buildings accounted for 42 percent of total assets in the hands of rural enterprises, of which three quarters were devoted to agricultural production. The value of land in agriculture, however, represented a smaller percentage of total assets than that normally observed in countries with developed

18

This figure excludes all: (a) enterprises with operations in rural areas, but with headquarters in urban areas, and Regies Autonomes; (b) enterprises not legally incorporated; (c) branch offices of financial institutions, public administration offices; (d) educational institutions; and (e) health care units.


9

agriculture. For instance, in the United States real estate has represented roughly from 70 to 80 percent of aggregate agricultural assets over the last 30 years. A combination of the following two elements may explain the deviation of Romanian agriculture from the international norm. First, land markets in Romania have not worked well which has led to low land values. Second, Romanian accounting norms do not allow revaluation of fixed assets. The upper bound for the share of real estate in the market value of total assets in the sector was 72 percent. This ratio results from adjusting the consolidated financial statements of enterprises according to International Accounting Standard (IAS) No. 29 (see Table 2) to account for high inflation in the period under analysis. This share is considered an upper bound because it is unlikely that the market value of land adjusted at the same pace as inflation. Rural enterprises in the aggregate financed 52 percent of their assets with debt. The most indebted sub-sector was trade and commerce, with a debt to assets ratio of 72 percent. Agriculture was the least indebted with a corresponding ratio of 43 percent. This level of indebtedness is at the lower end of the debt to assets ratios of non-financial sector enterprises in industrialized countries. These ratios varied from 51 percent in the United States to 80 percent in Japan.19 However, the capacity of the rural sector to carry debt is a matter of policy concern. There is a potential problem because illiquid assets, especially land, dominate the sector’s balance sheet. The capacity of assets to carry debt is directly related to their liquidity. This problem may be particularly serious for Romanian agriculture. Debt levels are already high in the sub-sector. The 43 percent debt to assets ratio of Romanian agricultural enterprises contrasts sharply with the equivalent ratios for agriculture in the United States, which varied from about 12 to 16 percent over the last 30 years. The profitability indicators of the enterprise sector are rather weak. These indicators vary significantly between private and state enterprises and across sub-sectors. The aggregate return on equity (ROE) and return on assets (ROA) of Romania’s rural enterprises in 1997 were much lower than inflation (19 percent and 9 percent, respectively, against an annual inflation rate of 155 percent). The ROE of private enterprises was 69 percent and that of state owned enterprises was negative 9 percent. The share of state enterprises which reported losses was 53 percent, while the equivalent share among private ones was 29 percent. The aggregate of agricultural enterprises reported losses. The remaining sectors generated aggregate profits. The trade subsector was, by far, the most profitable in terms of ROE.20 Cash flow analysis confirms the above findings (see Table 1). The value of the sales (products and services) of the entire rural enterprise sector was not sufficient to cover production costs and operational expenses in 1997. The gross net cash from operations was negative at the 19

The corresponding ratios for selected countries are 56 percent for the United Kingdom, 57 percent for France, 60 percent for Germany, 72 percent for Switzerland, and 76 percent for Italy. The consolidated debt ratio of Romanian rural enterprises, calculated on the basis of their financial statements adjusted by inflation, is 25 percent (see table1.A).

20

The financial statements adjusted for inflation indicate that the consolidated ROE for rural enterprises was 2.4 percent. Private sector enterprises had a consolidated ROE of 16 percent while their state-owned counterparts had a ROE of negative six percent.

10

Chapter One:

consolidated level and for all sub-sectors with the exception of trade. The net cash from operations was made (barely) positive by significant non-operational income, namely financial and exceptional revenues. A worrisome implication from Table 1 is that rural enterprises are not able, in the aggregate, to serve their existing debt. In particular, the agricultural and services sub-sectors need to incur additional debt to serve interest payments and amortize the principal amount of their outstanding debts. The table also shows that the state-owned sub-sector was the cause of this situation, as the negative balance on its net cash flow in 1997 was large enough to wipe out the net cash surplus generated by the private sector. Interestingly, the enterprise survey shows that the banking sector allocated 45 percent of all new credit flows to state enterprises with negative cash flows. The capacity of the sector to carry debt and its efficiency in allocating credit flows to the best alternative uses is analyzed in detail in Chapter IV. Nonetheless, it should be noted that a likely outcome of lending to state enterprises with negative cash flows is that these loans will have to be assumed by the Government or by the banking system, as the likelihood of these enterprises returning to a positive cash flow under state ownership is minimal and privatizing them will be difficult while they have a large debt overhang. Among private enterprises, the agricultural sub-sector is the least profitable with a ROE of 8 percent in 1997. Private enterprises in all sub-sectors, except trade, also had operating and production expenses above the value of sales. Thus, in the aggregate their gross cash from operations was negative. The difference was that private enterprises had more miscellaneous revenue and lower financing costs relative to assets. This situation allowed them to serve their existing debts without additional injections of external funding.


11

Table 1 Consolidated Financial Performance of Rural Enterprises in 1997 Economic Sector (in billion Lei) Balance Sheet (yearly avg.) Fixed assets Current assets Other assets Total Assets

Total 8,291 7,094 367 15,752

Agriculture 5,936 2,760 258 8,954

Industry & Construction 1,441 1,412 61 2,914

Ownership Type

Trade 669 2,691 40 3,399

Services Public Mixed Private 245 231 8 485

1,075 301 3 1,378

4,678 1,767 77 6,522

2,539 5,027 287 7,852

Equity 7,446 5,137 1,114 948 247 833 3,988 Provisions & others 59 18 37 4 0 0 18 Liabilities 8,178 3,788 1,752 2,425 213 545 2,489 Other Liabilities 69 11 12 22 25 0 27 Total liabilities & equity 15,752 8,954 2,914 3,399 485 1,378 6,522 Income Statement Total revenue 33,464 8,564 7,121 16,370 1,408 753 5,227 Total expenses 30,939 8,748 6,958 13,932 1,300 780 5,588 Net Income (Loss) before taxes 2,525 -184 163 2,438 108 -27 -361 Net Income (Loss) 1,398 -278 70 1,526 79 -40 -395 Financial Ratios (%) Debt Ratios Liabilities / Assets 51.9 42.3 60.1 71.3 43.9 39.6 38.2 Liabilities / Equity 109.8 73.7 157.4 255.7 86.2 65.4 62.4 Bank Loans / Liabilities 72.3 83.0 60.0 64.2 74.5 93.0 85.6 Assets / Equity 211.6 174.3 261.7 358.4 196.3 165.4 163.5 Profitability Ratios Return on Equity 18.8 -5.4 6.3 160.9 32.1 -4.9 -9.9 Return on Assets 8.9 -3.1 2.4 44.9 16.4 -2.9 -6.1 Profit Margin on Sales 4.7 -4.5 1.1 9.4 6.6 -7.1 -10.9 Statement of Cash Flowsa 1 Cash from Sales 21,003 3,118 3,516 13,409 959 522 1,358 2 Cash Production Costs -18,408 -3,105 -3,378 -10,921 -1,003 -425 -1,604 3 Gross Cash Margin (1+2) 2,595 13 137 2,488 -44 97 -246 4 Cash Operating Expense -2,736 -1,098 -562 -897 -179 -165 -500 5 Gross cash from operations (3+4) -141 -1,084 -425 1,591 -223 -69 -747 6 Miscellaneous Cash Income 2,439 1,351 734 159 195 168 833 7 Taxes paid -1,209 -157 -105 -905 -43 -32 -63 8 Net Cash from Operations 1,089 110 205 846 -71 68 23 (5+6+7) 9 Financing Costs and Exceptional -1,161 -816 -205 -120 -20 -180 -480 Costs 10 Net Cash Income (8+9) -71 -706 1 725 -91 -113 -456 11 Net capital expenditures -911 88 -310 -572 -117 -19 219 12 Financial Surplus (Requirements) -982 -618 -309 153 -208 -132 -237 (10+11) 13 External Financing 1,209 634 382 -26 220 152 233 14 Cash and Deposits after 227 16 72 127 12 20 -5 Financing (12+13) 15 Actual Change in Cash and -227 -16 -72 -127 -12 -20 5 Deposits a Excludes those enterprises for which the cash flow statement did not balance (about 15 percent of observations) Source: Survey of Rural Enterprises and Financial Services, 1998.

2,625 41 5,144 42 7,852 27,484 24,570 2,913 1,834

65.5 196.0 63.6 299.1 69.8 23.4 7.2 19,123 -16,378 2,744 -2,070 674 1,439 -1,114 998 -501 498 -1,111 -613 824 211 -211

12

Chapter One:

Table 2 Consolidated Financial Performance of Rural Enterprises in 1997 (Adjusted by Inflation)

Agri(billion Lei) Total culture Inflation Adjusted Balance Sheet (yearly avg.) Fixed Assets 19,919 14,976 Current Assets 12,625 5,373 Other assets 372 264 Total assets 32,915 20,613 Equity 24,440 Provisions & others 61 Liabilities 8,366 Other liabilities 49 Total Liabilities & Equity 32,915 Inflation Adjusted Income Statement Total revenue 49,954 Total expenses 48,244 Net Income (loss) before 1,710 Taxes Net Income (loss) 583 Financial Ratios (%): Inflation Adjusted Financial Ratios Liabilities / Assets 25.4 Liabilities / Equity 34.2 Assets / Equity 134.7 Return on Equity 2.4 Return on Assets 1.8 Net income / Sales 2.0 Sales / Avg. Assets 90.1

Economic Sector Industry & Construction Trade

Ownership Type Services

Public

Mixed

Private

3,205 2,076 60 5,341

1,236 4,813 39 6,089

502 363 8 872

2,670 511 3 3,183

12,011 3,639 81 15,731

5,238 8,475 288 14,001

16,660 19 3,924 11 20,613

3,512 37 1,785 7 5,341

3,633 4 2,443 8 6,089

635 0 214 24 872

2,634 0 549 0 3,183

13,099 19 2,587 27 15,731

8,707 42 5,229 23 14,001

19,647 20,269 -621

9,412 9,468 -56

19,111 16,787 2,324

1,783 1,719 64

2,524 2,593 -69

13,915 14,636 -722

33,515 31,015 2,500

-715

-149

1,412

35

-82

-755

1,420

19.0 23.6 123.7 -4.3 -3.5 -11.5 30.1

33.4 50.8 152.1 -4.2 -2.8 -2.4 114.5

40.1 67.3 167.6 38.9 23.2 8.7 265.5

24.5 33.7 137.5 5.5 4.0 2.9 137.1

17.3 20.9 120.9 -3.1 -2.6 -14.5 17.8

16.4 19.8 120.1 -5.8 -4.8 -20.8 23.1

37.3 60.1 160.8 16.3 10.1 5.6 181.9

Source: Survey of Rural Enterprises and Financial Services, 1998.

Chapter II: Rural Financial Intermediaries, Market Shares, Credit Products, and Deposit Services This chapter describes the Romanian financial sector in general and the providers of financial services in rural areas. In particular, the chapter analyzes financial service providers’ distribution network, market shares, preferences in lending, and the characteristics of the financial services that they provided to their clienteles. This information is necessary background for the study’s findings on the performance of rural financial markets and for the design of government interventions and policies to improve such performance. 21

Figure 4 Credit from Deposit-taking Banks to the Private Sector, 1998 (as percent of GDP) A ZE

3.3%

K AZ

6.2%

UKR

7. 6%

ARM

8 .6%

L TU

11.3%

BUL

12.7%

RO M

12.7%

RUS

12.9%

L AT

14.1%

M OL

14.4% 19.6%

POL H UN

23.3% 25 .3%

EST

32.9%

S LO CRO

40. 9% 45.9%

S VK

58.0%

CZE

0%

20%

40% Per cent of GDP

Source: Eichengreen and Rühl, 2000.

60%

80%

A. THE FINANCIAL SECTOR Traditional measures of financial market development, such as broad money to GDP, market capitalization to GDP, or outstanding private sector credit to GDP show that the financial sector in Romania is shallow and underdeveloped compared to other countries in the region, as well as other countries with similar levels of income per capita.22 Further, financial sector development in Romania is taking place in an environment where lenders and borrowers must contend with macroeconomic instability, an uncertain and insecure legal environment, and a taxation regime which is not friendly to financial intermediaries and transactions. Figure 4 shows that Romania’s financial sector ranks near the bottom among Central and Eastern European countries in terms of financing of private sector

21

The chapter attempts to provide the required information as succinctly as possible. Readers familiar with the sector may skip some sections accordingly. Those unfamiliar with the subject may benefit from reading Annex 2 of this study, which contains more detailed information on Romania’s financial sector.

22

Sections A and B of this Chapter are drawn largely from Chapter 5 (“Financial Sector Development”, Chaves, 2000) of the Romania Country Economic Memorandum (CEM), the publication of which is forthcoming.

14

Chapter Two:

activities. The role of market-based financial intermediation (enterprise finance provided through stock markets or other security markets) in Romania is even smaller than that of the banking sector, implying that the financial sector remains dominated by bank-based intermediation.23 Credit markets, in turn, are dominated by the banking industry, because the size and presence of non-banking sector lenders, including leasing and financial companies, are negligible. B. THE BANKING SUB-SECTOR The number of banks has moderately increased in Romania (see Table 3) since the early 1990s after the mono banking system was abandoned, and the number of commercial banks has remained stable over the last few years. By mid-2000, 42 banks operated in Romania, including 7 subsidiaries of foreign banks. Overall, Romania remains severely “undermonetized” and “underbanked”. It is undermonetized both in terms of the ratio of domestic credit from deposit-taking institutions to GDP and in terms of asset size (see Figure 4, Figure 5, and Table 3). It is underbanked in the sense that the absolute size and number of assets in the banking system is small relative to the existing number of banks, bank branches, and bank personnel. Total assets in the banking sector reached 192 trillion Lei in September of 2000 (about $7.6 billion), which is less than the assets of a medium-sized German bank. The banking system is dominated by state banks, which accounted for 71 percent of total banking assets and 81 percent of total bank deposits in national currency during the period covered by the surveys. Private banks are becoming important players in the capitalization of the banking system, however. Their share in the system’s capital increased by 10 percentage points to well above 40 percent from 1994 to 1996 (Davis Hare, 1997). State-owned, private, and foreign banks have traditionally specialized in different market niches in the aggregate economy24. State-owned banks have specialized in servicing state enterprises and the agricultural sector. The subsidiaries of international banks have been mainly interested in servicing multinational and corporate clients.

23

Because securities markets play such a limited role in Romanian financial markets, they are not discussed here. A detailed discussion of Romanian securities markets is presented in Chapter 5 (“Financial Sector Development”, Chaves, 2000) of the Romania Country Economic Memorandum (CEM), 2000.

24

The market shares of each type of bank and the kinds of clients to which they lent in rural areas are presented in detail in section D of this Chapter.

Rural Financial Intermediaries, Market Shares, Credit Products, and Deposit Services

15

Figure 5 Credit to the Private Sector: Transition Economies and Rest of the World, 1998 (as percent of GDP)

100% 90% 80% 70% Non-transition economies

60%

CZ

SEE

50%

CE and Baltics

SVK CR

40%

CIS SLO

30% EST

20%

FYRM BUL LAT

MOL

10%

ARM KYR

UKR

BEL RUS

RO KAZ

HU

PL

LIT

AL AZ

0% 0

5000

10000

15000

Income per capita at Purchasing Power Parity

Source: Romania: Country Economic Memorandum, publication forthcoming.

While the ownership structure of the banking sector is still behind other European transition economies in terms of the share of private banks, it has improved over the last few years. This is due to privatization efforts (Bank Post and the Romanian Development Bank), but even more so to the closure of the largest state-owned bank, Bancorex, in 1999. Improvements in the composition of the bad loan portfolio in commercial banks can be traced to the same cause (see Table 4): (a) the clean up of 1998 and 1999, when Bancorex was first put under special administration and then liquidated; and (b) the neutralization of Banca Agricola through its takeover by an NBR-sponsored management team. These events restricted Banca Agricola’s activities (in particular, by not allowing it to engage in any new lending and investment operations) and enhanced provisioning and capital adequacy ratios across the board.

16

Chapter Two:

Table 3 Composition of the Romanian Banking Sector, 1996-2000 1996

1997

1998

1999

2000:I

Number of Commercial Banks 35 37 Of which: Romanian incorporated banks 29 31 State-owned 7 7 Private 22 24 Of which joint venture with foreign 8 11 Branches of foreign banks 6 6 Banks under special treatment* 1 1 Share of Total Banking Sector Assets All commercial banks 100 100 Of which: Romanian incorporated banks 96.1 93.4 State-owned 77.8 74.7 Private 18.4 18.7 Of which joint venture with foreign 4.3 6.4 Branches of foreign banks 3.9 6.6 Banks under special treatment 3.7 1.7 * Suspended, special administration, in court, etc. Source: National Bank of Romania and International Monetary Fund, 2000.

45

41

42

36 7 29 15 9 3

34 4 30 19 7 3

35 4 31 22 7 3

100

100

100

94.3 71.0 23.3 10.4 5.7 2.5

92.9 46.8 46.2 40.5 7.1 1.8

92.5 44.3 48.2 44.1 7.5 2.0

Table 4 shows that there is no room for complacency. The aggregate balance sheet of Romania’s commercial banks, with more than one third classified as non-performing (doubtful and loss), remains one of the worst in the entire region. The improvements in loan loss provisioning and capital adequacy are in part (in the case of loan loss provisions) due to improved supervision and regulation or (in the case of capital adequacy) to an increased capital adequacy requirement (from 9 to 12 percent in 1999). They are, however, also partially the result of the large transfers of non-performing assets to the newly established asset recovery agency AVAB (Agentia de Valorificae a Activelo Bancare) that took place in 1999 as part of World Bank conditionality. Moreover, though the amount of non-performing assets in state-owned banks largely reflects past years’ exposure to political pressure to engage in directed lending, a factor which influenced the lending practices of these banks and exacerbated the bad loan problem, there is increasing evidence that private banks are getting into difficulties, and these difficulties are due to more complex and market-related factors. As in other transition economies, the banking sector does not have access to long-term funding and thus cannot provide the medium- and long-term credit which would be required to finance the long-term investments that bring about growth. After a prolonged period of high inflation, neither assets nor liabilities are available on maturities in excess of one year. In fact, the bulk of bank liabilities tend to be sight deposits that could be withdrawn at call. Although banks have invested these liabilities in mostly short-term assets, there is a maturity mismatch, because the weighted maturity of assets exceeds the maturity of liabilities. This maturity mismatch, the result of the lack of long-term funding makes long-term loans risky, because banks may experience operational losses if market interest rates increase. Banking supervision improved following a re-organization of the National Bank of Romania (NBR) which, in September 1999, consolidated on- and off-site supervision with bank


17

rating and early warning functions in a new Supervision Department. Another new Department, the Financial and Banking Policies Department, is responsible for licensing, formulation of prudential regulation, and the like. The frequency and coverage of on-and off-site supervision have also improved, and the current bank rating and early warning system is based on international standards. In practice, however, the NBR does not have a good track record in banking and financial market supervision, as the continuing difficulties in the banking sector (where several insolvent banks have remained active and are awaiting some sort of resolution for years) demonstrate. Table 4 Non-performing Loans, Provisions, and Capital Adequacy Ratio (1996-2000) 1996 1997 Share of Non-Performing Loans All commercial banks 100 100 Of which: Romanian incorporated banks 47.2 52.6 State-owned 43.0 51.1 Private 63.3 60.1 Of which joint venture with foreign 24.1 56.2 Loan Loss Provisions: Share of Actual to Required All commercial banks 100 100 Of which: Romanian incorporated banks 64.5 73.1 State-owned 59.2 74.5 Private 79.0 57.0 Of which joint venture with foreign 40.3 56.0 Capital Adequacy Ratio of the Banking System All commercial banks 14.0 13.6 Of which: Romanian incorporated banks 14.0 13.6 State-owned 13.2 12.0 Private 18.4 22.0 Of which joint venture with foreign 22.2 34.7 Source: National Bank of Romania and International Monetary Fund, 2000.

1998

1999

2000:I

100

100

100

58.5 52.9 73.9 45.1

35.4 32.3 37.5 26.0

35.4 36.2 34.8 34.2

100

100

100

73.8 72.3 77.4 57.6

102.7 114.5 94.6 90.7

94.4 91.2 96.9 97.3

10.3

17.5

21.4

10.3 10.3 10.0 36.6

17.5 17.5 17.5 27.0

21.4 20.4 22.1 22.2

Despite recent regulatory reforms, the state of the Romanian banking system remains uncertain and lags behind other transition economies (Davis and Hare, 1997; Meyer et. al, 1997; Schrieder and Heidhues, 1997). Unfortunately, government-mandated lending programs where banks had limited authority to decide on the allocation of credit persisted up to 1997 (Schrieder and Heidhues, 1997). The ability to appraise loans has been acquired only gradually, and other banking skills and business methods are still in their formative stages. Chronic asset quality problems, political interference in lending, shortage of liquidity, poor capitalization, burdensome non-performing loans, poor management, and lack of transparency are among the main issues that have negatively affected the performance of the banking sector. A volatile macroeconomic environment and the poor financial performance of enterprises in general have contributed to this adverse state of affairs. Substantial restructuring and privatization of state banks will be necessary to build a strong banking system. The privatization of Romanian Development Bank and of Banc Post in 1998,

18

Chapter Two:

the divestiture of Bancorex, and the recent decision to place Banca Agricola under special administration are a step forward in reducing political interference and ensuing credit losses in the system. Still, however, there will be a strong need to significantly improve the scope and quality of banking services, especially at the retail level. C. MUTUAL RURAL FINANCIAL INTERMEDIARIES This section presents data on credit cooperatives (CCs) and Casa de Ajutor Reciprocs (CARs) which are non-bank mutual financial intermediaries.25 These intermediaries date back to the mid-1800s and are owned by their members who are also depositors and borrowers. During the communist era, CARs were taken over by the labor unions of state enterprises and were merged with credit and consumer cooperatives. Since 1989, credit cooperatives and CARs have been classified as separate entities and have provided simple savings and loan services to their members independently. Credit Cooperatives Credit cooperatives are organized in a three-tiered system. There were 840 credit cooperatives operating at the comuna level, with a membership of about 1.8 million farmers, professionals, and self-employed individuals in 1998. These cooperatives were organized in 41 federations comprised of the credit cooperatives and consumer cooperatives that operate in each judet (FEDERALCOOP). There were from 15 to 20 credit cooperatives in each judet. At the national level, credit cooperatives are affiliated with an apex institution (CREDITCOOP). Lastly, the federation of credit unions is associated with the consumer cooperatives’ network, forming the National Cooperative Union (CENTROCOOP). As of December 1998, credit cooperatives had about US$92 million (1,000 billion Lei) in assets and US$63.1 million (688 billion Lei) in deposits from members. The value of their portfolio of outstanding loans was about US$69 million (750 billion Lei). While most credit cooperatives operate in rural areas, loans to agricultural activities accounted for only 10 percent of outstanding loans during the period covered by the surveys. These are small financial intermediaries, therefore. The average credit cooperative in Romania had assets of US$110,000 and 3.5 employees during the period covered by the surveys. The supervision of credit cooperatives rests with the House of Credit Cooperatives (CREDITCOOP). However, this responsibility is delegated at the judet level to Territorial Houses of Credit Cooperatives. The National Bank of Romania (NBR) has never supervised credit cooperatives. CREDITCOOP and the Territorial Houses are so involved in the lending process that, in practice, numerous credit cooperatives behave as branches, rather than as independent 25

There are an estimated 1,400 independent mutual financial intermediaries (MFIs) registered under Law 109/1996. The information presented in this section corresponds to the CCs and CARs affiliated with national systems. There was no information available on other non-affiliated MFIs, most notably Banca Populara. Chapter V addresses the regulatory hazards implied by the functioning of numerous unregulated MFIs, and provides possible options to ameliorate such risks.


19

intermediaries. Small loans under US$350 (3 million Lei) are approved by credit cooperatives themselves. Loans up to about US$825 (7 million Lei) must be approved by the corresponding Territorial House of Credit Cooperatives. Larger loans must be approved by CREDITCOOP. Casa de Ajutor Reciprocs Casa de Ajutor Reciprocs are mutual financial organizations that primarily serve workers of rural enterprises, commercial societies, and state-owned companies. CARs are also organized in a tiered system. Casa de Ajutor Reciprocs are the units at the comuna level. There are unions at the judet level, while the Uniunea Nationala a Caselor de Ajutor Reciproc (UNCAR) includes all the CARs in the country. As of March 1999, there were about 4,600 CARs out of which 400 were in rural areas. Membership was about 1.8 million individuals, outstanding loans amounted to US$70 million (767 billion Lei). The average loan outstanding loan was for US$192. CARs seem to have simple but strict loan underwriting standards, requiring a combination of cosigners and collateral. Various studies report that CARs experience virtually no loan losses (Meyer 1997). D. DISTRIBUTION NETWORK OF FINANCIAL SERVICES This section describes the Romanian distribution network of retail finance and the services it provides. The objective is to examine the ownership structure of this network and the role it plays in providing access to financial services, if any, especially in rural areas. In particular, the following questions are answered. First, who owns the distribution network of retail financial services? Second, which localities are more likely to have financial outlets and which specific economic and demographic factors are related to the presence (or absence) of financial outlets? Third, which factors are related to the total number of financial outlets in the different localities? Fourth, which economic and demographic factors explain the ratio of loans to deposits in branches located in different communities? While the financial sector in Romania is still relatively underdeveloped, the country possesses an extensive network of retail financial outlets in both rural and urban areas. This network is dominated by state banks and by unregulated mutual financial intermediaries (mostly credit cooperatives). The country had 3,156 bank branches and 840 credit cooperatives for a total of 4,076 retail outlets during the period covered by the survey. There was one retail outlet for every 58 km2 and for every 5,597 inhabitants, which indicates that the banking network is particularly dense. As shown in Figure 6, while the industrialized countries have more bank branches per capita, few developing countries have more bank branches per capita than Romania. An exception is India with 4,000 inhabitants per bank branch. Mexico is an example of the other extreme, with 28,000 per bank branch.

20

Chapter Two:

There are four types of bank retail outlets. Full branches (sucursula judetana), sub-branches (sucursula), agencies (agenties), and offices (point du lucru). Branches and sub-branches are very similar in terms of loan and deposit services offered to Figure 6 Population per Bank Branch customers. However, branches are located in the Romania capital of each judet. Most Spain decision-making is United States Canada conducted at the Britain branch/sub-branch level. Germany Agencies and offices do not France process or approve loan Italy applications. Instead, they Japan remit all loan applications to India the main branch in the Australia locality, or directly to Argentina headquarters. Nonetheless, Brazil Mexico approved loans are 5,000 10,000 15,000 20,000 25,000 30,000 disbursed and recorded at the agency level after Source: International Bank for Settlements, 1999. upstream approval. Agencies accounted for 61 percent of outlets, branches and sub-branches for 34 percent, and offices for four percent during the period covered by the survey. The banking sector’s distribution network was dominated by state banks which owned 87 percent of all retail outlets. Of the 3,156 bank retail outlets, 2,749 were owned by state banks. Private banks owned the remaining 407 outlets. This large network is concentrated in only a few banks, however. For instance, the Savings Bank (CEC) owned 1,970 outlets, which accounted for 60 percent of the total, while 86 percent of private outlets belonged to two private banks, which had 348 outlets between Figure 7 Percentage of Localities with Financial Outlets across them. Population Brackets 100

% locality bracket

90 80

All Localities

70 60

59

54

Up 2 thou 2-3.5 thou

50 40

3.5 -5 thou

30

5-8 thou

30

>8thou

20

9

10 0 with State-owned banks

with Private banks

with Credit cooperatives

Source: Survey of Financial Intermediaries, 1998.

with any financial outlet

Slightly more than half of all financial outlets were located in rural areas during the period covered by the survey (52 percent). State owned banks were the predominant institutions in rural areas (they owned 94 percent of


21

outlets in such localities). This dominance resulted because state banks not only had about five times more outlets than private banks, but also located 52 percent of them in rural areas. Private banks, in contrast, had 23 percent of their (fewer) outlets in rural areas. About 60 percent of the country’s localities had at least one financial retail outlet (either a bank office or a credit cooperative) during the period covered by the survey. State banks had established financial outlets in 54 percent of the country’s localities, private banks in about 9 percent, and cooperatives in 30 percent. Naturally, bank outlets tended to be concentrated in localities with more population. Only 25 percent of localities with 2,000 or less inhabitants had an outlet. In contrast, 95 percent of localities with more than 8,000 inhabitants had a branch (see Figure 7). Other regional and demographic variables are related to the likelihood of a locality having at least one outlet. An econometric model of the factors that explain the presence or absence of at least one financial outlets was applied to the data.26 The model showed that there were substantial differences across agroregions.27 Localities in Campia Romana Centrala and in Campia Dunarii de Jos were more likely to have outlets with statistical significance. All other agro-regions were less likely to have outlets. The econometric results also indicate that, everything else the same, localities more likely to have at least one outlet were those with: (a) larger population; (b) higher average education of population; and (c) higher share of professionals (doctors and teachers) and of farmers. There were statistically significant differences in the preferences for location of outlets between private banks and public banks. Private banks were more likely, everything else the same, to have branches in Campia de Vest, Subcarpati de Sud, and SAI. State-owned banks behaved in the opposite way. They were less likely to have established branches in these three localities. State-owned and private banks had a statistical preference for establishing outlets in Campia Dunarii de Jos and Campia Romana Centrala. State banks were also less likely to open outlets in Moldova de Podis and Moldova Deal. The presence of outlets at the locality level, albeit necessary, is not sufficient to guarantee retail customers effective access to financial services. The data presented below focus on the ratio of loans to deposits in these outlets and on whether there were systematic differences between public and private banks and between large and small localities.

26

A probit model explains a dichotomous dependent variable that takes the value of one when there is one or more outlets in a locality, and of zero when there is no outlet, on the basis of a vector of observable characteristics of the locality in question.

27

Romania can be divided into nine agro-regions: Transilvania, Campia de Vest, Moldova de Podis, Moldova Deal, Subcarpatii de Sud, Campia Dunarii de Jos, Oltenia de Sud, Campia Romana Centrala, and SAI (where Bucharest is located). An agro-region is composed of various judets with a similar pattern of land use. The groupings were determined using multivariate cluster analysis by finding the regions which minimize the variance of patterns of land use within all of Romania’s 41 judets.

22

Chapter Two:

Table 5 Consolidated Loans, Deposits, and Loan-to-Deposit Ratios by Agro-region and Population All Localities All Banks Loans 15,490,.25 Deposits 21,580.74 Loans/Deposits Ratio 0.72 Agroregions Transilvania Loans 4,679.81 Deposits 6,957,.7 Loans/Deposits Ratio 0.67 Câmpia de Vest Loans 1,334.83 Deposits 1.334,83 Loans/Deposits Ratio 0.64 Moldova de Podiº Loans 1,276.23 Deposits 1,459.46 Loans/Deposits Ratio 0.87 Moldova Deal Loans 1,373.85 Deposits 1,963.05 Loans/Deposits Ratio 0.70 Subcarpa?ii de Sud Loans 2,719.50 Deposits 4,421.91 Loans/Deposits Ratio 0.62 Câmpia Dunãrii de Jos Loans 1,492.02 Deposits 1,932.17 Loans/Deposits Ratio 0.77 Oltenia de Sud Loans 1,158.23 Deposits 1,416.85 Loans/Deposits Ratio 0.82 Câmpia Românã Centrala Loans 1,434.28 Deposits 1,226.41 Loans/Deposits Ratio 1.17 SAI Loans 21.49 Deposits 104.35 Loans/Deposits Ratio 0.21 Population Categories < 2,000 Loans 4.94 Deposits 48.84 Loans/Deposits Ratio 0.10 2,000 – 3,500 Loans 57.49 Deposits 435.59 Loans/Deposits Ratio 0.13 3,000 – 5,000 Loans 104.07 Deposits 648.14 Loans/Deposits Ratio 0.16 5,000 – 8,000 Loans 391.26 Deposits 1,249.90 Loans/Deposits Ratio 0.31 >8,000 Loans 14,932.48 Deposits 19,198.27 Loans/Deposits Ratio 0.78 Source: Survey of Financial Intermediaries, 1998.

Private Banks Only 2,430.49 2,746.88 0.88

State Banks Only 12,612.92 18,629.41 0.68

All Banks -CEC 15,222.44 16,429.56 0.93

Credit Coop 446.83 204.46 2.19

546.07 727.54 0.75

3,993.48 6,156.37 0.65

4,61839 5,536.05 0.83

140.26 73.46 1.91

216.14 216.14 0.58

1,055.63 1,055.63 0.62

1,317.48 1,660.91 0.79

63.07 29.88 2.11

290.86 232.30 1.25

949.50 1,213.50 0.78

1,261.01 1,075.76 1.17

35.88 13.66 2.63

188.84 239.65 0.79

1,152.79 1,708.33 0.67

1,335.63 1,446.59 0.92

32.23 15.07 2.14

408.87 520.03 0.79

2,233.17 3,868.02 0.58

2,665.43 3,230.37 0.83

77.46 33.87 2.29

188.12 220.11 0.85

1,269.95 1,699.84 0.75

1,469.46 1,449.29 1.01

33.94 12.22 2.78

265.09 252.15 1.05

859.65 1,152.66 0.75

1,112.79 1,041.57 1.07

33.49 12.04 2.78

315.58 155.81 2.03

1,088.20 1,056.33 1.03

1,420.78 884.67 1.61

30.50 14.26 2.14

10.93 29.80 0.37

10.56 74.55 0.14

21.49 104.35 0.21

0.00 0.00

0.00 0.00 -

3.83 48.37 0.08

2.36 3.92 0.60

1.11 0.48 2.33

3.99 2.46 1.62

37.24 425.84 0.09

37.30 78.34 0.48

16.27 7.29 2.23

20.71 12.86 1.61

52.25 620.73 0.08

74.00 95.50 0.77

31.11 14.55 2.14

85.29 89.28 0.96

252.11 1,134.74 0.22

348.64 468.13 0.74

53.86 25.88 2.08

2,320.50 2,642.27 0.88

12,267.50 16,399.73 0.75

14,760.14 15,783.67 0.94

344.49 156.27 2.20


23

As presented in Table 5, the consolidated ratio of loans to deposits for all bank outlets was 0.72 during the period covered by the survey.28 The consolidated loan portfolio of private banks as a share of their deposits (0.88) was greater than that of state banks (0.68). Removing the Savings Bank brings the ratio for state banks to 0.98. Interestingly, the data suggest that private banks lend more than what they collect in deposits in small localities. Private banks had outstanding loans worth 1.61 times the amount of deposits in localities with less than 8,000 inhabitants. In larger localities with more than 8,000 inhabitants, the ratio decreased to 0.78. In short, private banks are net lenders in small localities and net borrowers in larger localities. In contrast, state banks are net borrowers in all ranges of locality size. This behavior persisted even after removing the Savings Bank, which is a net borrower by design, from the data. State-owned banks (without the Savings Bank) had less loans than deposits. Their loans to deposits ratio was particularly low in small localities. E. MARKET SHARES IN RURAL FINANCIAL MARKETS This section summarizes the market shares of the different credit products that were available in rural areas and the different types of lenders that allocated credit during the period covered by the surveys.29 The shares considered in Table 6 correspond to the flow of credit during the period rather than to the Table 6 Market Shares of Credit Products amounts Households Enterprises outstanding. That is, % % these market shares % amount outstanding % amount outstanding reflect the allocation % trans disbursed amounts % trans disbursed amounts of credit transactions Formal Sector 3.5 16.6 14.6 23.1 68.7 71.0 entered between State Banks 1.6 9.6 6.1 16.1 55.7 56.1 rural agents and Private Banks 1.9 6.9 8.5 7.0 13.0 14.9 Semi-formal Sector 37.4 39.6 38.3 0.4 0.1 0.3 lenders during the CAR 28.2 21.5 19.5 0.1 period covered by Cooperatives 9.2 18.1 18.9 0.4 0.1 0.2 the survey, 59.1 43.8 47.0 76.5 31.2 28.7 Informal Sector regardless of the Moneylender & Others 0.7 1.9 3.6 0.8 0.1 3.6 term to maturity of Friends & Relatives 46.7 26.9 24.2 20.2 3.1 each credit Commercial Credit 7.1 12.8 18.8 41.6 22.9 25.1 Forward Sales 4.6 2.2 0.4 13.9 5.1 transaction. Hence, Total 100.0 100.0 100.0 100.0 100.0 100.0 loans granted prior Total Cash-Loans 88.3 85.0 80.7 44.5 72.0 74.9 to the period under Source: Household and Enterprise Surveys , 1998. consideration and

28

Banks do not only finance their operations with deposits. In Romania there were numerous government-financed directed credit lines and inter-bank borrowing which financed, along with banks’ own resources, the banking sector’s portfolio of loans. The ratio presented above is a proxy intended to capture whether certain types of outlets were more likely to have more loans relative to deposits.

29

Chapter IV provides empirical support to the prevalent perception that there are relatively too few credit transactions in rural areas. It should be kept in mind that this section presents the shares of different credit products and lenders in very thin markets.

24

Chapter Two:

still outstanding at the time of the survey are not considered, while some short term loans granted − but already canceled − during the period under study are considered. The household and enterprise surveys gathered information on three kinds of credit products: cash-loan, commercial or trade credit, and forward sales. Cash-loans are defined as credit transactions disbursed and repaid in cash, commercial credit as transactions extended in kind and repaid in cash, and sales with advances as credit extended in cash/kind and repaid in kind. The surveys also collected data on the credit and loans disbursed by three types of lenders, namely, formal, semi-formal, and informal. The main difference is whether they had a government license to provide financial services or whether they operated under the auspices of specific legislation. The formal sector includes any deposit-taking intermediary supervised by the NBR, mostly commercial banks, of which only seven had a significant presence in rural areas (see Annex 1). The semi-formal sector includes credit cooperatives and mutual help cooperatives (CAR), which are the only institutions with a significant presence in rural areas.30 Informal lenders consist of: (a) moneylenders, who provide cash loans in exchange for explicit interest payments; (b) friends and relatives, who provide cash loans without explicit pecuniary compensation; and (c) traders, merchants, and processors, who engage in commercial credit or sales with a down payment as defined above. The market shares of the credit products and of the lenders which granted them were estimated in terms of the total number of transactions and the total amount disbursed to rural households and enterprises. Individual transactions provided information on financial sector coverage and access. The consolidated amount of credit determined the weighted characteristics of the supply of credit available and the allocation among different agents. Table 6 summarizes the market shares. Financial markets in rural areas seem basically segmented. Friends, relatives, and the semi-formal sector serve households, while the formal sector and commercial suppliers give credit to rural enterprises. Cash loan transactions are the most important credit product. For households, these loans accounted for 88 percent of the number of credit transactions and for 85 percent of the total amount of credit disbursed during the period covered by the surveys. For enterprises, cash loans accounted for 48 percent the of number of transactions and for 50 percent of the amount disbursed. Romanian rural households rely significantly less than their counterparts in other developing countries on the informal sector. Commercial credit transactions and forward sales are a comparatively small source of credit, accounting for 13 percent and two percent of the volume of credit disbursed, respectively, during the period covered by the surveys. This scarcity of commercial credit and forward sales is consistent with the low levels of market activity and the lack of linkages with traders enjoyed by households.

30

There are some rural NGOs in Romania which provide credit. Nonetheless, their scale of operations is very small. Their operations were not reported with sufficient frequency to make any inference about their market shares.


25

Commercial credit plays a more important role among rural enterprises. It accounted for 41 percent of the amount disbursed and 40 percent of the number of credit transactions during the period covered by the surveys. The banking sector had a three percent share of the number of transactions and a 16 percent share of the amount of transactions involving households. The banking sector’ share of the enterprise market niche is significantly larger. Banks participated in 31 percent of the number of transactions and allocated 50 percent of the amounts of credit received by enterprises. State banks dominate the enterprise segment. These banks allocated five times more credit to rural enterprises than private banks during the period covered by the surveys. F. DISTRIBUTION OF THE FLOW OF CREDIT AMONG BORROWERS AND LENDER PREFERENCES The data in Table 7 indicate the sectors and enterprises which obtained the flows of rural credit allocated during the period covered by the surveys. The agricultural sector received 61 percent of the total amount, while the service sector received only 3 percent. Industry and trade received 19 and 16 percent, respectively, of the total credit allocated. This allocation of credit tracked very closely the shares of these sectors in the aggregate book value of assets owned by rural enterprises. Somewhat surprisingly, private banks did not discriminate against agriculture. Indeed, they granted to agriculture 65 percent of the total amount of rural credit they disbursed. This share is actually slightly higher than the share of credit that public banks allocated to agriculture (62 percent of their disbursements). Agriculture is also the sector which receives the largest share of subsidized credit. It obtained 90 percent of all preferential lending during the period covered by the surveys. State enterprises active in the agricultural sector captured about 55 percent of subsidized loans. Table 7 Distribution of Loan Amount Disbursed to Rural Enterprises by Type of Lender Total

Banks

Semi-Formal

State Private Credit % of Loan Amount Disbursed Banks Banks Cooperatives Total 100.0 100.0 100.0 100.0 Economic Sector Agriculture 61.0 62.4 65.4 Industry & Construction 19.2 19.8 19.7 Trade 16.5 15.5 9.3 100.0 Services 3.2 2.3 5.6 Type of Ownership Public 43.1 46.3 38.6 Private 56.9 53.8 61.4 100.0 Net Income (Loss) Negative 30.2 31.3 29.2 Positive 69.8 68.7 70.8 100.0 Made Investments No 40.7 44.4 19.5 17.4 Yes 59.3 55.6 80.5 82.6 Source: Survey of Rural Enterprises and Financial Services, 1998.

Informal

Subsidized Loans No Yes

Moneylenders 100.0

Other Sources 100.0

100.0

100.0

100.0 -

18.1 7.3 61.9 12.7

52.3 23.0 20.5 4.2

89.7 6.7 3.6 -

100.0

0.3 99.7

39.5 60.5

55.3 44.7

100.0 -

7.9 92.1

29.6 70.4

32.4 67.6

100.0

52.0 48.0

40.3 59.7

41.9 58.1

26

Chapter Two:

Lenders in rural areas allocated significant portions of credit to enterprises (as opposed to households) which experienced negative net incomes (losses) and which had negative gross cash flows. About a third of all credit went to enterprises with negative profits and about 40 percent to enterprises with negative cash flows. State and private banks behaved similarly in terms of granting credit to money-losing enterprises. Close to 30 percent of their loans (by amount) went to borrowers who reported losses in the same accounting cycle in which they received the loan. About half of the borrowers (by number of individual credits) which received loans from private banks did report losses. The equivalent percentage for state banks was 29 percent. Table 1 in Chapter I shows that the state-owned sub-sector caused the negative balance on the aggregate net cash flow of rural enterprises. Also, the enterprise survey shows that the banking sector allocated 45 percent of all the new flow of credit to state enterprises with negative cash flows. A likely outcome of lending to state enterprises with negative cash flows is that these loans will have to be assumed by the Government or by the banking system, since the likelihood of these enterprises returning to a positive cash flow under state ownership is minimal and privatizing them will be difficult while they have a large debt overhang. In the aggregate, lenders granted about half of the loans (by number of transactions) and more credit (by amount) to borrowers who made investments in the period in which they received credit. About 60 percent of the aggregate amount of credit went to such borrowers. Private banks allocated to borrowers who reported investments 80 percent of the amount of loans they granted, while state banks allocated 55 percent. G. CHARACTERISTICS OF CREDIT PRODUCTS This section examines the characteristics of the credit products received by rural agents during the period covered by the surveys. Special attention is given to the amount, maturity, use of credit, collateral requirements, speed of disbursements, transactions costs, and repayment problems. Cash Loans Amounts. By source of credit, banks provide the largest loans in rural credit markets. The average bank loan to enterprises (US$17,875) was almost 16 times higher than the average loan disbursed by informal sector (US$1,137) and 26 times larger than the average loan allocated by credit cooperatives and CARs (US$693) during the period covered by the survey. A similar situation occurred with the credit allocated to households. The average bank loan to households (US$797) was eight times larger than the average loan allocated by friends and relatives (US$173) and about seven times larger than the average loan disbursed by credit cooperatives and CARs (US$99). Credit cooperatives allocate significantly larger loans than CARs. For instance, 60 percent of the loans they granted to households during the period covered by the survey exceeded US$500. In contrast, 85 percent of loans made by CARs were below US$500. Finally, moneylenders and friends and relatives allocate very small loans. The evidence is that 66 percent


27

of the loans made by moneylenders and 80 percent of the ones made by friends and relatives during the period covered by the survey were below US$100. Maturity of cash loans. The large majority of loans received by borrowers in rural areas are short term loans of less than 12 months maturity. In fact, 93 percent of the loan transactions entered by households during the period covered by the survey had to be repaid in less than a year. The corresponding percentage for enterprises was 85 percent. Bank loans had the longest average term to repayment at 16 months. This average increased to 20 percent when weighted by term. Clearly, the larger loans granted by banks also tended to have longer terms. Reported use of loan proceeds. Households and enterprises were asked what type of expenditures they financed with the proceeds of the loans they received. Their responses are summarized in Table 8. Most of the enterprise loans were used to finance working capital (87 percent) and most of the household loans were used to finance consumption activities and household durables (53 percent).31 Loans reported to have financed investments accounted for 23 percent of the number of loans and 29 percent of the amount borrowed by enterprises. Households reported that 7.3 percent of loans financed business investments and that such loans accounted for 17.1 percent of the amounts of loans they obtained. Households were more likely to use loans from the formal sector to finance business investments than loans obtained from semi-formal and informal lenders. While only 8.4 percent of the total number of loans were used to finance business-related investments, 40 percent of the loans taken from formal sector were used for this purpose (see Table 8). Table 8 Use of Loans by Type of Lender and Borrower Total Formal % % % % trans amounts trans amounts

Semi-formal Informal % % % % trans amounts trans amounts

Used Loan for: Rural Enterprises Investment 23.4 28.6 27.0 28.6 17.7 46.6 Working Capital 87.0 78.7 81.7 78.7 100.0 100.0 96.3 94.1 Rural Households Business Investment 7.3 17.1 39.5 37.3 9.1 16.4 3.5 6.4 Business Working Capital 11.5 7.8 4.8 8.5 10.8 8.4 12.6 6.7 Household Investment or Consumption 59.3 57.0 59.6 56.0 83.2 81.8 40.4 23.3 Note: Totals in each category exceed 100 percent due to multiple responses. Source: Survey of Rural Households and Financial Services, 1998; Survey of Rural Enterprises and Financial Services, 1998.

Collateral and guarantees. The survey revealed that Romanian rural financial markets rely significantly on real assets as collateral for loans (see Table 9). Naturally, there are a large number of small loans guaranteed only by fiduciary contracts and verbal promises. These unsecured loans represented about a third of the aggregate amount of loans and were made almost entirely by the informal and semi-formal sectors during the period covered by the survey. 31

These results should be interpreted with caution, however, because they do not necessarily reflect the activities actually financed at the margin. Given that money is fungible, it is possible, for instance, that a loan actually invested in the hosuehold’s economic activity may have also allowed consumption to increase because a portion of rural entrepreneurs’ equity − which in the absence of the loan would have been invested in the rural enterprise − could instead have been used to finance consumption. Nonetheless, the results are interesting inasmuch as they seem to reflect general patterns of loan investment.

28

Chapter Two:

The remaining two thirds of the value of rural loans were secured with tangible assets by pledges on movable assets, mortgages on real estate, or both. Indeed, about half of the amount of secured loans was guaranteed by a pledge on movables and a mortgage simultaneously. When tangible assets were used as collateral for loans, the ratio of the market value of the pledged assets to the amount of the loans (collateral/loan) was very high. This ratio had an average of 4 for bank loans. That is, the assets securing repayment of the average bank loan were four times more valuable than the amount borrowed. The ratio for private banks was lower than that of state-owned banks (3.2 times versus 4.2 times). This seemingly excessive protection of loans was due, in part, to the costly and lengthy processes involved in repossessing assets pledged as collateral and to the lack of liquidity of rural real estate (see Chapter III, page 42). One consequence of excessive collateral is that the demand for loans decreases. Large numbers of otherwise creditworthy borrowers may opt out of credit markets. Peculiar collateral requirements together with the shortcomings of the legal framework could make borrowers' cost of defaulting disproportionate to the amount borrowed. Rural areas had no functioning mechanisms with which to auction property given as collateral and to ensure that any amount remaining after lenders have been fully compensated will be returned to the borrower. Hence, those potential borrowers that would be required to pledge collateral may face an artificially skewed risk-return distribution for their investments. Indeed the enterprise survey indicates that 27 percent of rural entrepreneurs and 8 percent of rural enterprises did not request loans because they consider borrowing too risky for this reason. Table 9 Collateral Use by Type of Lender (% of Amount Lent to Households and Enterprises) No Collateral Pledges Mortgages Shares on Lending Volumes by Type of Collateral State banks 0.7 18.2 24.2 Private banks 9.8 18.1 24.8 Semi-formal 49.0 38.9 5.4 Informal 96.2 0.1 Total 32.9 20.1 14.6 Shares of Lending Volumes by Type of Lender State banks 0.9 38.5 70.4 Private banks 3.5 10.7 20.0 Semi-formal 39.2 50.8 9.6 Informal 56.5 0.1 Total 100.0 100.0 100.0 Source: Survey of Financial Intermediaries, 1998.

Pledges and Mortgages

Total

57.0 47.4 6.7 3.7 32.4

100.0 100.0 100.0 100.0 100.0

75.1 17.3 5.4 2.2 100.0

42.6 11.8 26.2 19.3 100.0

The combination of lenders’ strong appetite for collateral, the regime for secured transactions, and the functioning of rural real estate markets pushed a wedge between demand and supply by making borrowing too risky as explained above (weakening the demand for loans) and by reducing the capacity of the rural sector to carry debt (weakening the supply of loans). In practice, the only rural real estate accepted as collateral for loans was non-residential buildings. The number of rural loans secured with residential real estate was negligible. The study’s analysis of the rural housing market revealed factors that explain the extremely limited use of housing as collateral. The price of houses located more than 10 km from an urban center was


29

about 25 percent of the construction costs of an equivalent unit. This may explain the high collateral to disbursement ratios, on one hand, but also the reluctance of owners to risk their house in pursuing entrepreneurial activities.32 The use of farm land to secure loans is also extremely low. The use of land as collateral was impossible during the period covered by the survey because transactions with restituted agricultural land were prohibited until late 1998. More than 90 percent of the country’s land is under this regime. Recently there has been an increase in land transactions, but mostly in land leases. Thin farm land markets combined with the structural features of land ownership (fragmentation, incomplete titling, poor registration) make land mortgages risky collateral. Limited mortgage lending should not be surprising, therefore. Transaction costs of obtaining loans. Borrowers care about the total cost of loans and about the timeliness of disbursement. The total cost of borrowing includes the financial expenses and the costs required to complete the Figure 8 Average Speed of Disbursement of Loans by Lender Type transaction. Timeliness Days 45 is especially important 41 38 40 when: (a) cash needs 35 are urgent and 30 27 30 unexpected; and (b) 24 25 liquidity needs are 19 17 20 seasonal (e.g., planting 15 11 season for farmers, 10 Christmas for 3 5 2 1 merchants). Thus, transaction costs and State Banks Private CAR Credit Moneylender Friends & the timeliness of Banks Coops Relatives disbursement greatly Enterprises Households affect the demand for Source: Survey of Financial Intermediaries, 1998. loans. For instance, 13 percent of households declared that, although they wanted loans during the period covered by the survey, they did not apply for them because of high transaction costs. The speed of loan disbursement is measured as the time elapsed between loan application and actual disbursement. This speed is positively related to the size of the loans (see Figure 8). Lenders which provide the smaller loans disbursed faster. Moneylenders took about one to two days, and friends and relatives took about three days during the period covered by the survey. More formal lenders, such as banks and cooperatives, took between 17 and 41 days.

32

These results are based on actual transactions which occurred in villages. There is a high variance in the price of rural residential real estate that is not explained by the characteristics of the house or its location. While high variance may reflect numerous unknown factors, including distressed sales, it indicates with certainty a high risk of lending against an asset whose value upon repossession is difficult to predict.

30

Chapter Two:

Borrowing from lenders which are slow to disburse also entails higher transaction costs. These costs were proxied by the sum of fees and commissions on the loan plus the costs of visiting the lender (number of trips times their cost). These costs were correlated with the amount borrowed. Repayment problems of cash loans. The survey collected data on the repayment of loans to determine the extent to which borrowers were able to serve their loans. The results are summarized in Figure 9. The percentage of loans (in terms of the aggregate amount and total number) that experienced repayment problems was used as a proxy indicator of delinquency.33 The number of enterprise loans that fell in arrears (15 percent) was almost three times that of households (5.5 percent). The loans that enterprises reported in arrears were very large. These loans accounted for 43 percent of the aggregate amounts received by the sector. In contrast, delinquent household loans were slightly Figure 9 Repayment Problems on Cash Loans below the average size 70 as 5.5 percent of loans 60 with delayed payments 50 represented 4 percent of the total amount. 40 30

The survey results indicate that 10 arrears are a more 0 serious problem for State Banks Private Mtual Help Credit Moneylender Friends & state-owned banks than Banks Coops Coops Relatives for private banks. The Households Enterprises, Not Subsidized Enterprises, Subsidized share in the amount of Source: Survey of Financial Intermediaries, 1998. the loan portfolio disbursed by state banks with repayment arrears was about 60 percent during the period covered by the survey, which was more than twice that of private banks (25 percent). 20

Delinquency on subsidized government credit lines was significant when state banks were the lenders (about 35 percent of the amounts).34 In contrast, when private banks allocated subsidized credit, the delinquency reported by borrowers was about 3 percent.

33

Two caveats apply to this measure. First, the information was collected from the borrowers themselves who, for various reasons, may underreport delinquency. Second, the measure used may overstate arrears problems because the amounts used correspond to the original amount of the loan and not to the outstanding balance at the time of the repayment problem. The resulting information can be used to study systematic differences in repayment across groups of borrowers and lenders, nonetheless.

34

The survey documented three mechanisms by which the Government subsidized rural credit: (a) direct rebates to borrowers on the interest paid; (b) credit at preferential rates below market rates; and (c) rebates on principal paid to borrowers upon canceling on time. The principal amount of these subsidized loans represented 23 percent of the amount received in loans by the entire rural sector during the period covered by the survey. State banks allocated 86


31

Commercial Credit Commercial credit is defined, for purposes of the study, as credit received in kind. Examples include suppliers credit and the inputs advanced to farmers by processing firms or traders. This form of credit represents a significant source of financing for the rural economy. It accounted for 9 percent of all credit transactions and about 20 percent of the flow of credit to rural households and enterprises between June 1997 to May 1998. Commercial credit is particularly important for enterprises. It was a source of financing for about 9 percent of enterprises, accounted for 40 percent of the number of their credit transactions, and represented 23 percent of the total amount they borrowed during the period covered by the survey, including all other forms of credit. Households use commercial credit less often and mostly to purchase durable goods and appliances. Commercial credit was a source of financing for 2 percent of households, accounted for 7 percent of household credit transactions, and represented 13 percent of the total amount borrowed by households. Private enterprises are the main supplier of commercial credit transactions. They granted 77 percent of commercial credit transactions with enterprises as debtors and 60 percent with households. State-owned enterprises were the creditors in about a fifth of transactions with enterprises and in 23 percent of transactions involving households. The debtor was a private company in 96 percent of all commercial credit transactions involving enterprises. Nonetheless, the 4 percent of transactions which involved state companies accounted for 34 percent of the aggregate amount of credit disbursed under this modality. Enterprises fully owned by the state and mixed enterprises accounted for two percent of enterprises, had 50 percent of all assets, and generated 18 percent of aggregate revenues in the sector. The incidence of commercial credit among households is highest among those which have non-agricultural entrepreneurs and commercially oriented farmers. These households accounted for 83 and 14 percent of transactions, respectively, during the period covered by the survey. Commercial credit finances almost exclusively working capital for enterprises and consumption for households. Enterprises used virtually all commercial credit for working capital, while for households 96 percent of the aggregate value was made of durable goods, special celebrations, and housing improvements. Commercial credit transactions tend to be smaller and have shorter terms to repayment than bank credit. For enterprises, the average commercial credit transaction (US$5,100) was for less than a third of the average bank loan amount during the period covered by the survey. The average term to repayment of commercial credit (4 months) was a fourth of the average maturity

percent of all subsidized loans. Private banks allocated the remaining 14 percent. Chapter II presents details on subsidized credit.

32

Chapter Two:

of bank loans. The average commercial credit transaction in which a household was the borrower was for US$300 and had a term of seven months. Commercial credit is granted mostly on the basis of trust, rather than on the basis of legal contracts or collateral. Households obtained 86 percent of their commercial credit transactions without pledging collateral (not even the goods acquired on credit) during the period covered by the survey. About half of the 48 percent of the transactions were based solely on the verbal promise of the debtor. Naturally, larger transactions used authenticated notarized contracts (15 percent of the aggregate amount) and real assets as collateral. Interestingly, a combination of mortgages and pledges on movables secured 45 percent of the aggregate amount of commercial credit. Co-signers assumed fiduciary responsibility for 35 percent of commercial credit transactions (45 percent of the aggregate amounts). Commercial credit in which enterprises are the debtors is not secured with real assets either, and was rather informal as well. More than 90 percent of these transactions did not involve pledging assets, and about half of them were based solely on the verbal promise of the debtor during the period covered by the survey. However, there were significant differences by enterprise ownership type. State-owned enterprises were able to obtain credit without pledging guarantees or notarizing contracts in all transactions. Private enterprises, in contrast, had to provide stronger assurances. Two thirds of the aggregate amount they received were secured with collateral, cosigners, and notarized contracts. H. PARTICIPATION OF RURAL ENTERPRISES AND HOUSEHOLDS IN FINANCIAL MARKETS AS DEPOSITORS AND SAVERS Rural enterprises make intense use of the formal financial sector to make and collect payments. Virtually all rural enterprises (99.9 percent) had sight deposits and/or checking accounts during the period covered by the survey. Most of these accounts had been opened in state banks (80 percent). The remaining 20 percent Figure 10 Percentage of Households with Savings Accounts by Per Capita Income Quartile of accounts were in private banks. Few rural enterprises 50 had made investments in 45 40 financial instruments. Less 35 than one percent of them 30 25 had certificates of deposit 20 or similar financial 15 instruments. 10 5 -

About 36 percent of rural households had financial savings. The Source: Survey of Rural Households and Financial Services, 1998. highest incidence of households that saved was among the well-off, farming households with more than two hectares of land, households practicing commercially-oriented agriculture, and households of which the head had higher levels of education. Regionally, the highest incidence of households with Lowest income quartile

2nd income quartile

3rd income quartile

Highest income quartile


33

savings was found in Subcarpa_ii de Sud (51 percent). The lowest incidence was in the area surrounding the capital city Bucharest (14 percent). Not surprisingly, income is a powerful predictor of the participation in the rural savings. While only 11 percent of the households belonging to the poorest income quartile saved during the period covered by the survey, the participation rate approached one half for households in the two richest quartiles. Table 10 Shares of Savings Accounts of Rural Households by Type of Instrument Sight Term Deposits Deposits 44.0 93.4 42.4 88.6 30.0 48.5 4.9 22.7 5.2 10.4 1.6 4.9 7.8 4.6 47.9 1.8

Commercial Banks State Banks CEC Banca Agrícola Banca Comerciala Romana Private Banks Credit Cooperatives Casa de Ajutor Reciprocs (Mutual Help Cooperatives) Others 0.3 Total 100.0 Row Percent 31.5 Source: Survey of Financial Intermediaries, 1998.

0.1 100.0 68.5

There is not much diversity in the instruments used by rural households to save or make payments. Savings accounts are the most common deposit instrument held by rural entrepreneurs. They represented 69 percent of the number of accounts and held 64 of the amounts deposited during the period covered by the survey. Current accounts and sight deposits held the remaining amounts. Three state-owned banks – Savings Bank, Banca Agricola, and Banca Comercial_ Român_ – kept more than 80 percent of the savings of rural inhabitants during the period covered by the survey. One reason for this dominance is that these three banks have a vast network of retail outlets (see section III.E, page 25). Table 10 presents the estimated market shares by type of instrument and intermediary. The three large state banks accounted for about 42 percent of sight deposit accounts. The rest of the accounts were kept primarily in Casa de Ajutor Reciprocs (Mutual Help Cooperatives), which had 48 percent of total number of rural sight deposits, and credit cooperatives which had 8 percent. Second, the average size of deposits is small relative to the average annual income in rural areas. Table 11 presents the average size and term to maturity of the deposits that were held by different intermediaries during the period covered by the survey. There was no variation in the nominal interest rate offered by banks to depositors, controlling for type of deposit and time.

34

Chapter Two:

Table 11 Average Amount and Maturity of Deposit Instruments of Rural Households Sight Deposits Amount (US$) 524 489 50

Term Deposits Amount Maturity (US$) (Months) 451 10 1,186 7 14 12

State Banks Private Banks Mutual Help Cooperatives Credit Cooperatives 112 Source: Survey of Financial Intermediaries, 1998.

575

6

Proximity to the intermediary was cited by half of the survey respondents as an important reason in the selection of intermediaries in which to open accounts. Only 22 percent of respondents, with the exception of private banks’ clients, mentioned higher interest rates as a main reason for choosing a financial institution. For the clients of the private banks, high interest rates seems to be the most important reason in choosing the depository institution, as acknowledged by 76 percent of them. The clients with the largest amounts of savings choose their deposit-taking institution primarily on the basis of trust. About 73 percent of the total amount invested belonged to households which considered the degree of trust as the most important reason to have opened an account in a given intermediary.

Chapter III: Limited Access to Loans: Weak Supply of and Weak Demand for Loans This chapter provides empirical support to the prevalent perception that there are too few credit transactions in rural Romania. Policy makers are justifiably concerned with this situation because credit constraints  unsatisfied demand for credit at current market conditions  could have a very negative impact on agricultural growth and rural poverty. Credit constraints affect not only the output and efficiency of rural households, but also their capacity to adjust to the major policy reforms of recent years and the aftermath of the exchange rate crisis of early 1997.35 Rural households may require adjusting their scale of operations, investing in new technologies, or initiating new activities. Their investment behavior  and therefore their growth potential  can be diminished by credit constraints. This has serious consequences for rural development, since rural households operate entirely out of retained earnings, saved assets, remittances, other businesses’ income, and sales of animals. Moreover, access to credit services affects rural households’ investment and risk management decisions, and thus differential access to these services could widen income disparities over time by having a long-term effect on asset accumulation and poverty (Chaves and Sánchez, 1998; Jalan an Ravallion, 1999). Finally, Romanian rural entrepreneurs are at a disadvantage when competing with counterparts in countries such as the members of the European Union or the United States, where more than 95 percent of rural entrepreneurs have access to credit from the formal sector. This chapter provides evidence that rural households and enterprises have limited use of loans, raising two questions. The first question is whether the supply of loans has been limited, resulting in households and enterprises experiencing an unsatisfied demand for loans. The second question is whether the scarcity of loans is linked to weak demand arising from, for example, the lack of profitable investment opportunities. It is found that the observed scarcity of credit transactions in rural areas has been caused by numerous factors which have weakened both the supply of and demand for rural credit. Lenders avoid rural credit and few rural agents demand credit anyway. Worse, the supply and demand do not match in that those agents which demand credit do not correspond to those to which lenders want to lend.36 A. PARTICIPATION OF ECONOMIC AGENTS IN THE MARKET FOR LOANS The overall access to loans by rural households and enterprises was limited. Table 12 shows that the percentage of these agents that used loans to finance consumption, operations, or investments was only 20 percent. Predictably, the incidence of borrowing was not uniform and

35

Main reforms include restitution of all cooperative land under the land reform of 1991, removal of price controls and subsidies on staple products, privatization of state-owned enterprises, and tax policies.

36

It is most likely that all other sectors of the economy have suffered from limited access to credit because the majority of these problems are common to all financial transactions in Romania, regardless of economic sector.

36

Chapter Three:

varies across agro-regions and economic sectors.37 For instance, 26 percent of households in the region of Subcarpatii de Sud had access to credit, which was better than the access enjoyed by their counterparts in Oltenia de Sud, where only seven percent received loans in the period. Further, households whose income originated mostly from wages and pensions had the highest incidence of borrowing (29 percent), followed by self-sufficient farm households (21 percent), and non-farm households (20 percent). The participation of rural enterprises in credit markets was 32 percent in Campia Dunarii de Jos, while in Campia de Vest it was only 18 percent. Agricultural enterprises ranked first in their use of loans (49 percent), while industrial and trade enterprises ranked second and third with rates of participation of 26 percent and 17 percent, respectively. Public enterprises had a much higher rate of participation in credit markets (54 percent) than their private counterparts (20 percent). B. WEAK SUPPLY OF CREDIT The household and enterprise surveys show that the financial sector, especially the banking industry, supplied very limited amounts of loan capital to the productive sectors of the rural economy (households and enterprises).

Table 12 Participation in the Market for Cash Loans

Rather than from lack of liquidity, this weak supply resulted Borrowers from: from an unfortunate combination of Formal lenders short-term circumstances and State banks structural factors, namely: (a) Private banks Government macroeconomic Semi-formal lenders policies; (b) Government policies Credit Cooperatives and participation in rural financial CARs markets and the rural economy; (c) Informal Lenders the institutional and legal Moneylender framework for financial Friends & Relatives transactions; (d) the existing debt Other Non-borrowers 79.8 79.7 overhang that limits the rural Source: Surveys of Rural Households and Enterprises, 1998. sector’s capacity to carry additional liabilities; (e) the lack of capacity or interest of the country’s banking industry to serve retail clients; and (f) missing input and output markets. These factors combined to make the risk-adjusted returns to rural lending unattractive relative to alternative investments in other sectors of the economy. Households (%) 20.2 1.1 0.5 0.6 10.1 2.9 7.8 9.9 0.1 9.8

37

Enterprises (%) 20.3 14.4 10.9 4.1 0.4 0.4 6.1 0.2 5.8

The country can be divided into nine agro-regions: Transilvania, Campia de Vest, Moldova de Podis, Moldova Deal, Subcarpatii de Sud, Campia Dunarii de Jos, Oltenia de Sud, Campia Romana Centrala, and SAI (where Bucharest is located). An agro-region is composed of various judets with a similar land use pattern. The groupings were determined using multivariate cluster analysis by identifying those regions with minimal variance in land use patterns for all of Romania’s 41 judets.

Limited Access to Loans: Weak Supply of and Weak Demand for Loans

37

Government Macroeconomic Policies

9

9

ec

-9

-9

ct

O

D

99

g-

99

Au

9

r-9

99

-9

n-

Ju

Ap

Fe

b-

8

8

-9

ct

ec

D

g-

98

O

98

Au

8

r-9

98

n-

Ju

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D

ec

-9

7

%

The financing of both unprofitable productive activities in state-owned industries and social expenditures has led the Government to compete with the productive sector in attracting funding. In fact, the Figure 11 Commercial Lending Interest Rate vs. T-Bill Rate vs. Government has Inflation crowded out the enterprise sector from 140 bank lending 120 portfolios. For 100 significant periods 80 over the last few years, it has been 60 more profitable and 40 less risky for banks to 20 invest their liquidity in 0 inter-bank lending and government securities than in credit to enterprises or Lending (to non-banks) T-Bills Inflation individuals (see Source: National Bank of Romania. Figure 11). Treasury bill yields have been consistently above the rates on commercial loans. In January 1998, the yield on treasury bills was about 4,400 basis points above the rate at which banks reported lending to their prime borrowers. The Government’s open market policies made investment in short-term and low-risk government securities and NBR deposits significantly more attractive than longer term and riskier loans to the real sector. Naturally, the banking system reacted by increasing their portfolio of government securities during 1997 and 1998 (World Bank, 1999). In 1997, outstanding government securities increased by 262 percent in nominal terms and by 44 percent in real terms. In 1998, outstanding government securities rose again by 101 percent in nominal terms and 43 percent in real terms.38 Government Participation in Rural Financial Markets The Government has competed successfully with the private sector in lending to rural borrowers. Massive government interventions in the sector hindered the private supply of rural credit. Private lenders were not in a position to compete with a poorly run government bank (Banca Agricola), which was not subject to a budget constraint, and with numerous directed 38

The fact that banks prefer to lend to the Government rather than raising the rates charged to the private sector is common in high-inflation environments. In Brazil, for example, the Government consistently paid interest rates that were substantially above those paid by the private sector. Lenders feared that charging private enterprises these same rates would result in adverse selection and skew their loan portfolios towards unacceptably risky borrowers. As a result there was little or no lending to companies during the high inflation period.

38

Chapter Three:

credit lines that financed rural loans at subsidized rates with a high probability of debt forgiveness. Naturally, these interventions crowded out private lenders from rural credit markets. Lenders with no access to subsidized funding to enable them charge borrowers rates below market and to permit arrears were at a competitive disadvantage. Debt forgiveness programs (implicit or explicit) have promoted strategic defaults and created obvious credibility problems for all rural entrepreneurs as viable borrowers. Rural lending has become (or at least is widely perceived as) an unattractive market niche for the banking sector to invest their resources − especially for emerging private banks. For example, a Government Ordinance issued in the spring of 1996 required banks (mainly Banca Agricola) to provide loans to delinquent borrowers and to borrowers without appropriate collateral. Strategic default became widespread. In 1997, the Government cleaned up Banca Agricola’s loan portfolio by converting delinquent loans into public debt. The amount involved in this de facto debt forgiveness program was equivalent to about half of the outstanding loans in Banca Agricola’s portfolio. Subsidized credit was a significant share of the total supply of rural credit. It accounted for about a quarter of the aggregate amount of credit received by the rural economy in the surveyed period. In 1997, the Government attempted to phase out directed credit programs and to make all subsidies transparent by putting all credit ordinances in the national budget. Budgeted credit programs to finance agriculture and agricultural machinery persist, but their costs remain in question. Even when these programs are successfully implemented, their benefits concern macro-economic aspects and transparency in the allocation of quasi-fiscal transfers. Although the objectives of these programs are well-intended, the programs still have negative effects on the development and efficiency of financial markets in rural areas. The Government’s main rural credit instrument, the Ordinance on Providing Finance for Crop Planting, Maintenance and Harvesting as well as for Livestock Raising and Feeding, created a permanent revolving fund (the Fund) which will be part of the regular administrative structure of the Ministry of Agriculture, Food and Forestry (MOAFF) rather than a transitory mechanism. The budgetary costs and real amount of subsidies in the ordinance are not transparent. The ordinance does not specify: (a) the interest rates payable by final borrowers and intermediary banks; (b) the amount of credit being made available; and (c) estimated disbursement schedules. These three variables together with inflation and treasury bill rates will determine the actual budgetary cost of the credit scheme. The Ordinance continues to distort rural financial markets by establishing a bonus for borrowers who repay their loans punctually. This rebate is 25 percent of principal regardless of the maturity and nominal interest rate on the loan. The ordinance also includes a “bonus on advanced payment” of 5 percent of principal for borrowers who repay their loans at least 20 days prior to maturity of their loans. The effects of these provisions are illustrated in Table 13. They include: (a) distortion of investment decisions by the establishment of different effective interest rates and, thus, different relative profitability for different crops; (b) the possibility of profitable opportunistic behavior on the part of borrowers − among others, there will be strong incentives to arbitrage across the


39

effective interest rates charged for different activities or to divert subsidized loans to financial investments;39 (c) the impossibility of determining, ex-ante, the true budgetary costs to government because these costs will depend on the turnover of the credit fund (i.e., “lending rounds”) − an allocation with a larger share of short-term livestock loans will be more expensive to the Government than another allocation with a larger share of long term wheat loans. Table 13 Structure of Effective Nominal Interest Rates on Loans for Different Agricultural Activities according to the 1998 Ordinance on Providing Finance for Crop Planting, Maintenance, and Harvesting, and for Livestock Raising and Feeding Annualized Effective Rate After Bonus on Term to Total Annualized Effective Principal and Early Repayment for a Interest Interest Paid Minus Rate After Bonus on Payment Discount Given Activity Paid Bonus on Principle Principal (percent) (days) (Lei) (Lei) (percent) Case A: Contractual rate 80 percent p.a. on a Lei 100 loan 360 80.00 55.00 55.00 48.22 340 75.55 50.55 53.33 46.24 305 67.77 42.77 50.48 44.58 245 54.44 29.44 43.25 31.98 210 46.66 21.66 37.13 23.15 Case B: Contractual rate 40 percent p.a. on a Lei 100 loan 360 40.00 15.00 15.00 8.22 340 37.77 12.77 13.52 6.24 305 33.88 8.88 10.48 4.57 245 27.22 2.22 3.62 - 8.01 210 23.33 - 1.27 - 2.86 - 16.04 The following is the formula used to calculate the above annual effective rates (AER). AER=(Annual contractual rate)-[(360/Days to repayment)*(Bonuses as percentage of principal)] The following are the maturities of loans intended to finance different products: a. 360 days for winter wheat, rye, barley, and two-row barley crops b. 340 days for vineyards, orchards, and vegetables c. 305 days for sugar beats d. 245 days for summer two-row barley e. 210 days for livestock

Source: Author’s calculations

An additional concern raised by the ordinance has to do with the incentives to commercial banks to disburse credit to agriculture in the form of a 4 percent disbursement fee and a 6 percent bonus on principal amounts recovered. This structure of incentives for banks has two negative effects: (a) it contributes to the difficulty of estimating the budgetary cost − for the same reason above; and (b) it provides banks with behavioral incentives similar to those of borrowers. This last point deserves further analysis. The opportunities for borrowers to profit by obtaining, and for banks by granting, a series of short term loans under the ordinance are very significant. Should borrowers obtain credit simply to, say, invest the proceeds in financial markets, then each lending round would bring the following net profits free of risk: (a) for the borrower, (30 percent bonus on principal) + (interest earned on back-to-back deposit in lending bank) - (interest paid on loan); and (b) for intermediary banks, (10 percent bonus on principal) + (intermediation margin). 39

Clearly, it is better to obtain two consecutive “livestock loans” to finance winter wheat than to get a winter wheat loan.

40

Chapter Three:

The upper bound or theoretical limit to these risk-free profits is the sum of the bonuses collected by banks and borrowers on a sequence of, say, one day loans. Bonuses such as those proposed in the ordinance allow strong incentives for collusive opportunistic behavior, therefore. In fact, the potential profits are large enough to expect that any amount allocated under the ordinance will be disbursed and repaid. Repayment is almost assured by the expectation of future access to similar loans. Repayment is more profitable than default. The survey results are consistent with this possibility. The share of rural loans contaminated with delinquency in the overall rural portfolio of private banks was about 25 percent and only 3 percent for the sub-set of the rural portfolio financed by governmentsubsidized credit lines. Although with less dramatic magnitudes, equivalent differences were observed in state banks where 60 percent of the overall rural portfolio was contaminated while only 35 percent of the subsidized portfolio suffered contamination. Inadequate Legal Framework for Financial Transactions: Collateral Issues This section summarizes the main findings of Annex 3, “Romania: How Problems in the Framework for Secured Transactions Limit Access to Credit”, which presents a detailed analysis of the legal framework for transaction secured with movable assets in Romania. There are significant structural impediments to financial transactions that have minimized the supply of credit, especially to the agricultural sector, small businesses, and individuals. The following features of the country’s legal and institutional framework have made credit transactions in Romania riskier and more costly than necessary, diminishing, therefore, the inclination of lenders to lend to all applicants, especially small and medium businesses. The flow of credit to the rural economy during the period covered by the surveys was insufficient in part because the majority of assets in the sector could not be effectively pledged as collateral for loans. Lenders care significantly about recovering their debts, and collateral is the most widely used instrument to insure repayment. In fact, two thirds of the value of rural loans were secured with tangible assets by pledges on movables, mortgages on real estate, or both. Indeed, about half of the amount of these secured loans was guaranteed by a pledge on movables and a mortgage simultaneously. When tangible assets were used as collateral for loans, the ratio of the market value of the pledged assets to the amount of the loans (collateral/loan) was very high. This ratio had an average of 4 for bank loans. That is, for an average bank loan the assets securing repayment were four times more valuable than the amount borrowed. Hence, the real estate and movable assets which represented 90 percent of the aggregate book value of assets in the hands of the enterprise sector in rural areas could be used effectively to secure credit transactions worth at most 22 percent of the sector’s assets. In countries with well-functioning collateral systems, assets carry about four times more debt than in Romania. For instance, in the United States loans guaranteed by mortgages normally finance up to 90 percent of the value of the real state pledged while loans secured with movables normally finance up to 95 percent of the goods pledged. The combination of lenders’ strong appetite for collateral, the regime for secured transactions, and the functioning of rural real estate markets pushed a wedge between demand


41

for, and supply of, loans by making borrowing too risky as explained above (weakening the demand for loans) and by reducing the capacity of the rural sector to carry debt (weakening the supply of loans). In practice, the only rural real estate accepted as collateral for loans was nonresidential buildings. Land. Land and buildings accounted for 42 percent of the aggregate book value of the assets owned by rural enterprises and were by far the single most important component of the wealth endowments of rural households (57 percent) during the period covered by the surveys. Nonetheless, agricultural land was not acceptable as collateral because transactions involving restituted agricultural land remained prohibited until late 1998. More than 90 percent of the country’s land is under this regime. Land markets have remained thin, in part due to lack of viable long term financing.40 Thin markets combined with the negative structural characteristics of land ownership such as fragmentation, incomplete titling, and poor registration make land too risky as collateral.41 The survey finds that basically only urban non-residential real estate was accepted by lenders as collateral should not be surprising under these circumstances. There are many reasons for this finding including the uncertain state of property rights in many parts of the country, difficult verification of previous liens and encumbrances, difficulties of repossession, the high transactions costs associated with valuing and recording fragmented property holdings, and the low value of agricultural land in rural areas that are remote from larger towns and cities. In the case of default, there is a procedure for banks to seize property. After three months of nonpayment the financial institution can commence court proceedings. While in principle these procedures should be complete within a few months and the property repossessed and sold, in practice there are many opportunities for the defaulter to delay the process so that it can easily take several years. Additionally, effective use of land as collateral requires land markets to work. For land markets to work, titling and registration institutions should allow for secure holdings and the inexpensive transfer of ownership. In Romania these criteria are not being met. Problems exist in several areas, but are centered around two particular issues. First, the institutions that are involved in titling are inadequate, and second, the process is costly by international standards. Romania’s property institutions do not work effectively. The Land Book offices (land registries) attached to the courts are poorly equipped, understaffed, and have inadequately paid personnel. More specifically: (a) the documents are stored under inadequate conditions that result in their deterioration so that the older records are degenerating badly; (b) personnel in the Land Book offices are either badly trained, unmotivated, or both, and all entries are made by 40

In a sense, there is a simultaneity issue here. The lack of financing leads to thin markets and thin markets, in turn, reduce the amount of financing available.

41

Under Law 18 of 1991, restitution takes place through restitution commissions which operate at the local government level and which include the mayor as president, local residents, and a representative from the local cadastre and the agricultural cadastre offices. The restitution process is largely complete, but many disputes remain to be resolved. These are now being adjudicated by the courts, which adds further to the congestion of the legal system and to the delays in titling and registration.

42

Chapter Three:

hand and are illegible, leading to errors; (c) there are insufficient personnel to handle the volume of transactions that are occurring as long backlogs have developed so that delays of 12 months or more to complete registration are common; (d) disputes resulting from documentation not being checked thoroughly are accumulating, adding to the delays; (e) the system is time consuming in that users have to complete many steps, adding to the cost of the process; and (f) the various steps in the process raise costs substantially above those required to ensure widespread titling and registration and are well above those in countries where the process has been well designed and is efficient. The actual object of registration is referred to as an “immobile” or parcel, which is a piece of land either with or without a building on it. Land is classified as either Intravilan or Extravilan. The latter classification means that no permanent buildings may be erected on this type of land. Intravilan land may be either for agricultural use or may be built on. All land, both Intravilan and Extravilan is classified by the Ministry of Agriculture, Food and Forestry. If land owners wish to change the use, they must apply to the Ministry of Agriculture, Food and Forestry for permission to do so. Law 51 of 1991 provides that a fee of up to 8 times the price of land must be paid for this conversion. The Ministry of Agriculture, Food and Forestry has the power to change the classification, which often leads to a lowering of the multiple that must be paid for conversion to about three times the sales price. Apart from applications for conversion for construction purposes, enforcement of the classification system appears to be lacking. However, uncertainty about future enforcement is ever-present. Movable assets. Equipment, machinery, inventories, livestock, and accounts receivable represented about 48 percent of the aggregate book value of assets of rural enterprises during the period covered by the survey. These movables assets had very limited capacity to carry debt because of imperfections in the country’s legal regime, which severely limited the creation, perfection, and enforcement of security interests in moveable property, as follows. 42 The framework failed to contemplate most important economic transactions by limiting the creation of security interests on inventory, accounts receivable, leases, fixtures, and chattel paper. Therefore, most formal lenders demanded additional security for loans in the form of a mortgage or fiduciary contract. The framework did not provide a unified and easily accessible system for publicly registering and ranking the priority of a lender to collect against the property by debtors (perfection of security interests). Lenders, consequently, ignored whether other lenders and creditors might have had prior claims against goods offered as collateral. The enforcement of security interests – the repossession and sale of goods in which a lender has a security interest – takes years in Romania, exceeding the economic life of an 42

The Government of Romania passed Law No. 99 of 26 May 1999, published in Monitorul Oficial 236 of 27 May 1999 "Law Regarding Some Steps to Speed Up Economic Reform, TITLE VI. The Legal Status of the Security Interests in Personal Property." Shortly thereafter, the Government issued the regulations for this Law. Preparation of the law and regulations was supported by the World Bank, which is also supporting the creation of an electronic filing archive for security interests. This archive will stand among the most modern in the world. The archive is presently under development and should begin operating before the end of 2000. It is expected that this new framework will correct the deficiencies mentioned above.


43

important portion of movable property. The result is that moveable property as collateral is not valued and borrowers offering movable property as collateral get no better terms than do those who offer nothing. In short, the Romanian framework did not meet certain minimum conditions that render a system for security interests economically useful. These conditions are: (a) the law must provide for creating an enforceable security interest against all property and this must be inexpensive; (b) enforcing the security interest must be inexpensive; (c) the security interest must produce real commercial value for the lender when enforced; (d) the lender must be able to determine before the loan is made, with certainty and at little cost, whether any other lender has a superior claim to the collateral; and (e) the secured lender must be protected from claims of third parties, including secured and unsecured creditors, a trustee in bankruptcy, or some purchasers of the collateral. Warehouse receipts. The rural sector did not have access to warehouse receipts (also called warrants) to finance inventories of commodities during the period covered by the survey. These are legal documents stating the ownership of a specific amount of a commodity or good with specific characteristics stored in a specific warehouse. These receipts play a key role in agricultural financing and marketing in countries where they are backed by a legal and institutional framework that allows their value to be used as collateral. In most developed countries, warehouse receipts can be pledged as collateral for loans, traded, sold, swapped, or used for delivery against a derivative instrument, such as a futures contract. The overall efficiency of financial and agricultural markets is greatly enhanced by the ability to convert agricultural commodities into tradable securities. Warehouse receipts do not work well in Romania because of the following reasons. The legal environment is inappropriate in that the rights, liabilities, and duties in each party to a warehouse receipt (e.g., producer, bank, warehouse) are not clearly defined or enforceable. In practice, receipts are not freely transferable by delivery or endorsement. In addition, potential lenders have no way to determine if there are competing claims on a given stock of commodities. There are no performance guarantees for warehouses. Farmers and traders are reluctant to store crops and banks are not willing to accept receipts as collateral because there is significant uncertainty on whether the goods exist in the quantities specified by the receipt or whether the quality is the same or worse than that noted on the receipt. Lack of performance guarantees is worsened by the lack of independent inspection and licensing of warehouses. The storage industry is not competitive and remains dominated by the state. Breaking Romcereal into Comcereals and Cerealcoms simply divided a large state monopoly into a collusive organization of local monopolies (still controlled by the state) without any positive impact on their operations. Anecdotal evidence suggests that the excessive prices charged by these elevators often makes it unattractive for farmers and traders to store. It is also argued that the elevators often return different amounts and qualities of commodities than originally stored. Even if an appropriate legal framework were passed, enforcement would remain a serious impediment in the presence of an oligopoly of state-controlled storage facilities.

44

Chapter Three:

Leasing. Leasing has been rendered an unprofitable business by uncertainty and inappropriate rules on depreciation, accounting, and taxation of fixed assets.43 Hence, Romania has had an experience with leasing that contrasts with that of other countries in which leasing is widely used to finance individuals and small, and medium sized companies. According to the Romanian Leasing Association, outstanding leasing contracts amounted only to about US$ 270 million during the period covered by the survey. These contracts were highly concentrated in a few large lessees, mostly in the industrial sector. The law does not provide clear definitions for financial and operational forms of leasing and it is unclear about the: (a) differing tax and accounting treatments accorded to each of these two arrangements; (b) how leased goods must be dealt in the balance sheets; and (c) on whom a lessor or lessee can claim credit on depreciation and rental payments under each type of leasing. Also, there is enforcement uncertainty because the law does not assign priority to lessors of leased assets in the case of bankruptcy or reorganization of the lessee, and because recovery of leased assets upon default by the lessee involves complicated, expensive, and time consuming judicial procedures. The Romanian Leasing Association reported that recovery of assets normally took more than six months of litigation, when successful, during the period covered by the survey. The depreciation schedules allowed by law on fixed assets are still too long compared with the normal life of a leasing contract. When such long depreciation schedules are applied to equipment leases of, for example three years, the lessor must report artificially-high net taxable profits because current period costs are not being matched with current period expenditures. This excessive taxation limits the ability of leasing companies to replace leased assets. In practice, the Government is taxing the difference between the historical value of assets and their current replacement cost (in nominal Lei). According to Romanian accounting law, all assets must be booked at their historical value and their revaluation is not allowed. This rule implies that, in the presence of inflation, depreciation expenditures are underestimated causing, again, artificially high taxable profits and low equity ratios for firms. The net effect is equivalent to a tax on investment in capital goods. Romanian law does not permit tax payers to deduct from their taxable income losses incurred when selling assets below their book value. Book value losses are unavoidable for Romanian leasing companies because of the very long depreciation schedules imposed by law and the comparatively short leasing periods, typically 3 to 4 years. In most cases, this combination causes the market value of fixed assets to be below their book value. Losses occur, therefore, when leased assets are sold. This practice gives leasing companies an unduly large tax burden. The payment of customs duties and value added tax (VAT) on equipment leased from a foreign leasing company are deferred until the end of the lease period and are calculated on the 43

The following codes and ordinances constitute the legal framework for leasing in Romania: (a) Commercial Code of 1897 and its reforms of 1923; (b) Code of Civil Procedures of 1897 and its reforms of 1923; (c) Depreciation Law; (d) Tax Code; (e) Accounting Law; and (f) Ordinance 51 of August 1997 as amended in 1998.


45

residual value of the assets. These practices favor cross border leasing and make it difficult to lease Romanian-made assets. In fact, the Romanian leasing association estimates that 99 percent of outstanding leasing contracts in the country are cross-border leasing. The practice also makes leasing a comparatively easy mechanism to avoid custom duties and the VAT on imported assets. Industrial companies would find it profitable to establish wholly-owned leasing companies in foreign countries for the sole purpose of leasing their fixed assets from these companies and reduce, thereby, the amounts paid on custom duties and VAT. The Capacity of the Rural Sector to Carry Additional Debt (Overhang) Rural enterprises, in the aggregate, had financed 52 percent of their assets with debt during the period covered by the survey. The most indebted sub-sector was trade and commerce with a debt to assets ratio of 72 percent. Agriculture was the least indebted with a ratio of 43 percent (see Table 1). The capacity of the rural sector to carry additional debt should be a matter of policy concern. The problem is that illiquid assets, especially land, dominate the sector’s balance sheet. The capacity of assets to carry debt is directly related to their liquidity. The problem seems particularly serious for Romanian agriculture because debt levels are already high in the subsector. The 43 percent debt to assets ratio of Romanian agricultural enterprises contrasted sharply with the equivalent ratios for agriculture in the United States, which have varied from about 12 to 16 percent over the last 30 years.44 Cash flow analysis confirms that the sector would have problems servicing new flows of debt. The value of the sales (products and services) of the entire rural enterprise sector was not sufficient to cover production costs and operational expenses (see section II.E, page 8 ). The gross net cash from operations was negative at the consolidated level and for all sub-sectors with the exception of trade. The net cash from operations was made (barely) positive by significant non operational income, namely financial and exceptional revenues. One implication is that rural enterprises were not able, in the aggregate, to serve their existing debt. In particular, the agricultural and services sub-sectors needed to incur additional debt to serve interest payments and amortize the principal amount of their outstanding debts. The state-owned sub-sector was the culprit of this situation as the negative balance on its net cash flow was large enough to wipe out the net cash surplus generated by the private sector. Interestingly, the banking sector allocated 45 percent of all the new flow of credit to state enterprises with negative cash flows.

44

One caveat applies to this measure. Romanian accounting and taxation laws do not allow revaluation of assets in the presence of inflation. Thus, these ratios may overestimate the debt burden as market values may be above their historic book values. The resulting information may be used to detect systematic differences across sectors. Comparisons across countries should be done with care, but could still be useful because it is unlikely that the market value of farm land has adjusted significantly to inflation because of the poor functioning of land markets.

46

Chapter Three:

Retail Lending Capacity in the Banking Industry The Romanian banking sector has not developed the capacity to profitably provide retail credit. The weak supply of these services is reflected in the fact that the share of loans to households and to small businesses in the portfolios of banks is almost negligible. Development of private financial markets in rural Romania requires the ability of the financial sector to supply retail and micro-finance services profitably. This necessity results form the fact that, by and large, rural clients demand very small transactions. Small and medium enterprises dominate the enterprise sector as the average rural private enterprise had US$11,900 of assets and the large majority (80 percent) had less than 5 employees. On the other hand, households are also small clients. The average monthly household income was US$67 per month and the value of household assets was US$1,564 (see Chapter I for details on enterprises and households). Several factors suggest that the supply of retail and micro-finance services will continue to be weak in the medium term in the absence of Government policy intervention. First, the methods or technologies of financial intermediation (TFI) used by the country’s banks render retail lending unprofitable. These technologies are important in that they represent the methods used by banks to: (a) raise funds and (b) to allocate and recover loans. This methods include: (a) business components such as (i) branches and points of sale, (ii) management information systems, (iii) internal control procedures, and (iv) asset and liability management techniques; and (b) an information component comprising (i) screening of loan applicants, (ii) monitoring of borrowers, and − to certain extent − (iii) enforcing credit contracts. These two types of components determine the fixed cost structure of a bank branch and the average cost of providing financial intermediation services, respectively. The TFIs used by the large majority of Romanian banks are inappropriate to provide retail financial services because: (a) they imply high fixed costs (expensive physical infrastructure, numerous employees) that could not be supported by comparatively small volumes of operations in retail and rural markets; and (b) the TFI’s information component (e.g., screening of loan applicants using feasibility studies or audited financial statements) implies costs of lending that render small loans (the majority of the potential demand) non-economical. The second factor that suggests that the supply of retail services will continue to be weak or actually weaken further is that the network of bank branches may shrink significantly during and after the expected privatization or divestiture of state-owned banks (see Chapter II). It is likely that struggling state banks will downsize by closing branches and that large commercial banks will close a significant number of existing branches after privatization as they adopt strategies focused on the corporate portion of the market. This tendency, which characterizes the behavior of the banking sector in most countries in Central and Eastern Europe, is already occurring in Romania where, for instance, Banca Agricola has recently closed more than a third of its branches. Another reason to expect a reduction in the number of bank branches is that a significant portion of the existing branches are not adequate to provide retail services, especially in rural localities. Many existing branches have fixed costs structures that are not sustainable in rural markets characterized by comparatively small populations which conduct mostly small


47

transactions. Reasonable intermediation margins may not be enough to sustain the high fixed costs of the existing network. Finally, privatized banks may close existing branches as macroeconomic stability would reduce the profitability of “deposits-only” branches. These branches have been used by the Government (in the case of CEC) and by other banks to arbitrage on restricted access, on the part of the population, to Government securities. Banks have enjoyed disproportionately high margins from collecting retail deposits to finance portfolios of such Government securities (see fig. 9). Macroeconomic stability would reduce the rather large yields on Government securities of the last few years, rendering many deposits-only branches unprofitable. There may be a need, therefore, to induce private banks to increase their presence in the retail portion of the market. In the first instance, this presence would be required to provide safe deposit services to large portions of the population which have bank deposits (see Chapter II). These services should be provided mainly by regulated intermediaries. The vacuum that may be left by a retiring state-owned banking sector introduces the risk of unregulated intermediaries increasing their share of the deposits of the population. As indicated in Chapter II, three stateowned banks held 80 percent of the deposits of the rural population. An appropriate distribution network will also be required to lend to small and medium businesses, including those in rural areas and farmers. Small credit transactions are highly elastic with respect to transaction costs, which are reduced in the presence of a point of sale in the locality of residence of borrowers. The presence of a network of retail finance will be required to allow for the massive redeployment of resources expected to occur in the rural economy. International experience attests that retail rural lending could be a profitable market niche for banks, provided they use appropriate methodologies. These methods require banks to: (a) sell few and simple credit products; (b) have low branch fixed costs; (c) use of local information to screen and monitor borrowers; (d) implement conducive incentive schemes for branch managers; and (e) deploy adequate internal control mechanisms.45 The irreversible trend of banks in economies with developed financial markets is to aggressively compete for the retail portion of the market. In Romania, increased availability of retail credit in rural areas may take a long time to develop if left solely to the market. In fact, there is a significant risk that the banking sector will reduce its retail network in rural areas after privatization, as indicated above. Missing Input and Output Markets The weak supply of informal sector credit to rural households may result from missing input and output markets. The overall scarcity of forward sales and inter-linked credit transactions contrasts with the stylized facts that characterize rural credit markets in other regions, notably Asia and Latin America. In countries with well developed input and output markets, traders are important agents in the financing of household productive activities.

45

These elements are common to some very successful rural financial intermediaries whose experiences are well documented in the professional literature (Chaves and Gonzalez, 1996).

48

Chapter Three:

The new land ownership and tenure system does not match the previous centrally planned arrangements for input procurement or output marketing, requiring adjustments across all segments of the chain. Changes in land tenure made established distribution channels in input and product marketing unsuitable for a very small and dispersed clientele. The dominance of the state in agricultural output and input markets prevented the development of innovative financial arrangements in the input and output markets. In 1992, the Government established a parastatal − the regie autonome RomCereal − to manage the country’s entire silo capacity. RomCereal acted as the sole provider of agricultural inputs and the sole buyer of grain and oilseeds in the country. RomCereal operated until 1996, when it was replaced by the National Agency for Agricultural Products (ANPA). Although some planned reforms of the agricultural marketing system should allow competitive informal credit markets to flourish, the process will take a long time. The informal sector may require a long time to fill the vacuum left by retiring state-owned institutions. C. THE DEMAND FOR LOANS: AN ECONOMETRIC MODEL The empirical findings of this study dispute the commonly held belief that the unwillingness of the banking sector to lend to rural agents (i.e., a weak supply) is the (only) cause of insufficient credit flows to rural areas. In the case of Romania, weak demand for loans was a very important determinant of the limited participation of rural agents in credit markets. The survey data show that the incidence of economic agents reporting a demand for loans in rural areas was rather limited, as only 31 percent of households with farm and other entrepreneurial activities and half of all rural enterprises reported having a demand for loans. Naturally, the demand for loans was not uniform, but varied by key characteristics of the agents such as size (measured as assets or revenues), economic sector, ownership, and agroregion. For example: (a) the 50 percent of enterprises reporting that they had a demand for loans controlled 82 percent of total assets and generated 62 percent of total revenues of the rural enterprise sector; and (b) rural enterprises owned by the public sector were more likely to respond that they had a demand for loans (71 percent) than their private counterparts (51 percent). Examples of the variation of demand for loans continue with substantial regional differences as: (a) the proportion of households demanding loans in the case of Oltenia de Sud is 20 percent, while in Subcarpatti de Sud the equivalent percentage is 39 percent; and (b) 78 percent of enterprises in rural Campia Romana Centrala reported loan demand while the equivalent percentage in the case of Campia de Vest was 37 percent. This variation of the reported demand for loans with various observed characteristics of rural agents made it necessary to use econometrics to isolate key variables. A probit model was used to separate the correlation between demand for loans and the characteristics of economic


49

agents.46 The results follow, first for the model applied to the data on households and then to the data on enterprises. Household Demand for Loans A probit model of which the dependent variable is whether or not the household reported a demand for loans was estimated. A total of 28 observed explanatory variables were used. These variables measured different characteristics of sampled households in four dimensions: sociodemographic, entrepreneurial activity, conditions in the locality of residence, and agro-region of residence. The results of the regression and the complete list of explanatory variables are presented in Table 14. The table also presents the results of three specifications of the model, which confirm that its results are robust. The following variables were found to be related, with statistical significance at conventional levels of confidence, to the likelihood of a household reporting a demand for loans. In terms of demographic characteristics the households more likely to have reported a demand for loans, everything else the same: (a) were headed by younger individuals; (b) were more numerous; (c) had more members who were pensioners; and (d) had a larger number of members working outside the agricultural sector. In terms of entrepreneurial and financial characteristics, the households less likely to have reported a demand for loans were those which, everything else the same: (a) had higher amounts of assets excluding land and financial deposits; (b) had more liquid financial assets in the form of bank deposits; (c) had higher levels of income generated by sales of agricultural and nonagricultural products and services; (d) self-consumed less of their own production; (e) had larger endowments of land; and (f) hired less workers. Finally, in terms of the characteristics of their locality of residence, the households more likely to have a demand for loans were those which, everything else the same, lived in localities: (a) that were more highly populated; (b) in which there were many farmers relative to population; and (c) that were located farther from large urban centers.

46

A probit model fits a dichotomous dependent variable that takes the value of zero when there is a lack of demand for loans and the value of one when there is a demand for loans against a vector of observable characteristics or explanatory variable. Annex 2 presents the details of the probit model used.

50

Chapter Three:

Table 14 Demand for Loans by Rural Households (Probit Model) Explanatory Variables Constant Sociodemographic variables Age of household head Marital status (1=married) Gender (1=male) Nationality (1=Romanian) Max education by HH member Family size Adults working in non-agriculture Number of pensionersin HH Characteristics ofEntrepreneurial Activity Log (assets,excluding land and deposits) Log (deposits) Log (monthly agricultural sales) Log (monthly non-agricultural sales) Log (monthly non-agricultural sales) Log (monthly self-consumption) Land holdings (Ha) Number of plots Number employees (ag and non-ag) Economic Conditions in the Locality Log (population) Log (population density per hectare) Owners of agricultural land /inhabitants (%) Log (Kms to nearest town) Agroregion Dummies Campia de Vest Moldova de Podis Moldova Deal Subcarpatii de Sud Campia Dunarii de Jos Oltenia de Sud Campia Romana Centrala

Regression Results Regression Results Coeff. S.D. Mean Xs Partials Coeff. S.D. Partials S.D. t-stat Prob Mean -2.2284 0.7841 *** -0.7578 -2.3210 0.7658 *** -0.7911 0.2604 -3.0380 0.0024 -0.0141 -0.1427 0.0943 -0.0794 -0.0021 0.0922 0.1453 0.1173

0.0024 0.1020 0.1066 0.1089 0.0201 0.0209 0.0468 0.0540

-0.0266 -0.0204 -0.0380 -0.0421 -0.0094 0.0209 -0.0704 0.0122 0.0106

0.0222 0.0085 0.0136 0.0218 0.0240 0.0220 0.0217 0.0117 0.0108

0.2099 -0.0138 0.6941 0.1594

Regression Results Coeff. S.D. -2.0684 0.7521 ***

*** 58.2769 0.6870 0.7538 0.9045 4.0523 *** 2.9319 *** 0.4666 ** 0.3117

-0.0048 -0.0485 0.0321 -0.0270 -0.0007 0.0314 0.0494 0.0399

-0.0140 -0.1525 0.0868 0.0065 0.0004 0.0885 0.1407 0.1218

0.0024 0.1013 0.1059 0.0982 0.0198 0.0207 0.0464 0.0529

*** -0.0048 a -0.0520 0.0296 0.0022 0.0001 *** 0.0302 *** 0.0480 ** 0.0415

0.0008 -5.7950 0.0000 58.2769 0.0345 -1.5070 0.1319 0.6870 0.0361 0.8200 0.4122 0.7538 0.0335 0.0660 0.9475 0.9045 0.0068 0.0200 0.9837 4.0523 0.0071 4.2720 0.0000 2.9319 0.0158 3.0360 0.0024 0.4666 0.0180 2.3040 0.0212 0.3117

-0.0134 -0.1487 0.0864 0.0537 -0.0026 0.1034 0.1219 0.1185

9.6296 2.7066 1.4296 0.2883 6.2475 5.5538 1.8454 3.3383 3.6787

-0.0091 -0.0069 -0.0129 -0.0143 -0.0032 0.0071 -0.0239 0.0042 0.0036

-0.0398 -0.0149 -0.0389 -0.0419 -0.0009 0.0365 -0.0908 0.0144 0.0175

0.0210 0.0084 0.0135 0.0217 0.0236 0.0210 0.0211 0.0112 0.0106

* * *** **

0.0072 0.0029 0.0046 0.0074 0.0081 0.0072 0.0072 0.0038 0.0036

-1.8930 -1.7730 -2.8910 -1.9280 -0.0400 1.7390 -4.3200 1.2800 1.6510

0.0584 0.0763 0.0038 0.0538 0.9682 0.0820 0.0000 0.2007 0.0988

9.6296 2.7066 1.4296 0.2883 6.2475 5.5538 1.8454 3.3383 3.6787

-0.0368 0.0201 *

-0.0126

-0.0991 0.0206 *** 0.0168 0.0111 a 0.0115 0.0100

-0.0339 0.0057 0.0039

0.0792 *** 8.3835 0.0714 0.0579 -0.4953 -0.0047 0.2313 *** 0.4256 0.2360 0.0441 *** 2.7481 0.0542

0.2169 0.0131 0.7999 0.1601

0.0760 *** 0.0529 0.2242 *** 0.0436 ***

0.0259 0.0180 0.0764 0.0148

2.8550 0.2480 3.5700 3.6810

0.0043 0.8040 0.0004 0.0002

8.3835 -0.4953 0.4256 2.7481

** *** **

***

0.0105 0.1155 0.0856 0.1284 0.0835 0.1242 0.3455 0.1037 *** 0.0381 0.1310 -0.0649 0.1291 0.1043 0.1254 SAI -0.3290 0.2314 Number of observations 2,409 Chi-squared 276.4580 df = 29 McFadden's Pseudo-R2 0.0933 Proportion YD=1 0.3047 a/*/**/*** significant at the 85%, 90%, 95%, and 99% confidence intervals,respectively Source : Author's calculations.

-0.0136 -0.0051 -0.0133 -0.0143 -0.0003 * 0.0124 *** -0.0309 0.0049 * 0.0060 0.0739 0.0045 0.2726 0.0546

0.1869 0.0073 0.8005 0.1558

0.0023 0.1004 0.1048 0.0959 0.0193 0.0199 0.0434 0.0521

*** a

Partials -0.7068

*** *** **

0.0754 *** 0.0526 0.2229 *** 0.0432 ***

-0.0046 -0.0508 0.0295 0.0183 -0.0009 0.0353 0.0417 0.0405

0.0639 0.0025 0.2735 0.0532

0.1038 0.0036 0.0872 0.0291 0.1038 0.0284 0.2159 0.1175 0.0706 0.0129 0.0872 -0.0221 0.0872 0.0355 0.0249 -0.1119 2,409 250.9545 21 0.0847 0.3047

2,409 232.8266 16 0.0786 0.3047

Enterprise Demand for Loans A similar exercise was conducted for rural enterprises. Also a total of 28 observed variables were used to explain enterprises’ demand for loans. These explanatory variables measured characteristics of sampled enterprises regarding their managers, economic sector, legal status and governance structure, financial indicators (e.g., assets, profitability, turnover), and the economic conditions in the locality where they are located. The results of the regression and the complete list of explanatory variables used in the model are presented in Table 15. The table also presents the results of three specifications of the model which confirm that its results are robust. The model indicates that the enterprises more likely to have reported a demand for loans: (a) Had a younger manager, which could be explained by several possibilities including that younger managers (i) may be less risk averse on the average, (ii) more able


51

to identify investment opportunities, and (iii) more familiar with the procedures to obtain banks loans than their older counterparts.47 (b) Were in sectors other than agriculture. Everything else the same, the probability that an enterprise in the industry, trade, and service sectors reported a demand for loans was, respectively, 36, 32, and 30 percentage points higher than the probability of an agricultural enterprise reporting a demand for loans. (c) Were bigger in terms of the book value of their assets and were within the group of very large enterprises those in agricultural are more likely to report demand than their (also) big counterparts in other sectors.

47

The model applied to the data on households found that households headed by younger individuals are also more likely to report a demand for loans. The “appetite” for debt of farming households, the large majority of Romanian rural households, seems to be highly influenced everywhere by life cycle patterns. In the United States, for instance, debt to assets ratios are highest in the younger age classes and decline steadily as age increases (Barry). Clearly, a life cycle argument for firms based on the age the enterprise’s manager does not hold.

52

Chapter Three:

Table 15 Demand for Loans by Rural Enterprises (Probit Model) Regression Results Explanatory Variables Coeff. Dependent Variable: 0=No Demand 1=With Demand for Loans Constant Manager of the Enterprise Log(age) Education Index Economic Sector Industry Dummy Trade Dummy Services Dummy Legal Status and Ownership Agricultural Stock Enterprise (1=yes) Non-Agricultural Stock Enterprise (1=yes) Private Owned Dummy Characteristics of Firm Activity Log ( years in business) Log (total assets in 1996) Log (total assets in 1996)*Agricultural Sector Dummy Fixed assets/total assets in 1996 Bank deposits/total assets in 1996 Log (turnover) Turnover/employees Associate members working in enterprise/employees Economic Conditions in the Locality Log (population) Log (population density per hectare) Agricultural employment ratio Log (Kms to nearest town) Agroregion Dummies Campia de Vest Moldova de Podis Moldova Deal Subcarpatii de Sud Campia Dunarii de Jos Oltenia de Sud Campia Romana Centrala SAI Number of observations Chi-squared df =

S.E.

Regression Results Mean Values

-0.3221 1.5240

Partials -0.1146

Coeff.

S.E.

0.9280 1.0437

Regression Results Partials

3.7915 5.6581

-0.2179 -0.6354 0.2390 *** 0.0074 0.0236 0.0317

1.0066 0.3617 *** 0.8876 0.3241 *** 0.8371 0.3621 **

0.1152 0.3239 0.0730

0.3580 0.3157 0.2977

-0.4363 0.2770 a -0.4745 0.4609 0.0233 0.2801

0.1575 0.0166 0.8860

-0.1552 -0.3998 0.2761 a -0.1687 -0.5139 0.4607 0.0083 0.0383 0.2788

-0.1424 -0.1830 0.0136

-0.0469 0.1365 0.2188 0.0609 ***

1.5849 4.1549

-0.0167 -0.0467 0.1349 0.0778 0.2232 0.0606 ***

-0.0166 0.0795

2.7799 0.3487 0.0766 4.8102 33.1162

0.0661 -0.0119 -0.2431 -0.0089 -0.0002

0.0617 -0.0120 -0.2442 -0.0074 -0.0002

0.3676

0.0692

8.3983 -0.4950 0.4227 3.0749

0.0476 0.0348 0.0869 0.0115

0.1849 0.2862 ** 0.2252 0.1743 0.2132 0.2440 a

0.1280 0.0653 0.0794 0.1895 0.1050 0.0832

-0.0246 0.2002 0.0956 0.0293 -0.0220 0.1393

0.2507 0.1990 -0.7596 0.3214 ** 781 169 28

0.1306 0.0359

0.0892 0.3391 0.1896 * -0.2701 -0.5846 0.2888 ** 781 165 24

0.1859 -0.0335 -0.6834 -0.0249 -0.0005

0.0754 *** 0.2042 0.3041 ** 0.0394 0.0008

0.1947 0.1503 0.1338 0.0977 0.2443 0.0323 -0.0691 0.5630 0.2688 0.0825 -0.0620 0.3917

0.1302 0.1166 0.3204 0.0789

McFadden's Pseudo-R2 0.1666 Proportion YD=1 0.6492 a/*/**/*** significant at the 85%, 90%, 95%, and 99% confidence intervals, respectively

0.1731 -0.0337 -0.6858 -0.0209 -0.0005

0.0744 ** 0.2027 0.3027 ** 0.0392 0.0008

0.1971 0.1487

0.0000 0.7216 0.3870 0.1837 0.0342 0.5110

0.1633 0.6492

0.1797 0.2599 *** 0.2136 * 0.1598 0.1990 0.2217 **

S.E.

0.3304 -0.1271 1.4798

-0.6128 0.2403 *** 0.0208 0.0319

0.9795 0.3596 *** 0.8672 0.3224 *** 0.8252 0.3596 **

Coeff.

-0.2263 -0.6225 0.2392 *** 0.0084 0.0136 0.0315 0.3488 0.3088 0.2938

0.0702

Partials -0.0453 -0.2216 0.0049

0.8923 0.3518 *** 0.7727 0.3125 *** 0.7252 0.3519 **

0.3177 0.2751 0.2582

0.0360 0.1305 0.2024 0.0582 ***

0.0128 0.0721

0.1499 -0.1655 -0.7075 -0.0160 -0.0004

0.0668 ** 0.1924 0.3028 ** 0.0388 0.0008

0.0534 -0.0589 -0.2519 -0.0057 -0.0001

0.2697 0.1434 *

0.0960

0.1223 0.1010 0.2293 0.0349

0.0436 0.0360 0.0817 0.0124

0.1295 0.1160 0.3193 0.0785

0.0000 -0.0677 0.1842 0.2570 0.5591 0.2850 ** 0.1378 0.2555 0.2244 0.0654 0.0699 0.1740 0.0122 -0.0631 0.2122 0.1820 0.3685 0.2419 a 0.1208 0.2222 0.1976 -0.2082 -0.7612 0.3217 ** 781 164 25

-0.0241 0.1991 0.0910 0.0249 -0.0225 0.1312 0.0791 -0.2710

0.1619 0.6492

Source : Author's calculations

Other interesting findings include that: (a) although simple cross-tabulations show that public enterprises demanded and, in fact, got more loans than private firms, once other variables are controlled for − government ownership by itself is not correlated with reporting a demand; (b) locality-level variables do not influence demand among enterprises; and (c) there were substantial differences in reported demand across agro-regions. Points (b) and (c) are in direct contrast with the corresponding findings of the model when applied to the data on households. Weak Demand for Credit The regression results on the household data suggest that, by and large, the demand for loans at the household level was associated with highly inelastic consumption needs rather than with investment opportunities and by absence of alternative financing means to loans. In short,


53

the demand for loans in rural areas seems to have been exercised along the “inelastic” portions of the demand curve – when liquidity was badly needed and when there were no substitutes for loans to obtain the required liquidity. The justification of this inference follows. Everything else the same, larger families have more cyclical (e.g., beginning of the school year, Christmas) and unexpected (e.g., medical emergencies) consumption needs. This feature may trigger recurrent demand for loans to finance household consumption. In fact, 53 percent of the households which had access to credit declared that they used it to finance consumption activities. Households with more pensioners were not only older on average, but also may be more likely to finance medical expenditures and to have sticky nominal incomes. Although their incomes have deteriorated in real terms, they are predictable enough to allow servicing of debts. Households with a greater involvement in non-agricultural activities tend to have higher wages and more stable income levels and are, thus, better positioned to trade present consumption for future income flows. On the other hand, households residing in comparatively large communities dedicated intensely to farming and which were distant from urban centers reported were more likely to have a demand for loans. In such an environment, local aggregate levels of economic activity were highly dependent on systemic factors such as weather or specialization in few regional crops, which may trigger simultaneous need for outside funding. Finally, households who had access to: (a) bigger endowments of assets and wealth, including larger landholdings; and (b) sources of liquidity, including bank deposits and sales revenues were more likely to report that they had no demand for loans. Indeed, 44% of the households which reported no demand for loans belonged to the top quartile in terms of the value of assets owned. It is reasonable to conclude, therefore, that households prefer internal sources of funding over external borrowing. One consequence of the observed excessive collateral requirements is that the demand for loans decreases. Large numbers of otherwise creditworthy borrowers may opt out of credit markets. Peculiar collateral requirements together with the shortcomings of the legal framework could make the borrowers’ cost of defaulting disproportionate to the amount borrowed. Rural areas have no functioning mechanisms with which to auction property given as collateral and to ensure that any amount remaining after lenders have been fully compensated will be returned to the borrower. Hence, those potential borrowers who would be required to pledge collateral may face an artificially skewed risk-return distribution for their investments. Indeed the survey indicates that 27 percent of rural entrepreneurs and 8 percent of rural enterprises did not request loans because they considered borrowing too risky for this reason. Clearly, there are also underlying profitability problems in the rural sector. Low profitability in the sector implies low values for sector specific assets, notably land. These low values restrict the demand for credit. As detailed in Chapter I section E, the profitability indicators of the enterprise sector were rather weak during the period covered by the survey. Although indicators varied significantly between private and state enterprises and across subsectors, the aggregate return on equity (ROE) and return on assets (ROA) of Romania’s rural enterprises were much lower than inflation in 1997 (19 percent and 9 percent, respectively), against an annual inflation of 155 percent.

54

Chapter Three:

In addition, the sector’s demand for credit was also weak because limited investment took place during the period covered by the survey. The link between credit and investment is intuitively straightforward. Investment outlays tend to be lumpy and require liquid resources. Thus, access to external credit may assist households and enterprises to take advantage of profitable investment opportunities. Availability of internal financing is not necessarily synchronized with investment opportunities. Efficient credit markets could be accessed when opportunities appear. The data indicate that a comparatively limited number of rural households and enterprises made investments in capital goods during the period for which data was collected.48 About 28 percent of rural households made some type of investment, of which 74 percent invested in productive activities (mostly agriculture) and 36 percent in housing and household durables.49 About 26 percent of enterprises invested in the period, of which 57 percent were in equipment and machinery. Macroeconomic uncertainty probably remains a significant concern of potential rural borrowers who must borrow at variable rates of interest – 87 and 75 percent of all bank loans granted to enterprises and households, respectively, had rates of interest adjustable with respect to some market index. Borrowers could go bankrupt when interest costs rise relative to their enterprise earnings, especially for households which have very with limited access to markets or enterprises in non-tradable sectors because of difficulties in hedging against devaluation of the Lei. Another factor that may be weakening the effective demand for credit is the high levels of ex-ante real interest rates on loans, whether denominated in Lei or in hard currency (taking into account expected devaluation). High real rates require investments to have very high marginal productivity. Smaller enterprises with low capital/labor ratios would be more willing, everything else equal, to borrow at the prevailing high real rates, while larger and more capital intensive businesses would not be able to afford such interest rates. In Romania, there may be an unfortunate mismatch in which smaller businesses which would demand credit even at high rates are not being served by banks, while larger enterprises which would be served by banks are not demanding credit at high (real) rates.50 48

Clearly, it is difficult to separate causality in this case. Limited demand for investment certainly implies weak demand for loans. On the other hand, limited investment may have been caused by limited access to loans. Chapter V separates empirically these effects, and also provides details on the measurement of investment outlays.

49

These figures do not add to 100 percent because some households invested in both productive and household activities.

50

Of course, borrowers who intend to get away with default are not concerned about the real interest rates on their loans.

Chapter IV: Credit Constraints and Rural Investment The previous chapter provided evidence that the observed limited flow of loans to rural households and enterprises during the period covered by the surveys was caused by a limited supply of credit in the whole economy, which was probably worse for the rural sector, and by a weak demand for rural credit under the conditions at which loans were available at the time. This chapter addresses the relevant public policy questions that arise from this evidence. How much of this limited flow of loans was due to weak supply of credit and how much was due to a weak demand for credit? In particular, was the demand weak because there were only a few profitable investment opportunities or because households and enterprises had sufficient internal funding relative to their needs. Equivalently, did the limited supply of loans relative to existing demand result in significant numbers of households and enterprises not taking advantage of the profitable investment opportunities that may have been present in rural areas because of constrained access to credit markets? If so, how much larger would rural investment have been in the absence of credit constraints? This chapter is organized in four sections. The first section presents the working definition of credit constraints and the empirical methodology used to assess the determinants of credit constraints in the rural sector. Then, the results are evaluated for the sample of households and enterprises in the following next two sections. The last section presents the effect of credit constraints on rural investments. A. THE EXTENT OF CREDIT CONSTRAINTS IN THE RURAL SECTOR The previous chapter identified empirically the households and enterprises that reported a demand for loans under the conditions they perceived the market would lend to them. Prevailing conditions included dimensions such as interest rate, collateral requirements, and transaction costs required to complete a credit contract. This section takes the analysis further by determining whether the agents which had a positive demand for loans were able to borrow the amounts they desired. That is, whether rural agents were credit constrained.51 Being “credit constrained” is necessarily a relative concept resulting from the comparison of an agent’s demand for credit with the supply of credit to which it has access. An agent which does not have a demand for credit can not be credit constrained by definition. Consequently, rural agents could be classified by comparing their self-reported demand with the actual amounts of loans they received during the period under analysis. In terms of

51

Credit constraints relative to demand for credit and credit rationing is an issue widely discussed in the economics literature (e.g., Milde and Riley, 1988; Gale and Hellwing, 1985). Credit rationing is explained as an equilibrium outcome under various circumstances such as interest rate restrictions or subsidized credit policies (e.g., GonzalezVega, 1984), imperfect information and profit maximizing behavior of lenders (e.g., Stiglitz and Weiss, 1981), and enforcement difficulties and ensuing opportunistic behavior of borrowers (e.g., Bell 1988).

56

Chapter Four:

credit constraints, every agent must, therefore, belong to one and only one of the following four groups. The first group includes those agents which were not interested in borrowing at the prevailing conditions. These agents did not have loans simply because they did not want loans, and may be called unconstrained non-borrowers. The second group corresponds to agents that did not get loans although they wanted credit. This group includes agents whose loan applications were denied and agents which did not apply for loans because of their (correct) perception that their applications would have been rejected, at least with high likelihood. This group corresponds to totally constrained non-borrowers. The third group of agents consists of those that received loans for exactly the amount they wanted under the prevailing conditions. These agents may be called unconstrained borrowers. The fourth and last group corresponds to those agents that Table 16 The Extent of Credit Constraints received loans for less than the Households Enterprises amount they would have wanted to (%) (%) borrow at the conditions prevailing Credit Constrained 24.3 41.1 at the time. This group is termed Constrained borrowers constrained borrowers. (partially constrained)

13.8

12.0

Table 16 summarizes the incidence of credit constraints in 29.1 10.5 rural Romania. The survey data Credit Unconstrained 75.7 58.9 show that the incidence of credit Unconstrained borrowers 6.4 8.3 constraints is significant. Only a Without loan demand 69.3 50.5 small percentage of rural agents Total 100.0 100.0 reported being unconstrained Source: Surveys of Households and Enterprises, 1998. borrowers. Six percent of households and 8 percent of enterprises were able to borrow the amounts that they wanted to borrow. The prevalence of credit constraints among rural enterprises doubled that of rural households. Enterprises reported that they were totally credit constrained three times more often than households. This greater incidence among enterprises resulted because they had a stronger demand for loans. Among households, 10 percent reported being totally credit constrained and 14 percent were partially credit constrained. Among enterprises, 29 percent reported being totally constrained, while 12 percent reported that they were partially constrained. Constrained non-borrowers (totally constrained)

Credit constraints resulted from the interaction of demand and supply factors. Hence, it is necessary to separate the influence of demand and supply to assess the performance of rural credit markets. An ordered probit econometric model was applied to the data on those agents which had a positive demand for loans. The model determines the probability of an agent being a totally constrained, partially constrained, or an unconstrained borrower as a function of observable variables. These variables influence both the demand for, and supply of, loans available to each agent and include specific observations related to lending costs (e.g., the number of financial services retail outlets in the locality).

Credit Constraints and Rural Investment

57

Table 17 and Table 19 present the estimated coefficients and the marginal effects of the explanatory variables on the above probabilities for rural households and enterprises, respectively.52 B. CREDIT CONSTRAINTS AT THE LEVEL OF RURAL HOUSEHOLDS As presented in Table 17 the ordered probit model shows that unconstrained and partially constrained households (i.e., those which borrowed) tend to be similar among themselves and tend to be very different from their totally credit constrained counterparts. After controlling for numerous other variables, totally credit constrained households are more likely (with statistical significance) than their borrowing counterparts to: (a) be headed by unmarried individuals; (b) be less educated; (c) have more members; (d) have less members working in the non-agricultural sector; (e) have smaller endowments of non-financial movable assets; (f) receive smaller amounts of fixed incomes such as salaries and pensions; (g) have smaller real state holdings; (h) live in localities where there are more farmers relative to total population; and (h) live in localities where there are more branches of state-owned banks. The (aggregate) supply of loans faced by households is very diverse as it ranges from altruistic friends and relatives to credit cooperatives owned by the credit applicants themselves to for-profit money lenders. Clearly, each type of lender imposes different conditions on its loans and has diverse criteria to approve requests for credit. Hence, the analysis of the supply of loans available to households should differentiate between informal sector lenders (mostly friends and relatives) and formal sector lenders (commercial banks and non-bank intermediaries such as credit cooperatives and Casa de Ajutor Reciprocs, CARs). 53 The probability of an agent being: (a) totally credit constrained; (b) a borrower from the informal sector; or (c) a borrower from the formal sector as a function of observable variables should complement the analysis above. A multinomial logit was applied to the data set of households with positive demand to find the variables that determine the probability of a rural household to obtain a loan from a particular type of lender or no loan at all. The results of the regression and the complete list of explanatory variables used in the model are presented in Table 18. These results expose the differences in the motivation and approval criteria between the formal sector and friends and relatives when lending money to households.

52

Annex 2, “Credit Constraints and Investment Behavior of Households and Enterprises in Romania’s Rural Areas: An Empirical Analysis”, presents the theoretical and technical aspects of the simple and ordered probit models applied to the data. The ordered probit measures the aggregate supply of loans faced by an agent relative to the agent’s total demand. It does not distinguish among different possible lenders. Another econometric model, whose results are presented below, calculates the probability that an agent with positive demand obtained a loan from a given type of lender. Annex 2 also provides statistical demonstration that the particular application of the ordered probit models yields good econometric fits to the data (e.g., χ2 and pseudo-R2 measures). It also shows that there are no sample selection problems in applying the ordered model only to the observations of households and enterprises that reported a demand for loans (Greene, 1997).

53

The market shares and the characteristics of the loans granted by each type of lender in rural Romania are summarized and described in great detail in Annex 1. The market shares as a percentage of the number of loans to households (as opposed to amounts lent) of moneylenders and commercial banks are very limited (0.7 percent and 4 percent, respectively).

58

Chapter Four:

Formal lenders (mostly credit cooperatives and CARs) were more likely, everything else the same, to have received and to have approved credit applications of households which: (a) were headed by married, female, and more educated individuals; (b) had fewer members; (c) were wealthier with higher values of movable and real estate assets and financial deposits; (d) had access to predictable and verifiable flows of income as indicated by higher levels of wage and pension incomes; (e) were more integrated into markets as suggested by more people working outside agriculture, lower levels of self-consumption of their production, less fragmented landholdings, residence in localities with a lower proportion of farmers, and being closer to a town or city. In contrast, the informal sector (mostly friends and relatives) were more likely, everything else the same, to have received requests for credit from, and granted credit to, households which: (a) were headed by younger and male individuals; (b) did not have alternative sources of liquidity in the form of bank deposits or the possibility of borrowing from a credit cooperative; and (c) were less integrated into markets as indicated by more members working in agriculture, fragmented agriculture with numerous plots, and living farther from a town or city. Statistically speaking, informal lenders, which comprise mostly friends and relatives, as a group were not concerned with wealth and income variables. These results strongly suggest that there was a matching of borrowers and lenders in that (among those who had borrowed) the better-off individuals with access to markets obtained their loans from the formal sector while comparatively worse-off and economically isolated individuals resorted to borrowing mostly from friends and relatives. Formal lenders provided 56 percent of their loans and 68 percent of their total amount of credit to households in the two richest asset quartiles. Additionally, the fact that households located in localities with a larger number of state bank branches were more likely to be totally credit constrained suggests that state banks not only grant few loans to households, but that their branches are possibly crowding out credit cooperatives and CARs which, in order to lend to households, need to compete in mobilizing savings with the state. Backing from the state gives state-owned banks an advantage in mobilizing savings over those lenders which did grant loans to households, albeit to the richest ones. In general, the regression results confirm that one reason why few Romanian rural households participate in credit markets is because there was a limited coincidence between those which want loans (the aggregate demand) and the willingness of all potential lenders to lend to them (the aggregate supply). In fact, a majority of characteristics that made households more likely to demand loans (see Table 18) also made lenders less willing to grant them loans. C. CREDIT CONSTRAINTS AT THE LEVEL OF RURAL ENTERPRISES Table 19 presents the results of two specifications of the ordered probit model applied to the enterprise survey data. The table presents the signs, magnitudes, and statistical significance of the estimated parameters and marginal effects that each of the variables has on the probability


59

that an enterprise had been totally constrained, partially constrained, or unconstrained at the time of the survey54. The results indicate that enterprises that were partially credit constrained or unconstrained tended to be statistically similar and that, as a group, they differ significantly from their totally unconstrained counterparts. In a sense, lenders to rural enterprises based their decisions to allocate any amount of credit (the amount actually requested or less) on basically the same criteria, as follows.55 Lenders were more likely, everything else the same, to have received and to have approved credit applications from enterprises which: (a) were managed by older and less educated individuals; (b) were operating in sectors other than industry and incorporated as stock corporations; (c) were large in terms of the value of their gross sales and the value of their assets; (d) were in the agricultural sector, but only among the very large enterprises; and (e) were domiciled in localities in which there were many branches of state-owned banks. That is, enterprises with those characteristics were less likely to be totally credit constrained and more likely to be either unconstrained borrowers or constrained borrowers, as indicated in the table. So What? The Effect of Credit Constraints on Rural Investment This section presents empirical evidence that credit constraints influence negatively the investment behavior of households and enterprises. In particular, such constraints reduce the number of agents that invest and the amounts they invest. The effect is especially negative at the enterprise level. Thus, credit constraints matter from a public policy point of view, because profitable investment opportunities are not pursued as a result of limited access to credit markets. This situation is very negative for rural Romania because there are few such opportunities anyway. The analysis that follows predicts the share of households and enterprises which would have invested during the period covered by the surveys, and the amounts of such investments, in the absence of credit constraints. The analysis also determines the characteristics of agents which were statistically related to their likelihood of investing and to their expected amounts of 54

The second specification (Model II) excludes the agro-region dummies to test whether the number of financial outlets in the locality may be related to regional differences captured already by the dummies. A likelihood test indicates that these dummies are not statistically significant determinants of the borrowing status of enterprises. Hence, the results summarized here correspond to the variables that were found to be statistically significant in both models. Variables that were significant at 85 percent in one model had to be significant at least at 90 percent in the alternative specification to be reported in the text.

55

The banking sector allocated to enterprises 99.5 percent of the amount of loans and about 70 percent of the number of transactions they received during the period. This concentration makes the supply of loans available to enterprises rather homogeneous. There is no need, therefore, to study the supply of loans independently as was the case at the household level where it was much more heterogeneous. While political considerations may result in differences in the lending behavior of state or private banks, and thus, in the probability of a rural enterprise obtaining loans, the majority of enterprises that received loans did so from state banks (88%). Thus, the results of the ordered probit are highly influenced by the lending criteria of state banks. On the other hand, private banks that are lending directed credit lines to rural enterprises may also be subject to political pressures.

60

Chapter Four:

investments. These results allow for estimation of the costs of credit constraints. They also outline areas for fruitful policy intervention. The link between credit and investment is intuitively straightforward. Investment outlays tend to be lumpy and require liquid resources. Thus, access to external credit may assist households and enterprises to take advantage of profitable investment opportunities. Efficient credit markets can be accessed when opportunities appear. In contrast, availability of internal financing is not necessarily synchronized with investment opportunities. The analysis begins by looking at the investments made by households and enterprises. Investments are defined as the expenditures incurred in acquiring capital goods including buildings, equipment, tools, machinery, Figure 12 Investment Decisions by Credit Constraints vehicles, livestock, and land.56 Total

A comparatively limited number of rural Partially credit constrained households and e n t e r p r i s e s m ade Borrowers investments in capital Without demand goods during the period Totally credit constrained for which survey data Enterprises was collected (see Households Non-borrowers Figure 12). About 28 0 5 10 15 20 25 30 35 40 45 50 percent of rural Source: Survey of Rural Households and Financial Services, 1998; Survey of households made some Rural Enterprises and Financial Services, 1998. type of investment, of which 74 percent invested in productive activities (mostly agriculture) and 36 percent in housing and household durables.57 About 26 percent of enterprises invested, of which 57 percent was in equipment and machinery. Credit unconstrained

The data also show that the amounts actually invested were very small relative to the income of rural enterprises and households. In the aggregate, they invested 4 and 6.5 percent of their gross annual incomes, respectively.58 The value of physical investment as a percentage of GDP in the EU and the OECD was 22 and 25 percent, respectively. Although Romanian, EU, 56

Inventory accumulation (a form of investment) was not included in the definition of investment used in the analysis. The poor performance of input and output markets in rural Romania does not allow for the distinction between inventories as investments and as storage of production that could not be sold. Investments in research and development, another form of investment, were not observed in rural Romania.

57

These figures do not add to 100 percent because some households invested in both productive and household activities.

58

Enterprise income is equivalent to the aggregate value of gross sales. Household income includes the gross value of sales of agricultural and non agricultural products and services, the gross value of wages, and the imputed value of self-consumption of agricultural products.


61

and OECD statistics are not directly comparable because of different measuring methodologies, the absolute differences in magnitude are sufficient to indicate low levels of investment relative to income in rural Romania. Figure 12 also illustrates substantial differences in investment decisions between the agents which borrowed and the ones which did not. About 38 percent of the households which borrowed made investments compared to 26 percent for their non-borrowing counterparts. For enterprises, the percentages are 44 percent for the ones which borrowed and 20 percent for the ones which did not. The main message is that the incidence of investments is positively correlated with access to loans. Totally credit constrained households and enterprises show lower incidence of investments when compared to the agents that borrowed. The remainder of this section is aimed at providing answers to the following questions: (a) What were the determinants of investment opportunities and the amounts of investments? (b) Would increasing access to loans also increase the incidence and amounts of investment? (c) Where would public policies have the greatest impact in improving the overall investment environment or in transferring assets among economic agents, including expenditures in technical assistance and training? What were the Determinants of Investment Opportunities and Amounts of Investments? The analysis estimated how much more investment would have occurred in rural Romania during the period covered by the surveys had credit constraints been removed, that is, how many more agents would have invested, and how much more, had they been able to borrow as much as they wanted at the prevailing conditions at the time. Two approaches were used in this study to empirically measure the influence that credit constraints had on investments. The first approach entailed dividing the data into the following two groups. The first group contains the households and enterprises for which it can be ascertained whether or not they had investment opportunities. This group includes agents which invested and agents which did not invest. Obviously, any agent which invested in the period had an investment opportunity. For the agents in this group which did not invest, the reason that prevented them from doing so was lack of opportunity and not lack of financing. Empirically, this group includes the observations of (a) all agents which invested, (b) all unconstrained borrowers, and (b) all agents with no demand for loans. The second group contains the agents which did not invest and for which the causes of the observed lack of investment could not be clearly ascertained. For these agents, lack of investment may have occurred because: (a) lack of investment opportunities; or (b) lack of funding to take advantage of opportunities; or (c) both. Empirically, this group includes all agents which did not invest and which were credit constrained.59 59

This separation of the observations to study investment behavior follows the logic of the Theory of Revealed Preference used in empirical demand analysis. Individuals who purchase a basket of goods prefer that basket and have the budget required to purchase it. Individuals who do not purchase any given basket within their budget set do not prefer such basket. Finally, no direct inference could be made about the individual’s preference over baskets outside her budget. The separation above divides the sampled rural agents into those for which direct similar

62

Chapter Four:

To understand investment decisions and amounts, a reduced-form equation was applied to the subset of households and enterprises for which there was no ambiguity regarding availability (or lack thereof) of investment opportunities (the first group above). The empirical model estimates two equations simultaneously: (a) one to analyze the decision to invest (yes or no, type of decision); and (b) another to analyze the amount of the investments made by those which actually invested.60 The estimated coefficients from these two equations were applied to the group of agents for which the reason for their lack of investment could not be inferred directly (the second group). The result of this exercise is the predicted probability that these agents had an investment opportunity and, if so, the expected value of the amount that they would have invested had they had access to funding. These predictions are, therefore, a function of the behavior of group one (estimated coefficients) and the observed characteristics of group two.61 Investments by Households Table 20 presents the explanatory variables and regression results for two specifications of the model. Table 21, on the other hand, presents the summary of the predictions made by the model about the effects that removing credit constraints would have on: (a) the number of households which would have invested; and (b) the amounts they would have invested. The base line for these predictions is the actual levels of investment during the period covered by the survey. The first table shows that household investment opportunities: (a) are negatively related to the age of the household head; (b) increase with the number of household members who are pensioners, mostly because of stability of cash flows and basically on consumer durables; (c) are positively related to the number of household members; (d) are more likely for households which hold bank deposits; (e) are more frequent for households with larger housing units, again associated to durable consumer goods; (f) are positively associated with the degree of connection to markets as proxied by the share of the value of agricultural sales in total household income − in fact, 45 percent of farm households with substantial market involvement made investments, inferences about their availability of investment opportunities could be made and those for which no direct inference could be made because they did not have an investment “budget.” 60

Annex 2 presents the theoretical and technical details of the methodology used. Both equations are estimated simultaneously to maximize the efficiency of the estimated parameters. The method of estimation was maximum likelihood.

61

The most commonly used method to analyze empirically the effects of credit constraints on investment decisions is a switching regression model where investment equations are fitted to two groups that differ only in terms of their excess demand for loans. An alternative approach had to be devised to be used here because of the impossibility of separating agents in two mutually exclusive categories on the basis of their excess demand for loans. In Romania and during the period covered by the survey, the investment behavior of households and enterprises varied dramatically with the degree of credit constraints (see Annex 2). The traditional switching regression model was applied to the data with poorer results in terms of fit to the data, robustness, and appropriateness of the signs.


63

compared to only 24 percent which consumed their production; and finally (g) vary significantly by regions, namely more frequent opportunities in Moldova de Podis, Subcarpati de Sud, Oltenia de Sud, and less frequent opportunities in Campia Dunarii de Jos and Campia Romana Centrala. The second part of Table 20 indicates that the amounts invested by households that perceived profitable opportunities tended to be larger for households: (a) headed by (i) younger, (ii) female, and (iii) less educated individuals; and (b) having more pensioners. Some of the characteristics of the entrepreneurial activities influenced the amounts invested. Indeed the households which invested larger amounts had: (a) more fragmented landholdings; and (b) more market involvement as indicated by the shares of their income originated in labor and output markets (farm and non-farm). Finally, households in agrarian localities, as proxied by the ratio of farmers to population and in Subcarpatii de Sud and Oltenia de Sud tended to invest lower amounts. Table 21 sheds light on the following key policy issues regarding rural households: (a) the set of investment opportunities available to rural households is rather limited; (b) lack of financing under the conditions prevailing at the time of the survey (debt or equity) was not a bottleneck to investment in the sense that most of the households which had investment opportunities actually took advantage of them; (c) mitigating credit constraints by providing additional credit under the (same) prevailing conditions would have a limited impact on the number of households which would have invested and on the aggregate amounts of household investments. In terms of numbers of households, according to the econometric analysis, had there been no credit constraints for households during the period covered by the survey, 29 percent would have invested. This is an increase of only 2 percent from the 27 percent of households which actually made investments. Still according to the analysis, the aggregate amount invested by households in the absence of credit constraints would have been 10 percent higher than the amount actually invested. This increase would have placed household investment levels at about 7.2 percent of their aggregate income instead of the 6.5 percent actually observed. Investments by Enterprises Table 24 presents the explanatory variables and regression results for two specifications of the model applied to the enterprise survey data. Table 25 presents a summary of the predictions made by the model about the effects that removing credit constraints would have on: (a) the number of enterprises which would have invested; and (b) the amounts they would have invested. The baseline for these predictions is the actual levels of investment during the period covered by the survey. The results suggest that the enterprises more likely to invest: (a) had younger managers; (b) were in sectors other than agriculture with the exception of large agriculture enterprises which were also more likely to invest; (c) were private in that the state had no participation in their ownership; (d) had high volumes of sales; (e) were those without large numbers of owners managing or working in them, as measured by the share of owners or members in the total work

64

Chapter Four:

force; and (f) were located in more densely populated regions. Enterprises in the regions of Moldova Deal and SAI were less likely to invest. The second part of Table 24 indicates that the amounts invested were statistically independent of economic sectors, legal status of incorporation, ownership, and economic conditions in the locality where the enterprises were located. The amounts invested were higher for enterprises with more: (a) more assets; (b) gross value of sales; and (c) leverage, as measured by their debt-to-asset ratios. The amounts invested by enterprises in the regions of Subcarpatii de Sud and Moldova de Podies tended to be smaller. Table 25 indicates that lack of financing under the conditions prevailing at the time of the survey (debt or equity) represented a significant impediment for rural enterprises to take advantage of the investment opportunities available. There would have been considerably more enterprises taking advantage of investment opportunities if credit constraints had not been present. Mitigation of credit constraints would have an especially significant impact on the aggregate amount of investments made by rural enterprises. In particular, the econometric analysis predicts that, in the absence of credit constraints, about 37 percent of enterprises would have invested during the period covered by the survey. This is an increase of 41 more than the 26 percent of enterprises which actually made investments. The aggregate amount invested in the absence of credit constraints would have been about 57 percent greater than the amount actually invested. D. INVESTMENT LEVELS: IS IT WHERE YOU ARE AND WHAT YOU HAVE OR WHAT YOU DO WITH IT? The design of policies to improve rural financial markets could be refined still further by better understanding the way in which access to credit affects investment. The facts are that about 40 percent of borrowing households made investment outlays during the survey period, while only 24 percent of their non-borrowing counterparts did. About 37 percent of the enterprises that borrowed invested. The incidence of investment among enterprises that did not borrow was about half (only 20 percent). Obviously there is a difference between borrowers and non-borrowers in their investment decisions. This section aims to answer the relevant policy question that arises from this observation. Suppose that it is possible to give credit to agents (households or enterprises) which did not have credit before without changing their productive characteristics or their location. Would those agents invest more? If so, how much more? The following approach to estimating the effect that access to credit had on investment decisions is based on examining the difference in the propensity to invest of borrowers and nonborrowers. These differences are influenced by observable and unobservable factors. For any agent (household or enterprise) in either group (borrowers or non-borrowers), the decision to invest, Ii, is a function of: (a) observable productive characteristics (number of employees, years in business, total assets, bank deposits, location); (b) the effect that each of these characteristics has on the agent’s decision to invest, β; and (c) a residual, ε, that captures all things that cannot be observed and that are specific to that particular agent. In a simple equation.


•

I*i = Xi β + εi

65

Ii = 1 if Y*i > 0 (the agent made an investment) Ii = 0

otherwise

The equation captures a simple fact. When two individual agents make different investment decisions, it must be because: (a) they have different productive characteristics, ∆X for example, level of assets or locality of residence; or (b) they have different structural factors, ∆β for example, entrepreneurial abilities, skills, and risk preferences, or (c) both. Statistically, differences in unobserved structural variables show up as different returns to observed productive characteristics. It follows that aggregate differences in the investment decisions made by borrowers and non-borrowers could be explained by aggregate disparities in endowments and differences in structural factors. If so, borrowers and non-borrowers invest differently because they are located in different places, have different endowments of productive characteristics, and use their endowments and their location differently. The strategy for the analysis is as follows. First, an agent’s investment decision is modeled as a dichotomous dependent variable (yes or no type of decision) using a probit specification. Second, the model is estimated separately for borrower and non-borrower samples to analyze differences in their investment behavior.62 Third, the observed differences in investment decisions between borrowers and non-borrowers are decomposed using the method below, I B − I NB = [Φ ( X B βˆ B ) − Φ ( X NB βˆ B )] + [Φ ( X NB βˆ B ) − Φ ( X NB βˆ NB )]

where I represents the percentage of households or enterprises that made investments among borrowers (B) and among non-borrowers (NB), X is the vector of the average values of the explanatory variables posited to influence investment decisions, and the β‘s are the estimated coefficients capturing the structural factors that affect investment decisions.63 The first term on the right-hand side of this equation captures the effect of borrowers and non-borrowers having different endowments of assets and being in different localities. It represents the difference between the actual investment decisions made by borrowers and the (predicted) investment decisions they would make if they had the asset endowments and locality of residence of non-borrowers. In short, this first term captures how much of the difference in investment is due to having more or less assets, more or less bank deposits, living in different places, etc. The second term of the equation captures the effect of the difference in investment decisions between borrowers and non-borrowers that is due to structural factors such as abilities and entrepreneurial capacity. It represents the difference between the (predicted) investments that

62

A likelihood ratio test was used to investigate the possibility of sample selectivity bias from classifying agents in the categories of borrowers and non-borrowers. The test rejected the bias on the basis a bivariate probit, that included a probit model of investment decisions and a probit model of being a borrower.

63

This method was first proposed by Jones and Makepeace (1996). Pagán and Tijerina (1999) provides an example of this separation and other technical details.

66

Chapter Four:

would have been made by borrowers if they had the assets and they lived in the localities of nonborrowers. These results can be used to estimate what percentage of the households and enterprises that did not have credit would have invested had they been given credit. In other words, would credit have changed the investment decisions of those agents which did not have credit? The results of this exercise follow, first for rural households and then for enterprises. Rural Households Table 22 presents the list of explanatory variables and estimated coefficients for (a) all sampled households, (b) borrowing households only, and (c) non-borrowing households only.64 Differences in investment decisions between borrowers and non-borrowers. All households, regardless of whether they borrow or not, invest more when they are headed by younger individuals. For borrowers, higher levels of education are positively related to the propensity to invest, while for non-borrowers education does not influence investment decisions. For non-borrowers, households headed by males and non-Romanians are more likely to invest. Family size and the number of pensioners in the household increase the likelihood that nonborrowers will invest, consistent with the results obtained in the previous approach. For borrowers and non-borrowers, investment decisions are positively related to dwelling size. Interestingly, farm size does not affect the likelihood of investment. Borrowers are less like to invest if they live in agrarian localities with low population densities. Plausibly, they borrow basically to smooth consumption. The availability of liquid assets in the form of bank deposits make it more likely for non-borrowers to invest, naturally. Non-borrowers who are integrated to output markets are also more likely to invest, especially those which have non-agriculture enterprises. There are substantial regional differences in the decisions to invest between households which borrow and those which do not. Borrowing households located in Moldova de Podis and SAI are more likely to invest than borrowing households situated in other regions. Significantly lower investment propensities in Campia Dunarii de Jose, Campia Romana Centrala, and SAI are found among non-borrowing households. Decomposing the differences in investment decisions between borrowers and non-borrowers. Table 23 reports the results of decomposing the differences in the investment decisions between borrowing and non-borrowing households. Remember that about 40 percent of borrowing households made investment outlays, 24 percent of their non-borrowing counterparts invested, and that the share of all households which invested was 27 percent. The probit model predicts that 31 percent of non-borrowing households would have invested if they had had access to credit, instead of the 24 percent that actually did invest, under the assumption that they had the structural factors. More investment by those which did not borrow would imply that, in the aggregate, 33 percent of all households would have invested 64

The Χ2 and Pseudo-R2 measures indicate that the regressions fit the data on households quite reasonably.


67

rather than the observed 27 percent for the entire population. This alternative estimation method predicts a larger effect on investment levels at the household level due to access to credit than the effect predicted by the previous section. The question remains as to why households which had access to credit were almost twice as likely to invest (40 percent) than households which did not borrow (24 percent). The model indicates that differences in the endowment of productive characteristics and in the localities between the two groups account for 54 percent of the incidence of investment decisions. The remaining 46 percent of the difference should be attributed to differences in structural factors across groups. Rural Enterprises Table 26 presents the estimated coefficients for all observations, borrowing enterprises, and non-borrowing enterprises for the same set of explanatory variables used for the model in the previous section.65 Differences in investment decisions between borrowers and non-borrowers. The results of the model applied to the entire data set of enterprises (whether they borrowed or not) indicate that the decision to invest was associated with statistical significance to six variables, namely: (a) economic sector − enterprises in the agricultural sector were less likely to invest than those in the other sectors; (b) private sector ownership − private enterprises invested more often than their state-owned; (c) liquidity − those with more money deposited in banks invested more; (d) sales − larger turnovers where associated with higher frequency of investments; (e) separation of ownership and workforce − enterprises in which numerous owners or members were also employees were less likely to invest (e.g., family associations); (f) density of population − enterprises located in densely populated areas were more likely to invest; and (g) primary sector − those enterprises located in agrarian localities, measured as the share of farmers in the population of the locality, were less likely to invest. The model applied to the data set of enterprises that borrowed during the period indicates that the decision to invest among such enterprises is related to mostly the same variables above. The difference with respect to the whole set of enterprises is that more of those with higher financial leverage were less likely to invest and that the share of owners who act as employees and density of population are not statistically significant for the enterprises which borrowed. The investment decisions of the group of enterprises which did not borrow were influenced by the same set of variables found to be associated with the investment behavior of the whole set of enterprises, with the addition of: (a) the age of the business as younger business were more likely to invest more often; and (b) more levered enterprises were less likely to invest. Decomposing the differences in investment decisions between borrowers and non-borrowers. As shown in,

65

Note that the Χ2 and Pseudo-R2 also indicate that the regressions have a reasonable fit to the enterprise data.

68

Chapter Four:

Table 27 the model predicts that the incidence of investment among non-borrowers would have been 33 percent, instead of the observed 20 percent, had they borrowed. Overall, the percentage of rural enterprises that made investments would have been 34 percent, rather than the 26 percent that actually did, in a situation in which non-borrowers would have had access to credit. In the case of enterprises, structural factors are the main cause of the different incidence of investment between non-borrowers and borrowers. Such factors account for 74 percent of the difference. In turn, differences in the productive characteristics between borrowing and nonborrowing enterprises accounted for only 26 percent of the differences in investment decisions. When it comes to enterprises and the decision to invest, it is not what they have and where they are but what they do with what they have. Entrepreneurial capacity seems to be less uniformly distributed among enterprises than among households, as the latter were basically made farm entrepreneurs by the land reform process (see section II.E).


69

Table 17 Rural Households: Credit Constraints (Ordered Probit Model) Explanatory Variables Constant Sociodemographic variables

Regression Results

Marginal Effects (evaluated at mean values)

Regression Results

Coeff.

Ptotally constrained

Coeff.

S.D.

-1.5779 1.3817

Age of household head -0.0036 0.0040 Marital status (1=married) 0.4381 0.1699 *** Gender (1=male) -0.2321 0.1841 Nationality (1=Romanian) 0.0985 0.1808 Max education by HH me mber 0.1115 0.0332 *** Family size -0.0930 0.0327 *** Adults working in nonagriculture 0.2028 0.0712 *** Number of pensioners in HH -0.1170 0.0885 Characteristics of Entrepreneurial Activity Log (assets, excluding land and deposits) 0.1088 0.0362 *** Log (deposits) 0.0108 0.0149 Log ( monthly agricultural sales) -0.0173 0.0235 Log ( monthly non-agricultural sales) -0.0588 0.0377 a Log ( monthly non-agricultural sales) 0.1699 0.0442 *** Log ( monthly self-consumption) -0.0014 0.0385 Land holdings (Ha) 0.1266 0.0403 *** Number of plots -0.0095 0.0211 Number employees (ag and non-ag) -0.0194 0.0163 EconomicConditions in the Locality Log (population) 0.0168 0.1411 Log (population density per hectare) 0.1162 0.0918 Owners of agricultural land /inhabitants (%) -0.8844 0.4207 ** Log (Kms to nearest town) -0.0326 0.0833 Agroregion Dummies Campia de Vest 0.1219 0.1899 Moldovade Podis 0.2924 0.2051 MoldovaDeal 0.1607 0.1980 Subcarpatii deSud 0.0162 0.1555 Campia Dunarii de Jos -0.0767 0.2036 Oltenia de Sud -0.2544 0.2436 Campia Romana Centrala 0.2736 0.1990 SAI -0.0748 0.7855 Number of Financial Outlets of: State-owned bank branches -0.2257 0.0863 *** Private-owned bank branches -0.0449 0.2463 Credit cooperatives -0.1123 0.1096 Moneylenders 0.0147 0.0165 Threshold Parameter ThresholdParameter (µ) 1.4691 0.0732 *** Number of observations 734 Chi-squared 209.8130 df= 33 a/*/**/*** sign ificant at the 85%, 90%, 95%,nd a 99% confidence intervals, respectively

Source: Author's calculations .

Ppartially constrained

P unconstrained

S.D.

0.5852

-0.2364

-0.3487

1.5109 1.3608

0.0013 -0.1625 0.0861 -0.0365 -0.0414 0.0345 -0.0752 0.0434

-0.0005 0.0657 -0.0348 0.0148 0.0167 -0.0139 0.0304 -0.0175

-0.0008 0.0968 -0.0513 0.0218 0.0246 -0.0206 0.0448 -0.0259

-0.0043 0.4266 -0.2339 0.1433 0.1089 -0.0882 0.2012 -0.1094

0.0039 0.1664 0.1810 0.1612 0.0329 0.0313 0.0696 0.0856

-0.0404 -0.0040 0.0064 0.0218 -0.0630 0.0005 -0.0470 0.0035 0.0072

0.0163 0.0016 -0.0026 -0.0088 0.0255 -0.0002 0.0190 -0.0014 -0.0029

0.0241 0.0024 -0.0038 -0.0130 0.0375 -0.0003 0.0280 -0.0021 -0.0043

0.1036 0.0104 -0.0171 -0.0563 0.1635 0.0028 0.1321 -0.0164 -0.0177

0.0351 0.0146 0.0231 0.0362 0.0432 0.0372 0.0386 0.0208 0.0158

-0.0062 -0.0431 0.3280 0.0121

0.0025 0.0174 -0.1325 -0.0049

0.0037 0.0257 -0.1955 -0.0072

0.0252 0.1128 -0.8995 -0.0311

0.1365 0.0840 0.4081 ** 0.0811

-0.0452 -0.1084 -0.0596 -0.0060 0.0284 0.0944 -0.1014 0.0277

0.0183 0.0438 0.0241 0.0024 -0.0115 -0.0381 0.0410 -0.0112

0.0269 0.0646 0.0355 0.0036 -0.0170 -0.0562 0.0605 -0.0165

0.0837 0.0166 0.0416 -0.0055

-0.0338 -0.0067 -0.0168 0.0022

-0.0499 -0.0099 -0.0248 0.0033

-0.2275 -0.0678 -0.1271 0.0179

0.0821 *** 0.2370 0.0982 0.0156

***

*** *** ***

***

a *** ***

1.4583 0.0723 *** 734 200.4 25

70

Chapter Four:

Table 18 Rural Households: Supply of Loans by Type of Lender (Multinomial Logit Model) Explanatory Variables Constant

Regression Results P semi-formal / P totallyconstrained

P informal / P totally constrained

Marginal Effects (evaluated at mean valu es) P totally onstrain P semi-formal c ed

P informal

Coeff.

Coeff.

Coeff.

S.D.

Coeff. -0.6846

0.6350 0.0017 a

S.D. -5.5883

S.D.

3.5052 a

-5.3059

3.1824 *

-0.0132

0.0087 a

S.D.

Coeff.

S.D.

1.3089 0.6779 **

-0.6243

0.6138

0.0021 0.0018

0.0006

0.0017

-0.0027

0.2492

0.0851 ***

-0.0415

-0.2734

0.0912 ***

0.2004

0.0821 0.0157 ***

0.1326 0.0534

0.0820 a 0.0140 ***

-0.0602 -0.0038

0.0749 0.0144

0.0499 0.0145 ***

-0.0505

0.0147 ***

0.0006

0.0137

0.0811

0.0313 ***

-0.0637

0.0335 *

-0.0223

0.0376

-0.0615

0.0405 a 0.0169

Sociodemographic variables Age of household head

-0.0027

0.0097

Marital status(1=married)

1.4534

0.4601 ***

0.3870

0.3438

Gender (1=male)

-1.2127

0.4928 ***

0.4266

0.3879

Nationality (1=Romanian) Max education by HH member

0.6796 0.3241

0.4598 a 0.0802 ***

-0.0034 0.1110

0.3672 0.0738 a

Family size

-0.3137

0.0819 ***

-0.1213

0.0661 *

Adults working in non-agriculture

0.3491

0.1816 **

-0.1500

0.1756

Number of pensioners ni HH

-0.2910

0.2102

-0.3930

0.1992 **

-0.2077

0.0763 ***

0.0731 0.0832 -0.0725 -0.0496 -0.0174

0.0373

0.0838 0.0410 **

0.0746 0.0840 **

Characteristics of Entrepreneurial Activity Log (assets, excluding al nd and deposits)

0.2943

0.0951 ***

0.0479

0.0174 ***

-0.0020

Log (deposits)

0.0569

0.0357 a

-0.0675

0.1071

0.0805 0.0364 *

0.0029 0.0074

0.0170

0.0062 ***

-0.0199

0.0071 ***

Log (monthly agricultural sales)

-0.0148

0.0580

-0.0711

0.0520

0.0111 0.0112

0.0033

0.0102

-0.0144

0.0103

-0.0353

0.0149 0.0170

-0.0155

0.0148

0.1406

0.0304 ***

Log (monthly non-agricultural sales)

-0.0952

0.0859

Log (monthly non-agricultural sales)

0.8277

0.1736 ***

Log (monthly self-consumption)

-0.1276

0.0903

0.0545

0.0937

Land holdings(Ha)

0.3616

0.1075 ***

0.1603

0.1015 a

0.2357

0.0793 0.0850 ***

-0.0459

-0.1203

0.0171 ***

0.0236 ***

0.0064 0.0189 -0.0602

0.0222 ***

0.0005

0.0154

-0.0203

0.0203

-0.0296

0.0158 *

0.0232

0.0184

0.0564

0.0173 ***

0.0038

0.0185

Number of plots

-0.0609

0.0528

0.0483

0.0462

0.0001 0.0104

-0.0161

0.0087 *

0.0160

0.0086 *

Number employees (agand non-ag)

-0.0866

0.0470 *

0.0553

0.0404

0.0019 0.0091

-0.0217

0.0078 ***

0.0198

0.0076 *** 0.0655

Economic Conditions in the Locality Log (population)

-0.1979

0.3533

0.1953

0.3311

-0.0049

0.0699

-0.0556

0.0617

0.0605

Log (population density per hectare)

0.2793

0.2325

0.3248

0.2191 a

-0.0734

0.0456 a

0.0260

0.0412

0.0474

0.0441

Owners of agricultural land/inhabitants (%) Log (Kms to nearest town)

-1.4799 -0.3643

0.9685 a 0.1989 *

0.4999 0.2785

0.8680 0.1896 a

-0.3319 -0.0953

0.1721 ** 0.0345 ***

0.2399 0.0934

0.1745 0.0370 ***

Campia de Vest Moldovade Podis

-0.0476 0.6115

0.4970 0.5303

0.7315 0.6533

0.4211 * 0.4505 a

-0.0927 -0.1529

-0.0732 0.0620

0.0862 0.0911

0.1659 0.0910

0.0828 ** 0.0874

MoldovaDeal Subcarpatii de Sud Campia Dunarii de Jos

0.7074 0.2948 -0.1634

0.4852 a 0.3965 0.5522

-0.4012 -0.2435 -0.1253

0.4854 0.3786 0.4458

-0.0223 0.0999 0.0009 0.0787 0.0343 0.0985

0.1728 0.0787 -0.0209

0.0835 ** 0.0699 0.0997

-0.1506 -0.0796 -0.0134

0.0955 a 0.0758 0.0921

Oltenia de Sud Campia Romana Centrala SAI

-0.5915 -0.0193 0.2624

0.6067 0.5324 1.2440

-0.6619 0.4612 1.4836

0.5011 0.4473 1.0582

0.1519 0.1088 -0.0596 0.0996 -0.2265 0.2417

-0.0573 -0.0441 -0.0786

0.1103 0.0927 0.2065

-0.0946 0.1037 0.3051

0.1043 0.0882 0.1969 a

-0.2398 -0.1109

0.2087 0.5812

-0.2512 -0.0427

0.1872 0.5645

-0.0247 -0.0179

0.0365 0.0967

-0.0346 0.0003

0.0372 0.1071

0.1591 0.0429 734 374.7346

0.2724 0.0438

-0.5020 0.0406

0.2495 ** 0.0331

0.0749 0.0048

0.0475 a 0.0079

-0.1249 0.0052

0.0498 *** 0.0069

0.0920 0.1847 0.0019 0.0399

Agroregion Dummies 0.0935 0.1007 a

Number of Financial Outlets of: State-owned bankbranches Private-owned bank branches Credit cooperatives Moneylenders Number of observations Chi-squared df=

66

a/*/**/*** significant at the 85%, 90%, 95%, and 99% confidence intervals, respectively Source : Author's calculations.

0.0593 0.0402 a 0.0176 0.1206 0.0500 0.0528 -0.0100 0.0076


71

Table 19 Rural Enterprises: Supply of Loans (Ordered Probit Model) Regression Results Coeff. S.E.

Explanatory Variables Dependent Variable: 0=Totally constrained,1=Partiallyconstrained, 2=Unconstrained Constant -2.5648 1.8974 Manager of the Enterprise Log(age) 0.5800 0.2826 ** Education Index -0.0609 0.0362 * Economic Sector Industry Dummy -0.5697 0.3902 a Trade Dummy -0.3571 0.3583 Services Dummy -0.4935 0.4167 Legal Status and Ownership Agricultural Stock Corporation (1=yes) -0.3246 0.2678 Non-agricultural Stock Corporation (1=yes) -1.1422 0.4616 *** PrivateOwned Dummy 0.0828 0.2705 Characteristicsof FirmActivity Log ( years in business) Log (total assets in 1996) Log (total assets in 1996)*(AgriculturalSector Dummy) Fixed assets/total assetsin 1996 Bank deposits/total assetsin 1996 Log (turnover) Turnover/employees Associatemembers working in enterprise/employees Economic Conditions inthe Locality Log (population) Log (population densityper hectare) Agricultural employment ratio Log (Kms to nearest town) Agroregion Dummies Campia de Vest Moldova de Podis Moldova Deal

totally constrained

partially constrained

unconstrained

totally constrained

partially constrained

unconstrained

Regression Results Coeff. S.E. -2.7391 1.2164

3.7879

-0.2262

0.0759

0.1504

0.5142 0.2754 *

-0.2007

0.0662

0.1345

0.4981 0.2738

5.9606

0.0237

-0.0080

-0.0158

-0.0564 0.0355 a

0.0220

-0.0073

-0.0148

-0.0533 0.0344

0.1124 0.2643 0.0611

0.2222 0.1393 0.1925

-0.0745 -0.0467 -0.0645

-0.1477 -0.0926 -0.1280

-0.6637 0.3781 * -0.4495 0.3482 -0.5516 0.4075

0.2591 0.1755 0.2153

-0.0855 -0.0579 -0.0710

-0.1736 -0.1176 -0.1443

-0.6802 0.3696 -0.4484 0.3422 -0.5477 0.3975

-0.4002 0.2634 a -1.0884 0.4478 **

0.1953 0.0178

0.1266 0.4455

-0.0425 -0.1494

-0.0842 -0.2961

-0.0323

0.0108

0.0215

-0.0285 0.1286 0.2685 0.0674 ***

1.6254 4.7770

0.0111 -0.1047

-0.0037 0.0351

-0.0074 0.0696

-0.1545 -0.0582 0.6255 0.1656

3.4235 0.3808 0.0510 5.2447

0.0603 0.0227 -0.2440 -0.0646

-0.0202 -0.0076 0.0818 0.0217

-0.0401 -0.0151 0.1622 0.0429

0.0752 ** 0.2549 0.4585 0.0414 ***

Model I Marginal Effects (evaluated at mean values) P P P

Regression Results Coeff. S.E. -2.5929 1.8276

0.8580

0.1562 0.4249

-0.0515 -0.1402

-0.1047 -0.2847

-0.3831 0.2627 -1.0736 0.4312

-0.0233

0.0077

0.0156

0.0718 0.2603

-0.0528 0.1226 0.2745 0.0666 ***

0.0206 -0.1072

-0.0068 0.0353

-0.0138 0.0718

-0.0573 0.1223 0.2709 0.0648

-0.1649 -0.0405 0.6007 0.1650

0.0644 0.0158 -0.2345 -0.0644

-0.0212 -0.0052 0.0773 0.0213

-0.0431 -0.0106 0.1571 0.0432

-0.1676 -0.0611 0.5827 0.1653

0.0598 0.2622

0.0732 ** 0.2478 0.4307 0.0405 ***

0.0721 0.2453 0.4211 0.0402

-0.0006 0.0010

33.6736

0.0002

-0.0001

-0.0001

-0.0007 0.0009

0.0003

-0.0001

-0.0002

-0.0008 0.0008

0.0554 0.1807

0.3699

-0.0216

0.0072

0.0144

-0.0069 0.1738

0.0027

-0.0009

-0.0018

0.0030 0.1660

8.4102 -0.5006 0.4453 3.0885

0.0308 -0.0843 0.0111 -0.0393

-0.0103 0.0283 -0.0037 0.0132

-0.0205 0.0561 -0.0074 0.0261

-0.0488 0.0886 -0.0267 0.0839

0.0191 -0.0346 0.0104 -0.0328

-0.0063 0.0114 -0.0034 0.0108

-0.0128 0.0232 -0.0070 0.0220

0.1183 0.0848 0.0848

-0.0761 0.0706 0.0802

0.0255 -0.0237 -0.0269

0.0506 -0.0469 -0.0533

-0.0789 0.2162 -0.0285 0.1008

0.1735 0.1433 a 0.3594 0.0890

0.1952 0.2226 -0.1809 0.2786 -0.2057 0.2284

Subcarpatii deSud

-0.3617

0.2178

CampiaDunariide Jos

-0.0644 -0.0538

0.2531 0.2621

Oltenia de Sud

Model I Marginal Effects (evaluated at mean values) P P Mean X P

*

0.1755

0.1411

-0.0473

-0.0938

0.1065 0.1006

0.0251 0.0210

-0.0084 -0.0070

-0.0167 -0.0139

CampiaRomana Centrala

-0.1290

0.2204

0.1479

0.0503

-0.0169

-0.0334

SAI

-0.6228

0.5817

0.0197

0.2429

-0.0814

-0.1615

0.1661 0.1285 0.3035 0.0812

Number of Financial Outlets of: State-owned bank branches

0.1718

0.1079

Private-owned bank branches

0.0440

0.2142

Credit cooperatives

a

0.7002

-0.0670

0.0225

0.0446

0.1794

0.1030

0.0789

-0.0172

0.0058

0.0114

0.0113

0.2084

0.4221

-0.0214

0.0072

0.0142

0.0712

0.1225

1.1268

0.0723

*

-0.0700

0.0231

0.0469

0.1881

0.0947

-0.0044

0.0015

0.0030

0.0285

0.1987

-0.0278

0.0092

0.0186

0.0766

0.1183

1.1259

0.0722

0.0549

0.1252

ThresholdParameter(µ)

1.1406

0.0736

Number of observations

507.0000

507.0000

507.0000

Chi-squared df=

143.0559

134.6758

133.4069

31.0000

23.0000

23.0000

Threshold Parameter

a/*/**/*** significant at ht e 85%, 90%, 95%, and 99% confidence intervals, respectively Source : Author's Calculations.

***

***

72

Chapter Four:

Table 20 Rural Households: Investment Decision and Investment Outlays Model I Model II Explanatory Variables Coeff. S.D. Coeff. Dependent Variable: 1=Investment Opportunity 0=No Investment Opportunity Number of Observations: 2,005 Constant -0.9599 0.8728 -0.6545 Sociodemographic variables Age of household head -0.0144 0.0029*** -0.0135 Marital status (1=married) 0.1200 0.1325 0.0717 Gender (1=male) 0.1382 0.1402 0.1542 Nationality (1=Romanian) -0.2152 0.1200* -0.0808 Max education by HH member 0.0200 0.0238 0.0299 Family size 0.0957 0.0253*** 0.0845 Adults working in non- 0.0552 0.0541 0.0376 agriculture Number of pensioners in HH 0.1557 0.0604*** 0.0662 Characteristics of Entrepreneurial Activity Dwelling size (mts2) 0.0035 0.0020* 0.0014 Land holdings (Ha) 0.0460 0.0469 0.0521 Land holdings ( H a ) -0.3338 0.4388 -0.4117 Squared/100 Number of plots 0.0095 0.0123 0.0100 Number employees (ag and 0.0069 0.0119 0.0177 non-ag) Log (deposits) 0.0254 0.0090*** 0.0254 Share of agricultural sales in 0.8817 0.4542** 0.5278 monthly income Share of non-agricultural sales -0.3484 0.3572 -0.5319 in monthly income Share of salary income in 0.0917 0.1840 -0.0548 monthly income Economic Conditions in the Locality Log (population) 0.0054 0.0919 -0.0142 Log (population density per -0.0798 0.0698 0.0259 hectare) Owners of agricultural land 0.1362 0.2680 0.4205 /inhabitants (%) Log (Kms to nearest town) 0.0811 0.0501ª 0.0617 Agroregion Dummies Campia de Vest 0.1913 0.1214ª Moldova de Podis 0.9373 0.1335*** Moldova Deal 0.0481 0.1447 Subcarpatii de Sud 0.2493 0.1177** Campia Dunarii de Jos -0.9675 0.2106*** Oltenia de Sud 0.4574 0.1315*** Campia Romana Centrala -0.6244 0.1707*** SAI -0.2769 0.2467 Dependent Variable: Log (Investment) for those that invested Number of Observations: 653 Constant 7.0910 1.5786*** 7.4166 Sociodemographic variables Age of household head -0.0243 0.0053*** -0.0343 Marital status (1=married) 0.1261 0.2426 0.2247 Gender (1=male) 0.4529 0.2519* 0.3464 Nationality (1=Romanian) -0.0790 0.2122 -0.3791 Max education by HH member 0.1308 0.0410*** 0.1298 Family size 0.0794 0.0428* 0.0682 Adults working in non- 0.0847 0.0889 0.1192 agriculture Number of pensioners in HH -0.2383 0.1030** -0.1268

S.D.

0.8100 0.0028*** 0.1197 0.1265 0.1106 0.0224 0.0237*** 0.0516 0.0562 0.0018 0.0448 0.4284 0.0123 0.0110 a 0.0086*** 0.4687 0.3286 a 0.1719

0.0835 0.0634 0.2495* 0.0443

1.6547*** 0.0057*** 0.2491 0.2682 0.2225* 0.0444*** 0.0449a 0.0960 0.1115


73

Model I Model II Explanatory Variables Coeff. S.D. Coeff. S.D. Characteristics of Entrepreneurial Activity Dwelling size (mts2) 0.0067 0.0034** 0.0095 0.0036*** Land holdings (Ha) 0.0484 0.0898 -0.0164 0.0928 Land holdings ( H a ) 0.1532 0.9043 0.7905 0.8774 Squared/100 Number of plots 0.0401 0.0224* 0.0683 0.0249*** Number employees (ag and 0.0570 0.0202*** 0.0643 0.0222*** non-ag) Log (deposits) 0.0151 0.0154 0.0216 0.0166 Share of agricultural sales in 2.3411 0.8270*** 2.5940 0.8689*** monthly income Share of non-agricultural sales 1.5312 0.7800** 1.3419 0.8239* in monthly income Share of salary income in 0.5682 0.3175* 0.8442 0.3312*** monthly income Economic Conditions in the Locality Log (population) -0.2259 0.1623 -0.2546 0.1699a Log (population density per -0.1049 0.1412 -0.2159 0.1309* hectare) Owners of agricultural land -0.8807 0.4367** -1.0543 0.4644** /inhabitants (%) Log (Kms to nearest town) 0.0365 0.0908 -0.0325 0.0933 Agroregion Dummies Campia de Vest 0.1726 0.2065 Moldova de Podis -0.2896 0.2632 Moldova Deal 0.2175 0.2577 Subcarpatii de Sud -0.4615 0.2297** Campia Dunarii de Jos -0.5135 0.4709 Oltenia de Sud -0.8654 0.2716*** Campia Romana Centrala -0.4993 0.2945* SAI -0.1349 0.5060 _ 1.5478 0.0885*** 1.7636 0.1023*** Rho 0.8510 0.0363*** 0.8733 0.0296*** Log likelihood Function -2076.7 -2219.6 Chi-squared a/*/**/*** significant at the 85%, 90%, 95%, and 99% confidence intervals, respectively Source: Author’s calculations

Table 21 Rural Households: Effect of Removing Credit Constraints on Investment Decisions and Investment Opportunities Model I Decision to Invest Actual 27.1% Predicted 29.4% Log (investment), for investors Actual 7.172 Predicted 7.181 Effect of Removing Credit Constraints Additional households that would 2.32% invest Investment outlays would increase by: 9.63%

Model II 27.11% 29.27% 7.167 7.199 2.16% 11.53%

Source: Estimated with regression results of Table 20.

74

Chapter Four:

Table 22 Rural Households: Investment Decisions for Borrowing and Non-Borrowing Households Explanatory Variables Constant Sociodemographic Variables Age of householdhead Marital status (1=married) Gender (1=male) Nationality (1=Romanian) Max education by HH member Family size Adults working in non-agriculture Number of pensioners in HH Characteristics of Entrepreneurial Activity Dwelling size (mts 2) Land holdings (Ha) Land holdings (Ha) Squared/100 Number of plots Number employees (ag and non-ag) Log (deposits) Share of agricultural sales in monthly income Share of non-agricultural sales in monthly income Share of salary income in monthly income Economic Conditions in the Locality Log (population) Log (population density per hectare) Owners of agricultural land /inhabitants (%) Log (Kms to nearest town) Agroregion Dummies Campia de Vest Moldovade Podis MoldovaDeal Subcarpatii de Sud Campia Dunarii de Jos Oltenia de Sud Campia Romana Centrala SAI Number of observations Chi-squared df=

All Households Coeff. S.D. -0.4576 0.8002 -0.0102 0.1868 0.1417 -0.2182 0.0237 0.0653 0.0986 0.1281

0.0026 0.1101 0.1162 0.1115 0.0210 0.0219 0.0486 0.0551

0.0044 0.0772 -0.5109 0.0100 -0.0003 0.0307 -0.2191 0.8680 0.0468

0.0018 0.0425 0.3957 0.0117 0.0106 0.0084 0.3106 0.4491 0.1644

-0.0812 -0.0534 -0.1315 0.0444

0.0834 0.0616 0.2414 0.0445

0.1844 1.0208 0.0692 0.2256 -0.9186 0.5123 -0.6223 -0.1571 2409 372.44 29

0.1158 0.1259 0.1300 0.1075 0.1801 0.1239 0.1539 0.2445

Borrowing Households Non-Borrowing Households Mean Xs Coeff. S.D. Mean Xs Coeff. S.D. Mean Xs 0.7749 1.8067 -0.5387 0.9245 *** * ** *** ** ** *** *

*** **

a *** ** *** *** ***

2

0.1323 McFadden Pseudo-R Mean dependent variable 0.2711 a/*/**/*** significant at the 85%, 90%, 95%, and 99% confidence intervals, respectively Source : Author's calculations

58.2769 0.6870 0.7538 0.9045 4.0523 2.9319 0.4666 0.3117

-0.0189 0.2035 -0.2008 -0.2175 0.0966 0.0214 0.1265 0.1779

0.0062 *** 51.3203 0.2825 0.8083 0.3101 0.8519 0.2597 0.9194 0.0447 ** 4.8322 0.0458 3.5403 0.0936 0.8170 0.1370 0.2505

-0.0077 0.1616 0.2190 -0.2595 -0.0016 0.0788 0.0555 0.1140

0.0029 0.1232 0.1291 0.1254 0.0247 0.0259 0.0605 0.0616

*** 59.9144 0.6585 * 0.7308 ** 0.9010 3.8687 *** 2.7887 0.3841 * 0.3262

39.9705 1.8454 0.0747 3.3383 3.6787 2.7066 0.0457 0.0117 0.5760

0.0060 0.1476 -1.5012 0.0251 -0.0096 -0.0111 0.4166 0.3522 0.0652

0.0037 * 0.1169 1.2254 0.0249 0.0231 0.0203 1.0491 0.9790 0.4035

42.7495 1.4906 0.0567 3.0131 3.8105 2.4712 0.0241 0.0122 0.6365

0.0051 0.0756 -0.4693 0.0057 -0.0032 0.0419 -0.3277 1.0227 -0.0446

0.0021 0.0471 0.4316 0.0138 0.0123 0.0095 0.3369 0.5196 0.1851

** a

39.3164 1.9289 0.0789 3.4149 3.6477 *** 2.7620 0.0507 ** 0.0115 0.5618

8.3835 -0.4953 0.4256 2.7481

-0.1202 -0.2531 -1.1198 0.0546

0.1893 0.1302 ** 0.5645 ** 0.1034

8.4555 -0.3925 0.4166 2.7350

-0.0878 0.0076 0.0549 0.0426

0.0966 0.0730 0.2784 0.0506

8.3666 -0.5195 0.4278 2.7511

0.1038 0.0872 0.1038 0.2159 0.0706 0.0872 0.0872 0.0249

0.0442 1.1565 0.0838 0.2370 -0.7561 0.3402 -0.0126 1.3373 459 84.17 29

0.2593 0.2794 *** 0.2611 0.2230 0.3553 ** 0.3456 0.2951 0.5400 ***

0.1002 0.0980 0.1242 0.2810 0.0545 0.0436 0.0828 0.0196

0.2125 0.9816 0.0492 0.2247 -0.9918 0.5449 -1.0139 -0.6313 1950 316.06 29

0.1314 0.1443 0.1539 0.1257 0.2166 0.1369 0.2131 0.3279

0.1362

a *** * *** *** *** **

0.1046 0.0846 0.0990 0.2005 0.0744 0.0974 0.0882 0.0262

0.1469

Table 23 Decomposition of Investment Decisions between Borrowing and Non-Borrowing Rural Households Mean Shares Borrowing Rural Households (XBBB) Non-borrowing Rural Households (XNBBNB) Predicted Shares For non-borrowing Rural Households (XNBBB) Differences in Investment Decisions Due to X's Due to betas

Source: Author’s calculations

0.4009 0.2405

0.3141 0.1604 0.0868 0.0735

54% 46%


75

Table 24 Rural Enterprises: Investment Opportunities and Investment Levels Model I Model II Explanatory Variables Coeff. S.D. Coeff. S.D. Dependent Variable: 1=Investment Opportunity 0=No Investment Opportunity Number of Observations: 483 Constant 1.2645 2.4408 1.1495 2.3696 Manager of the Enterprise Log(age) -0.6714 0.3442** -0.6485 0.3285** Education Index 0.0397 0.0518 0.0454 0.0495 Economic Sector Industry Dummy 1.6195 0.5565*** 1.5171 0.5149*** Trade Dummy 1.1340 0.5284** 1.0896 0.4945** Services Dummy 0.9460 0.5722* 0.9532 0.5320* Legal Status and Ownership Agricultural Stock Corporation -0.3907 0.4084 -0.3402 0.3835 (1=yes) Private Owned Dummy 0.6679 0.3895* 0.7284 0.3570** Characteristics of Firm Activity Log ( years in business) -0.2847 0.2329 -0.3369 0.2122a Log (total assets in 1996) 0.1067 0.0915 0.1201 0.0859 Log (total assets i n 0.1837 0.1061* 0.1667 0.0963* 1996)*Agricultural Sector Dummy Log (Bank deposits), in 1996 0.1102 0.0660* 0.1073 0.0615* Log (turnover), in 1997 0.1757 0.0680** 0.1684 0.0634*** Fixed assets/employees -0.0001 0.0057 0.0001 0.0053 Turnover/employees -0.0002 0.0013 -0.0004 0.0010 Debt/total assets, in 1996 -0.1758 0.4467 -0.1323 0.4173 Associate members working in -0.4977 0.2504** -0.5025 0.2371** enterprise/employees Economic Conditions in the Locality Log (population) -0.1318 0.2080 -0.1493 0.1939 Log (population density per 0.3991 0.2061** 0.2511 0.1636a hectare) Agricultural employment ratio -0.6290 0.4855 Log (Kms to nearest town) 0.0360 0.1290 Agroregion Dummies Campia de Vest -0.0573 0.2747 Moldova de Podis -0.2883 0.3857 Moldova Deal -0.8505 0.4032** Subcarpatii de Sud -0.2433 0.2738 Campia Dunarii de Jos -0.1120 0.3207 Oltenia de Sud -0.2362 0.3227 Campia Romana Centrala -0.2896 0.2991 SAI -0.7695 0.4589* Dependent Variable: Log (Investment) for those that invested Number of Observations: 206 Constant 13.1255 4.0655*** Manager of the Enterprise Log(age) -1.2367 0.6033** Education Index -0.0410 0.0910 Economic Sector Industry Dummy 1.4994 1.0106a Trade Dummy 0.4419 0.9521 Services Dummy 0.9628 1.0414 Legal Status and Ownership Agricultural Stock Enterprise 0.3504 0.6660 (1=yes) Private Owned Dummy 0.3832 0.6618 Characteristics of Firm Activity

-0.7300 0.0280

0.3844* 0.1125

12.7442

3.6670***

-1.3006 -0.0478

0.6049** 0.0890

1.4635 0.4895 1.1742

0.9976a 0.9489 1.0348

0.3314

0.6394

0.4272

0.6597

76

Chapter Four:

Model I Model II Explanatory Variables Coeff. S.D. Coeff. S.D. Log ( years in business) -0.2587 0.3985 -0.2208 0.4185 Log (total assets in 1996) 0.3236 0.1374** 0.3340 0.1353*** Log (total assets i n 0.0637 0.1667 0.0706 0.1626 1996)*Agricultural Sector Dummy Log (Bank deposits), in 1996 0.2058 0.1289a 0.2169 0.1251* Log (turnover), in 1997 0.2312 0.1173** 0.2029 0.1294a Fixed assets/employees 0.0081 0.0084 0.0059 0.0079 Turnover/employees 0.0021 0.0018 0.0017 0.0018 Debt/total assets, in 1996 0.8837 0.8433 1.1095 0.8207 Associate members working in 0.3962 0.5557 0.3560 0.5567 enterprise/employees Economic Conditions in the Locality Log (population) -0.3690 0.3757 -0.2900 0.3394 Log (population density per 0.4614 0.3597 0.1432 0.2738 hectare) Agricultural employment ratio -0.7506 0.8811 -1.0327 0.7990 Log (Kms to nearest town) 0.2304 0.2251 0.1678 0.2058 Agroregion Dummies Campia de Vest 0.2771 0.4214 Moldova de Podis -1.3046 0.5906** Moldova Deal -0.7202 1.1352 Subcarpatii de Sud -0.6815 0.4108* Campia Dunarii de Jos -0.4094 0.5179 Oltenia de Sud -0.0137 0.6549 Campia Romana Centrala -0.0327 0.4859 SAI -0.5540 0.7686 _ 1.5299 0.2217*** 1.5198 0.2303*** Rho 0.6705 0.2496*** 0.5721 0.3420* Log likelihood Function -590.7674 a/*/**/*** significant at the 85%, 90%, 95%, and 99% confidence intervals, respectively Source: Author’s calculations.

Table 25 Rural Enterprises: Estimated Effect of Removing Credit Constraints on Investment Decisions and Investment Levels Model I Decision to Invest Actual 26.4% Predicted 37.4% Log (investment), for investors Actual 10.2329 Predicted 10.3343 Effect of Removing Credit Constraints Additional enterprises that 11.0% would invest Investment levels would 56.9% increase by:

Source: Author’s calculations.

Model II 26.4% 37.3% 10.2329 10.3296 10.9% 57.1%


77

Table 26 Rural Enterprises: Investment Decisions for Borrowing and Non-Borrowing Enterprises Explanatory Variables Dependent Variable: 0=No Invested 1=Invested Constant Manager of the Enterprise Log(age) Education Index Economic Sector Industry Dummy Trade Dummy Services Dummy Legal Status and Ownership Agricultural Stock Corporation (1=yes) Private Owned Dummy Characteristics of Firm Activity Log ( years in business) Log (total assets in 1996) Log (total assets in 1996)*Agricultural Sector Dummy Log (Bank deposits), in 1996 Log (turnover), in 1997 Fixed assets/employees Turnover/employees Debt/total assets, in 1996 Associate members working in enterprise/employees Economic Conditions in the Locality Log (population) Log (population density per hectare) Agricultural employment ratio Log (Kms to nearest town) Number of observations Chi-squared df=

All Enterprises Coeff. S.D.

Borrowing Enterprises Non-Borrowing Enterprises Mean X Coeff. S.D. Mean X Coeff. S.D. Mean X

-1.0896 1.6156

-0.4049 2.7354

-1.8055 2.1797

-0.1946 0.2580 0.0288 0.0359

3.7915 -0.4167 0.4774 5.6581 0.0980 0.0616 a

3.8114 -0.0339 0.3218 6.2295 0.0101 0.0469

3.7797 5.3170

1.4238 0.4089 *** 1.1011 0.3794 *** 1.0821 0.4289 ***

0.1152 0.3239 0.0730

1.7240 0.7371 ** 1.5660 0.6679 ** 1.9772 0.7982 ***

0.0993 0.2021 0.0377

1.8240 0.6221 *** 1.3412 0.5959 ** 1.2202 0.6420 *

0.1247 0.3967 0.0941

-0.1480 0.2673 0.8187 0.2708 ***

0.1575 0.8860

0.0369 0.3850 0.6462 0.3907 *

0.2363 -0.4193 0.4117 0.8151 1.2078 0.4573 ***

0.1104 0.9284

-0.1631 0.1490 1.5849 0.2717 0.2865 1.6941 -0.3542 0.1928 * 1.5197 0.0456 0.0623 4.1549 -0.0400 0.1077 5.6838 0.0156 0.0879 3.2420 0.1245 0.0731 * 2.7799 0.1073 0.1212 4.3266 0.2968 0.1298 ** 1.8563 0.1540 0.0468 *** 1.1030 0.1960 0.0652 *** 1.6152 0.1318 0.0741 * 0.7972 0.1941 0.0492 *** 4.8102 0.2017 0.0949 ** 6.1606 0.1469 0.0606 ** 4.0038 -0.0013 0.0017 9.3653 -0.0003 0.0023 16.8130 -0.0038 0.0073 4.9180 0.0000 0.0008 33.1162 0.0023 0.0017 41.3321 -0.0003 0.0010 28.2102 -0.3668 0.2695 0.1275 -0.6637 0.3566 * 0.2753 -1.6717 0.9202 * 0.0392 -0.4352 0.1679 *** 0.3676 -0.1283 0.2804 0.3217 -0.6312 0.2211 *** 0.3951 -0.1574 0.1371 8.3983 -0.1742 0.2291 8.4208 -0.1835 0.1851 8.3848 0.1930 0.1139 * -0.4950 -0.1580 0.1995 -0.5261 0.3760 0.1517 *** -0.4764 -0.8875 0.3028 *** 0.4227 -1.3696 0.4780 *** 0.4582 -0.7721 0.4311 * 0.4016 0.0629 0.0857 3.0749 -0.0859 0.1395 3.0804 0.1515 0.1170 3.0717 781.0000 292.0000 489.0000 200.7169 105.4657 107.1425 20.0000 20.0000 20.0000

2

McFadden Pseudo -R 0.2227 Mean dependent variable 0.2638 a/*/**/*** significant at the 85%, 90%, 95%, and 99% confidence intervals, respectively Note: The hypothesis of sample selection was tested and it was rejected Source : Author's calculations.

0.2741

0.2187

Table 27 Rural Enterprises: Decomposition of Investment Decisions between Borrowing and NonBorrowing Enterprises Mean Shares Borrowing Rural Enterprises (XUBU) Non-borrowing Rural Enterprises (XCBC) Predicted Shares For non-borrowing Rural Enterprises (XCBU) Differences in Investment Decisions Due to endowments Due to structural factors Source: Author’s calculations.

0.3699 0.2004 0.3265 0.1695 0.0433 0.1261

26% 74%

Chapter V: Policy Options and Possible World Bank Support A. GENERAL STRATEGY AND EMPHASIS The shortcomings of rural credit markets identified in this study are due largely to the country’s institutional underdevelopment and to massive interventions in the rural economy. These problems can be overcome if the Government formulates implementable strategies for dealing with them. In particular, the Government's objective should be to increase the availability in rural areas of viable, competitively priced, and untargeted credit (and deposits). This effort would increase overall access to rural financial markets and change the composition of credit market participation by including more agents currently not interested in borrowing and more agents to whom lenders would not currently serve. Deepening financial markets in rural areas and increasing their outreach requires stronger credit supply and demand. Removing the main causes of the current low intensity of both is a necessary condition to attain these objectives, therefore. While the problem must be attacked simultaneously from both sides (supply and demand), it should be noted that efforts to shift the supply curve of rural credit to the right would probably yield results faster than interventions in the demand side. In Romania, an upward shift of the demand curve for credit would require increased demand for rural investment. Significant increases in the demand for investment will occur − with a time lag − following the full implementation of appropriate policies (privatization of state enterprises, land titling) and developing of infrastructure (warehousing system) in rural areas. While these actions are beyond the strict scope of financial markets, they are key determinants of the demand for capital because they would enlarge the set of investment opportunities, lengthen planning horizons, and reduce uncertainty in performance of contractual obligations.66 The core of the short term strategy should, therefore, be to augment the supply of credit by increasing the returns to rural lending, adjusted by risk and transaction costs. The ingredients are reduction of the credit risk and of the transaction costs of lending. An increased supply of credit translates into a lower total cost of borrowing, including lower and less volatile effective rates of interest, transaction costs of borrowing, and collateral requirements. Better conditions on credit will be followed by an increase in the amount of credit demanded in the form of a movement along the existing demand curve (as opposed to a shift in the demand curve). 66

An important exogenous factor that may increase the demand for private investments and for rural credit is the Special Accession Program for Agriculture and Rural Development (SAPARD). This program will be financed by the European Union. SAPARD will allocate a significant portion of _ 150 million per year during the period 20002006 in grants to finance eligible private sector investments in rural areas. These grants will finance up to 50 percent of eligible investments. The remaining 50 percent of the value of these investments will need to be financed by beneficiaries either with their own resources or with debt. There may be, therefore, a “step” increase in the demand for rural credit from the private sector to finance the counterpart funding requirements to obtain SAPARD grants.

Policy Options and Possible World Bank Support

79

The objective of reducing credit constraints (especially for rural enterprises) cannot be attained by allocating larger amounts of subsidized credit. In the presence of credit rationing, interest subsidies do little to improve access to credit. Interest rate subsidies primarily reduce reborrower payments. However, rationing exists because banks may perceive insufficient credit worthiness of borrowers − not because borrowers’ cannot pay high market interest rates. In contrast, improving the regime for secured transactions primarily raises the lender’s return adjusted by risk. Hence, increasing the returns to lenders (adjusted by risk and transaction costs) is much more effective than subsidies in reallocating credit to a target group which is credit rationed. The challenge is to create the conditions, mechanisms, and institutions that will allow new resources to flow to the rural economy and to re-deploy existing rural assets to better uses. In practice, this challenge requires: (a) removing the unfair competition between the state and the private sector for (i) controlling productive assets, (ii) collecting savings from the public, and (iii) allocating credit; (b) improving contract enforcement; and (c) increasing competition in the supply of deposit services and funding to private rural clients of which the large majority are farmers and micro, small, and medium enterprises. There are not many policy instruments available to the Government. The following is a sketch of the most important and urgent options available to the Government to implement a program aimed at meeting the above challenge.67 B. GOVERNMENT CREDIT LINES It cannot be emphasized enough that lending government money in the face of existing high costs, risks, and distortions will only perpetuate the existing problems. If credit resources must be directed to the sector, then credit lines should be: (a) transitory with a well defined ending period; (b) well targeted; (c) appropriately priced to cover all risks and costs to avoid hoarding, rent seeking, and distortions in the allocation of resources; (d) well-designed in terms of recovery incentives for participating intermediaries to begin introducing the repayment discipline so desperately needed in the sector; and (e) allocated competitively among interested intermediaries and final borrowers. The basic elements of a transitional program of directed credit for agriculture consistent with these principles is outlined below. Its implementation would allow the Government to meet its policy objective of progressively lowering directed credit to the sector through mechanisms that minimize market distortions. The objective should be to phase out directed credit as rapidly as possible (say, over two to three years) by establishing a series of monitorable policy targets to insure that: (a) the key variables involved in agricultural directed credit steadily approach market levels; (b) there would be a smooth transition towards an ideal situation of sufficient market-based credit flows to

67

The benefits, for the development of financial markets, of conducive macroeconomic conditions in the form of low and predictable inflation rates and exchange rate stability are obvious. It should suffice to mention as an example that an improved fiscal balance would allow the Government not to crowd out the private sector in financial markets. Policy recommendations to achieve macro stability are, however, beyond the scope of this study. While recognizing that such stability is a necessary (albeit not sufficient) condition for the development of rural financial markets, this chapter focuses on possible government interventions that may be required to achieve other necessary conditions for improved performance of these markets.

80

Chapter Five:

agriculture; and (c) the distortions in the functioning of rural financial markets are minimized in the meanwhile. Under such a program, sensible targets would be established for the following variables (see Table 28): (a) the amount, in real terms, of subsidized directed credit allocated to the sector; (b) the cost of funds to participating banks; (c) the interest rates charged to final borrowers; (e) rebate payments to borrowers on the interest they would pay on loans; (f) rebate payments to participating banks on the amount of loans allocated to the sector; and (g) limits in the amount of credit granted to a single borrower with program resources. Ideally, the program would be implemented under a single Government Ordinance on Directed Credit. One single Ordinance for the entire period, as opposed to issuing several ordinances every year for the financing of different investment activities (e.g., harvesting, machinery), has the advantage of allowing participants in rural financial markets to better plan their credit needs and sources of finance. In contrast, the current situation of yearly Ordinances imposes uncertainty in the planning process of banks and potential rural borrowers.68

68

During the discussions of the preliminary results of this study and during the preparation of a World Bank financed rural finance project (see below), the Ministries of Agriculture and Finance have agreed in writing to prepare and submit to the Government a new Ordinance on Agricultural Credit. The objective of this Ordinance, which is an agreed condition for the World Bank Loan, is the dissolution of all subsidized credit programs and all Government funds financing rural and agricultural credit, including Ordinance 36/99 (Support for Farm Equipment Purchases) and Ordinance 165/98 (Ordinance for Providing Finance for Crop Planting).

Table 28 Romania: Summary Matrix for a Proposed Transitional Directed Credit Program for the Rural Sector (2000-2003) Policy variable and actions Amount of subsidized directed credit allocated to the sector. Total phase-out over a period of three years. Under the program, budgeted allocations to directed credit would decline in real terms by 33 percent per year with respect to the amount allocated in 2000 until subsidized directed credit would be totally phased out by 2003. Since the proposed reductions are in real terms the nominal amounts may actually increase depending on inflation.

2000 base amount

Quantitative Targets b 2001 2002 66% of 33% of base base amount amount

Cost of Funds to Participating Banks. Determined based on a market and observable rate of interest such as BUBOR or the cost of deposits for the banking system. The cost of funds for banks should reach market levels over the life of the program. To reduce uncertainty, possibilities to “lockin” rates at the time of disbursement or to set “caps” for the life of the loan should be analyzed. The illustrative targets provided next are based on average cost of deposits for the banking system. These possibilities would require comparatively short term repayments for loans of one year maximum. Interest rate charged to final borrower. Negotiated by participating banks and borrowers according to market conditions and borrower specific risks. This pricing policy implies that margins for participating banks are completely liberalized reducing, thereby, biases against smaller loans.

85% of cost of deposits



N.A.

N.A.

N.A.

N.A.

N.A.

Interest rebates to final borrowers. Incentives to final borrowers, if any, should be in the form of a rebate on the amount of interests paid. For example, upon repayment borrowers would be refunded a percentage of the amount of interest repaid. Rebates ought to decline over the implementation of the program. For example if the rebate for 2000 is 25 percent of interest paid the rebates for 2001 and 2002 would be, respectively, 16.5 and 8.25 percent.

initial rebate on interest paid

66% of initial rebate


N.A.

Cost rebates to banks. Cost rebates for banks could be paid as a percentage of the principal amount of the loan. The rebates ought to be proportional to the term of loans (e.g., a six month loan would accrue 1/2 the cost rebate of a year loan) and would be collected by participating banks when disbursing the loans. Banks would return the corresponding proportion of the rebate on any loans that are repaid prior to their maturity. The rebates ought to be declining over the implementation of the program as banks learn to lend to agriculture and provide repeated loans to borrowers with good repayment performance.

initial rebate on loans disbursed



N.A.

Limits in the amount of credit to a single borrower. Credit to the sector would be better targeted by establishing limits in the amount of credit granted to a single borrower. These limits would be declining over time by, say, 33 percent annually. To allow better planning for borrowers and banks, these limits may be denominated in US dollars. To illustrate, if the maximum amount of credit that could be granted to a single borrower in 2000 is, say, the equivalent in Lei of US$ 250,000; then the limits for 2001 and 2002 would be of the equivalent in Lei of US$ 165,000 and US$ 82,500, respectively. Among other positive features, the proposed limits would (a) reduce the ability and incentives to capture subsidies by hoarding credit at below market rates and (b) may induce banks to supplement budgeted credit allocations with their own resources to fulfill large credit applications from worthy clients.

initial maximum amount

66% of initial maximum amount

33% of initial maximum amount

N.A.

a

a

2003 no subsidized directed credit

This matrix is intended only as a basis of discussion between the Government of Romania and the World Bank. Clearly, this study could not provide specific and definite suggestions for quantitative targets at this time. The World Bank would respond positively to any request by the Government to assist in fine-tuning a similar program. The targets provided above are mostly intended to illustrate the design of a transitional program. Source: Author’s calculations. b

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C. IMPROVING THE LEGAL AND INSTITUTIONAL ENVIRONMENT FOR FINANCIAL TRANSACTIONS Movable Assets as Collateral There has been significant progress in passing legislation that may correct the shortcomings analyzed in Section B of Chapter III. This legislation will allow for greater and more effective use of movable assets as collateral, most notably, farm equipment, inventories, accounts receivable, and consumer goods. In particular, the Government passed Law No. 99 of 26 May 1999, published in Monitorul Oficial 236 of 27 May 1999m "Law Regarding Some Steps to Accelerate Economic Reform, TITLE VI. The Legal Status of the Security Interests in Personal Property." Preparation of the law and its regulations was supported by the World Bank, which is also supporting the creation of an electronic filing archive for security interests. The legal framework and the archive will stand among the most modern systems of securing transactions with movable assets in the world. The archive is presently under development and should begin operations during first quarter 2001. It is expected that this new framework will correct the deficiencies mentioned in Chapter III allowing, therefore, effective use of movable assets as collateral Two actions still need to be undertaken to fully reap the benefits of the new secured transactions system. First, implementation of a registry for security interests in movable goods should continue. Second, the mechanisms for expeditious recovery of collateral included in the legislation should be implemented without hindrances as assets pledged as security in the rural and agricultural sectors tend to have a comparatively short life span. These are important elements because, on the one hand, they will reduce credit risk for lenders, thus increasing their risk adjusted return on lending. On the other hand, they will also increase the capacity to carry debt of movable assets, which is tantamount to reducing the average ratio of collateral values to the amounts of loans. The quantity demanded of credit should increase as large collateral to loan amount ratios were found to be a significant element in reducing the demand for credit (see Chapter III). Warehouse Receipts The legal environment for warehouse receipts was also improved by Law 99 above. This law clarified and defined the rights, liabilities, and duties of each party to a warehouse receipt (e.g., producer, bank, warehouse) by making receipts freely transferable by delivery or endorsement. In addition, potential lenders will be able to use the new security interest electronic archive to determine if there are competing claims on a given stock of commodities. Two actions are still required to overcome the shortcomings of the warehousing framework described in Chapter IV. First, independent inspection and licensing of warehouses should be established. Second, a system of performance guarantees for warehouses should be developed, including establishing an indemnity fund and/or requiring mandatory insurance among licensed warehouses. Farmers and traders will be reluctant to store crops, and banks will


83

not be willing to accept receipts as collateral unless there is significant certainty on whether the goods exist in the quantities specified by the receipt and on whether the quality is the same as that noted on the receipt. More competition should be introduced into the storage industry, which remains dominated by the state. Breaking Romcereal into Comcereals and Cerealcoms simply divided a large state monopoly into a collusive organization of local monopolies (still controlled by the state) without any positive impact on their operations. Anecdotal evidence suggest that the excessive prices charged by these elevators often makes it unattractive for farmers and traders to store. It is also argued that the elevators often return different amounts and qualities of commodities than originally stored. Leasing and Investments on Depreciable Assets Priority should also be given to solving the remaining problems in the accounting and fiscal treatment of leasing and, more generally, of depreciable fixed assets (see Chapter IV). There have been important steps in establishing a western-style leasing system. Late in 1998, the Government passed the “Law on Amending Ordinance No. 51/1997.” This law is an important step in that it corrects problems in the previous regime. In particular, this new law: (a) provides clear definitions for financial and operational forms of leasing and clarifies the differing tax and accounting treatments accorded to these two arrangements;69 and (b) decreased the disadvantages for Romanian leasing companies vis a vis cross border lessors by unifying imports tariffs and customs guarantees. The Law on Amending Ordinance No. 51/1997 and Law 99 (see above) also provide enforcement certainty by: (a) assigning priority to lessors over leased assets in case of bankruptcy or reorganization of the lessee; and (b) by simplifying the procedures for repossessing leased assets upon default. Significant problems remain, however. As long as Romanian depreciation and accounting procedures do not embrace generally accepted principles in the treatment of depreciable fixed assets, leasing will not fully develop. Leasing is merely one of several instruments to finance investments in such assets. In other words, one should not expect leasing to grow because investment in the types of assets that are typically leased is taxed excessively. Specific recommendations follow. (a) Allow for shorter depreciation schedules on fixed assets. The current schedules are too long compared with the normal life of a leasing contract. When such long depreciation schedules are applied to equipment leases of, for example three years, the lessor would have to report artificially high net taxable profits because current period costs are not being matched with current period expenditures. This excessive taxation limits the ability of leasing companies to replace leased assets. In practice, the Government is taxing the difference between the historical value of assets and their current replacement cost (in nominal Lei). 69

This law introduced a clear distinction between the treatment of financial leasing and operational leasing with specific regulations on: (a) how leased goods must be dealt in the balance sheets; and (b) on who can (lessor or lessee) claim credit on depreciation and rental payments under each type of leasing.

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(b) Allow reasonable revaluation of assets over their historical book values to compensate for inflation. According to current Romanian accounting law, all assets must be booked at their historical value and their revaluation is not allowed. This rule implies that, in the presence of inflation, depreciation expenditures are underestimated causing, again, artificially high taxable profits and low equity ratios for firms. The net effect is equivalent to a tax on investment in capital goods. (c) Allow tax payers to deduct, from their taxable income, losses incurred when selling assets below their book value. These deductions are not permitted. Book value losses are unavoidable for Romanian leasing companies because of the very long depreciation schedules imposed by law and the comparatively short leasing periods (typically 3 to 4 years). In most cases, this combination causes the market value of fixed assets to be below their book value. Losses occur, therefore, when leased assets are sold. This practice gives leasing companies an unduly large tax burden. (d) Finish leveling the playing field between domestic and cross border lessors. The payment of value added tax (VAT) on equipment leased from a foreign leasing company is still deferred until the end of the lease period and is calculated on the residual value of the assets. These practices favor cross-border leasing and make it difficult to lease Romanianmade assets. In fact, the Romanian leasing association estimates that 99 percent of outstanding leasing contracts in the country are cross-border leasing. (e) Eliminate the customs duty incentives provided by the Law on Amending Ordinance 51/99 namely, total exemption of import tariffs, duties, and custom guarantees on assets to be leased. This regime has resulted mainly in an increase in the number of inter-company leasing arrangements as a means of avoiding customs duties, and not in the growth of real leasing transactions. D. IMPROVING THE LEGAL AND INSTITUTIONAL ENVIRONMENT FOR USING LAND AS COLLATERAL There are many economic benefits that result from well-defined property rights and secure title to real estate that go beyond financial markets. These benefits include: (a) greater incentives for the maintenance of and investment in property as well as the reduced probability of long-term environmental degradation as generally secure rights tend to be associated with more intensive farming and with a stronger commitment to preserve the integrity of natural resources; and (b) reallocation of land to those who have both the ability and the resources to use land most productively. There are also obvious advantages for rural finance; namely, the ability to use land as collateral which both enhances financial market development and promotes greater investment. In particular, titled land which has secure registration generally has a much higher market value. While this is not sufficient for a well functioning financial system, insecure property rights unambiguously reduce the development of financial markets, especially in rural areas where farm land represents an important portion of all assets.


85

Rights in fixed property have, as their foundation, an effective legal system. Without effectively functioning laws, records, and enforcement mechanisms, property rights will not be secure. This, in turn, will hamper the development of property markets. The features of a good system of fixed property are: (a) it secures ownership and property rights; (b) it develops and encourages a system which supports property transactions; and (c) it allows for the mortgaging of property. In turn, the following are the conditions necessary for a successful titling and registration system. These elements should be at the center of effective government action: (a) Acquire support from land and property owners who wish their titles to become more secure. Unless there is demand for land registration from this group, a successful program will be difficult to implement. The way property owners perceive the system of titling and registration is therefore critical. If, for example, titling and registration programs are viewed as an attempt to collect additional taxes, widespread support is unlikely. Similarly, if the process is perceived to be corrupt or unduly subject to political influence, it will not be widely used. (b) Invest in making property rights and property boundaries clearly recognizable and easily definable. Otherwise, the land registration system will become bogged down by disputes. Records on ownership need to be easily accessible and accurate. (c ) Hire qualified survey and registry staff and train these staff to ensure they are suitably competent. The public must have faith in the titling and registration process. (d) Improve the ability of the court system to enforce and protect property rights. This requires both the appropriate laws, strong institutions involved in titling and registration, and the appropriate enforcement mechanisms, as well as courts that are able to render judgment without undue delay. (e) Decrease the degree of regulation of land sales. While zoning regulations are probably unavoidable, the rules should be transparent and the procedures for applying for zoning changes should be simple and relatively inexpensive. Rules regarding uses to which agricultural land must be put or restrictions on the size or ownership of holdings have a negative effect on efficiency. (f) Reduce the statutory costs of property transactions, as well as those of private agents involved in the transfer and registration of title should be low so as to keep the prices for the buyer and the seller as close together as possible. If these margins are high, transactions that could enhance efficiency and improve the utilization of property will not take place. This applies not only to the first registration but to all subsequent transactions. International experience has shown that even if the first registration is inexpensive, if property transactions are costly, registries are not used, many transactions go unrecorded, and the registry information quickly becomes outdated so that the value of the initial efforts are severely reduced.

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Chapter Five:

E. RETAIL LENDING Development of private financial markets in rural Romania requires the ability of the financial sector to supply retail and micro-finance services profitably. This necessity results form the fact that by and large rural clients demand very small transactions (see Chapter II). Section B of Chapter III argued, however, that the supply of retail and micro-finance services will continue (at best) to be weak in the absence of Government policy intervention. While the irreversible trend for banks in economies with developed financial markets is to aggressively compete for the retail portion of the market, in Romania increased availability of retail credit in rural areas may take a long time to develop if left alone to the market. In fact, it is likely that the banking sector will reduce their retail network in rural areas after privatization. There may be a need, therefore, to induce private banks to increase their presence in the retail portion of the market. In the first instance, this presence would be required to provide safe deposit services to large portions of the population which have bank deposits (see Chapter II). These services should be provided mainly by regulated intermediaries. The vacuum that may be left by a retiring state banking sector introduces the risk of unregulated intermediaries increasing their share of the deposits of the population. As indicated in Chapter II, three state owned banks held 80 percent of the deposits of the rural population at the time of the survey. An appropriate distribution network will also be required to lend to small and medium businesses, including those in rural areas, and farmers. Small credit transactions are highly elastic with respect to transaction costs, which are reduced in the presence of a point of sale in the locality of residence of borrowers. The presence of a network of retail finance will be required to allow for the massive redeployment of resources expected to occur in the rural economy. Government support may be required to provide technical assistance to private banks to accelerate their understanding of the rural sector, of how to evaluate business plans from new private farms and rural businesses, of how to use and value rural assets that might be pledged as security, of how to dispose of such assets, and so forth. Financial and technical assistance should also be provided to non-profit organizations to support the provision of micro-credit to the poorest segments of the rural population (those which will not be reached by the banking sector). The Government could also assist in the development and introduction of technologies and institutional arrangements that could reduce the costs and risks of retail banking and micro-credit in the rural areas (e.g., character based lending, credit bureaus). These instruments are particularly important for small and medium enterprises. The idea is that the Government could fund experiments in developing sustainable technological packages for delivering retail and micro-credit in rural localities. The objective is to establish general guidelines for providing financial services to small, medium, and micro entrepreneurs by adapting to Romanian conditions the experience of successful rural financial in other countries. International experience attests that rural retail lending could be a profitable market niche for banks, and that micro-finance could be a sustainable activity to non-profit organizations, provided that they use appropriate methodologies. These methods require banks and NGOs to: (a) sell few and simple credit products; (b) have low branch fixed costs; (c) use local information


87

to screen and monitor borrowers; (d) implement conducive incentive schemes for branch managers or credit agents; and (e) deploy adequate internal control mechanisms.70 Government support for these activities is justified from a public policy point of view.71 The development of sustainable technologies for delivering financial services to retail and micro rural clients requires extensive local experimentation. The problem is that the investment in experimentation may be inadequate unless the government provides the necessary stimulus. Since no single lender can capture a significant portion of the social value of improved lending, the rational strategy is to wait for someone else to assume the risks and costs of experimentation and, in the case that the new technologies were successful, to copy them. It is also justifiable for the Government to invest in this experimentation because past government interventions in financial markets have been extremely costly. Any future mistakes are likely to also be expensive. Hence, limited support to private intermediaries that will avoid future government direct involvement may be a good policy. Micro-finance, on the other hand, has proven to be a cost effective and sometimes sustainable instrument to deal with the rural poor. There is credible empirical evidence that the necessary conditions exist in Romania for rural bank branches to operate profitably by allocating retail credit and to collecting deposits, and for NGOs to allocate micro-loans in a sustainable manner. The Technical Annex to this study analyzes the potential profitability of providing retail financial services in rural areas of Romania through the introduction or modification of specially designed rural bank branches and micro credit programs. The analysis was conducted on the basis of conservative assumptions and parameters derived from the survey and other official data. The annex suggests that such a branch or program could begin to generate operational surpluses early in its operations if it adopts best practices which ensure its ability to control the overall cost of operations, in particular loan losses and administrative overheads.72

70

These elements are common to some very successful rural financial intermediaries whose experiences are well documented in the professional literature (Chaves and Gonzalez, 1996).

71

The next section on possible World Bank support provides an outline of an operationally feasible way for the Government to support these efforts.

72

The study is based on the results of a computerized financial projection model used to project the potential profitability of a new rural bank branch and a new micro credit program in Romania. The model results are based on a set of conservative assumptions and parameters derived from official survey and other data on the lending and saving behavior of individuals, households, and enterprises in rural Romania, the macroeconomic environment, size and make-up of the market area to be covered by a new branch or program in terms of potential clients, interest rates at which a new branch or program will mobilize and lend funds, types and characteristics of financial products to be offered, loan portfolio performance, existing banking regulation, start-up costs, and operating expenses.

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Chapter Five:

F. REGULATORY CONCERNS REGARDING CHARTERED NON-BANK MUTUAL FINANCIAL INTERMEDIARIES The Problem The stability of the overall financial sector and the protection of the savings of the population are paramount ingredients in the development of financial markets in rural areas. The estimated 1,400 independent mutual financial intermediaries (MFIs) registered under Law 109/1996, most notably Banca Populara, and Credit Cooperatives should be a matter of concern in this regard. A majority of these intermediaries are domiciled in rural areas. The reasons for concern are that the Government may have assumed important contingent liabilities by chartering MFIs and that they may constitute a regulatory hazard because they can be used to profitably arbitrage on the general regulation of the banking sector. MFIs have large numbers of depositors and their operations take place outside the regulatory authority of the National Bank of Romania (NBR). The Government may be unable to credibly commit not to bail them out in case of financial difficulty. This implicit deposit insurance would only make incentive problems implicit in their governance rules (see below) all the worse and may contribute further to their instability. The failure of individual MFIs would endanger the deposits made by largely unsophisticated and poor rural households. The biggest risk posed by MFIs, however, is that they could be used to profitably arbitrage on the general regulation of banking sector. This opportunity arises because their activities are not supervised and because they have the ability to: (a) provide basically all credit and deposits services allowed to commercial banks; (b) lend to other MFIs; and (c) invest in the equity of other MFIs and commercial banks. These elements make the growth of a network of related MFIs with negligible capital possible. This growth may occur exclusively on the basis of deposits when members of the network use debt to finance equity investments in other members of the group (i.e., “cascading” or “pyramiding” of capital). The financial statements of any MFIs in the group would reflect “healthy” leverage ratios when analyzed individually. The consolidated system, however, could have negligible or no equity at all. MFIs have caused disruption in the financial markets of other countries for diverse reasons. Their failure has resulted in the loss of deposits and/or expensive bailouts by tax payers in numerous countries including the United States (Savings and Loans), Mexico (Uniones de Crédito), and France (Credit Agricole System). Credit Cooperatives have experienced recent problems in numerous Latin American countries such as Costa Rica, Colombia, Panama, and Argentina. Romanian credit cooperatives and Banca Populara have a governance structure stipulated in Law 109/1996 which makes their regulation more difficult than that of private banks. The governance structure includes the following principles: (a) ownership by depositors and borrowers; (b) one-man-one-vote with simple majority rules; and (c) open doors for admission and withdrawal of members. These rules may allow the individuals in control of these organizations to become residual claimants of their profits but not of their losses. This situation is known as borrower


89

domination.73 Based on a one-man-one-vote and simple majority rules, decisions such as interest rates, collateral on loans, enforcement of credit contracts are made by members who may have a clear conflict of interest by acting simultaneously as borrowers and owners. The international experience with these governance rules has been mixed even in countries with well-developed cooperative structures, legal and institutional frameworks, and bank supervision capacities. Credit cooperatives have been financially unstable, more susceptible than other intermediaries to (minor) changes in their environments, and with few exceptions unable to capitalize significant subsidies, special tax treatments, and regulatory forbearance that donors and governments have given them. In particular, they: (a) have been borrower dominated; (b) have been created with significant subsidies from donors and governments; (c) are normally undercapitalized by their owners; and (d) have been particularly difficult (more so than other intermediaries) to regulate and supervise. 74 Current Proposals May not Remedy the Problem Clearly, the elimination or management of the risks imposed by existing MFIs in Romania is not a simple task. The authorities have taken the initial important step of suspending the licensing of new MFIs. The challenge of what to do with the existing ones remains, however. Two options have been proposed in Romania, namely: (a) bringing the system under the supervision of the NBR; and (b) introducing self-regulation by requiring individual MFIs to join second-tier groups such as federations of credit cooperatives which would supervise their members. Neither option may be suitable, however. The first may strain the supervisory capacity of the NBR, as it would increase the number of intermediaries it currently supervises from 45 commercial banks to more than 1,400; in one single step. The second option has significant shortcomings, including: (a) the federations (the supervising entities) which would be owned and controlled by MFIs (the supervised entities) – the managers of a tightly-run federation may be replaced by a laxer management team; and (b) federations and MFIs would be private entities and thus, MFIs may choose to exercise their constitutional right of free association by either moving from tightly-run federations to lax federations or to no federation at all. The Government may not be able to condition the existence or functioning of a MFI on belonging to a federation.

73

Borrower domination occurs when members acquire control of a client-owned intermediary, such as a credit cooperative, with the purpose of seizing private benefits generated at the expense of the organizations financial health. Examples of such practices adopted by borrower dominated intermediaries are weak collection of loans and low interest rates.

74

There is a significant body of literature which documents this performance, including the following examples: (a) Black, H. and R. Dugger. (1981) “Credit Union Structure, Growth, and Regulatory Problems.” The Journal of Finance 2:529-538; (b) Bonus, H. and G. Schmidt. (1990). “The Cooperative Banking Group in the Federal Republic of Germany: Aspects of Institutional Change.” Journal of Institutional and Theoretical Economics 146:180-207; and (c) Porter, P. and Scully G. (1987). “Economic Efficiency in Cooperatives.” Journal of Law and Economics 30:489-512. The most notable exceptions to this general pattern of financial instability are the Cooperative Banking Group in Germany and the Credit Union financial intermediaries in the United States.

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A Third Option Seems to be Required The following sequence of actions may represent a viable option to ameliorate the risks involved in the operations of MFIs: (a) Maintain the status quo, leaving existing MFIs outside NBR’s regulatory authority and supervisory responsibility. (b) Pass legislation, possibly by amending Law 109/1996, so that: (a) MFIs are no longer allowed to use the word “bank” in their names (e.g., Banca Populare); (b) MFIs be obliged to register with the NBR with the (only) purpose of establishing a complete inventory of them; (c) The NBR has the authority to request some basic financial data on MFI performance, including external audits for MFIs above asset thresholds; (d) NBR has the authority to regulate the “act” of financial intermediation rather than specific financial intermediaries (e.g., bank charter only) allowing the NBR to take discretionary actions with respect to selected MFIs without acquiring the obligation of supervising all MFIs. (c ) Pass new, or amend existing, legislation that would allow for the creation of a totally new financial intermediary charter. This “small regional bank” (SRB) charter would be subject to a complete regulatory framework which would correct the governance problems detailed above.75 The new legislation would allow the NBR to define whether the proposed SRBs would be subject to the same prudential standards applicable to commercial banks or whether there should be specific standards for them. Prudential norms appropriate for commercial banks may not necessarily be appropriate for the proposed SRBs. Examples of the norms that ought to be specifically defined for these banks and which may need to be different from those applied to commercial banks include: (a) maximum levels of exposure to the risks of financial intermediation (e.g., interest rate and liquidity risks); (b) rules about their ability to make equity investments in other organizations; (c) capital adequacy ratios; (d) investments in non-financial activities; (e) risk weighted provisioning against loan losses, and (f) nature and legal character of their owners. The general principle suggested is that the prudential norms may have to impose different norms on different types of intermediaries if and only if required to reduce risks. There may be valid justifications for different norms to account for differences in: (a) the environment in which intermediaries operate; (b) the size and characteristics of the market niches they serve; and (c) their institutional design and governance structure.76 For example, SRBs would have lower minimum capital requirements to be licensed (consistent with the size of the markets they would serve), but they should also be subject to stricter capital adequacy ratios than those of normal commercial banks and should not be allowed to take foreign exchange risks or take equity positions in other entities. In general, the prudential norms for SRBs would be stricter than those applicable to commercial banks.

75

The positive experience of small regional banks in Indonesia (Badan Perkreditan Rakyat ) prior to the late 1990’s crisis encourages the possibility of passing a “small bank law.”

76

Institutional design refers to the property rights and rules of control over the organization's assets. For example, as mentioned above cooperatives are controlled by a one-man-one-vote rule, while commercial banks are controlled by a one-share-one-vote rule.


91

(d) The NBR would undertake immediate efforts to develop its capacity to enforce SRB compliance with the above prudential norms. These efforts should include establishing a well-staffed unit devoted to this purpose. The NBR would need to design indicators to measure risks, to monitor and analyze the impact that external events might have on the performance of SRBs, and to make sure that the data reported by SRBs are accurate. The surveillance of SRBs would have the following two basic components of banking supervision: (i) An early-warning system based on data reported by SRBs. This would be the off-site component of the supervisory structure. Its purpose would be to provide a frequent depiction of the financial health and risks of each one of the SBR supervised. This system would use standardized computer models to identify SRBs likely to experience financial distress.77 Off-site supervision would be used to set priorities regarding the more expensive on-site inspection and would entail specialized computer software to periodically process the returns submitted by the SRBs, a scoring method to rank them, and “industry” standards to assess their individual performance. (ii) On-site supervision necessary to undertake inspections that, because of their nature, cannot be performed by an off-site analysis (e.g., quality of internal control) and to verify that the data fed to the off-site surveillance system are correct. (e) Existing MFIs would be eligible to be licensed under the new regulations under a “fast track” procedure. This special procedure would be available for a limited period, say 12-18 months. During this period existing MFIs that would opt to comply with the new regulations and get licensed under the new framework would be provided technical assistance to meet the new regulatory standards, including the adoption of charts of accounts, management information systems, and reporting requirements. The NBR would give preference in licensing to MFIs willing to merge with others. The new regulations would include provisions to facilitate mergers and to insure that the resulting SRBs would become the legal successors to the previous MFIs. (f) Existing MFIs that refuse to migrate to the new charter and to comply with the new regulatory framework would remain unregulated informal financial intermediaries. The NBR could consider the possibility of making the public aware of the risks involved in maintaining deposits in such intermediaries by publicizing their status. The development of a system of SRBs with disparate minimum initial capital requirements should not cause regulatory apprehension in itself. These banks should be subject to sound 77

Most of these models are based on multivariate discriminatory analysis using a series of financial ratios as predictive variables. These methods, although sophisticated, are not particularly difficult to implement and, when properly applied, can be very efficient in predicting the failure of intermediaries. In effect, the specialized literature reports that these models are almost as effective in such predictions as the more expensive bank supervisor visits. For instance, the off-site supervision methods used by the United States regulatory agencies signaled financial instability in 96 percent of the 347 cases of bank failure occurred between January 1989 and August 1990. The early warning system used, denominated CAMEL (i.e., capital adequacy, asset quality, management, earnings, and liquidity), gives banks a composite grade from 1 (best) to 5 (worst).

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prudential norms such capital adequacy requirements in the form of minimum solvency or maximum leverage ratios. This practice represents sound regulation. In contrast, capital requirements in the form of an absolute minimum amount of capital needed to enter the industry are, conceptually, anti-competitive regulation. The justification for this latter type of regulation is the practical difficulty of supervising potentially large numbers of intermediaries with smallscale operations. Numerous such intermediaries already exist and actions to ameliorate the implied risk must be taken sooner rather than later. G. MARKET DEVELOPMENT, BALANCED RURAL DEVELOPMENT, AND PRIVATIZATION The empirical findings of the survey provide strong support to the claim that the following actions would contribute to increasing investment in rural areas: (a) integrating households into markets and allowing concentration of land holdings; (b) formulating balanced rural development policies (in contrast to focussing on agriculture only); (c) privatizing state enterprises; and (d) privatizing state banks. For instance, Chapter IV found that household investment opportunities are positively associated with the degree of connection to markets as proxied by the share of the value of agricultural sales in total household income and negatively associated with the age of the heads of households. In fact, during the survey period, 45 percent of farm households with substantial market involvement made investments, in contrast with only 24 percent of the farm households which consumed their production. In turn, market involvement requires eliminating the restrictions for exiting agriculture faced by the large numbers of elderly landowners who have small-scale operations and lack agriculture equipment. These farmers created by the land reform process will remain engaged in subsistence farming and will remain disconnected from markets. The results in Chapter IV indicate that the enterprises more likely to invest were, everything else the same, in sectors other than agriculture and were private in that the state had no participation in their ownership. These results are also consistent with those of Chapter III, which show that, everything else the same, the probability that an enterprise in the industry, trade, and service sectors had a demand for loans was respectively, 36, 32, and 30 percentage points higher than the probability of an agricultural enterprise reporting a demand for loans. Finally, private banks were more amicable to financing investments that their state-owned counterparts. During the survey period, private banks allocated 80 percent of their loans to borrowers who reported having made investments in the period in which they received the loan, while the equivalent share allocated by state banks was 55 percent. H. POLICY COORDINATION Rural finance in Romania is a complex multi-sector subject with important political implications. It is an issue with multiple influences on the economy ranging from macroeconomic stability to impact on rural poverty. A consistent set of policies towards rural financial markets is a vital concern, therefore. A steering committee should coordinate general policies and, maybe, guide the reform of specialized government institutions and programs. This


93

committee should consist of representatives from the government agencies involved, including the Ministry of Agriculture Food and Forestry, the Ministry of Public Finance, and the National Bank of Romania.

94

Figure 13 Romania by Agro-Region

Chapter Five:

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Financial markets, credit constraints, and investment in rural Romania, Volumes 23-499 issue 499

New Issues in Financial and Credit Markets

Finance Investment - The Econometrics of Financial Markets

Financial Institutions and Markets: Current Issues in Financial Markets

Beyond Microfinance: Building Inclusive Rural Financial Markets in Central Asia

Finance: Capital Markets, Financial Management, and Investment Management

Applied C' in financial markets

Financial markets in continuous time

Financial crises in emerging markets

Financial crises in emerging markets

Financial Policies in Emerging Markets

Quantitative analysis in financial markets

Applied C# in financial markets

European Financial Markets and Institutions

Information Efficiency in Financial and Betting Markets

Financial Markets and Corporate Strategy

Economists and the financial markets

Capital Markets and Financial Intermediation

Financial markets and corporate strategy

Economists and the Financial Markets

Argiculture Investment Sourcebook: Agriculture and Rural Development

Oecd Investment Policy Reviews Romania (Oecd Investment Policy Reviews)

Asian Financial Markets

Mathematics of Financial Markets

Mathematics of financial markets

FORECASTING FINANCIAL MARKETS

Japanese Financial Markets

Statistics of Financial Markets

Japanese Financial Markets

Mathematics of Financial Markets

Economics for financial markets

Financial markets, credit constraints, and investment in rural Romania, Volumes 23-499 issue 499

New Issues in Financial and Credit Markets

Finance Investment - The Econometrics of Financial Markets

Financial Institutions and Markets: Current Issues in Financial Markets

Beyond Microfinance: Building Inclusive Rural Financial Markets in Central Asia

Finance: Capital Markets, Financial Management, and Investment Management

Applied C' in financial markets

Financial markets in continuous time

Financial crises in emerging markets

Financial crises in emerging markets

Financial Policies in Emerging Markets

Quantitative analysis in financial markets

Applied C# in financial markets

European Financial Markets and Institutions

Information Efficiency in Financial and Betting Markets

Financial Markets and Corporate Strategy

Economists and the financial markets

Capital Markets and Financial Intermediation

Financial markets and corporate strategy

Economists and the Financial Markets

Argiculture Investment Sourcebook: Agriculture and Rural Development

Oecd Investment Policy Reviews Romania (Oecd Investment Policy Reviews)

Asian Financial Markets

Mathematics of Financial Markets

Mathematics of financial markets

FORECASTING FINANCIAL MARKETS

Japanese Financial Markets

Statistics of Financial Markets

Japanese Financial Markets

Mathematics of Financial Markets

Economics for financial markets

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