wpS 3¶9 POLICY RESEARCH WORKING PAPER 2996 Bank Competition, Financing Obstacles, and Access to Credit Thorsten Beck Aslh Demirgiiu-Kunt Vojislav Maksimovic The World Bank Development Research Group Finance March 2003 | POLICY RESEARCH WORKING PAPER 2996 Abstract Theory makes ambiguous predictions about the effects of of bank concentration and financing obstacles is bank concentration on access to external finance. Using a dampened in countries with well developed institutions, unique data base for 74 countries of financing obstacles higher levels of economic and financial development, and financing patterns for firms of small, medium, and and a larger share of foreign-owned banks. The effect is large size, Beck, DemirgUc-Kunt, and Maksimovic assess exacerbated by more restrictions on banks' activities, the effects of banking market structure on financing more government interference in the banking sector, and obstacles and the access of firms to bank finance. The a larger share of government-owned banks. Finally, it is authors find that bank concentration increases financing possible to alleviate the negative impact of bank obstacles and decreases the likelihood of receiving bank concentration on access to finance by reducing activity finance, with the impact decreasing in size. The relation restrictions. This paper-a product of Finance, Development Research Group-is part of a larger effort in the group to understand the effects of bank competition. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Kari Labrie, room MC3-456, telephone 202-473-1001, fax 202-522-1155, email address klabrie@worldbank.org. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at tbeck@worldbank.org or ademirguckunt@worldbank.org. March 2003. (50 pages) The Policy Research Working Paper Senes disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An obhectve of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findnzgs, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent Produced by the Research Advisory Staff BANK COMPETITION, FINANCING OBSTACLES AND ACCESS TO CREDIT Thorsten Beck, Asli Demirgfi,-Kunt and Vojislav Maksimovic Keywords: Financial Development; Financing Obstacles; Small and Medium Enterprises; Bank Concentration JEL Classification: G30, G10, 016, K40 Beck and Demirgiiu-Kunt: World Bank; Maksimovic: Robert H. Smith School of Business at the University of Maryland. We would like to thank Arturo Galindo and Margaret Miller for sharing their data on credit registries with us, and Patrick Honohan and participants at the Fedesarrollo seminar in Cartagena for useful comments. 1. Introduction While the recent empirical literature provides empirical evidence on the positive role of the banking sector in enhancing economic growth through a more efficient resource allocation, less emphasis has been put on the effect of the banking market structure.' Theory makes conflicting predictions about the relation between bank market structure and the access to and cost of credit. While general economic theory points to inefficiencies of market power, resulting in less loans supplied at a higher interest rate, information asymmetries and agency problems might result in a positive or nonlinear relation between the market power of intermediaries and the amount of loans supplied to opaque borrowers, in a dynamic setting. Similarly, empirical studies have derived conflicting results, showing a positive or a negative relation between competition in banking and the access to credit, its costs and economic growth. Most of these studies, however, focus on a specific country, mostly the U.S. This paper explores the impact of bank competition on firms' financing obstacles and access to credit for a cross-section of 74 developed and developing countries. Specifically, we use survey data on the financing obstacles perceived by finrns and their financing patterns and relate these data to the competitive environment in the country's banking market. We use both the market share of the largest three banks and regulatory policies that influence the competitive framework in which banks operate, such as share of bank license applications rejected and restrictions on banks' activities. We control for l For cross-country studies on finance and growth, see Beck, Levine, and Loayza (2000), Rousseau and Wachtel (2001) and Wurgler (2000). Rajan and Zingales (1998) show that industries that depend more on external finance grow faster in economies with better developed financial sectors. Demirguc-Kunt and Maksimnovic (1998) show that countries with better developed banking and stock markets have a higher share of firms that grow beyond the rate predicted by their cash flow. Beck, Demirguc-Kunt and Maksimovic (2002) show that firms with higher financing obstacles grow more slowly, a relation that is dampened by better developed banking systems. the ownership structure, and the institutional environment. We assess the impact of the market structure on firms of different sizes, while at the same time controlling for a large number of other firm characteristics. Our results indicate that in more concentrated banking markets firms of all sizes face higher financing obstacles and are less likely to receive bank financing. This effect decreases as we move from small to medium and large firms, and holds when we control for a large array of firm and country characteristics, the institutional and regulatory framework of the country, and the ownership structure of the banking system. We find that the effect of bank concentration on fins depends on the country's institutional and regulatory framework and on who owns the banks. The relation of bank concentration and financing constraints turns insignificant in countries with well developed institutions, high levels of economic and financial development and a high share of foreign banks. Public bank ownership and a high degree of govemrnment interference in the banking system, on the other hand, exacerbate the impact of bank concentration on financing constraints. The interaction between bank concentration and restrictions on banks' activities also shows that with very few activity restrictions bank concentration may actually reduce financial obstacles and increase access to bank finance. Our results provide evidence for theories that focus on the negative effects of bank market power on access to credit, especially for developing countries. For the most part, the results are not consistent with theories that predict a positive impact of bank concentration on alleviating financing obstacles for small firms and allowing them access to credit. Our findings underline the importance of tking into account the institutional 2 and regulatory framework when assessing the impact of bank concentration on firm's financing obstacles, thus broadening the focus to the competitive and regulatory environment in which banks operate. They also stress the importance of regulations, institutions, and ownership structure for policy makers who are interested in alleviating financing obstacles. While the concentration of the banking system cannot be changed directly through policies and might be more related to historic determinants than policies, policy makers can influence the ownership structure and regulatory framework of the banking system. For example, removing activity restrictions in a concentrated banking system alleviates the negative impact of bank concentration on access to finance. This paper makes several contributions to the literature. First, while most empirical papers assessing the effect of bank concentration focus on a specific country, mostly the U.S., this paper uses cross-country analysis, including developed, developing and transition economies. Given the specific regulatory and institutional development of the U.S. a cross-country approach is important for drawing conclusions for policy makers in developing countries. We construct country-level measures of bank concentration from Bankscope and test for the robustness using data from Barth, Caprio, and Levine (2001). Second, to our knowledge this is the first paper using firm-level data to evaluate the effect of market structure on access to credit and firms' financing obstacles across a broad cross-section of both developed and developing countries and across firms of different sizes.2 Large parts of the theoretical literature on bank concentration has 2 While Cetorelli and Gambera (2001) use industry-level to assess the effect of bank concentration on industry growth, they are not able to differentiate between firms of different sizes. As discussed below, Clarke, Cull and Martinez-Peria (2001) include concentration in their firm-level analysis, but focus on the effects of foreign bank entry. 3 focused on small and young firms, so that being able to differentiate firms by size is important in testing these theories. We use the World Business Environment Survey (WBES), a major cross-sectional firm level survey conducted in 80 developed and developing countries, which includes the assessment of growth obstacles as perceived by the firms of different sizes, financing patterns of new investment, and other firm-specific information. The detailed information provided about the firms and the inclusion of small and medium-size firms makes this database unique. Third, unlike previous studies we can exploit cross-country variance not only in bank concentration, but also in the regulatory environment and the ownership structure of the banking sector. We are thus able to take a broader perspective on the competitive environment of the banking market by including measures of the share of bank license applications rejected, restrictions on bank's activities and the ownership structure. We use indicators of regulatory policies and ownership structure from Barth, Caprio, and Levine (2001). This paper is related to three other recent papers. Cetorelli and Gambera (2001) show that industries that depend more on external finance grow relatively faster in more concentrated banking sectors, while the overall effect of bank concentration on growth is negative. However, they base their analysis on industry-level data rather than individual firms. While they can exploit the variance across industries in term of dependence on external finance, they cannot exploit variance in the size of firms as in this paper. Beck, Demirguc-Kunt, and Maksimovic (2002) explore the effects of financing and legal obstacles as well as corruption on firm growth, using the WBES database. They find that firms that report higher obstacles grow more slowly. This effect is stronger for small 4 firms, but is dampened in countries with higher levels of financial and institutional development. Here we focus on financing obstacles, as opposed to other obstacles to growth and explore whether the structure of the banking market affects financing obstacles and access to credit. Finally, our paper is closely related to a recent paper using similar data by Clarke, Cull and Martinez Peria (2001) that assesses the impact of foreign bank ownership on financing obstacles and the share of investment financed with bank finance. They find that a larger foreign bank presence decreases financing obstacles and increases the share of investment financed with bank finance, results that are robust to controlling for bank concentration and regulatory entry restrictions. Furthermore, they also present results that show that concentration has a negative impact on access to bank loans. However, because their study focuses on the impact of foreign penetration on access to credit they do not explore whether concentration impacts large and small firms differently, nor whether the impact is different in countries at different levels of institutional development. The remainder of the paper is organized as follows. Section 2 discusses the motivation and theoretical underpinnings of our empirical analysis. Section 3 presents the data and section 4 describes the econometric methodology. Section 5 discusses the results and section 6 concludes. 2. Motivation Theory makes contradictory predictions about the effect of bank concentration on the supply and cost of loans. On the one side, standard economic theory predicts that market power results in a lower supply at a higher cost, thus reducing firrn growth (we 5 refer to this prediction as the structure-performance hypothesis). On the other side, taking into account informational asymmetries and agency costs leads to theories that predict a positive or nonlinear relation between market power and access to loans for opaque borrowers in a dynamic setting. We refer to this set of theories as the information- based hypothesis. Further, other characteristics of the banking sector, such as the ownership structure and legal and informational environment might influence the relation between market concentration and supply and costs of loans. This section will discuss the different theories and the existing empirical literature.3 Standard economic theory suggests that any deviation from perfect competition results in less access by borrowers to loans at a higher cost (structure-performance hypothesis). Using an endogenous growth model, Pagano (1993) interprets the absorption of resources, resulting in a savings-investment ratio of less than one, and thus the spread between lending and deposit rates as reflecting "the X-inefficiency of the intermediaries and their market power." Guzman (2000) shows that a banking monopoly is more likely to result in credit rationing than a competitive banking market and leads to a lower capital accumulation rate. Informational asymmetries between lender and borrower, resulting in adverse selection, moral hazard and hold-up problems, however, may change the relation between market structure and access to loans from a negative to a positive or nonlinear one, as shown in several theoretical contributions. Petersen and Rajan (1995) show that banks with market power have more incentives to establish long-term relationships with young borrowers, since they can share in future surpluses. Similarly, Marquez (2000) shows that 3 See also Cetorelli (2001) for an overview over the empirical and theoretical literature on bank concentration. 6 borrower-specific information becomes more disperse in more competitive banking markets, resulting in less efficient borrower screening and most likely in higher interest rates. Ding (2000), on the other hand, shows that the effect of competition on access to loans depends on the source and level of competition. He shows that there is an inverted U-shaped relation between the amount of relationship lending and the number of banks, with an intermediate number of banks able to sustain the maximum amount of relationship lending. Similarly, Cetorelli and Peretto (2000) show that there are offsetting effects of bank concentration. While bank concentration reduces the total amount of loanable funds, it increases the incentives to screen borrowers and thus the efficiency of lending. The optimal banking market structure is thus an oligopoly rather than a monopoly or perfect competition. However, all these models assume a high degree of enforcement of contracts and of the capacity of banks to screen potential borrowers and do not model differences in the legal and institutional environments in which banks operate. These assumptions are theoretically important and empirically relevant. The positive relation between market power and lending to small and young borrowers might only hold if lenders are able to recover their collateral in case of failure and if they are able to screen the borrowers before-hand. Recent empirical literature has established a relation between availability and cost of loans and the legal and informational environment in which lenders and borrowers operate.4 These findings suggest that institutions might affect the relation between market structure and access to loans. 4Beck and Levine (2002), Demirguc-Kunt and Maksimovic (1998) and Rajan and Zingales (1998) show that legal institutions influence the availability of financing to industries and the creation of new establishments. Claessens and Laeven (2003) show that in countries with strong investor protection laws, firms with less collateral have an easier time getting extemal finance than similar finns in countries with 7 The regulatory structure of the banking system might have important implications for the relation between market concentration and access to finance. High regulatory entry barriers might reduce the contestability and thus competitiveness of the banking system, independent of the actual market structure. Regulatory restrictions and government interference in the intermediation process, on the other hand, do not have a- priori clear relation with the competitiveness of the banking system and borrowers' access to finance. These restrictions might decrease the competitiveness and efficiency in the banking system and impede banks from using their informational advantages. Restricting banks in their activities, however, might also increase their competition in the area they are limited to. Finally, the effect of concentration on access to finance might depend on the regulatory restrictions bank face and vice versa. The ownership structure of banks might also influence the relation between market power and access to and costs of external financing. Domestically owned banks might have more information and better enforcement mechanisms than foreign owned banks, and so might be more willing to lend to opaque borrowers.5 Government-owned banks are mostly non-profit-maximizing and often have the explicit mandate to lend to certain groups of borrowers.6 The relation between bank concentration and access to loans might therefore differ across different ownership structures. Most empirical studies of the effect of bank concentration on access to external finance and firm growth have focused on individual countries, and mostly the U.S. more poorly functioning legal institutions. Pagano and Jappelli (1999) show empirically the importance of information sharing between intermediaries for financial development. 5 There is mixed evidence on the effects of foreign bank entry on small borrowers' access to finance. Compare the survey by Clarke et al. (2003) and the literature quoted therein. 6 La Porta, Lopez-de-Silanes and Shleifer (2001), however, show that bank lending is more concentrated in banking systems that are dominated by government-owned banks. 8 Hannan (1991) finds strong evidence that concentration is associated with higher interest rates across U.S. banking markets, thus providing evidence for the structure-performance hypothesis. Similarly, Black and Strahan (2002) find evidence across U.S. states that higher concentration results in less new firm formation, especially in states and periods with regulated banking markets. Petersen and Rajan (1995), on the other hand, find that small firms are more likely to receive financing at a lower cost and are financially less constrained in more concentrated local banking markets in the U.S. Bergstresser (2001) finds that in the U.S. consumers are financially less constrained in more concentrated banking markets. DeYoung, Goldberg, and White (1999) find for a sample of small and young banks across local U.S. banking markets that concentration affects small business lending positively in urban markets and negatively in rural markets. Jackson and Thomas (1995) find a positive effect of bank concentration across U.S. states on the employment growth rate of new firms in manufacturing industries, and a negative effect on the employment growth rate of mature firms. Using data for Italian provinces, Bonaccorsi di Patti and Dell'Ariccia (2001) find that bank concentration has a non-linear relation with firm growth, increases in concentration being associated with higher firm growth rates at lower levels of concentration and lower firm growth rates at higher levels of concentration. Further, the range of a positive relation between concentration and firm growth is larger for industries with a higher degree of opaqueness. Bonaccorsi di Patti and Gobbi (2001) find that concentration has a positive effect on the credit volume to small and medium size Italian firms, and a negative impact on large firms. Cetorelli and Gambera (2001) use industry-level data for 41 countries to explore the effect of bank concentration on growth. They show that while bank concentration 9 imposes a deadweight loss on the overall economy by depressing the average industry growth rate, it fosters the growth of industries whose younger firms depend heavily on external finance. However, this positive effect is off-set in banking systems that are heavily dominated by government-owned banks. Further, Cetorelli and Gambera show that the positive effect of bank concentration on industries that are heavily dependent on external finance works through an increase in the number of firms rather than an increase in the average size thus rejecting the hypothesis that bank concentration leads to industrial concentration. Using a similar model, Cetorelli (2001), however, shows that financially dependent industries are more concentrated in countries with more concentrated banking systems. Overall, both theoretical and empirical contributions yield contradictory conclusions. The structure-performance hypothesis predicts a negative relation between bank concentration and access to credit, while the information-based hypothesis predicts a positive or non-linear relation. Further, the relation might vary for firms of different sizes and across different institutional environments and ownership structures of the banking system. Using a panel data set of both developed and developing countries and of firms of different sizes, we will therefore test: o Is bank concentration positively or negatively related to financing obstacles and the access to credit? o Does the relation between concentration and financing obstacles and the access to credit vary across firms of different sizes? 10 * Does the relation between concentration and financing obstacles and the access to credit vary across different regulatory regimes, ownership structures and institutional environments? 3. Data and Summary Statistics This section describes the different data sources and the variables we will be using in the empirical analysis. Our empirical analysis uses data from three main sources: the World Business Environment Survey (WBES) for firm-level data, Bankscope for our main concentration indicator, and Barth, Caprio and Levine (2001) for country-level data on bank ownership structure and regulatory measures. Table 1 presents the country-level variables for the 74 developed and developing countries in our sample. Descriptive statistics and correlations are in Table 2. The WBES firm-level data consist of firm survey responses of over 10,000 firms in 80 countries, both developed and developing. We have information on firm size, government ownership, foreign ownership, and whether the firm is an exporter. The survey has a large number of questions on the business environment in which firms operate including assessment of growth obstacles firms face. The database also includes information on firm sales, industry, growth, financing patterns, and number of competitors. We use survey responses on to what extent entrepreneurs perceive finance as an obstacle to growth. To explore the link between bank market structure and the financing obstacles we use the survey question: "How problematic is financing for the operation and growth of your business?" Answers vary between 1 (no obstacle), 2 (minor 11 obstacle), 3 (moderate obstacle), and 4 (major obstacle). Table 1 shows that perceived financing obstacles do not only vary across firms within a country, but also significantly across countries. Portuguese firms rate financing obstacles as less than minor (1.73), while firms in Haiti rate financing obstacles as more than moderate (3.48). Overall, 38% of all firms in the sample report financing as major obstacle, 27% as moderate obstacle, 17% as minor and 18% as no obstacle. Apart from this General Financing Obstacle, we also use indicators of more specific financing obstacles, such as high interest rates, the need for special connections, access to long-term loans, the lack of financial/credit informnation, collateral requirements, bank bureaucracy and corruption of bank officials. Answers also vary between one and four and the assessments of specific financing obstacles are highly correlated with the General Financing Obstacle (Table 2 Panel B). We also explore the relation between banking market structure and the actual access to bank finance by firms. WBES has information on financing patterns, i.e. the share of investment that is financed internally, by equity, by trade credit, by bank finance etc. Using these data we construct a dummy variable Bank Finance that takes the value one if firms obtain bank financing from banks and zero if they do not. 39% of all firns in our sample receive bank finance. This share, however, varies significantly across countries, from 6% in Armenia to 88% in Trinidad and Tobago. We control for several firm attributes such as ownership. Government takes on the value one if the firm is owned by the government, and Foreign takes on the value one if the firm is foreign owned. Our sample includes 12% government owned firms and 19% foreign firns. We include dummy variables for exporting firms, the manufacturing and 12 service sector, as well as the log of the number of competitors. 37% of the firms in our sample are in manufacturing and 45% in service, and on average they face 2.3 competitors. Finally, we include the log of sales in USD as indicator of size, which ranges from -2.12 to 25.3, with an average of 9.9. The correlation analysis in Table 2 Panel B indicates that government-owned firms, domestically owned firms, non-exporting firms, smaller firms (as measured by sales), and firms with more competitors face higher financing obstacles. Privately owned, foreign, exporting, and larger firms, as well as firms with few competitors are more likely to receive bank financing. Interestingly, the correlation between the General Financing Obstacle and Bank Finance is insignificant, although Bank Finance is significantly correlated with some of the individual financing obstacles. We use bank-level data from the BankScope database to calculate the concentration ratio. The BankScope database covers at least 90% of the banking sector in most countries. We use data on commercial, savings, and cooperative banks as well as non-bank credit institutions to calculate Bank Concentration as the share of the assets of the largest three banks in total banking sector assets. We use the average for the concentration measures for 1995-99. This concentration measure has a wide variation, from 18% for the U.S. to 100% for Belize, as Figure I shows. Firms of all sizes report higher financing obstacles and face a lower probability of access to bank finance in more concentrated banking systems, as shown by the correlations in Table [I and illustrated by Figures II and III. For these two figures we split countries into two groups, with concentration ratios below and above the median of 61%. As can be seen, firms of all sizes report higher financing obstacles in countries above the 13 median concentration ratio and face a lower probability of receiving bank finance. Surprisingly, not all individual financing obstacles are positively correlated with bank concentration (Table II Panel B). Firms in more concentrated banking systems face less obstacles due to the need for special connections, collateral requirements and bank bureaucracy. To test the robustness of our results, we use the deposit share of the five largest banks in total banking system deposits, from Barth, Caprio, and Levine (2001). Unlike the BankScope measure, this indicator is based on deposits, and on a survey of Central Banks and regulatory and supervisory authorities. While the survey measure does not suffer from problems of coverage as the BankScope measure, it might be subject to measurement error, due to different definitions across countries. This survey was undertaken in 1999, so that this alternative concentration measure is approximately for the same time period as our principal measure. The correlation coefficient between the two concentration measures is 0.76, significant at the 1%-level. Bank concentration, as measured by the market share of the largest banks, captures only one dimension of the competitiveness of the banking system. Restrictions on banks' activities and the contestability of the banking market constitute other dimensions. We therefore control for these aspects, as well as interact them with our concentration measure. Specifically, we use Restrict, which is an index of the degree to which bank' activities are restricted in the underwriting of securities, insurance, real estate, and in owning shares in non-financial firms. This indicator ranges from 4 to 16, with higher values indicating more restrictions on banks' activities. We use Fraction Denied, the fraction of applications for bank licenses rejected as indicator of the 14 contestability of the banking market.7 Both regulatory indicators are from Barth, Caprio, and Levine (2001). We use an indicator of the amount of information that is available to lenders from credit registries in the country. Credit Bureau is the average of four variables that indicate (i) whether the credit registry offers only negative or also positive information about borrowers, (ii) the amount of information available about borrowers, (iii) which institutions have access to the data, and (iv) whether information is available for each loan or only aggregated for each borrower. The indicator is normalized between zero and one, with higher values indicating more information being available to more institutions. Data are from Galindo and Miller (2001) and available for 30 countries.8 Finally, we use a general indicator of Banking Freedom from Heritage Foundation, which indicates the absence of government interference in the banking system and is averaged over the period 1995-99.9 We use indicators of the institutional environment of a country to (i) control for institutional development when assessing the effect of concentration, and (ii) assess whether the effect of concentration varies across countries with different levels of institutional development. Specifically, we use Rule of Law, an indicator of the degree to which inhabitants of a country can trust the legal system of their country to up-hold their rights. This indicator is from International Country Risk Guide (ICRG) and reflects the assessment of foreign investors. It ranges from one to six, with higher numbers 7 In the case where there were no applications (and therefore no rejections), this indicator takes the value one. 8 Galindo and Miller (2001) also take into account which types of loans are reported in the registry. However, including this variable would have reduced our coverage by another six countries. However, results are similar when using this more comprehensive indicator. 9 Specifically, this indicator is based on five questions: 1. Does the government own banks? 2. Can foreign banks open branches and subsidiaries? 3. Does the government influence credit allocation? 4. Are banks free to operate without government regulations such as deposit insurance? 5. Are banks free to offer all types of financial services like buying and selling real estate, securities and insurance policies? 15 indicating a better legal environment. Corruption (ICRG) is an indicator of corruption and ranges from one to six, with higher numbers indicating less corruption. Institutional Development is a summary variable from Kaufman, Kraay and Zoido-Lobaton (2001) that averages six indicators proxying for voice and accountability, regulatory quality, political stability, rule of law, control of corruption and effectiveness of government. Finally, we use the log of real GDP per capita. Recent research has established a robust relation between well-developed institutions and income per capita, so that GDP per capita can be seen as an overall proxy for institutional development.'° As discussed above, the ownership structure of the banking sector might affect both the market structure and the functioning of the banking sector, thus affecting firmns' financing obstacles and access to credit. We therefore include the share of banking system's assets in banks that are 50% or more government owned (Public Bank Share) or 50% or more foreign owned (Foreign Bank Share). Both measures are from Barth, Caprio and Levine (2001). Finally, we include a measure of financial intermediary development, Private Credit, which is the share of claims by financial institutions on the private sector in GDP. To assess the robustness of the relation between market structure and firms' access to external financing and growth, we include other country-level variables. We include the growth rate of GDP per capita since firms in faster growing countries are expected to grow faster and face lower obstacles. We use the inflation rate to proxy for monetary instability, conjecturing that firms in more stable monetary environments face fewer obstacles. '° Acemoglu, Johnson and Robinson (2001) show a relation between institutional development and economic development that is robust to reverse causation and simultaneity bias. 16 Many of the country-level variables are highly correlated with each other, as shown in Panel C of Table 2. More concentrated banking systems have lower levels of financial, economic and institutional development, have more foreign banks, share less information, and face more restrictions and more government interference. Many of the explanatory country-level variables are also highly correlated with each other, which underlines the importance of controlling for these country characteristics when assessing the impact of bank concentration. 4. The Empirical Model To explore the effect of bank concentration on firms' financing obstacles access to credit, we estimate two different empirical models. To estimate the effect of bank concentration on financing obstacles, we use the following regression: Financing Obstaclej,k = a + ,B Governmentj,k + ,2 Foreignj,k + 13 Exporterj,k + P4 No. of Competitorsj,k + P5 Manufacturingj,k + P6 Servicesj,k + P7 SiZejk + P8lnflationk + 9 Growthk + PIo Concentrationk +£j,k. (1) Given that Financing Obstacle is a polychotomous dependent variable with a natural order, we use the ordered probit model to estimate regression (1). We assume that the disturbance parameter E has a normal distribution and use standard maximum likelihood estimation. The coefficient of interest is 1lo; a positive coefficient would be evidence in favor of the structure-performance hypothesis, while a negative or insignificant coefficient evidence for theories of the information-based hypothesis. The coefficients, 17 however, cannot be interpreted as marginal effects of a one-unit increase in the independent variable on the dependent variable, given the non-linear structure of the model. Rather, the marginal effect is calculated as 4(3'x)p, where 4 is the standard normal density at ,B'x. To assess whether bank concentration has a different effect on firms depending on their size, we interact concentration with dummy variables indicating whether the firm is small (5-50 emnployees), medium-size (51-500 employees) or large (more than 500 employees). In altemative specifications, we also control for measures of institutional environment, ownership structure of the banking system and regulatory variables, as well as their interaction with bank concentration. Finally, we replace the dependent variable by individual financing obstacles, as described in the previous section. We also assess the effect of bank concentration on the actual access of firms to bank finance with the following baseline regression: Bank Financej,k = a + PI Governmnentj,k + 02 Foreigni,k + P3 Exporterj,k +43 No. of Competitorsj,k + P5 Manufacturing9,k + f36 Servicesjk + P7 Sizej,k + I38Inflationk + f9 Growthk + P1o Concentrationk + qj,k. (2) Since Bank Finance is a dummy variable, we use probit regressions to estimate (2). A negative coefficient on PI 0 would be evidence in favor of the structure- performance hypothesis, while a positive or insignificant coefficient evidence for theories of the information-based hypothesis. As before we introduce interactions with size 18 dummies, control for the institutional and regulatory environment and ownership structure of the banking system and interact Concentration with these variables. 5. Results Firms face higher financing obstacles and are less likely to access bank financing in more concentrated banking systems. In column 1 of Table HI, Bank Concentration enters significantly positive, indicating that firms in countries with more concentrated banking systems report higher financing obstacles. Bank Concentration enters significantly and negatively in column 4 indicating that firms in more concentrated banking systems are less likely to receive bank finance. When we interact Bank Concentration with dummy variables for small, medium, and large firms, the interactions for small and medium firms enter significantly at the 5% level in the regression of General Financing Obstacle, while only the interaction with the Small Firm dummy enters significantly at the 5% level in the Bank Finance regression (columns 2 and 5). Further, the interaction with Small is largest in both regressions, indicating that the growth-impeding effect of bank concentration is largest for small firms. " l Finally, we use our altemative concentration measure from Barth, Caprio and Levine (2001) and confirm our results of a positive relation of bank concentration with the General Financing Obstacle and a negative relation with the probability of firms receiving bank finance (columns 3 and 6).12 The Table III results also indicate that foreign owned firms and services firms and larger firms face less financing obstacles. Exporting and large firms are more likely to " We also find that the interactions with the Small and Medium dunmnies in column 3 are significantly different from the Large dummy. 19 receive bank financing. Firms in faster growing economies with lower inflation face less financing obstacles and are more likely to receive bank financing. The Table III results are not only statistically significant, but also of economic significance, as illustrated in Table IV. Here we present the probability that enterprises rank financing as major obstacle to growth and operation (Financing Obstacle=4) and the probability that enterprises finance their investment with bank finance, at different levels of Concentration. Holding constant all other factors that determine firms' financing obstacles, moving from the 25% percentile of Concentration (Peru) to the 75% percentile (Senegal) increases the probability that financing is reported as major obstacle by 14%, while reducing the probability of access to bank finance by 15%, compared to the sample means of 38% and 39%, respectively. This effect is much stronger for small enterprises (16% and 23%, respectively) than for large enterprises (5% and 2%, respectively). Overall, these results are supportive of the structure-performance hypothesis, but inconsistent with the information-based hypothesis. The market share of the largest three banks, however, is only one dimension of the competitiveness of a banking sector. Contestability, absence of government interference, information sharing and restrictions on banks' activities constitute other important elements of this competitive environment in which banks operate. In Table V, we therefore introduce measures of the regulatory environment. Firms in countries where banks are more restricted in their entry and in their activities outside the traditional credit and deposit market report higher financing obstacles. Firms in countries with higher levels of government interference in the banking system report higher financing obstacles and have a lower probability of receiving bank finance. While the coefficient estimates 12 We also tried regressions with a quadratic term of concentration, but it never entered significantly. 20 suggest that having firms in countries with better developed credit registries report higher financing obstacles and facer a lower probability of accessing bank finance, these results are not significant at the 5% level. Bank Concentration enters significantly in all regressions of the General Financing Obstacle, when we control for restrictions on banks' activities, the fraction of bank license applications denied, banking freedom and credit registry. Bank Concentration does not enter significantly, however, in the regressions of Bank Finance, when we control for regulatory policies, except for the regression controlling for Credit Registry. In the case of Restrict and Fraction Denied, this is due to the smaller sample that we utilize when including these variables. More restrictions on banks' activities, more government interference in the banking system and less information sharing through credit registries exacerbate the negative association of bank concentration with financing obstacles, as shown in Table VI. Here we interact Bank Concentration with the different regulatory measures. This suggests that policies that restrict banks' possibilities of diversifying outside the credit and deposit business, increase government interference and restrict information sharing increase the impact that bank concentration has on financing obstacles. However, the coefficient estimates also indicate that firms in more concentrated banking systems face lower financing obstacles if there are few regulatory restrictions on banks' activities. The positive effect of bank concentration and Restrict is not very widespread, however, since banks in concentrated banking systems face more restrictions on their activities, as shown by the positive correlation in Table II C. Indeed, for most of the sample bank concentration either has an insignificant or adverse effect on financing obstacles and bank 21 finance.'3 Similarly, higher levels of concentration exacerbates the negative effects of activity restrictions. Furthermore, better information sharing increases the likelihood of receiving credit, but decreases it in concentrated banking systems, while Banking Freedom reduces the negative effect of concentration on the probability of receiving bank finance. There does not seem to be any interaction between bank concentration and the share of bank license applications denied. The empirical relation between Bank Concentration and firms' financing obstacles and access to credit is robust to controlling for the institutional environment, as shown in Table VII. Controlling for Rule of Law, Corruption, Institutional Development, and GDP per capita we still find a significant association of Bank Concentration and Bank Finance. The relation between Bank Concentration and firms' financing obstacles is weakened when we control for GDP per capita, but robust to the inclusion of Rule of Law, Corruption and Institutional Development. Higher levels of Rule of Law, Corruption, Institutional Development and GDP per capita alleviate financing obstacles, while higher levels of Institutional Development and GDP per capita increase the likelihood that firms receive bank financing. The estimates in Table VIII suggest that the positive association of bank concentration with firms' financing obstacles and the negative relation with access to credit holds only for countries with low levels of institutional development. Here, we interact Bank Concentration with indicators of the institutional environment. The interaction terms with Rule of Law, Corruption, Institutional Development and GDP per capita enter significantly and negatively in the regression of the General Financing 13 At restrict values higher than 8 (7 if we also control for institutions) the impact of concentration on financing obstacles is insignificant or positive. 22 Obstacle (columns 1-4), indicating that bank concentration has less of an effect in countries with high levels of institutional development. Considering the coefficient size suggests that there is no effect of bank concentration on financing obstacles in the countries with the highest levels of institutional development. The interactions of Bank Concentration and Corruption, Institutional Development and GDP per capita enter significantly positive in the Bank Finance regressions, indicating that the negative effect of bank concentration on the likelihood of receiving bank financing, is reduced or even eliminated in countries with high levels of institutional development.'4 The results in Table IX suggest that the relation between concentration and financing obstacles is robust to controlling for the level of financial intermediary development and the ownership structure of the banking system. Bank Concentration does not enter significantly in the Bank Finance, when we control for the share of foreign owned and state-owned banks (columns 4 -6 ), a result that is due to the smaller sample. While a higher level of financial intermediary development and a larger presence of foreign banks alleviate financing obstacles, a larger share of government-owned banks increases financing obstacles.'5 A larger presence of foreign banks increases the likelihood of receiving Bank Finance, while a larger presence of state-owned banks decreases it. There does not seem to be a robust relation between the level of financial development and access to finance. The presence of foreign banks alleviates the association of concentration with financing obstacles, while public bank ownership exacerbates it, as shown by the results 14 Surprisingly, Corruption enters significantly and negatively in the Bank Finance regressions. Considering the coefficient estimates this indicates that in countries with concentration ratios below 0.56, absence of corruption decreases the likelihood of receiving bank finance. 23 in Table X. Here we not only control for financial development and ownership structure, but also interact these variables with Bank Concentration. The interaction of Bank Concentration with Foreign Bank Share enters significantly and negatively, suggesting that foreign bank ownership alleviates the negative impact of bank concentration on financing obstacles. The interaction of Bank Concentration with Public Bank Share enters significantly and positively, while Bank Concentration does not enter significantly and the share of government-owned banks enters positively and significantly. This seems to indicate that government-owned banks can actually help alleviate financing obstacles in countries with low concentration ratios and that bank concentration affects financing obstacles only in banking systems with government-owned banks. There does not seem to be an interaction of bank concentration and Private Credit in their effects on financing obstacles. More bank concentration in countries with high levels of financial intermediary development, on the other hand, seem to decrease firns' probability of receiving bank finance. A higher level of financial development, on the other hand, dampens the negative effect that Bank Concentration has on the probability of receiving bank financing. There is no effect of the ownership structure on the relation between Bank Finance and Bank Concentration. The effect of bank concentration is not equal across the different dimensions of the financing obstacles finns face. Panel A of Table XI presents the results for a number of specific financing obstacles that firms were asked about in the WBES survey. We find that firms in more concentrated banking systems report higher financing obstacles due to high interest rates, access to long-term loans, credit information, and bank corruption. In 5 The result for foreign bank market share is consistent with the results found by Cull, Clarke and Martinez Peria (2002). 24 more concentrated banking systems, however, firms report lower financing constraints due to bank bureaucracy. Panel B presents regressions where we interact Concentration with Institutional Development. These results indicate that firms report less financing constraints due to high interest rates in more concentrated banking systems, unless being in institutionally well developed economies, where there is no effect. Further, firms report lower financing constraints due to special connections, collateral and bank bureaucracy, an effect that is strengthened by institutional development in the cases of special connections and bank bureaucracy. Firms still report higher financing constraints due to credit information, unless being in a institutionally developed country. We interpret these seemingly contradicting results as indicating that bank concentration is a multi-faceted phenomenon with both positive and negative effects on firms' financing choices. Further, taking Panel A and Panel B results together underlines the importance of controlling for the level of institutional development, when evaluating the effect of bank concentration. 6. Conclusions This paper assessed the importance of the competitiveness of the banking system for financing obstacles firms face and the likelihood of receiving bank finance. A recently compiled firm database allows us to distinguish between the effect of the market structure on small, medium-size and large firms. Further, a broad cross-country survey on bank regulation allows us to focus on the overall competitive environment in the banking market beyond simple concentration ratios. 25 We find that bank concentration increases financing obstacles and decreases the probability of receiving bank finance. The effect is stronger for small and medium compared to large firms. The effect of bank concentration on financing obstacles is dampened in countries with more efficient legal systems, less corruption, higher levels of financial, economic and institutional development, and a larger presence of foreign banks. The effect of bank concentration is exacerbated, on the other hand, in countries with more restrictions on banks' activities, high government interference in the banking system and a higher share of government-owned banks. Further, firms in countries with more government interference in the banking system, a lower share of foreign and a higher share of government-owned banks face higher financing obstacles. In addition the results indicate that in concentrated banking systems it is possible to reverse the adverse affects of concentration on access to finance by removing restrictions on bank activities. Our results shed light on the theoretical debate on the effects of banks' market power on firms' access to credit. Our findings provide qualified evidence for theories that focus on the negative effects of bank power (structure-performance hypothesis), while they are inconsistent with theories that stress the potential positive effects of bank concentration (information-based hypothesis). However, our results also underline the importance of controlling for the institutional and regulatory environment when assessing the effect of market competitiveness. While we find a strong relation between bank concentration and higher financing constraints and a lower probability of bank finance in institutionally less developed economies (consistent with the performance-structure hypothesis), this relation is insignificant for institutionally, financially and economically well developed economies. 26 Our findings send important messages for policy makers, especially in developing countries. 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Marquez, Robert (2002): Competition, Adverse Selection, and Information Dispersion in the Banking Industry, The Review of Financial Studies, forthcoming. Mauro, Paul, 1996, "The Effects of Corruption on Growth, Investment and Government Expenditure," IMF Working Paper 96/98. Petersen, Mitchell A. and Rajan, Raghuram G (1995): The Effect of Credit Market Competition on Lending Relationships, Quarterly Journal of Economics 110, 407- 443. Rajan, Rhaguram and Luigi Zingales, 1998, Financial dependence and growth, American Economic Review 88, 559-587. Schiffer, Miijam and Beatrice Weder, 2001, Firm Size and the Business Environment: Worldwide Survey Results, IFC discussion paper number 43. Shleifer, A. and R. Vishny, 1993, Corruption, Quarterly Journal of Economics, 108 (3), 995-1025. 30 : - . _ -_ ............ _ I . - - - United States Panama ^', . - _ Guatemala Italy _. . . C France % r . . . t: : -- Germany Colombia ,_,, - . .tArgentina India Philippines Malaysia Russia Indonesia 0) ~~~~~~~~~~~~United Kingdom Brazil G -_ . . . . _~~~~~* Nicaragua e .-> . .. . . | . : ~~Honduras - - Portugal Chile Bolivia a >- . . = : Spain _ .: . l - ._ ~~~~~~~~Tunisia !:t *- a,.' w . -; w - . . _ _ Nigeria CD ..t - Poland Ca .... E E3 ........ Hungary 2 * a 5S= F p = Venezuela 45 ^ . . 1z: C ~~~~~~Turkey a . . . . . e d = d . Kenya o y .. . = ._ . . ~~~~Canada O ~ t++ t > A 1131 9Sft | w e + tThailand t) & r. _ _rJ'- ;= _ t|- ;_a rlw=mi:_ Ukraine " 30 . . . 1 -1- -- -;- -; - Egypt p > : , O *'f. . . ~~~~~~~Croatia 0 32 ... Slovenia (Sc . e r _ v_._ . _ Singapore 'O o - Dominican Republic J9 - Czech Republic _- ; . DZimbabwe C- r '-r + _ . -- - _ ........ .Pakistan o = . .< . rr . ~~~~~~Mexico c C Vt ; # ~~~~~~~~~~Slovakida ° .GY.b__ Costa Rica U ~~~~~~~~~~~~~~~Bulgaria pb qc . 4 . ; - ~~~~~~~~South Africa cDo + I Ecuador u .; El Salvador Trinidad & Tobago vC e =, *, K is_w , .t * _ Urdguay Sweden .° ; 1 . ............... ;_ ._Ghana S ^ e-t - - | - - --,* - r- Zambia O, t _ Moldova :S - Tanzania o ; - . w~~~~~~~~~Nanmilbiaa ' tr z -=_ ~~~~~~China - - _ ..Kazakhstan o . -- .................. i _._ ._. iGeorgia O ''............ Z0"F~;- Belarus X -- .............. -r - --. .Romania c . . ..................... = SG _Estonia oO t X ..................... X-i _Lfthuania o E Sle _ . j ~~~~~~Armenia .^ eS e:E ~~~~~~~~Cote d Ivoire *. . 1 " _ ^ 8s i ~~~Botswana + < .^ _ = 2S ~~~Cameroon G 2t + 4_ _j s | __w9;__,Malawl -__G7_r_S ~6sther m T--Madagascar i=-; AzerbaiJan Aze.Belkie _ 0 co s (o uz xr n N o~~~Hait Figure H: Financing ObseacWs in Hogh- and Low-ConcGntratlon Countries Concentration Is given by the share of the largest three banks in total banking sector assets. Average for 1995-99. Source: BankScope. Countries are divided according to whether a countiys concentration ratio Is below or above the median value (0.61). The financing obstacle is the the response to the question How problematic Is financing for the operaton and growth of your business? Answers vary between 1 (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Firms are defined as small if they have less than 50 employees, as medium if they have between 50 and 500, and as larme If thev have more than 500 emolovees 3- 2.8 - L~~~~~~~~~~~~~~~~~~~~~~~~ 2.6 _- - F , . _ _ i l L r- _OHigh concentration I , C . | O Low concentration 2.4 _ _ _ _ _ _ _ _ _ _ _- - 2.2 - - - - _., 2 3 Fintancing obstacle Financing obstacle-small fiffns Financing obstacle-medium firmns Financing obstacle-arge firmns 32 Figure III: Access to Finance In High- and Low-Concentration Countries Concentration is given by the share of the largest three banks in total banking sector assets. Average for 1995-99. Source: BankSrope. Countrles are divided according to whether a country's concentration ratio is below or above the median value (0.61 ).Bank Finance is a dummy variable that takes on the value one n the firm receives bank finance and zero otherwise. Firms are defined as small if they have less than 50 employees, as medium if they have between 50 and 500, and as large if they have more than 500 employees. 0.7 - 0 6 - 0.5 0 High concentration 0 4 -E Low concentration 052 - -| |= | 1l 0 1 0 . Bank Finance Bank Finance-small firms Bank Finance-medium firms Bank Finance-large firms 33 Table 11 Economic Imndicators and Obstacles to Firm Glrowth General Financing Obstacle is the response to the question "How problemattc is financing for the operation and growth of your business?" Answers vary between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Bank Finance is a dummy vanable that takes on the value one if the firm receives bank finance, and zero otherwise. Concentration is the share of the largest three banks in total banking assets. GDP per capita is real GDP per capita in US$ Pnvate Credit is claims on the private sector by financial institutions as share of GDP. Rule of Law is the extent to which a country's cittzen tust its legal system. Coruption indicates the absence of corruption. Institutional Development is an average of six indicators measuring voice and accountability, control of conuption, regulatory quality, political stability, rule of law, and government efficiency.. Foreign Bank Share is the share of assets in banks that are majority foreign owned Public Bank Share is the share of assets in banks that are majonty state-owned. Restnct is an indicator of the degree to which banks' activities are restricted outside the credit and deposit business. Fraction denied is the share of bank license applications rejected. Credit registry is an aggregate mdhcator of the infonnation available through credit registries. Banking Freedom isa general indicator of the absence of government interference in the banking sector. Detailed variable definitions and sources are given m the appendix. General Financing Bank GDP per Private Institutional Foreign bank Public Bank Fraction Credit Banking Obstacle Finance Concentration capita Credit Rule of Law Corruption Development Share Share Restnct denied registry Freedom Argentina 3.03 0.69 0.34 8,001 0.21 5.00 2.00 0.33 49.00 30.00 7 0.00 0.60 3.80 Armenia 2.65 0.06 0.88 844 0.04 -0.43 3.00 Azerbaijan 2.86 0.07 0.96 408 -0.78 2.00 Belarus 3.28 0.20 0.81 2,235 0.06 4 00 4.00 -0.76 2.80 67.30 13 0.00 0 69 3.00 Belize 2.69 0.60 1.00 2,738 0.41 3.00 Bolivia 3.04 0.62 0.46 939 0.51 3.00 3.00 0.02 42.30 0.00 12 1.00 0.59 3.60 Botswana 2.34 0.90 3,546 0.11 4.00 3.00 0.56 97 61 2.39 10 0.00 3.80 Brazil 2.71 0.51 0.40 4,489 0.32 2.05 3.00 0.00 16.70 51.50 10 0.74 0.83 3.00 Bulgaria 3.13 0.22 066 1,418 014 4.00 4.00 001 3.00 Cameroon 3.07 0.91 631 0.14 3 00 2.00 -0.72 2.20 Canada 2.07 0.63 0.54 20,549 0.83 6.00 6 00 - 1.43 0.00 7 000 4.00 Chile 2.43 0.76 0.46 4,992 0.68 5.00 4.00 0.88 32.00 11.70 11 1 00 0.65 3.00 China 3.34 0.31 0.80 677 0.85 5.00 2 00 -0.20 14 0.25 3 00 Colombia 2.68 0.64 0.32 2,381 0.36 2.00 1.55 -0.41 0.53 4.00 Costa Rica 2.51 0.50 0.66 3,641 0.15 4.00 5.00 0.81 0.80 3.00 Cote d'lvoire 2.81 0.90 763 0.26 3 00 2 00 -0 19 3.00 Croatia 3.34 0.46 0.58 3,846 0.00 5.00 2 00 0.03 6.67 36.99 7 0 56 3.00 Czech Republic 3.13 0.21 0.61 5,163 0.58 5.14 4.00 0.68 26.00 19.00 8 0.36 5.00 DominicanRepublic 2.58 0.64 061 1,712 0.24 4.00 4.00 -0.11 0.49 3.00 Ecuador 3.34 0.40 0.67 1,538 0.30 3.36 3.00 -0.32 0.49 3.00 Egypt 3.00 0.57 1,108 0.33 4.00 2.00 -0.15 4.20 66.60 13 1.00 3.40 El Salvador 2.87 0.60 0.68 t,706 0.36 3.00 4.00 -0 03 12 50 7.00 13 0.00 4.00 Estonia 2 49 0.55 0.85 3,664 0.16 4.00 5.00 0.61 85.00 0.00 8 0.00 0 65 4.00 Ethiopia 2.97 0.97 109 0.21 5.00 200 -0.12 200 France 2.76 0.47 0.27 27,720 0.84 5.00 3.86 1.03 6 0.00 3.00 Georgia 3.23 0.26 0.81 411 -0.61 2.00 Gennany 2.54 0.58 0.32 30,794 1.06 6 00 5.00 1.37 4.20 42.00 5.00 0 00 0.45 3.60 34 General Financing Bank GDP per Private Institutional Foreign bank Public Bank Fraction Credit Banking Obstacle Finance Concentration capita Credit Rule of Law Corruption Development Share Share Restrict denied registy Freedom Ghana 3.07 0.75 393 0.05 3.00 3.00 -0.14 54.30 37.90 12.00 0.80 3 00 Guatemala 2.97 0.63 0.26 1,503 018 2.14 4.00 -0 51 4.93 7.61 13.00 0.30 0.56 3.60 Haiti 3.48 0.41 0.97 369 0.12 2.59 2.23 -1.14 044 160 Honduras 2.85 0.56 0.41 708 0.26 2.05 2 00 -0.43 1.60 1.10 9.00 0.20 3.00 Hungary 2.67 0.31 0.51 4,706 0.22 6 00 5.00 0.87 62.00 2.50 9 0.50 3.80 India 2.54 0.35 414 0.21 4.00 3.00 0.00 0.00 80.00 10 0.55 2.00 Indonesia 2.86 0.29 0.39 1,045 0 52 2.64 1.32 -0.77 7.00 44.00 14 1.00 280 Italy 2.11 078 0.27 19,646 057 6.00 355 0.91 500 1700 1O 0.27 0.51 3.60 Kazakhstan 3.17 0.14 0.81 1,313 4.00 3.00 -0.53 2.00 Kenya 2.84 0.54 339 0.34 2.45 2.05 -0.78 10 0.85 3.60 Lithuama 2.88 0.25 0.86 1,907 0.11 4 00 3.00 0.26 48 00 44.00 9 0.67 2.75 Madagascar 3.13 095 238 0.13 3.00 4.00 . -0.38 2.00 Malawi 2.74 0.94 154 0 11 4.00 3.00 -0.17 8.30 48 90 13 0.00 3.00 Malaysia 2.65 0.54 0.36 4,536 1.30 4.59 3.59 0.51 1800 000 10 1.00 0.07 3.00 Mexico 3.40 0.22 063 3,393 0.22 241 2.73 -007 19.90 25.00 12 0.51 200 Moldova 3 44 0.24 0.76 666 0.06 5 00 2 00 -0 20 33.37 7 05 7 0.60 2 60 Namibia 1.91 0.79 2,325 0.38 6.00 4 00 0 47 11 0.67 4 00 Nicaragua 3.17 0.43 0.41 447 0.31 4.00 4.00 -0 41 280 Nigena 3.14 0.50 254 0.08 3.00 1.45 -1.00 0 00 13.00 0.00 2.20 Pakistan 3.28 0.50 0.63 503 0.23 3.14 3.00 -0.59 3.40 Panama 2.18 078 0.22 3,124 078 3.00 200 0.11 38.33 1156 8 0.00 049 5.00 Peru 3.04 0 60 0.46 2,335 0.18 3.00 3 00 -0.18 40.40 2.50 8 0.00 0.63 4.00 Philippines 2.68 0.44 0 36 1,125 0.50 4.00 3.50 0.21 12.79 12.12 7 0 00 3 00 Poland 2.41 0.33 0.51 3,216 0.12 5.00 4.82 0.70 2640 43.70 10 0.00 3.00 Portugal 1 73 0 29 0.43 11,582 0.73 5.00 5.00 1.20 1170 20.80 9 0.00 0.40 3.00 Romania 3.30 0.27 0.83 1,365 0.09 4.77 3.00 -0.08 8.00 70.00 13 0 38 3.00 Russia 3.22 0.20 0.38 2,214 0.08 3.45 1.91 -0 54 9.00 68.00 8 038 3 60 Senegal 3 00 0 78 563 0.21 3.00 3.00 -0 30 015 3.00 Singapore 1.85 0.59 0.60 25,374 1.11 6.00 4.00 1.44 50.00 0.00 8 1.00 400 Slovakia 3.31 0.24 0 65 3,805 0.30 5 00 3 36 0 28 3.00 Slovenia 2.29 0.46 0 60 10,226 0.26 5.00 4 00 0.85 4.60 39.60 9 1.00 4.00 35 General Public Financing GDP per Institutional Foreign bank Bank Fraction Credit Banking Obstacle Bank Finance Concentration capita Pnvate Credit Rule of Law Corruption Development Share Share Restrict denied registy Freedom South Afnca 2.45 0.67 3,920 1.18 2.59 3.73 0.11 5.20 0.00 8 0.33 3.00 Spain 224 0.55 0.47 15,858 0.79 4.00 5.00 1.10 11.00 0.00 7 0.00 0.16 3.60 Sweden 1.89 0.53 0.72 28,258 0.82 6.00 6.00 1.53 1.80 0.00 9 0.08 0.61 3.60 Tanzania 3.00 0.77 182 0.09 5.00 3.00 -0.13 3.00 Thailand 3.11 0.56 2,835 1.46 5.00 2.14 0.15 7.16 30.67 9 100 043 3.00 Trinidad&Tobago 3.03 0.88 0.70 4,526 0.40 4.00 3.00 0.59 7.90 15.00 9 0.50 400 Tunisia 1.69 0.48 2,200 0.60 5.00 3.00 0.30 3.60 Turkey 3.13 0.50 0.54 3,007 0.16 3.91 2.00 -0 33 6.00 35.00 12 0.29 4.00 Uganda 3.13 0.56 324 0.04 4.00 2.00 -0.34 3.00 Ukraine 3.45 0.18 0.57 867 0.01 -0.58 0.48 2.20 United Kingdom 2.25 0.32 0.40 20,187 1.16 6.00 5.00 1.50 0.00 5 5.00 United States 2.33 0.69 0.18 29,253 1.84 6.00 4.00 1.30 4.70 0.00 12 0.00 0.83 4.00 Uruguay 2.72 0.77 0.72 6,114 0.27 3.00 3.00 0.57 0.51 3.80 Venezuela 2.49 0.41 0.53 3,471 0.10 4.00 3.00 -0.37 33.72 4.87 10 0.00 0.49 3.20 Zambia 2.71 0.76 394 0.06 4.00 3.00 -0.20 64.00 23.00 13 0.00 4.00 Zimbabwe 3.03 0.62 693 0.29 4.00 2.00 -0.53 3.00 36 Table I Summary Statistics and Correlations Summary statistics are presented in Panel A and correlations in Panels B and C, respectively. General Financing Obstacle is the response to the question "How problematic is financing for the operation and growth of your business?" Answers vary between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). High interest rates, special connection, long-term loans, credit information, collateral requirements, bank bureaucracy, and bank official corruption are constructed m a smilar way. Bank Finance is a durmy variable that takes on the value one if the firm receives bank finance, and zero otherwise Government and Foreign are dummy variables that take the value I if the firm has govemment or foreign ownership and zero if not. Exporter is a dummy vanable that mdicates if the firm is an exporting firm. Manufacturing and Services are industry dummes. Sales is the loganthm of sales in USS. Number of Competitors is the logarithm of the number of competitors tbe firm has. Concentration is the share of the largest three banks in total banking sector assets. Restrict is an indicator of the degree to which banks' activities are restricted outside the credit and deposit business. Fraction denied is the share of bank license applications rejected. Banking Freedom is a general indicator of the absence of govemment interference in the banking sector. Credit registry indicator is a summary variable of the amount of infornation and the number of institutions that have access to borrower information from credit registries in a country. Rule of Law is the degree to which citizens trust its country's legal system Corruption indicates the degree to which there is no corruption in a country. Institutional Development is an average of six indicators measuring voice and accountability, control of corruption, regulatory quality, political stability, rule of law, and government efficiency. Pnvate Credit is claims on the private sector by financial institutions as share of GDP. Foreign Bank Share is the share of assets in banks that are majority foreign owned. Public Bank Share is the share of assets in banks that are majonty state-owned. Growth is the growth rate of GDP. Inflation is the log difference of the consumer price index. GDP per capita is real GDP per capita in USS. Detailed definitions and the sources are in the data appendix. Panel A: Summary Statistics: Variable Obs Mean Median Std. Dev. Max Mm Generalfinancingobstacle 6,716 2.84 3 1.12 4.00 1.00 High interest rates 6,822 3.23 4 1.03 4.00 1.00 Special connection 6,461 2 19 2 1 08 4.00 1.00 Long-tern loans 5,382 2.62 3 1.26 4.00 1.00 Credit information 5,955 2.23 2 1.12 4.00 1.00 Collateral 6,492 2 49 3 1.16 4.00 1 00 Bank bureaucracy 6,629 2.50 3 1.08 4.00 1.00 Bank official corruption 5,761 1.72 1 1.03 4.00 1.00 Bank finance 4,693 0 39 0 0.49 1.00 0.00 Government 7,186 0.12 0 0.33 1.00 0.00 Foreign 7,186 0.19 0 0.39 1.00 0.00 Exporter 7,186 0.37 0 0.48 1.00 0.00 Manufacturing 7,186 0.37 0 0.48 1.00 0.00 Services 7,186 0.45 0 0.50 1.00 0.00 Sales 7,186 9.94 12 6292 8.15 25 33 -2.12 NumberofCompetitors 7.186 0.83 0.6931472 0.33 2.20 0.00 Concentration 74 0.61 0 61 0.21 1.00 0 18 Restrict 48 9.73 9 50 2.39 14.00 5.00 Fraction denied 44 0.36 0.26 040 1 00 0.00 Banking Freedom 74 3.21 3.00 0.72 5.00 1.60 Credit registry 30 0.51 0.51 0.18 0.83 0.07 RuleofLaw 69 4.09 4.00 1.15 6.00 2.00 Corruption 69 3.24 3.00 1.11 6.00 1.32 Institutional Development 73 0.10 -0.07 0.66 1.53 -1.14 GDP per capita 74 4971.57 2206.96 7712.29 30794.02 109.01 Private Credit 71 0.40 0 26 0.38 1.84 0.00 Foreign Bank Share 43 22.89 11.70 23.94 97.61 0.00 Public Bank Share 45 23.10 15.00 23 43 80.00 0.00 Inflation 74 0.13 0 08 0 16 0.86 0.00 Growth 74 0.02 0.02 0.02 0 07 -0.03 37 Panel 3: Correlatlons between furm-Revel varlinbRes General High Special Long- Credit Collateral Bank Bank official Bank Govemnment Foreign Exporter Manufact Services Sales Number of financing interest connection term infonnation bureaucracy corruption finance uring competitors obstacle rates loans High interest rates 0.33*** 1 Special connection 0.30°°° 0a3S°° I Long-tenn loans 0.46°°° 0.45** 0.440" I Credit information 0.29°°° 0.29*° 0.370°° 0 46°°° I Collateral 0.36*°° 0.42*** 0 4600o 0 42°° 0.33°° I Bank bureaucracy 0.2S°°° 0.4200° 0.51°° 0.36000 033eoo 0.58°° 1 Bank off conuption 0.26-° 0.27*0* 0.47*** 0.40"O 0.3goo 0.28°° 0.35"OO I Bankfinance -001 0.05°°° 0.01 -0.02 4001 0.07°°° 0.02 -0.10°°° I Government 0.05°° -0.03°° 4.08°° -0.02 -0 04°° -0.05°°° 4,05°°° - 05°°° 4,04°°° I Foreign 4,.17°°°* 0.09°¢ 40.08°°° 40,11* 4003° -0.11°° 40.06°°° -0.09°° 0.10** -0.06*** 1 Exporter 0.06°°° -0.01 -0 06°° -0.03°° 0.03° .0.04°° -0.03° -0.410°° 0 IS** 0.06°°° 0.24°°° I Manufacturing 0 02° 0.0500 -0.02 0.03** 0.04°°° 0.02 0.02 -0.05°°° 0.12*°* 0.0S**o 0 11°° 0.32°°° I Services -4.10°° -10°°° -0.01 -0.09°° -0.07°° -0.05°° 40.04°°° 0 01 -0.07* -0.06°°° 4.06°° .0.260* 40.69°°° I Sales -0.18°° -009°° -0.00 -0.13*o -0.02 .0.03*** -0.03° -0.410°° 0.31" -0.21°°° 0.270°° 0.15°°° 008° 001 I No. of competitors 0.09-° 0.09°° 0.02 0.09°°° 0.07*°° 0.04°°° 0.050° 0.0OS°° -0.16** .0.08*** .10*0 .004*o -009** -0.01 .0.29°0° I Concentration 0 I0** 0.0300 -0.03** 0.08*°* 0.07°°° .003*0* -0.07°°° 0.08°°° -0.415°° 0.l -0.03°o 0.01 -003°° -006°° -0.270°° 0.11°°° 38 Panel C: Correlations between country-level variables Foreign Public Fraction Banking Rule of Institutional GDP per Private Bank Bank Concentration Restrict denied Freedom Credit registry Law Cormption Development capita Credit Share Share Inflation Restrict 030"* 1 Fraction denied 003 0.22 1 Banking Freedom -0 39"** 426 -0.16 1 Credit registry 4.04'. 0.24 -0.12 0.10 I Rule of Law 0 08 -034* -0.06' 027P 0.03 1 Conruption 0.08 4.31* 4.29* 0.29" 0.15 049"* 1 Institutional Development 4.32*-* -053* -O11 0.53'* Oil 0.71** 073"* 1 GDP per capita 4.40"' 4.47"' -0.22 0.38"* 0.13 0.59** 0.56"* 0.79"' Private Credit 4.43"* 425' 0.11 0.33"' -0.08 0.41"' 0.32"* 0.60** 0.66'* 1 ForeignBankSbare 035" 4.11 4.05 030" 020 0.05 009 0.14 4.15 4.24 1 Public Bank Share 012 0.32** 0.21 438" -0.09 4.11I"' 4.34" 438"' 4.300 4.40' 4.33" 1 Inflation 014 0.42*' 4.12 4.10 -0.01 4.16"* 4 11 4.35*' 4.29* 4.39"* 4.08 0.46* 1 Growth 014 0.05 0.35 400 0.18 0.29* 0.31" 0.24" 0.09 0.03 0.14 0.10 431*** 39 Table III Concentration, Financing Obstacles and Access to Bank Finance The regression estimated m columns 1-3 is. General Financing Obstacle = a + P Government + , Foreign + P3 Exporter + P4 Manufactuiring + ,6 Semvces + f6 Sales +P No. of Competitors + Inflaton + f,Growth + pis Concentration + . General Financing Obstacle Is the response to the question "How problematic is financing for the operation and growth of your business?" Answers vary between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Govenment and Foreign are dununy variables that take the value I if the firm has goverment or foreign ownership and zero if not. Exporter is a dummy variable that indicates if the firm is an exporting firm. Manufactunng and Sevices are industry dummues. Sales is the logarithm of sales in USS. Number of Competitors is the loganthm of the number of competitors the firm has. Growth is the growth rate of GDP. Inflation is the log difference of the consumer price index. Concentradon is the share of the largest three banks m total banking sector assets. Concennabon-BCL is an alternative indicator of bank concentation, measuring the deposits of the largest five banks as share of total deposit m the banking system. Small, Medium and Large are dummy variables, mdicatng the size of the firm. Firms with 5 to 50 employees are defined as small, firms with 51 to 500 employees as medium and firms with more than 500 employees as large. The regression is run with ordered probit. The regression estimated in columns 4-6 is: Bank Finance = a + 01 Government + fl Foreign + 3 Exporter + ,4 Manufacturing + f6 Services + N Sales +N No. of Competitors +f6 Inflation + f6G rowth + tio Concentration + e. Bank Finance is a dununy variable that takes on the value one if the firm receives bank finance, and zeo otherwise The regression is run as probit. Detailed variable definitions and sources are given in the appendix. P-values are reported in parentheses. General General General Financing Financing Fmancing Bank Obstacle Obstacle Obstacle Bank Finance Bank Finance Finance Govenment 0.062 0.105 0.060 -0.037 -0.189 -0.035 (0.160) (0.023)** (0.283) (0.545) (0.004)**S (0.640) Foreign -0.352 -0.330 -0.322 -0.028 - 085 -0.033 (0.000)*** (0.000)*** (0.000)*** (0.627) (0.141) (0.633) Exporter -0.045 -0.023 -0.042 0.348 0.300 0.262 (0.136) (0.459) (0.263) (0.000)*** (0.000)** (0.000)** Manufactunng -0.074 -0.070 -0.112 0.109 0.120 0.151 (0.057) (0.074)* (0.024)** (0.068)* (0.045)** (0.043)** Services -0.282 -0.292 -0.313 -0.055 0.007 0.014 (0.000)*e* (0.000)*** (0.000)*** (0.333) (0.907) (0.847) Sales -0 016 -0.014 -0.014 0.042 0.037 0.034 (0.000)*** (0.000)**4 (0.000)W** (0.0o0)*** (0.000)*** (0.00O)* Number of Competitors 0.051 0.043 -0.026 -0.060 -0.043 0.037 (0.257) (0.336) (0.647) (0.354) (0.508) (0.657) Inflation 0.233 0.275 0.405 -0.064", -0.131 -0.395 (0.024)0o (0.009)*** (0.001)'** (0.625) (0.324) (0.012)** Growth -6A95 -6.420 -5.507 3.018 3.048 3.010 (0 000)*** (0.000)0*0 (0.000)*** (0.000)*** (0.000)*** (0.003)*** Concentration 0.433 -0.481 (0.000)*** (0.000)*** Concentration BCL 0.239 -0.545 (0.006)*** (0.000)*** Concentration Small 0.493 -0.729 (0.000)*** (0.000)** Concentration* Medium 0.434 -0.219 (0.000)*** (0.078)* Concentration Large 0.165 -0.046 (0.080)* (0.751) Constant -0.451 -0.449 -0.267 (0000)*** (0000)*** (0.103) Pseudo R2 0.034 0.035 0.030 0.093 0.103 0.078 Observations 6716 6714 4429 4693 4692 3011 ',**,*** indicate significance levels of 10,5, and I percent, respectively. 40 Table IV Concentration, Financing Obstacles and Access to Bank Finance - Quantifying the Effect Based on the regressions of Table 111, estimated probabilities of (i) ratng financmg as major obstacle to the operaton and growth of the enterpnses (Financing Obstacle=4) and (ii) probability of financng investment with ban finance are presented for the 25/, 50% and 75% percentiles of Concentration. Estimated probabilities are calculated for each enterpnse settng all vanables at its actual value, except for Bank Concentration, which is set at either the 25%, 50%/o or 75% percentile of the sample. The probabilities shown are averages for all firms in the sample or for firmis of the specific size class. Bank Concentration at 25% (0.46) 50% (0.61) 75% (0.78) |Change beteen 25% Based on regression I I I and 75% perfeDles Average estimated probability that enterpnse will rate financing as major obstacle for opertion and growth All enterprises 0.325 0.388 J 0.464 0.139 Table 111,I Small enterpnses 0.333 0.406 1 0.492 0.158 Table til, 2 Medium enterpnses 0.339 0.403 0.479 0.139 Table 111, 2 Large enterpnses 0.275 0.299 0.328 0.053 Table 111, 2 Avenge estimated probability that enterpnse will finance their investment with bank finance All enterprises 0.452 0.381 0.298 -0.154 Table 111, 4 Small enterprses 0.399 0.291 0.165 -0.234 Table 111, 5 Medium enterprises 0.457 0.425 0.387 -0.070 Table 111,5 Large enterpnses. 0.573 0.566 0.558 -0.015 Table 111, 5 41 Tabile V Coineentrationn, FanancinLmg bDastzeDes and Access to I3mlk Figannce - Controfing for the Regulldoim of the 13 Rdimng Sectonr The regression estimated in columns 1-4 is: General Fnancing Obstacle = a + p, Govemment + f6 Foreign + 03- Exporter + 04 Manufacturing + p, Services + 06 Sales +fNo. of Competitors +f6lnflation + IsG rowth + PloConcentration + Pi, Regulation + F. General Financing Obstacle is the response to the question "How problematic is financig for the operation and growth of your business?" Answers vary between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Govemment and Foreign are dummy variables that take the value I if the firm has govemment or foreign ownership and zero if not Exporter is a dummy variable that indicates if the firm is an exporting firm. Manufacturing and Services are industry dummies. Sales is the logarithm of sales in US$. Number of Competitors is the logarithm of the number of competitors the firm has. Growth is the growth rate of GDP. Inflation is the log difference of the consumer price mdex. Concentration is the share of the largest three banks in total banking sector assets. Regulation is one of four regulatory variables. Restnct is an indicator of the degree to which banks' activities are restricted outside the credit and deposit busiess Fraction denied is the share of bank license applications rejected. Banlung Freedom is a general indicator of the absence of govemment interference in the banking sector. Credit regtstry indicator is a summary variable of the amount of information and the number of stitutions that have access to borrower iformation from credit registries in a country. The regression is run with ordered probit. The regression estmated in columns 5-8 is. Bank Finance=ac+ p1 Government + f Foreign + Exporter+ 04Manufacturing+ fsServices+ p6Sales+07No. of Competitors +fslnflation +p Growth + P1 Concentration + Pi Regulation + F. Bank Finance is a dummy variable that takes on the value one if the firm receives bank finance, and zero The regression is run as probit. Detailed variable defiitions and sources are given in the appendix. P-values are reported in parentheses. General General General General Financing Financing Financing Financing Bank Obstacle Obstacle Obstacle Obstacle Finance Bank Finance Bank Finance Bank Finance Govermment 0.047 -0.009 0.059 0.099 -0.013 -0.069 -0.034 -0.033 (0.381) (0.877) (0.182) (0.165) (O 855) (0.421) (0.585) (0.718) Foreign -0 315 -0.328 -0.352 -0.410 -0 086 -0.077 -0.042 -0.041 (0 000)*00 (0 0()°°° (0.0W0)°* (0.000)°°° (0.181) (0.258) (0.463) (0.589) Exporter -0.036 -0.058 -0.026 0 006 0.298 0.265 0.320 0.260 (0.329) (0.141) (0.392) (0.904) (0.000)0-* (0.(000)0 (O 000)** (0.000)** Manufactiring -0.084 -0.054 -0.092 -0.198 0.145 0.221 0.124 0.112 (0.079)° (0.320) (0.019)00 (0.002)000 (0.039)0° (0.008)000 (0 039)** (0.169) Services -0.277 -0.220 -0.278 -0 407 -0.006 -0.002 -0.053 0.048 (0.0O0)003 (O 00O)*** (O 000)°°° (0.000)000 (0.923) (0.978) (0.354) (0.540) Sales -0 021 -0.012 -0.016 -0.021 0.036 0.033 0.042 0.037 (0.0O0)*** ( 0000)00 (0.000)*Oc (0.000)000 (0.000)**0 (0.000)3°° (0.000)0°° (O 000)°°° Number of Competitors -0.014 -0021 0.025 0.036 -0.016 -0.099 -0.063 0 115 (0 797) (0.717) (0.587) (0.602) (0.843) (0.273) (0.333) (0 228) Inflation 0.188 0.683 0.253 0.187 -0.397 -0.678 -0058 -0.613 (0 176) (0.000)000 (0.015)*0 (0.217) (0.031)** (0.001)°°° (0.651) (0.001)000 Growth -7.239 -6 355 -6.256 -8.092 2 571 2.213 2.361 6.532 (0 000)°°° (0.000)°°° (0.000)°°° (0.000)°°0 (0 017)°° (0 052)0 (0.006)000 (0.000)000 Concentration 0.171 0.263 0.226 0 521 -0.132 -0.186 -0.122 -0.393 (0.080)0 (0.019)00 (0004)°°° (0.000)°°° (0.385) (0.298) (0.333) (0.017)°° Restrict 0.041 0.005 (0 000)°°° (0.724) Fraction denied 0.107 0.007 (0.026)°° (0 923) Bankng Freedom -0.165 0.215 (0.000)000 I (0.000)°°° Credit Registry 0.209 -0.046 (0.092)° (0.803) Constant -0.568 -0.361 -1.345 -0.440 (0.000)0°° (0.037)00 (0.000)"0° (0.010)°° 0.034 0.027 0.037 0.050 0.071 0.077 0.101 0.092 Observations 4783 3926 6716 3254 3335 2542 4693 2460 0,00,000 indicate significance levels of 10,5, and t percent, respectively. 42 Table VI Concentration, Financing Obstacles and Access to Bank Finance - The Interaction with the Regulation of the Banking Sector The regression estimated in columns 1-4 is. General Financing Obstacle = aA + 0, Govemment + f6 Foreign + P3 Exporter + P4 Manufacturing + , Services + P6 Sales +p7No. of Conipetitors+p,lnflation + P,Growth + p,1Concentration + pi, Regulation + 0i2 Concentration*Regulation+ C. General Financing Obstacle is the response to the question "How problematic is financing for the operaton and growth of your business?" Answers vary between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Government and Foreign are dummy variables that take the value I if the firm has government or foreign ownership and zero if not. Exporter is a dummy variable that indicates if the firm is an exporting firm. Manufacturing and Services are industry dummies. Sales is the logarithm of sales in US$. Number of Competitors is the logarithm of the number of competitors the firm has Growth is the growth rate of GDP. Inflation is the log difference of the consumer price mdex. Concentration is the share of the largest three banks in total banking sector assets Regulation is one of four regulatory vanables Restrict is an indicator of the degree to which banks' activities are restrcted outside the credit and deposit business. Fraction denied is the share of bank license applications rejected. Banking Freedom is a general indicator of the absence of government interference in the banking sector. Credit registry indicator is a summary variable of the amount of information and the number of institutions that have access to borrower mformation from credit registries in acountry. The regression is run with ordered probi. The regression estimated in columns 5-8 is: Bank Finance = a + 0, Government + fl Foreign + P3 Exporter + fl4 Manufacturng + 05 Services + p6 Sales +p, No. of Competitors + Inflabon + 09 Growth + P1sConcentration + pi, Regulation+ 012 Concentration*Regulation + r.- Bank Finance is a dummy variable that takes on the value one if the firm receives bank finance, and zero The regression is run as probiLt. Detailed variable definitions and sources are given in the appendix. P-values are reported in parentheses. General General General General Financing Financing Fmancing Financing Obstacle Obstacle Obstacle Obstacle Bank Finance Bank Finance Bank Fmance Bank Finance Concentration -2.568 0.289 0.955 2 241 2.791 -0.132 -1.092 1.353 (0000)** (0.036)** (0.001)t** (0.000)*** (0000)*** (0.551) (0019)** (0.059) Restrict -0.088 0 152 (0.000)*** (0.000)*** Concentration*Restnct 0.274 -0.302 (0.000)* (O 0O0)*** Fraction denied 0.156 0.116 (0 367) (0.664) Concentration*Fraction denied -0.098 -0.214 (0.762) (0.671) Banking Freedom -0.024 0.027 (0 676) (0 772) Concentration'Bankmg Freedom -0.236 0.302 (0.008)*** (0 030)** Credit Registry 1.614 1.442 (0.000)*** (0 022)** Concentration*Credit Registry -3.133 -3.222 (0.000)** (0 013)* 0.037 0.027 0.038 0.052 0.077 0.077 0.102 0.094 Observations 4783 3926 6716 3254 3335 2542 4693 2460 , indicate significance levels of 10,5, and I percent, respectively 43 11Table VIII Concentration, Financing Obstacles and Access to Bank Finance - Conitrolling for the Institutional Environment The regression estimated in columns 1-4 is- General Financing Obstacle = a + PI Government + X6 Foreign + 06 Exporter + p4 Manufacturing + P Services + P6 Sales +f7No. of Competitors +Ps Inflation + 09Growth + PloConcentration + Pni Institution + e. General Financing Obstacle is the response to the question "How problematic is financing for the operation and growth of your business?" Answers vary between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Government and Foreign are dummy variables that take the value I if the firm has government or foreign ownership and zero if not. Exporter is a dummy variable that indicates if the firm is an exporting firm. Manufacturing and Services are industry dummies. Sales is the logarithm of sales in USS. Number of Competitors is the logarithm of the number of competitors the firm has. Growth is the growth rate of GDP. Inflation is the log difference of the consumer prie index. Concentration is the share of the largest three banks in total banking sector assets. Institution is one of four variables. Rule of Law is the degree to which citzens trust its country's legal system. Corruption indicates the degree to which there is no corruption in a country. Instutdonal Development is an average of six indicators measuring voice and accountability, control of corrupdon, regulatory quality, political stability, rule of law, and government efficiency. GDP per capita is real GDP per capita. The regression is rUn with ordered probit. The regression estimated in columns 5-8 is: Banak Finance = a + ,1 Government + ,h Foreign + JI Exporter + p4 Manufacturing + sServices + 6Sales+0,No. of Competitors4+pinflation+ 09Growth + p,oConcentration + p Institution + e.. Bank Finance is adummy variable that takes on the value one if the firm receives bank finance, and zero Tbe regression is run as probit. Detailed variable defmitions and sources are given in the appendix. P-values are reported in partheses. General General General General Financing Financing Financing Financing Obstacle Obstacle Obstacle Obstacle Bank Finance Bank Finance Bank Finance Bank Finance Government 0.052 -0.005 0.064 0.061 -0.059 -0.063 -0.037 -0.041 (0.275) (0.922) (0.145) (0.164) (0.370) (0.344) (0.548) (0.503) Foreign -0.370 -0 382 -0.366 -0.363 -0.059 -0 060 -0.032 -0.033 (0.000)000 (0.000)Oes (0.000)0es (0.000)000 (0.308) (0.299) (0578) (0.562) Exporter -0.055 -0.040 -0.004 -0.021 0.299 0.298 0.314 0315 (0.081)0 (0.204) (0.897) (0.484) (0.000)o* (0.000)°°° (0.000)000 (0.000)000 Manufacturng -0.081 -0.077 -0.077 -0080 0.131 0.133 0.128 0.134 (0.046)** (0 059)° (0.048)00 (0.040)0° (0.038)°° (0.036)°° (0.032)°° (0.026)°0 Services -0.257 -0.227 -0.245 -0.239 -0 039 40.038 -0.058 -0.051 (0.000)000 (0.000)*** (0.000)°°0 (0.000)0°0 (0.511) (0 525) (0.307) (0.366) Sales -0.019 -0.015 -0.014 -0.015 0.038 0.039 0.041 0.040 (0.000)(00 (0.000)0°° (0.000)°°° (0.000)000 (0.000)000 (0.000)000 (0.000)000 (0.000)0** Number of Competitors 0.021 -0.071 0.011 -0.012 -0.018 -0.020 -0.054 -0.066 (0 655) (0.148) (0.815) (0.802) (0.800) (0.782) (0.399) (0.306) Inflation 0.024 0.157 -0.156 0.179 -0.263 -0.248 0.122 -0.017 (0.821) (0.133) (0.137) (0.083)* (0.057)° (0.065)0 (0.356) (0.896) Growth -5.310 -2.290 4.247 -5.296 2.872 2.836 2.242 2.148 (0.000)°*0 (0.002)**0 (0.000)0oo (0.000)00 (0.003)000 (0.006)*** (0.010)000 (0.013)°° Concentration 0.479 0549 0.155 0.062 -0150 -0.248 -0.415 -0.272 (0.000)0°° (0.000)*** (0.048)00 (0.446) (0.043)*0 (0.046)°° (0 001)*00 (0.028)00 Rule of Law -0.120 -0 011 (0.000)°°° (0.578) Corruption -0.208 -0.004 (0.000)°°° (0.822) Institutional Development -0.377 0.165 (0.000)0°0 (0.000)°°° GDP per capita -0.146 0.096 (0.000)000 (0.000)*00 Constant -0.455 -0.493 -0.514 -1.303 (0.002)00° (0000)0°0 (0.000)000 (0 000)000 0.037 0.046 0.047 0.041 0.077 0.077 0.098 0.097 Observations 6111 6111 6687 6716 4135 4135 4673 4693 0,00,0*, indicate significance levels of 10,5, and I percent, respectively. 44 Table VIII Concentration, Financing Obstacles and Access to Bank Finance - The Interaction with the Institutional Environment The regression estimated in columns 1-4 is: General Financing Obstacle = a+ Govermnent+ f6 Foreign + 03Exporter+ fManufacturing+ fiServices + N6Sales +j7No. of Competitors +,s Inflation + f,Growth + ploConcentration + p Institution + Pl2 Concentrationlstution+ E. General Financing Obstacle is the response to the question "How problematic is financtng for the operation and growth of your bustness?" Answers vary between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Government and Foreign are dummy variables that take the value I if the firm has govermment or foreign ownership and zero if noL Exporter is a dummy variable that ndicates if the firm is an exporting firm. Manufacturing and Services are industry dummies. Sales is the logarithm of sales in USS. Number of Competitors is the logarithm of the number of competitors the firn has. Growth is the growth rate of GDP. Inflation is the log difference of the consumer price index. Concentration is the share of the largest three banks in total banking sector assets. Institution is one of four variables. Rule of Law is the degree to whicb citizens rust ita country's legal system. Corruption indicates the degree to wbich there is no corruption in a country. Instutional Development is an average of six indicators measuring voice and accountability, control of corruption, regulatory quality, political stability, rule of law, and government efficiency. GDP per capita is real GDP per capita. The regression is run with ordered probit. The regression estiuated in columns 5-8 is. Bank Finance - a + p Government + f6 Foreign + f6 Exporter+ 04Manufactunng+ psServices + 5eSales +pNo. of Competitors +flnflation + , Growth + p,iConcentation + p lnstitution+ 512 Concentrationlnstitution + e.- Bank Fmance is a dummy variable that takes on the value one if the firm receives bank finance, and zero The regression is rtn as probit. Detailed varnable definitions and sources are given in the appendix P-values are reported in parentheses. General General General General Financing Financing Fmancing Financing Obstacle Obstacle Obstacle Obstacle Bank Fnance Bank Finance Bank Fmance Bank Finance Concentration 1.357 1.789 0.153 0.836 0.140 -1.419 -0.383 -2.341 (0.000)'0 (0.000)'* (0 051)) (0.030)* (0.756) (0.000)* (0.002)0 (0.00l)* RuleofLaw -0.014 0.036 (0.700) (0.523) Concentration*Rule of Law -0.217 -0.097 (0.002)*** (0.371) Corruption 0.009 -0.214 (0.827) (0.001)** Concentration*Corruption -0.398 0.381 (0.000)*** (0.000)*** Institutional Development -0.215 -0.187 (0.00l)*** (0.058)* Concentration5lnstitutional -0.292 0.606 Development (0.006)*** (0.000)** GDP per capita -0.088 -0.060 (0.004)0*$ (0.275) Concentration*GDP per capita -0.104 0 270 (0.038)' (0.002)* 0.037 0.048 0.048 0.041 0.077 0.079 0.100 0.098 Observations 6111 6111 6687 6716 4135 4135 4673 4693 indicate significance levels of 10,5, and I percent, respectively. 45 Table IX Concentration, Financing Obstacles and Access to Bank Finance - Controlling for the Development and Structure of the Banking Sector The regression estimated in columns 1-3 is: General Financing Obstacle - a + ,1 Government + I2 Foreign + 03Exporter + f4Manufacturing + ,6 Services + 06Sales +p7No. of Competitors +f51nflation + pgGrowth + pConcentrtion + pi Bank + E. Gener Financing Obstacle Is the response to the question "How problematic is financing for the opestion and growth of your business?" Answers valy between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Government and Foreign are dummy variables that take the value I if the firm has government or foreign ownership and zero if not Exporter is a dummy vanable that indicates if the firm is an exporting firm. Manufacturing and Services are industry dummes. Sales is the logarithm of sales in USS. Number of Competitors is the logarithm of the number of competitors tbe fihn has. Growth is the growth rate of GDP. Inflation is the log difference of the consumer pnrce index. Concentration is the share of the largest three banks in total banking sector assets. Bank is one of three variables. Private Credit is claims on the private sector by financial institubons as share of GDP. Forign Bank Share is the sbare of assets in banks that are majority foreign owned. Public Bank Sbare is the share of assets in banks that are majority state-owned. The regression is run with ordered probit The regression estimated in columns 4-6 is: Bank Finance = a + 01 Govemment + f6 Foreign + fl Exporter + 0 Manufacturing+ PsSrvices+ p6Sales+p7No. of Competitors +IInflation+ PgGrowth+ ,oConcentration+ p Bank+ E.. BankFinance isadummlyvarnablethat takes on the value one if the fiun receives bank finance, and zero The regression is run as probit Detailed variable definitions and sources are given in the appendix. P- values are reported in parentheses. General Generl General Financng Financing Financing Obstacle Obstacle Obstacle Bank Finance Bank Funance Bank Finance Govenment 0.047 0.023 0.035 -0.054 0.021 0.014 (0.306) (0.682) (0.523) (0.404) (0.774) (0.846) Foreign -0.363 -0.335 -0.348 -0.047 -0.057 -0.047 (0.000)**' (0.000)*" (0.000)e** (0.418) (0.404) (0.479) Exporter -0.044 -0.004 0.017 0.323 0.248 0.249 (0.155) (0.925) (0.647) (0.000)00* (0.000)* (0.000)"' Manufacturing -0.083 -0.132 -0.135 0.089 0.183 0.173 (0.039)00 (0.009)*** (0.006)*** (0.152) (0.012)** (0.015)** Services -0.277 -0.301 -0.292 -0.068 0.001 -0 001 (0.000)"* (0.000)*** (0.000)°* (0.244) (0.988) (0.989) Sales -0.012 -0 018 -0.016 0.042 0.044 0.035 (0.000)*** (0.000)**' (0.000)*** (0.000)oo * (0.000)*** (0.000)** Number of Competitors 0.022 0.031 0.015 -0.028 0.010 -0.001 (0.632) (0.579) (0.797) (0.675) (0 903) (0.986) Inflation 0.123 0.434 0.369 -0.209 -0.257 -0.125 (0.255) (0.001)** (0.005)*es (0.122) (0.133) (0.477) Growth -7.072 -8.457 -8.829 3.173 4.365 4.222 (0.000)** (0.000)ee (0.ooo)Se (0.000)*¢* (0.000)*** (0.000)*** Concentration 0.352 0.223 0.253 -0.310 40.066 -0.129 (0.000)*** (0.045)" (0.017)** (0.01 1)** (0.678) (0.429) Private Credit -0.193 -0.065 (0.000)"* (0.390) Foreign Bank Share -0.001 0.002 (0.095)e (0.072)* Public Bank Share 0.003 -0.004 (0.002)0*e (0.002)*** Constant -.476 40.730 -0.484 (0.000)*°' (0.000)'*' (0.002)*** 0 035 0.038 0.041 0.084 0.083 0.081 Observations 6346 4405 4578 4357 3099 3226 ' indicate significance levels of 10,5, and I pereent, respectively. 46 Table X Concentration, Financing Obstacles and Access to Bank Finance - The Interaction with the Ownership Structure of the Banking Sector The regression estimated in columns 1-3 is: General Financing Obstacle = a + Pi Government + f6 Foreign + f6 Exporter + Pi Manufactunng + fs Services + P6 Sales +>No. of Competitors +pglnflation + f,Growth + P,Concentration+ ,,Bank+ 512Concentration Bank + a. General Financng Obstacle is the response to the question "How problematic is financing for the operation and growth of your business?" Answers vary between I (no obstacle), 2 (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Government and Foreign are dunnmy variables that take the value I if the firm has government or foreign ownership and zero if noL Exporter is a dunmmy vanable that indicates if the firm is an exporting firmL Manufacturing and Services are industry dummies. Sales is the logarithm of sales in USS. Number of Competitors is the logarithm of the number of competitors the firm has. Growth is the growth rate of GDP. Inflation is the log difference of the consumner price index. Concentration is the share of the largest three banks in total banking sector assets Bank is one of three variables. Private Credit is claims on the private sector by financial institutions as share of GDP. Foreign Bank Share is the share of assets in banks that are majority foreign owned. Public Bank Share is the share of assets in banks that are majority state-owned.The regression is run with ordered probit The regression estimated in columns 4-6 is: Bank Finance = a + , Govemment + f Foreign + %3Exporter+ 04Manufacturing+ ,sServices+ fSales+>No. of Competitors + Inflation + N Growth + ,oConcentration + p Bank+ 012 Concentration *Bank + F.. Bank Finance is a dunmmy variable that takes on the value one if the firm receives bank finance, and zero The regression is run as probit. Detailed variable definitions and sources are given m the appendix. P-values are reported in parentheses. General General General Financing Financing Financing Obstacle Obstacle Obstacle Bank Finance Bank Finance Bank Finance Concentration 0.273 0434 -0.128 -0.107 -0.147 0.004 (0.007)0'' (0 001)"' (0.385) (0.489) (0.483) (0.986) Private Credit -0.293 0.195 (0.001)''* (0.188) ConcentrationVPrivate Credit 0.220 -0.618 (0.218) (0.037)" Foreign Bank Share 0.005 0.000 (0.055)' (0.990) Concentration*Foreign Bank Share -0.010 0.004 (0.008)"' (0.544) Public Bank Share -0.004 -0.002 (0.049)** (0.608) Concentration 0 014 -0.004 Public Bank Share (0.000)*** (0.422) 0.036 0.039 0042 0085 0.083 0.081 Observations 6346 4405 4578 4357 3099 3226 ,","'indicate significance levels of 10,5, and I percent, respectively. 47 Table XI Concentration, Financing Obstacles and Individual Financing Obstacles The regression estimated in Panel A is: Financing Obstacle = a + 1 Government + 02 Foreign + P3 Exporter + 04 Manufacturng + 5 Services + 6 Sales +fNo. of Competitors +Is Inflation + f6 Growth + PioConcentration + a. Financing Obstacle is the response to one of seven questions. Answers vary between I (no obstacle), 2. (minor obstacle), 3 (moderate obstacle), and 4 (major obstacle). Govemment and Foreign are dumtny variables that take the value I if the firm has govemment or foreign ownership and zero if noL Exporter is a dummy vanable that indicates if the firm is an exporting firm. Manufacturing and Services are industry dummies. Sales is the logarithm of sales in USS. Number of Competitors is the loganthm of the number of competitors the firm has. Growth is the growth rate of GDP. Inflation is the log difference of the consumer price index. Concentration is the share of the largest three banks in total banking sector assets. The regression estimated m Panel B is: Financmg Obstacle =a+ , Govermment+ f6 Foreign + liExporter+ P4Manufacturing+ I3Services + 06Sales+7No. of Competitors +0stnflation+ CGrowth + PIoConcenbation + p , Institutonal Development + Ps2 Concenbation'lnstitutional Development + a The regression is rnm with ordered probt. Detailed variable definitions and sources are given in the appendix. P-values are reported in parentheses. Panel A High interest Special Long-term Credit Bank Bank official rates connection loans information Collateral bureaucracy corruption Government -0.159 -0.257 -0.178 -0.110 -0.180 -0.150 -0.249 (0.001)'*' (0.000)*** (0.000)ee (0.018)0* (0.000)*** (0.00l)4* (0.000)*** Foreign -0.222 -0.211 -0.216 -0 090 -0.283 -0.122 -0.168 (o.000)** (0.000)*Qe (0.000)o** (0.014)0* (0.000)*** (o00'J'J)* (o.o0o)** Exporter 0.026 -0.079 -0.000 0.052 -0.025 -0.024 -0.162 (0.405) (0.008)0e0 (0.994) (0.096)e (0 401) (0.410) (O.000)*** Manufacturing -0 023 -0.057 -0.055 0.028 -0.019 -0.021 -0.044 (0.588) (0.147) (0.281) (0.505) (0.623) (0.593) (0336) Services -0.261 -0.116 -0.227 -0.137 -0.154 -0.131 -0.052 (0.000)*** (0.003)000 (0.000)** (0.001)000 (0.000)*P* (0.001)000 (0.234) Sales -0.012 -0 004 -0.011 -0.004 -0 004 -0.006 -0.010 (0.000)''@ (0.115) (0000)0* (0.105) (0.052)0 (0011)** (0.000)0** Number of 0148 -0004 0072 0.199 0.051 0.095 0.133 Competitors (0.002)**- (0.926) (0.172) (0.000)*°° (0.246) (0.031)°° (0.014)0* Inflation 0.121 -0.352 0.180 -0 616 0.027 0 081 -0.062 (0.330) (0.001)0*9 (0 132) (0.000)**° (0.792) (0.416) (0.591) Growth -6.854 -5.237 -8.219 -6.757 -5.145 -3.362 -6.079 (0.000)**o (0.000)0*e (0.000)** (0.000)*** (0.000)**0 (0.000)*o* (0.000)0u Concentration 0.177 -0045 0.501 0.465 -0.104 -A08 0.474 (0.019)" (0.542) (0.000)*¢* (0000)900 (0.160) (0.000)*** (0.000)¢o Observations 6822 6461 5382 5955 6492 6629 5761 Panel B High mterest Special Long-term Credit Bank Bank official rates connection loans information Collateral bureaucracy corruption Concentration -0.230 -0.257 0.120 0.208 -0.176 -0.517 0.120 (0.006)*** (0.001)0** (0.230) (0.010)** (0.023)** (0.ooo)0e (0 179) Institutional Development -0.596 -0.055 -0.548 -0.055 -0.072 0.022 -0 294 (0.000)*** (0.379) (0.000)"* (0.402) (0.225) (0.721) (0.000)9** ConcentrationOlnstitutional 0.264 -0.361 0.020 -0.481 -0.065 -0.206 -0.274 Development (0.013)** (0.001)00° (0.860) (0.000)*** (0.524) (0.049)** (0.032)** Observations 6822 6461 5382 5955 6492 6629 5761 ¶", indicate significance levels of 10,5, and I percent, respectively. 48 ADpendix: Variables and Sources Variable Definifton Original source GDP per capita Real per capita GDP, average 1995-99 World Development Indicators Growth Growth rate of GDP, average 1995-99 World Development Indicators Inflation rate Log difference of Consumer Price Index International Financial Statistics (IFS), line 64 Private Credit {(0.5)*[F(t)/P_e(t) + F(t-l)/P_e(t-l)]}/[GDP(t)/P_a(t)], where F IFS is credit by deposit money banks and other financial institutions to the private sector (lines 22d and 42d), GDP is line 99b, P_e is end-of period CPI (line 64) and P_a is the average CPI for the year. Law and Order Measure of the law and order tradition of a country. It is an International Country Risk average over 1995-97. It ranges from 6, strong law and order Guide (ICRG). tradition, to 1, weak law and order tradition. Corruption Measure of corruption in government. It ranges from I to 6 and International Country Risk is an average over 1995-97. Lower scores indicate that "high Guide (ICRG). government officials are likely to demand special payments" and "illegal payments are generally expected throughout lower levels of govemment" in the form of "bribes connected with import and export licenses, exchange controls, tax assessment, policy protection, or loans." Institutional Development Average value of six indicators measuring voice and Kaufman, Kraay and Zoido- accountability, political stability, regulatory quality, govemment Lobaton (2001) effectiveness, control of corruption and rule of law. Each of these indicators, in tum is constructed from a wide array of survey indicators in the respective area. Restrict Degree to which banks' activities are restricted outside the credit Barth, Caprio and Levine and deposit business (2001) Fraction denied Share of bank license applications rejected. If there were no Barth, Caprio and Levine applications, the value is one (2001) Foreign bank share Share of banking assets in banks that are majority owned by Barth, Caprio and Levine foreign shareholders (2001) Public bank share Share of banking assets in banks that are majority owned by the Barth, Caprio and Levine government (2001) Banking freedom General indicator of the absence of govermnent interference in Heritage Foundation the banking sector Ctedit Registry Average of four variables that indicate (i) whether the credit Galindo and Miller (2001) registry offers only negative or also positive information about borrowers, (ii) the amount of information available about borrowers, (iii) which institutions have access to the data, and (iv) whether information is available for each loan or only aggregated for each borrower. The indicator is normalized between zero and one, with higher values indicating more 49 information being available to more institutions. Government Dummy variable that takes on the value one if any govermnent World Business Environment agency or state body has a financial stake in the ownership of the Survey (WBES) firm, zero otherwise. Foreign Dummy variable that takes on the value one if any foreign World Business Environment company or individual has a financial stake in the ownership of Survey (WBES) the firm, zero otherwise. Exporter Dummy variable that takes on the value one if firm exports, zero World Business Environment otherwise. Survey (WBES) Manufacturing Dummy variable that takes on the value one if firm is in the World Business Environment manufacturing industry, zero otherwise. Survey (WBES) Services Dummy variable that takes on the value one if firm is in the World Business Environment service industry, zero otherwise. Survey (WBES) No. of Competitors Regarding your firm's major product line, how many competitors World Business Environment do you face in your market? Survey (WBES) Firm size dummies A firm is defined as small if it has between 5 and 50 employees, World Business Environment medium size if it has between 51 and 500 employees and large if Survey (WBES) it has more than 500 employees. Sales Logarithm of firm sales World Business Enviromment Survey (WBES) General Financing How problematic is financing for the operation and growth of World Business Environment Obstacle your business: no obstacle (1), a minor obstacle (2), a moderate Survey (WBES) obstacle (3) or a major obstacle (4)? Collateral Are collateral requirements of banks/fmnancial institutions no World Business Environment obstacle (1), a minor obstacle (2), a moderate obstacle (3) or a Survey (WBES) major obstacle (4)? Bank bureaucracy Is bank paperwork/bureaucracy no obstacle (1), a minor obstacle World Business Environment (2), a moderate obstacle (3) or a major obstacle (4)? Survey (WBES) High interest rates Are high interest rates no obstacle (1), a minor obstacle (2), a World Business Environment moderate obstacle (3) or a major obstacle (4)? Survey (WBES) Special connections Is the need of of special connections with banks/financial World Business Environment institutions no obstacle (1), a minor obstacle (2), a moderate Survey (WBES) obstacle (3) or a major obstacle (4)? Credit mfornation Is inadequate credit/financial information on costumners no World Busmess Environment obstacle (1), a minor obstacle (2), a moderate obstacle (3) or a Survey (WBES) major obstacle (4)? Long-term Is the access to long-term finance no obstacle (1), a minor World Business Enviromment loans obstacle (2), a moderate obstacle (3) or a major obstacle (4)? Survey (WBES) Bank official corruption Is the corruption of bank officials no obstacle (1), a minor World Business Enviromment obstacle (2), a moderate obstacle (3) or a major obstacle (4)? Survey (WBES) Bank Finance Dummy variable that takes on value one if firm has financed its World Business Environment investment with loans from commercial banks, zero otherwise Survey (WBES) 50 Policy Research Working Paper Series Contact Title Author Date for paper WPS2968 Refining Policy with the Poor: Local Edwin Shanks January 2003 N. Lopez Consultations on the Draft Carrie Turk 88032 Comprehensive Poverty Reduction and Growth Strategy in Vietnam WPS2969 Fostering Community-Driven Monica Das Gupta January 2003 M. Das Gupta Development: What Role for the Helene Grandvoinnet 31983 State? Mattia Romani WPS2970 The Social Impact of Social Funds Vijayendra Rao February 2003 P Sader in Jamaica: A Mixed-Methods Ana Marfa lbainez 33902 Analysis of Participation, Targeting, and Collective Action in Community- Driven Development WPS2971 Short but not Sweet New Evidence Jishnu Das February 2003 H Sladovich on Short Duration Morbidities Carolina Sanchez-Paramo 37698 from India WPS2972 Economic Growth, Inequality, and Richard H Adams, Jr February 2003 N Obias Poverty Findings from a New Data Set 31986 WPS2973 Intellectual Property Rights, Guifang Yang February 2003 P. Flewitt Licensing, and Innovation Keith E Maskus 32724 WPS2974 From Knowledge to Wealth: Alfred Watkins February 2003 A Watkins Transforming Russian Science and 37277 Technology for a Modern Knowledge Economy WPS2975 Policy Options for Meeting the Francisco H. G. Ferreira February 2003 P. Sader Millennium Development Goals in Phillippe G. Leite 33902 Brazil Can Micro-Simulations Help? WPS2976 Rural Extension Services Jock R. Anderson February 2003 P Kokila Gershon Feder 33716 WPS2977 The Strategic Use and Potential Christopher Desmond February 2003 H Sladovich for an HIV Vaccine in Southern Africa Robert Greener 37698 WPS2978 The Epidemiological Impact of an HIV Nico J. D. Nagelkerke February 2003 H Sladovich Vaccine on the HIV/AIDS Epidemic Sake J. De Vlas 37698 in Southern India WPS2979 Regulation and Internet Use in Scott Wallsten March 2003 P. Sintim-Aboagye Developing Countries 37644 WPS2980 Living and Dying with Hard Pegs: Augusto de la Torre March 2003 E Khine The Rise and Fall of Argentina's Eduardo Levy Yeyati 37471 Currency Board Sergio L Schmukler WPS2981 Voice Lessons Local Government Vivi Alatas March 2003 A Sachdeva Organizations, Social Organizations, Lant Pritchett 82717 and the Quality of Local Governance Anna Wetterberg WPS2982 Trade Liberalization and Labor Nina Pavcnik March 2003 A. Pillay Market Adjustment in Brazil Andreas Blom 88046 Pinelopi Goldberg Norbert Schady Policy Research Working Paper Series Contact Title Author Date for paper WPS2983 Telecommunication Reform in Ghana Luke Haggarty March 2003 P Sintim-Aboagye Mary M. Shirley 37644 Scott Wallsten WPS2984 Finance and Income Inequality. George Clarke March 2003 P Sintim-Aboagye Test of Alternative Theories Lixin Colin Xu 37644 Heng-fu Zou WPS2985 The Impact of Minimum Wages on Vivi Alatas March 2003 T. Mailei Employment in a Low Income Lisa Cameron 87347 Country: An Evaluation Using the Difference-in-Differences Approach WPS2986 Government Bonds in Domestic and Stijn Claessens March 2003 E. Khine Foreign Currency. The Role of Daniela Klingebiel 37471 Macroeconomic and Institutional Sergio Schmukler Factors WPS2987 East Asia's Dynamic Development Ho-Chul Lee March 2003 L. James Model and the Republic of Korea's Mary P. McNulty 35621 Experiences WPS2988 Trade Facilitation and Economic John S Wilson March 2003 P Flewitt Development. Measuring the Impact Catherine L. Mann 32724 Tsunehiro Otsuki WPS2989 Decentralization and Public Services: Peyvand Khaleghian March 2003 H. Sladovich The Case of Immunization 37698 WPS2990 Ways Out of Poverty Diffusing Best Michael Klein March 2003 F Shah Practices and Creating Capabilities- 84846 Perspectives on Policies for Poverty Reduction WPS2991 Tenure Security and Land-Related Klaus Deininger March 2003 M Fernandez Investment Evidence from Ethiopia Songqing Jin 33766 Berhanu Adenew Samuel Gebre-Selassie Berhanu Nega WPS2992 Market and Nonmarket Transfers of Klaus Deininger March 2003 M. Fernandez Land in Ethiopia: Implications for Songqing Jin 33766 Efficiency, Equity, and Nonfarm Berhanu Adenew Development Samuel Gebre-Selassie Mulat Demeke WPS2993 Dealing with the Coffee Crisis in Panos Varangis March 2003 P. Varangis Central America: Impacts and Paul Siegel 33852 Strategies Daniele Giovannucci Bryan Lewin WPS2994 Options for Financing Lifelong Miguel Palacios March 2003 E. James Learning 31756 WPS2995 Commodity Market Reform in Africa: Takamasa Akiyama March 2003 P. Kokila Some Recent Experience John Baffes 33716 Donald F Larson Panos Varangis