POLICY RESEARCH WORKING PAPER 2432 Funding Growth in Bank- How the relative development of a country's Based and Market-Based stock market and banking Financial System s system affects firms'growth is closely tied to how well developed the country's Evidence from Firm-Level Data contracting environment is. How differences in the contracting environment Asll Demirgu-Kunt affect the relative Vojislav Maksimovic development of the stock market or banking system may have implications for which firms and which projects get financing. The World Bank Development Research Group Finance August 2000 POLICY RESEARCH WORKING PAPER 2432 Summary findings Demirgiuc-Kunt and Maksimovic investigate whether banking system have different effects on access to firms' access to external financing to fund growth differs external markets. The development of securities markets between market-based and bank-based financial systems. is related more to the availability of long-term financing, Using firm-level data for 40 countries, they compute whereas the development of the banking sector is related the proportion of firrns in each country that relies on more to the availability of short-term financing. external finance and examine how that proportion They find no evidence, however, that firms' access to differs across financial systems. They find that the external financing is predicted by an index of the development of a country's legal system predicts access development of stock markets relative to the to external finance and that stock markets and the development of the banking system. This paper-a product of Finance, Development Research Group-is part of a larger effort in the group to study financial structure and development. The study was funded by the Bank's Research Support Budget under the research project "Financial Structure and Economic Development" (RPO 682-41). Copies of this 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 www.worldbank.org/research/workingpapers. The authors may be contacted at ademirguckunt@worldbank.org or vmaksimovic@worldbank.org. August 2000. (36 pages) The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the niames of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the autbors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Produced by the Policy Research Dissemination Center Funding Growth in Bank-Based and Market-Based Financial Systems: Evidence from Firm Level Data Asll Demirguc-Kunt Vojislav Maksimovic* * The authors are at the World Bank and the University of Maryland at College Park, respectively. We would like to thank Ross Levine and Thorsten Beck for useful discussions. 1. INTRODUCTION A key question in development economics is the relation between a country's financial system and its economic development. Historians such as Gerschenkron (1962) have sought to explain a perceived relation between the differences in the pattern of economic development between Britain and the Continental European economies and the differences between bank-based and market-based financial systems. More recently, the differences in the relative performance of the Japanese and the US economies have led observers to conclude that bank-based and market-based financial systems may produce different growth patterns. 1 This view has been challenged by Laporta, Lopez-de-Silanes, Shleifer and Vishny (LLSV) (1998, 1999), who argue that the legal system in a country is a primary determinant of the effectiveness of its financial system. An implication of this hypothesis is that the distinction between market-based and bank-based financial systems may not be of primary importance for policy. In this paper we use firm-level data from a panel of forty countries to analyze how a country's legal and financial systems affect firms' access to external finance to fund growth. For each country we predict a financial system based on the country's legal environment. We use our estimates to ask: Does the financial system have an effect independent of the legal system? Is the use of external financing different in market- based and bank-based systems? Do the market-based and bank-based systems differ in the provision of long-term and short-term funds? We find that the use of external financing by firms is positively related to the development of both the predicted banking system and the securities markets in each 3 country. However, in our sample we do not find evidence that variations in the development of the financial system that are unrelated to the legal system affect access to external finance. In particular, we find no evidence that firms use external financing differently if they are in countries classified as bank-based or market-based, on the basis of the development of their banking sector relative to their securities markets. These results are consistent with the LLSV approach that stresses the primacy of the legal system. The policy implication that flows from the results is that the way to improve access to external finance is to aid in the development of a country's legal system, and then to let firms and investors contract either directly (as in a market-based system) or through the intermediation of banks. We also find that securities markets and bank development have a different effect on the type of external finance firms obtain, particularly at relatively low levels of financial development. In those countries where the legal contracting environment predicts a high level of development for securities markets, more firms grow at rates requiring long-term external finance. We do not find the same effect for predicted bank development. Thus, especially for countries with lower levels of financial development, differences in contracting environments that affect the relative development of the stock market and the banking system may have implications for which firms and which projects obtain financing. There exists a growing literature on the effect of financial sector development on economic development. King and Levine (1993a,b) highlight the importance of financial development for macro-economic growth. Recently Levine and Zervos (1998), Rajan and ' For a critical examination of the effect of the legal and market environment on corporate finance see Stulz (1999). Allen (1993) and Allen and Gale (1999) provide analyses of the relative benefits of market-based 4 Zingales (1998) and Demirguc-Kunt and Maksimovic (1998) explore the relation between financial development and growth of countries, industries and firms, respectively.2 The importance of the legal system for corporate finance was first explored by LLSV (1998). Modigliani and Perotti (1999) argue that in the absence of a strong legal system that can protect the rights of external investors, financial transactions are intermediated through institutions or concentrated among agents who have sufficient bargaining power to enforce their rights privately. Empirical evidence on the effect of legal effectiveness on firm growth and financing is provided by Demirguc-Kunt and Maksimovic (1998, 1999), and on growth at more aggregated levels by Levine (1998, 1999, 2000). This paper extends the methodology of Demirguc-Kunt and Maksimovic (1998) to address the questions of the differences in bank-based and market-based systems in firm growth. The rest of the paper is organized as follows. Section 2. briefly discusses reasons to believe that bank-based and market-based systems perform differently, and our approach to testing those differences empirically. Section 3. introduces the data and summary statistics. Our principal results are reported in Section 4.. Section 5. concludes. 2. BANK-BASED AND MARKET-BASED FINANCIAL SYSTEMS 2.1 How do the systems differ? Among a financial system's major tasks is to mobilize resources for investment, select investment projects to be funded, and to provide incentives for the monitoring of and bank-based financial systems. 2 See also Wurgler (2000) for an analysis of industry growth. 5 the performance of the funded investments. A large body of theoretical and empirical research has analyzed how these tasks are performed in a market-based system, and how they are performed in a system where banks and other financial intermediaries play a major role. This research has identified significant differences in incentives. These differences raise the possibility that a bank-based or a market-based system is inherently superior, and that economic performance can be enhanced by adopting the superior system. A second approach, identified with LLSV (1999), stresses the importance of the legal system in determining the enforceable contracts between firms and investors. According to this view, the relevant differences between countries is in the extent to which their financial systems protect investor rights. The distinction between bank-based and market-based systems is seen as secondary. In our examination of the differences between bank-based and market-based financial systems we adopt a maintained hypothesis that has elements of both of these approaches. We posit that there exist significant differences in outcomes between systems in which financial intermediaries like banks play the dominant role and those where they do not. For example, as explored by Allen and Gale (1999), banks and stock markets may have a comparative advantage in selecting different types of investment projects. Banks may also have a comparative advantage in providing short-term financing. In common with the legal approach, we posit that the absolute quality of the banks and securities markets in a country depends on the legal system's ability to enforce contracts. However, we argue that the legal systems in different countries may have a comparative advantage in supporting a quality banking system or a quality securities 6 markets. Thus, for example, a country with an inefficient legal system may have a low- quality financial system. However, it may, through a combination of administrative regulation of the banking system, and strong banks with bargaining power vis-a-vis their customers, partially compensate for the effect of the deficiency of the legal system on banks. It may be more difficult to compensate for the effect of poor legal protections on a securities markets. Thus, while the level of development of the legal system in each country may be the major determinant of the quantity of financial services supplied, the comparative advantage in supporting intermediaries and markets may determine the optimal mix of banks versus markets. These considerations suggest the following hypotheses: Hi. For each country there is a "warranted" level of development of the banking sector and of stock markets, as a function of the level of development of the contracting environment. The provision of external financing to firms is greater, the higher the warranted level of development of these sectors. H2. The expansion of one of the sectors, banks or securities markets beyond the levels warranted by the contracting environment is unlikely to produce an improved allocation of resources. H3. Because the banking system and securities markets have a comparative advantage in providing different services, cross-country differences in the warranted development levels of markets and the banking sectors may affect the type of finance constraints faced by firms. 7 2.2 Testing for differences in performance between the systems Differences between outcomes in market-based and bank-based systems should, if they exist, be observable at the country, industry or firm levels. In principle, a test would relate a performance measure, usually the growth rate, to the financial system or legal system characteristics. While this results in straightforward applications at the country level, there exists a potential selection bias when this procedure is applied at lower levels of aggregation, such as the industry and firm levels. The selection bias may arise because the way in which production is organized in different countries may depend on their legal and financial systems. Thus, the firms that are observed in a country are those that are adapted to the financial system of that country. Analyzing growth rates of those firms does not take into account the possibility that a different financial system might induce a different mix of firms, and that the different mix might increase wealth. To fix ideas, consider an example involving two countries, B and M. Country B has a bank-based financial system (perhaps because its legal system favors that type of contracting). Country M has a market-based system. Assume that the two financial systems have different comparative advantages in supplying financing. In particular, assume that market-based systems are superior at providing long-term financing. Consider entrepreneurs in each country starting firms in the same industry. Entrepreneurs in country M have a greater choice of technology and organizational forms since they have greater access to long-term financing. As a result, economy M is better off. However, once the initial investment is made, each individual firm, and the industry as a whole, may grow at the same rate in country B and in country M. Indeed, firms in 8 country B may grow faster, because they can switch to a superior technology as they accumulate enough funds over time to self-finance its acquisition. In this case, a comparison of firm or industry growth rates across countries may not identify the benefits of a market-based financial system. An alternative approach, developed in Demirguc-Kunt and Maksimovic (1998), is to test for differences between financial systems by testing whether the proportion of firms growing at rates that exceed the rate that they can self-finance, or finance using short-term instruments only, differs across different financial or legal systems.3 This is the approach we employ below, using firm-specific data to determine whether each firm in the sample is constrained. While the use of firm-specific data brings advantages, it also entails two potential costs. First, the firms for which data is available are likely to be a relatively small number of the largest publicly traded firms in each economy. While such firms are of independent interest, they may not be fully representative of firms in the economy.4 Second, as discussed by Ball (1995), the quality of firm-level financial data may differ across countries. Thus, the findings of firm-level and industry-level studies need to be assessed jointly. 3. DATA AND SUMMARY STATISTICS 3.1 Description of Sample The firm-level data consist of financial statements for the largest publicly traded manufacturing firms in 40 countries (SIC codes 2000-3999). Our sample of firms contains 45,598 annual observations over the period 1989-1996. The sample is from 3 This approach would identify the financial system in economy M above as being superior. 9 Worldscope and contains data from both developed and developing countries as listed in Table Al in the Appendix. For each of the countries we also use data on financial system development compiled by Beck, Demirguc-Kunt and Levine (1999). In Table 1 we present pertinent facts about the level of economic and institutional development in the sample countries. The countries are arranged from highest to lowest average per capita Gross Domestic Product (RGDPPC) in 1990 dollars. They range from Switzerland, with a per capita income of $26,972 to Pakistan, with a per capita income of $319. Table 1 Legal and Financial Indicators GDP/CAP is the real GDP per capita in 1990 US$. Law and order indicator, produced by Intemational Country Risk rating agency, reflects the degree to which the citizens of a country are willing to accept the established institutions to make and implement laws and adjudicate disputes. It is scored 0-6 with higher scores indicating sound political institutions and a strong court system. Lower scores indicate a tradition of depending on physical force or illegal means to settle claims. Common Law Dummy takes the value one for common law countries and the value zero for others. Creditor rights is an index that ranges from 0 to 4 and aggregates creditor rights and Shareholder rights is an index that ranges from 0 to 5 and aggregates shareholder rights as described in the text. These three variables are obtained from La Porta, Lopez-de-Silanes, Shleifer and Vishny (1996). Tumover is the total value of shares traded in the stock exchange divided by market capitalization. Stock market data are from IFC's Emerging Market Data Base. BankWGDP is the total assets of the deposit money banks divided by GDP. It is obtained from IMF, Intemational Financial Statistics. Marketl is a variable that takes on the value I for market-based financial systems and 0 for bank-based systems as defined in Demirguc-Kunt and Levine (1999). All values are 1989-96 averages. GDP/CAP Law and Common Creditor Shareholder Tumover Bank/GDP Marketl (US S) Order Law Dummy Rights Rights Indicator Index Index Switzerland 26972 6.00 0 1 2 0.74 1.74 0 Japan 23467 5.44 0 2 4 0.43 1.31 0 Norway 22162 6.00 0 2 4 0.52 0.71 0 Denmark 21447 6.00 0 3 2 0.42 0.51 0 United States 19998 6.00 1 1 5 0.71 0.75 1 Sweden 19582 6.00 0 2 3 0.42 0.55 1 Finland 18521 6.00 0 1 3 0.32 0.79 0 Germany 17804 5.75 0 3 1 1.25 1.19 0 France 17588 5.50 0 0 3 0.47 1.01 0 Austria 17433 6.00 0 3 2 0.61 1.25 0 Netherlands 16744 6.00 0 2 2 0.55 1.10 1 Canada 16243 6.00 1 1 5 0.44 0.62 1 Belgium 16104 6.00 0 2 0 0.15 1.07 0 Italy 14783 5.00 0 2 1 0.39 0.72 0 Australia 13873 6.00 1 1 4 0.41 0.73 1 United Kingdom 13067 5.31 1 4 5 0.50 1.13 1 4 Industry-level data may suffer from the opposite bias: many of the firms included in industry statistics are very small and would not qualify for significant external financing under any financial system. See Rajan and Zingales (1999) discussion of European data. 10 Ireland 12034 5.00 1 1 4 0.62 0.36 0 Singapore 11707 5.19 1 4 4 0.47 0.93 1 New Zealand 11332 6.00 1 3 4 0.25 0.76 0 Israel 9787 3.31 1 4 3 0.65 0.95 0 Hong Kong 9565 4.69 1 4 5 0.50 1.49 1 Spain 9506 5.00 0 2 4 0.57 0.95 0 Greece 5257 4.25 0 1 2 0.30 0.42 0 Korea 4785 3.69 0 3 2 1.21 0.53 1 Portugal 4620 5.19 0 1 3 0.33 0.76 0 Argentina 3623 3.56 0 1 4 0.36 0.21 0 Malaysia 2708 3.69 1 4 4 0.44 0.79 1 South Africa 2287 2.69 1 3 5 0.08 0.63 0 Chile 2243 4.19 0 2 5 0.10 0.46 1 Brazil 2034 3.75 0 1 3 0.55 0.32 1 Mexico 1824 3.00 0 0 1 0.41 0.22 1 Turkey 1626 3.19 0 2 2 0.86 0.19 1 Thailand 1517 4.31 1 3 2 0.77 0.77 1 Colombia 1321 1.19 0 0 3 0.09 0.17 0 Peru 775 1.69 0 0 3 0.30 0.11 I Philippines 619 2.13 0 0 3 0.26 0.34 1 Indonesia 610 3.00 0 4 2 0.40 0.45 0 India 405 2.50 1 4 5 0.40 0.34 0 Pakistan 319 1.88 1 4 5 0.29 0.36 0 As an indicator of the ability of finns to enter into financial contracts we use a commercial index of experts' evaluations of the efficiency of the state in enforcing property rights within each country. This measure, produced by the International Country Risk rating agency, reflects the degree to which the citizens of a country are willing to accept the established institutions to make and implement laws and adjudicate disputes. It is scored on a zero to six scale, with higher scores indicating sound political institutions and a strong court system. Lower scores indicate a tradition of depending on physical force or illegal means to settle claims. This indicator has been used in previous studies comparing institutions in different countries (e.g., Knack and Keefer (1995), Demirguc- Kunt and Maksimovic (1998)). We place more weight on this indicator than on a comparison of specific differences in the legal codes across countries. Such a comparison may be misleading, because firms may be able to compensate for the absence of specific legal protections by altering the 11 provisions of contracts. It is likely to be more difficult to compensate for the systemic failures of the legal system to adjudicate claims captured by the law and order indicator. In Demirguc-Kunt and Maksimovic (1999), we show that the index is a good predictor of the use of long-term debt by large firms in our sample of countries. By contrast, we find less evidence that the indicators of specific legal protections identified by LLSV predict the use of long-term debt. However, for completeness we also present indicators obtained by LLSV. Common Law Dummy takes the value one for common law countries and the value zero for others. As argued by LLSV, common law legal systems are more likely to offer protections to outside investors than civil law systems. Creditor rights is an index that ranges from 0 to 4 and aggregates creditor rights, and shareholder rights is an index that ranges from 0 to 5 and aggregates shareholder rights as described in the text. The creditor and shareholder rights variables are described in LLSV. Table 1 shows that our sample contains countries with legal systems of very diverse levels of effectiveness. It contains highly effective common law legal systems (such as the United States and Canada) and less effective legal systems (such as India and Pakistan), as well as highly effective civil systems (such as Switzerland) and less effective systems such as those in Columbia and Peru. For each country we also present three indicators of financial system development. As an indicator of whether the financial system is bank-based or market-based we use a dummy variable, MARKET1, defined in Demirguc-Kunt and Levine (1999). The variable classifies countries as being market-based when they have larger, more active and efficient stock markets compared to banks.5 5 Market I is a dummy that takes the value I for higher than mean values of an aggregate Structure index. Structure index is the means-removed average of relative size, relative activity and relative efficiency 12 We also present two other measures of the development of the market and the banking sector separately. Turnover, TOR, is the total value of shares traded in the stock exchange divided by market capitalization. Stock market data are from IFC's Emerging Market Data Base.6 Bank/GDP is the total assets of the deposit money banks divided by GDP. It is obtained from IMF, International Financial Statistics. Both variables have been used in our previous firm-level studies (Demirguc-Kunt and Maksimovic (1998, 1999). Countries scoring high on TOR include East Asian economies which were experiencing a market boom at this time, and the United States and the United Kingdom. Countries with low scrores include Latin American countries such as Chile and Columbia, and Peru, as well as European countries such as Greece and Portugal. Countries with a large banking sector include Switzerland, Japan, Germany and Hong Kong, whereas Mexico, Turkey and Columbia have small banking sectors relative to their GDP. 3.2 Measures of firm growth To measure whether firms' growth in an economy is financially constrained we adopt the approach of Demirguc-Kunt and Maksimovic (1998). For each firm in an economy we estimate a rate at which it can grow, relying only on its internal funds or on short-term borrowing. We then compute the proportion of firms that grow at rates that exceed each of these two estimated rates each year. We then examine whether the proportions of firms growing faster than each of the two estimated rates differ between bank-based and measures. Relative size is given by the ratio of stock market capitalization to total assets of deposit money banks; relative activity is defined as the total value of stocks traded divided by bank credit to the private sector; and finally relative efficiency is given by the product of total value traded on the stock market and average overhead costs of banks in the country. See Demirguc-Kunt and Levine (1999) for a discussion of alternative ways of defining market-based and bank-based systems. 6An alternative measure, used in Levine (2000), is the ratio of total value traded to GDP. Since our sample consists of firms that are already listed on the stock exchange, the ratio of value traded to market capitalization provides a measure of the activity levels of the financial markets that is more relevant to these firms. 13 market-based financial systems, and whether they are affected by the level of development of the legal system. Our estimate of the firm's growth rate is based on the standard "percentage of sales" financial planning model (Higgins (1974)). This model relates a firm's growth rate to its need for external funds. The external financing need at time t of a firm growing at g, percent a year is given by EFN, =g, * Assets, -(1 + g,) *Earningst * b(1) where EFNt is the external financing need and bt is the proportion of the firm's earnings that are retained for reinvestment at time t. Earnings are calculated after interest and taxes. The first term on the right-hand side is the required investment for a firm growing at g, percent. The second term is the internally available capital for investment, taking the firm's retention ratio as given. The financial planning model makes several implicit assumptions about the relation between the firm's growth rate and the EFN,. First, the ratio of assets used in production to sales is assumed to be constant. Thus, the required total investment increases in proportion to the firm's growth in sales. Second, the firm's profit rate per unit of sales is constant.7 Third, we assume that the economic depreciation of existing assets equals that reported in the financial statements. We use two estimates of each firm's attainable growth rate. The internally financed growth rate IG, is the maximum growth rate that can be financed if a firm relies only on its internal resources and maintains its dividend. It is obtained by assuming that 7 This assumption was examined in Demirguc-Kunt and Maksimovic (1998). The results in that paper were not sensitive to different assumptions about the rate of return on marginal sales. 14 the firm retains all its earnings (i.e., bt =1), equating EFNt to zero and solving (1) for gt, and is given by IGt =ROA,/(J- ROAd, where ROAt is the firm's return on assets, or the ratio of earnings after taxes and interest to total assets. IG, is increasing in the firm's return on assets. Thus, more profitable firms can finance higher growth rates internally. The short-term financed growth rate SGR, is an estimate of the maximum growth rate that can be attained if the firm uses only short-term external financing. It is obtained by using only the value of assets that are not financed by new short-term credit in place of total assets in equation (1). The assets not financed by short-term debt are termed "long-term capital" ROLTCt and are obtained by multiplying total assets by one minus the ratio of short-term liabilities to total assets. More specifically, SFGt is given by SFGt =ROLTC/(J- ROLTCd. The use of the current realized ratio of short-term borrowing to assets to calculate SFGt ensures that the estimate is feasible, and does not assume levels of short-term credit that are so costly that firms would not choose them. The estimates of IGt and SFGt are conservative in several ways. First, each estimated maximum growth rate assumes that a firm utilizes the unconstrained sources of finance no more intensively than it is currently doing.8 Second, firms with spare capacity do not need to invest and may grow at a faster rate than predicted by the financial planning model. We attempt to mitigate the potential problem posed by spare capacity by using each firm' s maximum constrained growth rates averaged over the second half of 8 In the case of IG the unconstrained source of finance is trade credit. In the calculation of SFG the unconstrained sources are trade credit and short-term borrowing. 15 the sample period in our tests below. Third, the financial planning model abstracts from technical advances that reduce the requirements for investment capital. Thus, it may overstate the cost of growth and underestimate the maximum growth rate attainable using unconstrained sources of finance. For each country in the sample we compute the proportion of firms whose mean annual real growth rate of sales exceeds the means of the two maximum constrained growth rates defined above. Thus, taking IG as an example, for each firm f in each country c and for each year t we estimate IGfc, We form a dummy variable for each firm f which takes on the value one if the firm inflation-adjusted realized growth rate exceeds the predicted rate, and zero otherwise: dfct=l if gfct> IGfc and is 0 otherwise. Finally, for each country and each year we obtain STCOUNTC, the proportion of firms that grow at average rates exceeding the IGfc, rate in year t, Ef dfclnct, where nt is the number of firms in each country in year t. We repeat the same calculations with SFG in place of IG to obtain LTCOUNT,t the proportion of firms that grow at average rates exceeding the SFGfc, rate in year t. Thus, LTCOUNTc, is an estimate of the proportion of firms that obtain long- term financing (debt and/or equity), by issuing public or privately placed securities or by borrowing from the financial sector. Our final variable is DCOUNTC, the proportion of firms in a country that grow at a rate that exceeds IG1 but does not exceed SFG,. Thus, this variable measures the proportion of firms that have access to short-term financing, but not necessarily access to long-term financing. Thus, DCOUNT proxies for the relative availability of short-term financing compared to the availability of long-term financing. 16 Table 2 Firm Characteristics LTCOUNT is the proportion of firms in a country whose mean growth of real sales exceeds their mean maximum short-term financed growth rate (SFG). STCOUNT is the proportion of firms whose mean growth of real sales exceeds their mean internally financed growth rate (IG). DCOUNT is given by (STCOUNT-LTCOUNT)/STCOUNT. NFATA is the net fixed assets divided by total assets. NSNFA is the net sales divided by net fixed assets. SIZE is the total assets of the firm divided by the GDP of the country. The data set, obtained from WorldScope, consists of 45,598 annual firm level observations over the period 1989-1996. These are the largest publicly traded manufacturing films in 40 countries. All values are 1989-96 averages. LTCOUNT STCOUNT Y NFATA NSNFA SIZE Argentina 0.41 0.45 0.11 0.49 2.36 2.60 Australia 0.44 0.49 0.13 0.36 3.88 2.90 Austria 1.00 1.00 0.00 0.30 4.87 2.57 Belgium 0.52 0.58 0.11 0.27 5.39 3.65 Brazil 0.42 0.43 0.01 0.56 1.63 3.34 Canada 0.53 0.57 0.07 0.39 4.51 1.66 Chile 0.30 0.38 0.34 0.52 1.60 8.62 Colombia 0.24 0.26 0.14 0.29 3.04 9.20 Denmark 0.42 0.50 0.17 0.36 4.07 1.96 Finland 0.51 0.57 0.11 0.36 4.01 13.60 France 0.41 0.50 0,20 0.22 6.79 1.75 Germany 0.91 0.93 0.02 0.29 6.35 0.67 Greece 0.35 0.45 0.25 0.33 4.11 1.13 Hong Kong 0.47 0.49 0.06 0.38 2.84 5.77 Indonesia 0.50 0.59 0.15 0.39 3.33 1.30 Indonesia 0.43 0.59 0.29 0.41 3.41 0.80 Ireland 0.40 0.52 0.21 0.38 3.47 11.90 Israel 0.68 0.75 0.12 0.30 4.64 6.46 Italy 0.42 0.48 0.12 0.26 4.87 0.99 Japan 0.48 0.55 0.14 0.29 4.02 0.35 Korea 0.69 0.75 0.08 0.39 2.66 4.92 Malaysia 0.51 0.58 0.14 0.46 2.26 3.60 Mexico 0.49 0.53 0.09 0.61 1.37 3.81 Netherlands 0.37 0.47 0.23 0.38 4.56 3.76 New Zealand 0.40 0.42 0.04 0.39 3.44 11.60 Norway 0.46 0.51 0.12 0.31 5.53 5.74 Pakistan 0.28 0.39 0.28 0.37 8.66 0.75 Peru 0.46 0.50 0.10 0.53 1.83 2.30 Philippines 0.28 0.34 0.17 0.44 2.84 2.50 Portugal 0.47 0.51 0.09 0.44 2.76 2.56 Singapore 0.46 0.55 0.19 0.34 3.37 7.62 SouthAfrica 0.11 0.20 0.51 0.35 6.13 5.39 Spain 0.37 0.42 0.17 0.39 3.69 1.41 Sweden 0.44 0.52 0.18 0.33 4.16 7.68 Switzerland 0.48 0.53 0.12 0.37 3.81 8.36 Taiwan 0.37 0.47 0.21 0.40 2.29 5.85 Thailand 0.32 0.48 0.35 0.43 3.10 1.34 Turkey 1.00 1.00 0.00 0.33 6.03 2.39 United Kingdom 0.35 0.44 0.26 0.36 4.85 0.62 United States 0.46 0.51 0.11 0.29 6.20 0.17 17 Table 2 shows the country averages for LTCOUNTC,I, STCOUNTIt and DCOUNTC,. The table also presents three descriptors of the firmns in each country: The net fixed assets divided by total assets NFATA, the net sales divided by net fixed assets NSNFA, and SIZE, the total assets of the firm divided by the GDP of the country. The table shows interesting variation in the proportion of firms obtaining external financing. Thus, for example, approximately half the US firms in our sample grow at rates exceeding IGt, but only 20% of the South African firms do so. The variation in the proportion of firms obtaining external financing may be driven by differences in legal and financial systems. However, they may also be caused by differences in firm characteristics. For example, firms with a higher average ratio of net fixed assets to total assets may require more long term financing than firms with a lower ratio. This may be one of the reasons why we observe a relatively high LTCOUNT for a country like Peru. Also firms that are larger relative to their economy may enjoy better access to the available external financing than smaller firms in the same country. To the extent that the firms in our sample from the less developed economies are larger relative to their economy than firms in more developed economies, Table 2 overstates access to external financing in less developed economies. Finally, inflation adjustment in calculating real sales growth may lead to additional problems in high inflation countries, as in the case of Turkey. In our regressions, we try to control for firm characteristics and macro variables. We also test the sensitivity results to outliers. 18 3.3 Summary Statistics We treat each date/country combination as a separate observation and analyze the resulting panel. Table 3 presents the summary statistics for our sample. Panel A presents the univariate statistics. Table 3 Summary Statistics LTCOUNT is the proportion of firms in a country whose mean growth of real sales exceeds their mean maximum short-term financed growth rate (SFG). STCOUNT is the proportion of firms whose mean growth of real sales exceeds their mean internally financed growth rate (IG). DCOUNT is given by (STCOUNT-LTCOUNT)/STCOUNT. LAW & ORDER, scored 1 to 6, is an indicator of the degree to which the citizens of a country are able to utilize the existing legal system to mediate disputes and enforce contracts. GROWTH is the growth rate of the real GDP per capita. INFLATION is the inflation rate of the GDP deflator. SIZE is given by total assets divided by country GDP. NFATA is the net fixed assets divided by total assets. NSNFA is net sales divided by net fixed assets. MARKET is a dummy variable that takes the value I for values of TOR/(BANK/GDP) that are higher than the sample median and 0 otherwise. COMMON is a dummy that takes the value I for common law countries and the value zero for others. BANK/GDP is the total assets of the deposit money banks divided by GDP. TOR is stock market turnover defined as the total value of shares traded divided by market capitalization. GDP/CAP is the real GDP per capita in thousands of US$. All country level variables are annual figures, averaged over the 1989-1996 period. All firm-level variables are averaged over firms in each country and over the 1989-1996 period. Panel A presents the summary statistics for the countries listed in Table I. Panel B reports correlation coefficients. Panel A: Summary Statistics N Mean Std Dev Minimum Maximum LTCOUNT 389 0.467 0.279 0 1 STCOUNT 389 0.531 0.260 0 1 DCOUNT 383 0.152 0.176 0 1 LAW & ORDER 336 4.546 1.579 1 6 GROWTH 388 0.026 0.036 -0.135 0.114 INFLATION 417 0.170 0.511 -0.001 4.328 SIZE 407 0.007 0.023 0.000 0.199 NFATA 411 0.376 0.093 0.151 1 NSNFA 394 3.929 1.963 1.000 19.627 MARKET 387 0.501 0.501 0 1 COMMON 420 0.333 0.472 0 1 BANK/GDP 405 0.722 0.397 0.058 1.818 TOR 402 0.552 0.607 0.004 5.277 GDP/CAP 396 10.165 8.187 0.242 27.828 19 Panel B: Correlation Matrix LTCOUNT STCOUNT DCOUNT LAW GROWTH INFL. SIZE NFATA NSNFA MARKET COMMON BANK/ TOR GDP STCOUNT .964*** DCOUNT -.570*** -0.380*** LAW .178*** 0.161*** -.243*** GROWTH .145*** .194*** .006 .058 INFLATION .051 .008 -.140** -.313*** -.155*** SIZE .101** .073 -.123** .150*** .059 -.041 NFATA -.126** -.151*** -.028 -.335*** -.002 .423*** -.005 NSNFA .053 .089* .145*** .083 -.130*** -.222*** -.165*** -.672*** MARKET .069 .092* -.018 -.223*** .147*** .140*** -.156*** .177*** -.114** COMMON -.145*** -.106* .171*** -.035 .003 -.154*** -.087* -.009 -.162*** -.085* BANK/GDP .078 .075 -.045 .552*** -.024 -.321*** -.090* -.354*** .143*** -.258*** -.019 TOR .077 .113** .005 .109* .119** -.048 -.131*** -.013 -.029 .460*** -.108** .307*** GDP/CAP .157*** .143*** -.161*** .774*** -.093* -.279*** .192*** -.501*** .299*** -.188*** -.099** .609*** .052 ** and *** indicate significance levels of 10, 5 and I percent respectively. 20 The correlation matrix is presented in Panel B. Inspection of Panel B shows that the measures of the availability of external financing LTCOUNT and STCOUNT are highly positively correlated with the level of development of the legal system. Consistent with Demirguc-Kunt and Maksimovic (1998), a larger proportion of firms in countries with good legal systems grow at rates requiring external financing. More firms also use external financing in economies that are growing fast, and in economies with higher per capita incomes. The firm characteristics associated with external financing are firm size and a low ratio of net fixed assets to total assets. However, the interpretation of the pairwise correlation is unclear. The ratio of net fixed assets to total assets is highly negatively correlated with the efficiency of the legal system, the GDP per capita and with the size of the banking system, and highly positively correlated with the inflation rate. The pairwise correlations between LTCOUNT and STCOUNT and our descriptors of financial structure are weak. STCOUNT is positively related to TOR and to MARKET, a dummy variable which takes a value of 1 when the ratio of TOR to BANK/GDP exceeds the sample median, and zero otherwise. However, LTCOUNT is not significantly correlated with either. BANK/GDP is not significantly correlated with STCOUNT or LTCOUNT. DCOUNT is strongly negatively correlated with LAW and GDP per capita. Thus, in countries with efficient legal systems and high incomes, a smaller proportion of firms has access to short-term financing but grows at rates below those requiring long-term 21 financing. By contrast, in countries in which firms have a high ratio of sales to assets, firms are more likely to rely on short-term rather than long-term financing.9 An interesting finding is that the firmns in our sample in common law countries are less likely to grow at rates requiring external financing than firms in civil law countries. A positive correlation between DCOUNT and the common law dummy also suggests that in common law countries a larger proportion of firms that require external financing grow at rates that do not require access to long-term financing. The pairwise correlation results must be interpreted with caution. Inspection of Panel B shows that in our sample the average firm in countries where the legal system is efficient and in civil law countries is larger relative to its country's GDP then the average firm in countries where the legal system is less efficient and in common law countries. Firm descriptors NFATA and NSNFA are also correlated with the efficiency of the legal system and legal origin. We control for those firm effects in our multivariate analysis. 4. EXCESS GROWTH OF FIRMS AND FINANCIAL STRUCTURE We analyze the effect of a country's financial system on firm growth in three stages. First, we regress our fmancial system indicators, TOR and BANK/GDP on descriptors of the contracting environment. These regressions yield the estimates of the securities markets activity level and the size of the banking sector predicted by the level of development and characteristics of the legal system. We next regress our excess growth variables STCOtNT, LTCOUNT and DCOUNT on these predicted values, and on control variables. These regressions allow us to test whether the legal system 9 Inflation is also negatively correlated with DCOUNT. However, in view of the potential effect of inflation on firn growth rates we treat inflation as a control variable in the regressions and do not interpret it directly. 22 influences excess growth by affecting the development of the financial system. Finally, we augment these regressions by indicators of the relative development of the stock markets to the banking system. These regressions allow us to test whether market-based or bank-based systems perform differently. We instrument for TOR and BANKIGDP variables used in the second stage using variables that proxy for the contracting environment in each country. This choice is motivated by the hypotheses that the development of the legal system can be taken as exogenous and that financial system development depends primarily on the ability of investors or financial intermediaries on one hand, and firms, on the other hand, to enter into effective contracts. We use the LAW&ORDER indicator of legal effectiveness as a proxy for the contracting environment. As suggested by LLSV we also use a legal origin variable, the common law dummy, and the specific indices of shareholder and creditor rights. Finally, as a proxy for the ability to enter into financial contracts, we use the rate of inflation. In the second stage we regress the dependent variables on the predicted values of TOR and BANK/GDP and several control variables. In the case of STCOUNT, for example, the estimated equation is STCOUNT = 71 + 2TOR + Y3 BANK/GDP +y4 GROWTH 75 INFLATION + 76 SIZE + 77 GDP/CAP + 78 LAW & ORDER+E We interpret these predicted financial sector variables as the stock-market activity levels and the size of the banking sector that is predicted by a country's contracting environment, respectively. We also include LAW & ORDER separately, to test for the additional channels, independent of the financial system, by which the contracting environment may affect the firms' access to financing. 23 We also include several control variables.'0 We include GROWTH to control for the possibility that the firms' desire to grow at rates that require external financing depends on the rate of growth of the economy.1' We also include INFLATION to control for the possibility that in economies with high inflation the growth rates of firms will be overstated. We also include two additional control variables. SIZE measures the average size of the firms in each country as a proportion of their GDP. We hypothesize that large firms have more access to the country's financial markets and institutions. Thus, this variable controls for the differences in sample selection across countries. There may exist differences in access to financing that are related to the level of development but not specifically related to the development of the legal system. We include GDP per capita in the equation to serve as a proxy for these differences. Our regression is estimated as a year-country unbalanced panel using a random effects estimator. This methodology allows us to include dummy variables, which are constant across countries in our specifications. The use of random effects panel estimators is also indicated when the explanatory variables are subject to measurement error (Moulton (1987)). 10 Additional firm-specific variables NFATA and NSNFA were included in unreported runs. They were not significant and did not affect the reported results. " If the economy is growing fast, the rate of profit is likely to be high. This will also tend to increase the rates IG and SGR, permitting faster growth without access to external financing. The variable GROWTH allows for the possibility of additional effects of the growth in the economy. 24 Table 4 Excess Growth of Firms and Financial Structure Panel A: Constraints on Short-Term and Long-Term Debt -- The regression equation estimated is: STCOUNT = V + 3,TOR + 32 BANK/GDP +33 GROWTH +34 INFLATION + 35 SIZE + E6 GDP/CAP + 37 LAW & ORDER + 3s MARKET + 39ETOR + 310E BANK/GDP +,. The sample consists of 45,598 manufacturing firms in 40countries over the period 1989-1996. Firm level variables are averaged for each country, each year. Dependent variable is the proportion of firms whose mean growth of real sales exceeds their mean internally financed growth rate (IG). TOR is stock market turnover defined as the total value of shares divided by market capitalization. BANK/GDP is the total assets of the deposit money banks divided by GDP. GROWTH is the growth rate of the real GDP per capital. INFLATION is the inflation rate of the GDP deflator. SIZE is total assets of firms divided by GDP of the country, in thousands. GDP/CAP is real GDP per capita in thousands of US$. NFATA is net fixed assets divided by total assets. LAW & ORDER, scored 1 to 6, is an indicator of the degree to which citizens of a country are able to utilize the existing legal system to mediate disputes and enforce contracts. MARKET is a dummy variable that takes the value I for values of TOR/(BANKIGDP) that are higher than the sample median and 0 otherwise. TOR and BANK/GDP used in estimation are the predicted values obtained from the following regressions: TOR = V + 3, LAW & ORDER + 32 COMMON-LAW DUMMY + 33 INFLATION + 34 SHARE HOLDER RIGHTS + , and BANK/GDP = V + 3, LAW & ORDER + 32 COMMON-LAW DUMMY + 33 INFLATION + 34 CREDITOR RIGHTS + ,. SHAREHOLDER RIGHTS is an index that ranges from 0 to 5 and aggregates shareholder rights and CREDITOR RIGHTS is an index that ranges from 0 to 4.5 and aggregates creditor rights as described in the text. COMMON- LAW DUMMY takes the value I for common law countries and the value zero for others. ETOR and EBAM4KoDp are residuals from the above regressions. Regressions are estimated using panel data with random effects. Standard errors are given in parentheses. (1) (2) (3) CONS. -.082 -.068 -.060 (.185) (.174) (.162) TOR .735** .692*** .720*** (.220) (.291) (.266) BANK/GDP .357* .376** .327* (.220) (.206) (.192) GROWTH 1.702*** 1.589*** 1.425*** (.468) (.479) (.482) INFLATION .061** .094*** .087 (.032) (.032) (.033) SIZE 2.475 .216 -.838 (6.125) (5.947) (5.584) GDP/CAP .001 .002 .005 (.004) (.004) (.004) LAW & ORDER -.019 -.024 -.024 (.023) (.022) (.021) MARKET .026 (.034) E BANK/GDP -.130* (.079) E TOR .046 (.055) R2 within .06 .07 .06 R2 between .24 .25 .32 No. of 283 267 267 Observations * * and *** indicate significance levels of 10, 5 and 1 percent respectively. 25 Panel B: Constraints on Long-Term Debt -- The regression equation estimated is: LTCOUNT =V +El 3,TOR + 32 BANK/GDP +33 GROWTH +34 INFLATION + 35 SIZE + 36 GDP/CAP + 3, LAW & ORDER + 3. MARKET + 39 ETOR + 3B,IE BANK/GDP + . The sample consists of 45,598 manufacturing firms in 40 countries over the period 1989-1996. Firm level variables are averaged for each country, each year. Dependent variable is the proportion of firms in a country whose mean growth of real sales exceeds their mean maximum short-term financed growth rate (SFG). TOR is stock market turnover defined as the total value of shares divided by market capitalization. BANK/GDP is the total assets of the deposit money banks divided by GDP. GROWTH is the growth rate of the real GDP per capital. INFLATION is the inflation rate of the GDP deflator. SIZE is total assets of firms divided by GDP of the country, in thousands. GDP/CAP is real GDP per capita in thousands of US$. NFATA is net fixed assets divided by total assets. LAW & ORDER, scored 1 to 6, is an indicator of the degree to which citizens of a country are able to utilize the existing legal system to mediate disputes and enforce contracts. MARKET is a dummy variable that takes the value I for values of TOR/(BANK/GDP) that are higher than the sample median and 0 otherwise. TOR and BANKIGDP used in estimation are the predicted values obtained from the following regressions: TOR = V + 3, LAW & ORDER + 32 COMMON-LAW DUMMY + 33 INFLATION + 34 SHARE HOLDER RIGHTS +, and BANK/GDP = V + 31 LAW & ORDER + 32 COMMON-LAW DUMMY + 33 INFLATION + 34 CREDITOR RIGHTS + ,. SHAREHOLDER RIGHTS is an index that ranges from 0 to 5 and aggregates shareholder rights and CREDITOR RIGHTS is an index that ranges from 0 to 4.5 and aggregates creditor rights as described in the text. COMMON- LAW DUMMY takes the value I for common law countries and the value zero for others. ETOR and EBANKIGDP are residuals from the above regressions. Regressions are estimated using panel data with random effects. Standard errors are given in parentheses. (1) (2) (3) CONS. -.176 -.133 -.144 (.208) (.200) (.184) TOR .843*** .819*** .830*** (.360) (.338) (.307) BANK/GDP .261 .230 .202 (.249) (.237) (.220) GROWTH 1.738*** 1.704*** 1.517*** (.496) (.510) (.514) INFLATION .089*** .124*** .118*** (.034) (.036) (.035) SIZE 3.904 1.864 .866 (6.789) (6.728) (6.305) GDP/CAP .001 .002 .006 (.005) (.005) (.005) LAW & ORDER -.014 -.018 -.019 (.024) (.024) (.023) MARKET .011 (.037) E BANK/GDP -.137* (.089) E TOR .024 (.060) R2 within .07 .08 .08 R2 between .19 .18 .25 No. of 283 267 261 Observations ** and *** indicate significance levels of 10, 5 and I percent respectively. 26 Panel C: Proportion Long-Term Constrained - The equation estimated is: DCOUNT = V + 31TOR + 32 BANK/GDP +33 GROWTH +34 INFLATION + 35 SIZE + 36 GDP/CAP + 37 LAW & ORDER + 3s MARKET + 39 ETOR + 310E BANKp + ,. The sample consists of 45,599 manufacturing firms in 40 countries over the period 1989-1996. Firm level variables are averaged for each country, each year. Dependent variable is given by (STCOUNT-LTCOUNT)/STCOUNT, the proportion of firms in a country that grow at a rate that exceeds (IG) but does not exceed (SFG). TOR is stock market turnover defined as the total value of shares divided by market capitalization. BANK/GDP is the total assets of the deposit money banks divided by GDP. GROWTH is the growth rate of the real GDP per capital. INFLATION is the inflation rate of the GDP deflator. SIZE is total assets divided by GDP of the country, in thousands. GDP/CAP is real GDP per capita in thousands of US$. NFATA is net fixed assets divided by total assets. LAW & ORDER, scored I to 6, is an indicator of the degree to which citizens of a country are able to utilize the existing legal system to mediate disputes and enforce contracts. MARKET is a dummy variable that takes the value I for values of TOR/(BANKI/GDP) that are higher than the sample median and 0 otherwise. TOR and BANK/GDP used in estimation are the predicted values obtained from the following regressions: TOR = V + 31 LAW & ORDER + 32 COMMON-LAW DUMMY + 33 INFLATION + 34 $HARE HOLDER RIGHTS +, and BANK/GDP = V + 3I LAW & ORDER + 32 COMMON-LAW DUMMY + 33 INFLATION + 34 CREDITOR RIGHTS + ,. SHAREHOLDER RIGHTS is an index that ranges from 0 to 5 and aggregates shareholder rights and CREDITOR RIGHTS is an index that ranges from 0 to 4.5 and aggregates creditor rights as described in the text. COMMON- LAW DUMMY takes the value I for common law countries and the value zero for others. ETR and EBANy;oop are residuals from the above regressions. Regressions are estimated using panel data with random effects. Standard errors are given in parentheses. (1) (2) (3) CONS. .465*** .343*** .346*** (.131) (.119) (.118) TOR -.411** -.400** -.403** (.224) (.197) (.196) BANK/GDP .148 .231* .234* (.156) (.140) (.140) GROWTH -.674** -.557* -.542* (.332) (.313) (.317) INFLATION -.084*** -.076*** -.075*** (.024) (.022) (.022) SIZE -.981 -.853 -.875 (4.314) (3.985) (3.974) GDP/CAP .002 -.000 -001 (.003) (.003) (.003) LAW &ORDER -.038*** -.024* -.023* (.016) (.014) (.014) MARKET -.001 (.023) E BANK/GDP .020 (.056) E TOR -.000 (.037) R2 within .08 .07 .06 R2 between .25 .24 .25 No. of 279 264 264 Observations ** and*** indicate significance levels of 10, 5 and 1 percent respectively. 27 Table 4 presents the second-stage regression results. In Panel A the dependent variable is STCOUNT. Thus, the panel investigates the proportion of the firms in each country growing at a rate that requires external financing. The basic specification is given in equation (1). The proportion of firms growing at rates requiring outside financing is higher in countries with high predicted TOR and BANK/GDP. Thus, a larger proportion of firms obtain outside financing when the contracting environment is conducive to the development of a large banking sector and an active stock market. This is in line with the implications of previous studies. The two control variables GROWTH and INFLATION are also significantly positive. We do not identify any effects of average firm size relative to GDP or of the general level of development measured by GDP per capita on financing. We also do not identify any additional effects of the efficiency of the legal system not already accounted for in the development of the financial system. Specification (2) augments the equation with a variable which takes the value one for those observations where the ratio of TOR to BANK/GDP exceeds the sample median, and zero otherwise. The MARKET dummy identifies market-based economic environments. Inspection of specification (2) reveals that there is no evidence that the relative ratio of market activity to the size of the banking sector affects the proportion of firms that obtain external financing. In the specification (3) we augment the basic estimating equation with the residuals from the first-stage regressions. ETOR is the component of the market activity level not predicted by the legal environment. EBANK/GDP is the difference between the 28 ratio of actual BANK/GDP and the level BANK/GDP predicted by the country's contracting environment. Positive coefficients for these variables would suggest that there is a benefit to market activity and or a large banking sector respectively, independently of the legal system. The coefficients of ETOR and EBANKJGDP are not significant at the five percent level, suggesting that there is little identifiable benefit to having a larger financial sector than that predicted by the legal contracting environment. If anything, the marginal significance of EBANK/GDP hints that an overexpansion of the banking sector beyond the predicted level may be evidence that resources are being misallocated. However, this result is sensitive to outliers in our sample. If we drop countries such as Peru and Turkey from the estimation, EBANK1GDP is not even marginally significant and BANK/GDP becomes significant at five percent in all specifications. Panel B presents analogous regressions for LTCOUNT. Thus in this panel we explain the proportion of firms growing at rates that require additional long-term external financing. The results in Panel B are analogous to those presented in Panel A, with one exception. The coefficient for BANK/GDP, while remaining positive throughout, is no longer statistically significant.12 Thus, we find less evidence that the size of the banking sector is an important determinant of the availability of long-term financing for the firms in our sample. This is consistent with the lack of significance of the MARKET indicator in specification (2). The dependent variable in Panel C is DCOUNT, the proportion of firms that obtain external financing but do not grow at rates that require additional long-term 12 Dropping outliers does not make BANK/GDP significant in LTCOUNT regressions although EBANUKGDP loses significance as in STCOUNT regressions.. 29 capital. This proportion is likely to be high when the financial system is able to supply short-term financing efficiently, but is not able to supply long-term financing. Inspection of all three specifications in Panel C shows that DCOUNT is negatively related to TOR and positively related to BANK/GDP. Firms that require external financing in economies with strong securities markets are more likely to obtain long-term financing. By contrast, firms that require external financing in economies with a strong banking sector are less likely to grow at rates that require long-term financing. This is consistent with the notion that well-developed securities markets facilitate long- term financing, whereas a well-developed banking sector facilitates short-term financing. Interestingly, LA W&ORDER also has a strong negative effect on DCOUNT independent of its effect through TOR. 13 The financial structure variables MARKET, of ETOR and EBANKIGDP are again not significant. The coefficients of the control variables GROWTH and INFLATION are significant in the expected directions. In high-growth economies a larger proportion of firns requiring external financing grows at rates that require long-term financing. In economies with high inflation rates, a higher proportion of externally financed firms grows at rate that exceeds the predicted rates IG and SFG. We also investigated possible nonlinearities in the way financial variables may affect firm growth rates by including squared TOR and BANK/GDP terms into all specifications in Table 4. The squared TOR and BANK/GDP terms enter the DCOUNT regressions significantly with positive and negative signs, respectively. TOR and BANK/GDP terms also remain significant with their initial signs. This indicates that the positive impact of bank development on short term financing and stock market 30 development on long term financing are especially important at lower levels of financial development. 14 This finding raises the possibility that relative development of banks versus markets may be particularly important at lower levels of development. To test this, we added an interaction term of MARKET with GDP per capita to specification (2) in all panels of Table 4. However, this variable failed to develop a significant coefficient. Another possibility is that financial structure is only important if the underlying legal structure is inadequate. This may be true since markets in general require a better developed legal system to function efficiently. However an interaction term of MARKET with LAW & ORDER variable does not develop a significant sign in any of the regressions in Table 4. In sum, Table 4 yields several results: First, we have no evidence that the relative levels development of the securities markets and the size of the banking sector, by itself, affect firms' access to external financing. Thus, there is no evidence that the development of a market-based or bank- based financial systemper se affects access to financing. Second, the securities markets and the banking system affect firms' ability to obtain financing in different ways, especially at lower levels of financial development. While the development of both improves access to external financing, the development of securities markets is more related to long-term financing, whereas the development of the banking sector is more related to the availability of short-term financing. Thus, for these countries differences in contracting environments that affect the relative development of 3 Dropping outliers makes TOR less significant but LAW &ORDER more significant. 31 the stock market and the banking system may have implications for which firms and which projects obtain financing. Third, the effect of the securities markets and banking system development is closely tied to the level of development of the country's contracting environment. Differences in the activity level of the securities markets not predicted by the contracting environment are not significantly related to the ability of firms do obtain external financing. This is consistent with the emphasis in LLSV on the importance of the legal system on financing. Fourth, the proportion of firms that grow at rates that cannot be self-financed is positively related to the development of both the securities markets and the banking system. This is consistent with the findings of Demirguc-Kunt and Maksimovic (1998). 5. CONCLUSION The relative development of banks versus markets varies considerably across countries. The financial systems of some countries, such as the US, are market-based, whereas the financial systems of other economies, such as Japan, are bank-based. In this paper we investigate whether this difference in the organization of financial systems affects firms' ability to obtain external financing for growth. Our initial finding that that the proportion of firms that grow at rates that cannot be self-financed is positively related to the development of both the securities markets and the banking system. This is consistent with the findings of Demirguc-Kunt and Maksimovic (1998), and with parallel findings of Levine and Zervos (1998), at the country level, and Rajan and Zingales (1998), at the industry level. 14 The squared terms do not develop significant coefficients in STCOUNT regressions. In LTCOUNT 32 Our results show that the effects of the stock market and banking system development on firms' growth is closely tied to the level of development of the country's contracting environment. Development of the financial system beyond that predicted by the contracting environment are not significantly related to the ability of firms to obtain external financing. This is consistent with the emphasis on the importance of the legal system in LLSV on financing. We find no evidence that the relative levels of development of the securities markets compared to that of the banking sector, affect firms' access to external financing. Thus, there is no evidence that the development of a market-based or bank-based financial system per se affects access to financing. Finally, the securities markets and the banking system affect firms' ability to obtain financing in different ways, especially at lower levels of financial development. While the development of both, if predicted by the contracting environment, improves access to external financing, the development of securities markets is more related to long-terrn financing, whereas the development of the banking sector is more related to the availability of short-term financing. Thus, for these countries differences in contracting environments that affect the relative development of the stock market and the banking system may have implications for which firms and which projects obtain financing. regressions only the squared TOR is marginally significant in some specifications with a negative sign. 33 Appendix Table Al Number of Firm Level Observations in Each Country The data source for firm level variables is WorldScope. Number of Firm Observations Argentina 93 Australia 452 Austria 382 Belgium 370 Brazil 514 Canada 1133 Chile 173 Colombia 68 Denmark 700 Finland 480 France 2506 Germany 2717 Greece 363 Hong Kong 385 India 1219 Indonesia 366 Ireland 105 Israel 91 Italy 866 Japan 9411 Korea 825 Malaysia 774 Mexico 251 Netherlands 727 New Zealand 109 Norway 330 Pakistan 339 Peru 72 Philippines 121 Portugal 230 Singapore 341 South Africa 442 Spain 468 Sweden 661 Switzerland 771 Taiwan 503 Thailand 620 Turkey 222 United Kingdom 4475 United States 10706 34 REFERENCES Allen, Franklin and Gale, Douglas. 1999 Comparing Financial Systems. Cambridge, MA: MIT Press. Allen, Franklin, 1993, Stock markets and resource allocation, in Mayer, Colin, and Xavier Vives, eds.: Capital Markets and Financial Intermediation, (Cambridge University Press, Cambridge, England). Beck, Thorsten; Demirguc-Kunt, Asli; Levine, Ross, 1999, "A New database on Financial Development and Structure" Washington, D.C.: World Bank, mimeo. Demirguc-Kunt, Asli and Ross Levine, 1999, "Financial Structures Across Countries: Stylized Facts" Washington, D.C.: World Bank, mimeo. Demirguc-Kunt, Asli and Ross Levine, 1996, Stock market development and financial intermediaries: stylized facts, World Bank Economic Reviewl O, 291-321. Demirguc-Kunt, Asli and Vojislav Maksimovic, 1999, Institutions, Financial Markets And Firm Debt Maturity, Journal of Financial Economics. Demirguic-Kunt, Asli and Vojislav Maksimovic, 1998, Law, Finance, and Firm Growth, Journal of Finance 53,.2107-2137. Demirguc-Kunt, Asli and Vojislav Maksimovic, 1996, Stock Market Development and Firms' Financing Choices, World Bank Economic Review 10, 341-369. Diamond, Douglas W., 1996, Liquidity, banks and markets, Policy Research Working Paper No 1566, The World Bank. Gerschenkron, Alexander, 1962, Economic Backwardness in Historical Perspective, Belknap Press of Harvard University Press, Cambridge, MA. King, Robert G. and Ross Levine, 1993a, "Finance, Entrepreneurship, and Growth: Theory and Evidence," Journal of Monetary Economics 32, 513-42. King, Robert G., and Ross Levine, 1993b, Finance and growth: Schumpeter might be right, Quarterly Journal of Economics, 108, 717-738. Knack, Stephen and Phillip K. Keefer, 1995, Institutions and economic performance: cross-country tests using alternative institutional measures, Economics and Politics 7, 207-227. Kumar, Krshna.B., Rajan, Raghuram, and Luigi Zingales, 1999, What determines firm size? mimeo. 35 Laporta, Rafael; Lopez-de-Silanes, Florencio; Shleifer, Andrei; and Vishny, Robert W. "The Quality of Government, 1999, Journal of Law, Economics, and Organization 15, 222-279. Laporta, Rafael; Lopez-de-Silanes, Florencio; Shleifer, Andrei; and Vishny, Robert W. 1998, Law and Finance, Journal of Political Economy 106, 1113-1155. Levine Ross, and Sara Zervos, 1998, Stock markets, banks, and economic growth, American Economic Review. Levine, Ross, 2000, Bank-based or market-based financial systems: Which is better? University of Minnesota, mimeo. Modigliani, F., and E. Perotti, 1999, Security Markets versus Bank Financing and the Enforcement of Legal Rules, mimeo. Morck, Randall, Shleifer, Andrei, and Robert W. Vishny, 1990, The Stock Market and Investment: Is the Market a Sideshow? Brookings Papers on Economic Activity 0, 157-202. Myers, Stewart C. and Nicholas S. Majluf, 1984, Corporate financing and investment decisions when firms have information that investors do not have, Journal of Financial Economics 13, 187-221. Rajan, Rhaguram and Luigi Zingales, 1996, Financial dependence and growth, forthcoming in American Economic Review. Stulz, Rene M. "Financial Structure, Corporate Finance, and Economic Growth," 1999, Ohio State University mimeo. 36 Policy Research Working Paper Series Contact Title Author Date for paper WPS2416 The Swiss Multi-Pillar Pension Monika Queisser August 2000 A. Yaptenco System: Triumph of Common Sense? Dimitri Vittas 31823 WPS2417 The Indirect Approach David Ellerman August 2000 B. Mekuria 82756 WPS2418 Polarization, Politics, and Property Philip Keefer August 2000 P. Sintim-Aboagye Rights: l inks between Inequality Stephen Knack 37644 and Growth WPS2419 The Savings Collapse during the Cevdet Denizer August 2000 I. Partola Transition in Eastern Europe Holger C. Wolf 35759 WPS2420 Public versus Private Ownership: Mary Shirley August 2000 Z. Kranzer The Current State of the Debate Patrick Walsh 38526 WPS2421 Contractual Savings or Stock Market Mario Catalan August 2000 P. Braxton Development-Which Leads? Gregorio Impavido 32720 Alberto R. Musalem WPS2422 Private Provision of a Public Good: Sheoli Pargal August 2000 S. Pargal Social Capital and Solid Waste Daniel Gilligan 81951 Management in Dhaka, Bangladesh Mainul Huq WPS2423 Financial Structure and Economic Thorsten Beck August 2000 K. Labrie Development: Firm, Industry, and Asll Demirgu,-Kunt 31001 Country Evidence Ross Levine Vojislav Maksimovic WPS2424 Global Transmission of Interest Jeffrey Frankel August 2000 E. Khine Rates: Monetary Independence and Sergio Schmukler 37471 the Currency Regime Luis Serven WPS2425 Are Returns to Investment Lower for Dominique van de Walle August 2000 H. Sladovich the Poor? Human and Physical 37698 Capital Interactions in Rural Vietnam WPS2426 Commodity Price Uncertainty in Jan Dehn August 2000 P. Varangis Developing Countries 33852 WPS2427 Public Officials and Their Institutional Nick Manning August 2000 C. Nolan Environment: An Analytical Model for Ranjana Mukherjee 30030 Assessing the Impact of Institutional Omer Gokcekus Change on Public Sector Performance WPS2428 The Role of Foreign Investors in Debt Jeong Yeon Lee August 2000 A. Yaptenco Market Development: Conceptual 38526 Frameworks and Policy Issues Policy Research Working Paper Series Contact Title Author Date for paper WPS2429 Corruption, Composition of Capital Shang-Jin Wei August 2000 H. Sladovich Flows, and Currency Crises 37698 WPS2430 Financial Structure and Bank Asli DemirgOu-Kunt August 2000 K. Labrie Profitability Harry Huizinga 31001 WPS2431 Inside the Crisis: An Empirical Asli Demirgu,-Kunt August 2000 K. Labrie Analysis of Banking Systems in Enrica Detragiache 31001 Distress Poonam Gupta