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External Dependence and Industry Growth Does Financial Structure Matter? Thorsten Beck and Ross Levine February 2000 Abstract: Are market-based or bank-based financial systems better at financing industries that depend heavily on external finance? Are market- or bank-based financial systems better at facilitating the formation of new firms? We find evidence for neither the market-based nor the bank-based hypothesis. We find overwhelming evidence that industries that are heavily dependent on external finance grow faster in economies with a higher level of overall financial development and with better protection of outside investors. We also find that overall financial development stimulates the establishment of new firms, which is consistent with the Schumpeterian view of creative destruction. While overall financial development matters, financial structure per se offers little additional information. JEL Classification: G1; G2; O4 Keywords: Financial Structure; Economic Growth; External Finance Beck: World Bank; Levine: Carlson School of Management, University of Minnesota. This paper’s findings, interpretations, and conclusions are entirely those of the authors and do not necessarily represent the views of the World Bank, its Executive Directors, or the countries they represent. Work for this paper was completed while both authors were visiting the Banco Central de Chile, which provided an excellent research environment. We would like to thank Asli Demirgüç-Kunt for helpful comments. 1. Introduction An intensive debate focuses on the relative advantages of bank-based versus market-based financial systems.1 Some authors stress the advantages that banks have over markets in financing firms and promoting the establishment of innovative firms. Others stress the relative merits of markets in providing external finance and stimulating the creation of new firms. Historically, empirical research on financial structure – that is, research on the relative merits of bank-based versus market-based financial systems – has concentrated on a handful of industrialized countries. New data, however, permits a more rigorous, cross-country analysis of financial structure and economic performance. Levine (2000b) shows that financial structure is not a good predictor of growth: neither bank-based nor market-based financial systems are closely associated with economic growth. While the overall level of financial development is robustly linked with long-run growth, focusing on financial structure per se does not help in understanding cross-country growth differences. 2 Levine (2000b), however, examines Gross Domestic Product (GDP) growth. He does not examine whether financial structure influences external financing or the creation of new firms. In contrast to existing empirical work on bank-based and market-based financial systems, this paper examines the following questions: (1) Do industries that depend heavily on external finance grow faster in bank-based or market-based financial systems? (2) Are new firms more likely to form in a bank-based or market-based financial system? Thus, this paper concentrates on specific mechanisms through which financial structure might influence economic activity. This paper empirically assesses the validity of four competing theoretical perspectives regarding bank-based and market-based financial systems in the process of economic development. The bank-based view highlights the positive role of banks in providing external finance and funding new firms. The bank-based view takes skeptical view of markets. Alternatively, the market-based view stresses the importance of markets in funding firms and 1 See Levine (2000b) for references. 1 promoting new, innovative enterprises. The financial services view [Levine, 2000b] argues that the bank-based versus market-based debate is of second-order importance. Financial services provide key services: they research firms, exert corporate control, ease risk pooling and management, facilitate resource mobilization, and ease transactions. In comparing countries, the first-order issue is the quality and availability of these financial services, not whether banks or market provide these services. While financial structure may be important, the financial services view focuses on the overall provision of financial services. The legal-based view [LaPorta, Lopez-de-Silanes, Shleifer, and Vishny, 1999b] rejects the analytical relevance of financial structure altogether. They instead argue that the key distinguishing feature across countries is the legal system that defines and enforces the rights of outside investors. We now describe the theoretical foundations for each of these views of financial structure and its importance for external financing and the emergence of new firms. In bank-based systems, banks play a dominant role in providing financial services. To provide these services, they frequently establish close relations with firms. 3 These close relationships facilitate the flow of information and thereby promote effective corporate control. Advocates of bank-based systems not that in stock markets, small investors are reluctant to expend resources acquiring information and exerting corporate control and would rather free-ride off other investors. This free-riding means that too little information is gathered and too little corporate control is provided by market participants. According to its supporters, bank-based system are therefore better in revealing information and more effective in corporate control than market-based systems. Banks might be especially effective in providing external resources to new firms that require staged financing – investors make additional funding decisions as the project develops and investors can learn about it [Stulz, 1999]. Critics of bank-based systems point to several problems arising from powerful banks. First, excessively powerful banks may hinder the ability of new, innovative firms to obtain external financing. By acquiring inside information about these firms, they can extract informational rents from firms [Hellwig, 1991]. The banks’ market power thus reduces the incentives of firms to undertake profitable projects [Rajan, 1992]. Second, bankers tend to be ineffective corporate 2 For work showing that financial development enhances economic growth, see Demirgüç-Kunt and Maksimovic (1998), Levine and Zervos (1998), Levine (1998, 1999, 2000a), Levine, Loayza, and Beck (2000) and Rajan and Zingales (1998). 3 In Germany this system is often referred to as Hausbank-system, in Japan as main-bank system. 2 controllers due to their insider status. In bank-based systems, bankers often hold equity and vote the shares of other shareholders. Thus, bankers might collude with managers against other creditors and minority shareholders and thus reduce the effectiveness of corporate control [Hellwig, 1998; Wenger and Kaserer, 1998]. Given the lack of price signals, banks might also continue financing firms even for projects with negative returns [Rajan and Zingales, 1999]. Thus, bank-based systems may inhibit the efficient flow of external finance to the newest, most profitable endeavors. In market-based systems, markets play important roles in stimulating the acquisition of information, exerting corporate control, stimulating capital mobilization, providing risk management vehicles, and stimulating exchange. Big and liquid market can aggregate views on new technologies and display this in public prices. Furthermore, in liquid markets, agents that obtain valuable information can quickly profit by trading in these markets, which in turn stimulates market participants to acquire information about firms.4 Stock markets stimulate greater corporate control by facilitating takeovers and making it easier to tie managers’ compensation to performance. This aligns the interests of managers with those of equity holders.5 According to the market-based view, stock markets are effective at stimulating the acquisition and dissemination of information and in promoting corporate control. Thus, marketbased systems may be important for (i) the growth of industries dependent on external finance and (ii) the emergence of new firms. Critics of market-based systems point to weaknesses of stock markets in exerting corporate control and revealing information. First, there is a basic free-rider problem in markets. Individual investors might be reluctant to invest time and money in researching firms and projects if others profit rapidly from this information through efficient and liquid markets [Stiglitz, 1985]. Thus, market-based systems may not be as effective as bank-based systems in revealing information about firms and projects and therefore at providing external finance to these firms, especially young firms. Second, stock markets are also less effective in corporate control, for several reasons. Liquid markets offer an easy exit option for shareholders and thus reduce the incentives 4 Allen and Gale (1999) show that industries that display more risk and more diverse views about their perspectives can assure external resources more easily in a market-based financial system. These industries might be the more innovative ones, as Allen (1993) suggests. He argues that market-based economies such as the U.S. have been better in developing new and innovative industries than bank-based economies, such as Germany or Japan. 5 Evaluating the efficiency of stock markets in exerting corporate control also has to take into account whether equity is held by a few large share holders or by many small shareholders. See Stulz (1999). 3 for intensive corporate control [Shleifer and Vishny, 1986]. Atomistic shareholders also have incentives to capture the benefits from a takeover by holding on to their shares instead of tendering them, thus turning a takeover attempt futile [Grossman and Hart, 1980]. The informational asymmetry between insiders and outsiders also reduces the effectiveness of takeover threats, thus reducing the value of corporate control exerted through markets. On the other hand, this information asymmetry impedes a proper project evaluation by stock markets and thereby increases management’s incentives to avoid risky but profitable projects and pushes them towards short-termism [Stulz, 1999]. Finally, an incestuous relationship between management and shareholders sitting on the board reduces the effectiveness of corporate control through stock markets [Allen and Gale, 1999]. This less effective corporate control through stock markets reduces the ability of firms to access external finance in market-based systems since investors are aware of the corporate control problems and therefore more reluctant to provide financing than in bank-based systems. This negative effect hits industries that rely heavily on external finance especially hard. Alternatively, the issue might not be banks or markets, but rather banks and markets. According to this financial services view both banks and markets provide important services. The availability and quality of financial services is important, not so much who provides them. Furthermore, banks and markets might complement each other. The existence of stock markets constitutes an exit option for entrepreneurs and therefore decreases banks’ market power [Stulz, 1999]. Stock markets also enable an entrepreneur who has obtained external financing through banks to realize profits from a successful project by selling it. This increases the return for the entrepreneurs and thus the incentives to undertake risky and innovative projects. According to this view, it is not financial structure per se, but rather the overall level of financial development that stimulates the flow of external funds to firms that are heavy users of external finance; according to the financial services view, it is the overall level of financial development that will foster the creation of new, innovative firms in these industries. The legal-based approach is an extension of the financial service approach and emphasizes the legal determinants of financial development. According to the legal-based view, countries with legal codes that protect outside investors and legal systems that enforce those codes will have financial systems that facilitate external finance and the financing of new firms. Thus, the legal-based view predicts that the component of overall financial development defined by the 4 legal-system is critical for industries that require external finance and for the creation of new firms in these industries. Methodologically, we use the innovative approach by Rajan and Zingales (1998). They show that industries that depend more on external finance grow relatively faster in economies with a higher level of financial development. This result is robust to the use of alternative measures of financial development and external dependence. Furthermore, Rajan and Zingales show that the effect of financial development on the industrial growth pattern is mostly through the growth of number of establishments rather than the growth of the average size of establishments. So financial development improves disproportionately the prospects of young firms in industries that rely heavily on external finance. While these results show the importance of financial development for resource allocation, they do not address whether it is markets or banks that are better at providing external finance and easing the creation of new firms. This paper evaluates the market-, the bank-based, the financial services and the legal-based approach in a panel of 34 countries and 36 industries. Specifically, we test the hypotheses that industries that depend more heavily on external finance, grow faster in either market- or bankbased financial systems, or, alternatively, that the overall level of financial development, and more specifically the legal rights of outside investors, enhance the growth of these industries. We then decompose industry growth into the growth of the number of establishments and the growth of the average size of establishments. The results give no support to either the market- or bank-based view. Industries that depend heavily on external finance do not grow faster in either bank-based or market-based financial systems. The results are supportive of the financial-services and the legal-based approach. Industries that depend more on external finance grow faster in economies with higher levels of overall financial development. They also tend to grow faster in economies that protect the rights of creditors and minority shareholders and enforce these rights efficiently. When we decompose the industry growth rates into the growth in the number of establishments and the growth in the average size of establishments, we again find no significant impact of financial structure on the creation of new firms. In contrast, overall financial development and its legal determinants explain cross-country variation in the growth in the number of establishments, but not in the growth in the average size of establishments. Thus, overall financial development is critical for the creation of new firms, but neither bank-based nor market-based systems plays a 5 particularly critical role in the establishment. We also find that unbalanced financial systems – financial systems that either extremely bank-based or market-based impede the establishment of new firms. We speculate that unbalanced systems either (a) exacerbate the power of banks, in the case of an unbalanced bank-based system, or (b) fail to provide staged financing, in the case of an unbalanced market-based system. In either case, unbalanced systems hinder new firm development. This finding needs more rigorous theoretical research, however. The remainder of this paper is organized as follows. Section 2 describes the methodology and the basic econometric model that we use. Section 3 presents the data on financial development and structure, external dependence and industrial growth. Section 4 provides and discusses the empirical results. Section 5 concludes. 2. Methodology This paper primarily evaluates the impact of financial structure on (1) the relative performance of particular industries, where industries are distinguished by their reliance on external finance and (2) the emergence of new firms. This section describes the econometric model. 2.1. External Dependence and Financial Structure Financial intermediaries and markets help overcome market frictions that drive a wedge between the price of external and internal finance. Lower costs of external finance facilitate firm growth. Therefore, industries that are naturally heavy users of external finance should benefit disproportionately more from greater financial development than industries that are not naturally heavy users of external finance. Rajan and Zingales (1998) assess the empirical importance of this channel with industrylevel data. Using a panel of 41 countries and 36 industries with data averaged over the 1980s, they examine the hypothesis that industries that rely more heavily on external finance grow faster in countries with a better developed financial system. They find evidence for their hypothesis using different measures of financial development and external dependence. Furthermore, Rajan and Zingales show that the effect of financial development on the industrial growth pattern is mostly through the growth of number of establishments rather than the growth of the average 6 size of establishments. So financial development improves disproportionately the prospects of young firms in industries that rely heavily on external finance. This paper extends the analysis by Rajan and Zingales and explores whether industries with a high need of external finance grow faster in economies with a specific financial structure or whether the overall level of financial development and more specifically, the legal determinants of finance determine industrial growth patterns across countries. Following Rajan and Zingales, we then decompose industry growth into the growth in the average size of establishments and the growth in the numbers of establishment to evaluate the importance of financial structure, financial development and its legal determinants for the sources of growth. 2.2. The Econometric Model We examine whether the structure of the financial system, the level of financial development and its legal determinants interact with the need for external finance in determining the industrial composition of growth. We define our indicators of financial structure in such a way that higher values imply a more market-based system. In evaluating our hypothesis we follow a method developed by Rajan and Zingales (1998) that implies interacting industry characteristics with country characteristics, in this case the need for external finance across industries and indicators of financial development and structure across countries. By including dummy variables for industries and countries, the interaction term of interest only captures effects relative to variables that vary both across countries and across industries. Specifically, we will run the following regression to assess the impact of the interaction of financial development, financial structure and the need of external finance on industry growth. Growthi, k = ∑ α j Country j + j ∑ β Industry + γ Share l l i, k i, k + δ1 ( Externalk * FD i ) + δ2 ( Externalk * FS i ) + ε i,k , l where Growthi,k is the average annual growth rate of value added in industry k and country i. Country and Industry are country and industry dummies, respectively, and Sharei,k is the share of industry k in manufacturing in country i in 1980. Externalk is the external dependence for industry k as measured for a sample of U.S. companies over the period 1980-89. FDi and FSi are indicators of financial development and financial structure for country i, respectively. 7 The different hypotheses imply different predictions about the sign and significance of δ1 and δ 2 . The market-based view predicts that industries that are dependent on external finance grow faster in economies with market-oriented financial systems and higher levels of financial development, thus implying δ1 >0 and δ2 >0. The bank-based view predicts that industries that are dependent on external finance grow faster in economies with bank-oriented financial systems and higher levels of financial development, thus implying δ1 >0 and δ2 <0. The financial-services approach predicts that industries dependent on external finance grow faster in economies with a higher level of overall financial development, whereas the financial structure should not matter, thus implying δ1 >0 and δ 2 =0. The legal-based approach, finally, predicts that industries dependent on external finance, grow faster in economies that protect the rights of outside investors more efficiently, whereas financial structure should not matter. If we replace FDi with indicators of these legal rights and contract enforcement, this implies δ1 >0 and δ 2 =0. We run both Ordinary-Least-Squares (OLS) regressions and Two-Stage-Least-Squares (TSLS) regressions. Whereas the results from simple OLS only allow us to make statements about partial correlations between the dependent variable and the interaction terms of interest, TSLS regressions allow us to address the issue of endogeneity of independent variables. Specifically, we want to control for the possible endogeneity of the level and the structure of financial development. Whereas the above equation suggests that an exogenously given level or structure of financial sector activity might interact with the external dependence of industries to determine industry growth rates, financial markets and institutions might have arisen due to a given industrial structure. By using appropriate instruments we can control for simultaneity bias and reverse causality. We will use the legal origin and the religious composition of countries as instrumental variables for the level and structure of financial sector development.6 Legal systems with European origin can be classified into four major legal families [Reynolds and Flores, 1996]; the English common law and the French, German, and Scandinavian civil law countries. 7 Most countries have acquired their legal systems through occupation and colonialism, so that the legal origin can be regarded as exogenous. Furthermore, LaPorta, Lopez-de-Silanes, Shleifer and Vishny (1997, 1998) have shown that the legal origin of a country materially influences its legal 6 7 Data on legal origin and religious composition are from LaPorta, Lopez-de-Silanes, Shleifer and Vishny (1999a). For a more detailed description see Levine (1998) and Levine, Loayza, and Beck (2000). 8 treatment of creditors and shareholders, its accounting standards and the efficiency of contract enforcement. Since these regulatory and informational characteristics determine the efficiency of financial intermediaries and markets, we regard the legal origin of countries as good instruments for financial development. Anecdotal and statistical evidence also suggests that the development of institutions is partly driven by the dominant religion in a country.8 3. The Data To assess our hypothesis in a country-industry panel we need measures of dependence on external finance, industry growth rates and indicators of financial development and structure. Our sample contains 34 countries and 36 industries. This section describes the measure of external dependence, the indicators of financial development and structure and the industrial growth data. 3.1. External Dependence The industry-level data on external dependence are from a study by Rajan and Zingales (1998). The underlying assumption for their and for our work is that for technological reasons some industries depend more heavily on external finance than others. Scale economies, gestation period or intermediate product intensity might constitute some of these technological reasons. Unfortunately, we can only observe the actual use of external finance, but not the demand for it. If financial markets were relatively frictionless, the actual use of external finance would represent the equilibrium of supply and demand. Assuming that the variance of the need of external finance across industries persists across countries, however, we can use the actual external dependence of industries as observed in a country with a relatively well developed financial system, where firms face a perfectly elastic supply curve of external finance, like the U.S., as proxying for the “natural” dependence of industries on external finance in other countries.9 8 See LaPorta, Lopez-de-Silanes, Shleifer and Vishny (1999a). 9 For a more detailed discussion of why the dependence on external finance as measured for the U.S. constitutes a good proxy for the demand for external finance in other countries, see Rajan and Zingales (1998). 9 Rajan and Zingales use data from Standard and Poor's Compustat for U.S. firms in 36 industries. Since this database contains only publicly listed firms, we can regard the assumption of a perfectly elastic supply curve of external finance for these firms as being fulfilled. A firm's dependence on external finance is defined as the share of investment that cannot be financed through internal cash flows; or as capital expenditures minus cash flow from operations divided by capital expenditures. Both numerator and denominator are averaged over the 1980s to smooth temporal fluctuations. The industry values are calculated as medians rather than means to thus prevent outliers from dominating the results. Table 1 lists the external dependence for all 36 industries. Drugs is the industry most dependent on external finance, whereas the tobacco industry has no demand for external finance, i.e. our dependence measure is less than zero. 3.2. Indicators of Financial Development and Structure To test our hypotheses we need appropriate indicators of the efficiency with which financial intermediaries and markets reveal information and exert corporate control, and therefore channel external resources to industries that need them most. While the perfect indicators certainly do not exist, the recent literature has developed indicators that proxy relatively well for financial intermediary and stock market development across countries. More difficult is the empirical definition of market- and bank-based systems. Following DemirgüçKunt and Levine (1999), we therefore use an assortment of different measures of financial structure to test the robustness of our results. In the following we will present indicators of (i) overall financial development, (ii) financial structure, and (iii) the legal rights of outside investors and the enforcement of these rights. 3.2.1 Indicators of Financial Development Finance-Activity is a measure of the overall activity of the financial intermediaries and markets. It is defined as the log of the product of Private Credit, the value of credits by financial intermediaries to the private sector divided by GDP, and Value Traded, the value of total shares traded on the stock market exchange divided by GDP. Private Credit is the most comprehensive indicator of the activity of financial intermediaries by including both bank and nonbank intermediaries. It captures the amount of external resources channeled through the financial 10 sector to private firms. Value Traded measures the activity of the stock market trading volume as share of national output and should reflect the degree of liquidity that stock markets provide to the economy, and therefore the degree of ease with which firms can raise funds at the stock market. Finance-Size is a measure of the overall size of the financial sector and is defined as the log of the sum of Private Credit and Market Capitalization. Market Capitalization is defined as the value of listed shares divided by GDP, and is a measure of the size of stock markets relative to the economy. Finance-Size thus indicates the total amount of outstanding claims that outside investors have on firms. Finance-Aggregate combines the previous two measures and is thus a conglomerate indicator of the size and activity of the financial sector. Specifically, it is the first principal component of Finance-Activity and Finance-Size. Finance-Dummy isolates countries that have both underdeveloped financial intermediaries and markets. Specifically, it equals zero if both Private Credit and Value Traded are less than the sample mean and one otherwise. 3.2.2 Indicators of Financial Structure All four measures of financial structure are constructed in a way that higher values indicate more market-based financial systems. These measures therefore indicate the degree to which firms rely on markets rather than on banks as source of external finance. Structure-Activity indicates the activity of stock markets relative to the activity of banks and is defined as the log of the ratio of Value Traded and Bank Credit. Bank Credit equals the claims of the banking sector on the private sector as share of GDP. Compared to Private Credit, we exclude claims of nonbank financial intermediaries to thus focus on the commercial banking sector. Structure-Size indicates the size of stock markets relative to the size of the banking sector and is defined as the log of the ratio of Market Capitalization and Bank Credit. Structure-Aggregate combines the previous two measures and is thus a conglomerate indicator of the size and activity of stock markets relative to banks. Specifically, it is the first principal component of Structure-Activity and Structure-Size. 11 Structure-Dummy is a simple bivariate classification of market- versus bank-based financial systems. Specifically, it equals one if Structure-Aggregate is greater than the sample median and zero otherwise. 3.2.3 The Legal Environment We will be using three indicators of the rights of outside investors and the degree to which these rights are enforced. These data are from La Porta, Lopez-de-Silanes, Shleifer and Vishny (1998). Creditor is an index of the degree to which the legal codes of the country protect the claims of secured creditors in the case of reorganization or liquidation of a company. It ranges from zero to four and is the sum of four dummy variables that indicate whether (i) the reorganization procedure does not impose an automatic stay on assets, thereby not preventing secured creditors from taking possession of loan collateral, (ii) secured creditors are ranked first in the case of liquidation, (iii) management does not stay in charge of the firm during reorganization, thereby enhancing creditors’ power, and (iv) management needs creditors’ consent when filing for reorganization. In economies with higher values of Creditor, outside investors have more rights relative to the management and other stakeholders, and should therefore be more willing to provide the external resources that industries need. Anti-Director is an index of the degree to which the legal codes of the country protect minority shareholder rights. It ranges from zero to six and is the sum of six dummy variables that indicate whether (i) shareholders are allowed to mail their proxy vote to the firm, (ii) shareholders are not required to deposit their shares prior to the General Shareholders’ Meeting, (iii) cumulative voting or proportional representation of minorities on the board of directors is allowed, (iv) an oppressed minority mechanism is in place, (v) the minimum percentage of share capital that entitles a shareholder to call for an Extraordinary Shareholders’ Meeting is less than or equal to 10 percent, and (vi) shareholders have preemptive rights that can only be waived by a shareholders’ vote. In economies with higher values of Anti-Director, minority shareholder are better protected against expropriation by management and large shareholders and should therefore be more willing to provide the external resources that industries need. Rule of Law is an assessment of the law and order tradition of a country that ranges from 10, strong law and order tradition, to 1, weak law and order tradition. This measure was 12 constructed by ICRG and is an average over the period 1982-1990. In countries with a higher law and order tradition, outside investors can more easily enforce their claims and rights and should therefore be more willing to provide external finance. Table 2 provides descriptive statistics and the correlations for our measures of financial development and structure. There is a large variance in the measures of both financial development and structure. Japan shows the highest value for Finance-Activity and Sri Lanka the lowest. Structure-Activity classifies Great Britain as the most market-based system and Sri Lanka as the most bank-based system. We also note that most indicators of financial development are positively correlated with the indicators of financial structure, i.e. financially more developed economies tend to have market-based systems. Table A1 lists all measures of financial development, structure and the legal indicators for the countries included in our study. 3.3. Industry Growth Rates Our dependent variables is the average annual growth rate of value added. We use the data obtained by Rajan and Zingales from the Industrial Statistics Yearbook database put together by the United Nations Statistical Division (1993). We also use a decomposition of the industry growth rate. Specifically, we consider the growth in the number of establishments and the average size of establishments. 10 Table 3 lists descriptive statistics and correlations between the three different dependent variables. We note that the growth rate in the number of establishments is negatively correlated with the growth rate in the average size of firms. 10 There are no cross-country data available on firms. An establishment is defined as a “unit which engages, under a single ownership or control, in one, or predominantly one, kind of activity at a single location.” The growth in the number of establishments (average size of establishment) is defined as the log difference of the number of establishments (value added in the industry divided by number of establishments) at the beginning and the end of the period. 13 4. The Results 4.1 Financial Development and Industry Growth We first present the results of regressions of industry growth rates on the interaction of financial development and external dependence. Our regressions differ from those presented by Rajan and Zingales to the extent that (i) our measures of financial development capture both the effects of financial intermediary and stock market development, and (ii) we include the indicators of financial sector development in logs instead of levels to thus allow for nonlinearity in the relationship between financial development and growth. To make our results comparable to Rajan and Zingales’ results, we include the “Differential in real growth rate”. This indicates how much faster the industry at the 75th percentile of external dependence (Machinery) would have grown than the industry at the 25th percentile (Beverages) in the country at the 75th percentile of the respective measure of financial development as compared to the country at the 25th percentile. The results in Table 4 indicate a significantly positive interaction of external dependence and financial development on industry growth. The coefficients on the interaction terms of all our indicators of financial sector development and external dependence are significantly positive at the five percent level. We start with the top panel and Finance-Activity. The results of the OLS regressions indicate that, for a given industry with a positive external dependence ratio, a higher level of Finance-Activity results in a higher growth rate of this industry. To illustrate the significance of this result, consider the growth differential of 0.8 percent. The coefficient estimate thus predicts that Machinery grows 0.8 percentage points faster than Beverages in Israel as compared to Greece. The results in columns 2 through 4 indicate that this result is robust to the use of other measures of financial sector development. The results of the instrumental variable regressions reported in the bottom panel of Table 4 strengthen these results and show that the link between external dependence, financial development and industry growth is not due to simultaneity bias or reverse causality. We report the regression results using TSLS and the legal origin dummies as instruments for financial sector development. The interaction terms with all three indicators of financial development show coefficients that are significant at the five percent level and the coefficients are of larger 14 size than in the OLS regressions.11 These results therefore indicate that financial intermediaries and markets ameliorate market frictions and that therefore industries with higher need of external finance grow faster in these economies. 4.2 Financial Structure and Industry Growth The results reported so far, confirm the results reported by Rajan and Zingales; industries that depend heavily on external finance, grow faster in economies with higher levels of financial development. We will now turn to the question whether a specific structure of financial system enhances growth of these industries. The results in Table 5 indicate that the financial structure does not have an independent impact on industrial growth patterns across countries. Although the interaction terms with Structure-Activity and Structure-Aggregate show coefficients that are significant at the five percent level in the OLS regressions, these results are not confirmed by the instrumental variable regressions. These results might be due to deficiencies in our measures of financial structure. So is Mexico classified as market-based financial system not because of a high Value Traded, but because of a relatively low value for Bank Credit. Sri Lanka, on the other hand, is classified as bank-based, not because of a high level of Bank Credit, but rather because of a low level of Value Traded. We therefore now turn to regressions where we include interaction terms with indicators of both financial development and financial structure. The results in Table 6 indicate that even when controlling for the level of financial development, the interaction of external dependence and financial structure does not have a significant impact on industrial growth patterns across countries.12 Whereas the interaction terms with all indicators of financial development are significant at the five percent level, none of the interaction terms with our financial structure measure is significant. These results indicate strong evidence in favor of the financial services view and against both the bank-based and market-based view. Neither a bank-based nor a market-based system seems to be better in ameliorating market frictions. 11 12 We do not include Finance-Dummy, since it cannot be instrumented for. In the following we will only present the TSLS results. The OLS regressions yield similar results. 15 To evaluate the legal-based approach we replace our indicators of financial development with Creditor, Anti-director and Rule of Law. 13 To test for the joint significance of these legal variables we include a F-test of the three interaction terms. The results in Table 7 provide support for the legal-based approach. While none of the interaction terms of our financial structure variables is significant, the interaction terms of the three legal variables are jointly significant. The p-values for the individual interaction terms indicate that it is especially the enforcement of rights that explains industrial growth patterns across countries. 4.3 Unbalanced Financial Systems and Industry Growth The results so far indicate that financial structure does not have any impact on industrial growth patterns across countries. However, one could argue that although the specific mix of banks and markets does not matter, unbalanced financial systems that either have only welldeveloped banks or only well-developed markets can hurt economic growth. We therefore construct three additional variables. Unbalanced-Bank equals one if Bank Credit is greater than the sample median and Value Traded is less than the sample median, and zero otherwise.14 Unbalanced-Market equals one if Value Traded is greater than the sample median and Bank Credit less than the sample median, and zero otherwise. 15 Finally, Unbalanced equals one if either Unbalanced Bank or Unbalanced Market equals one, and zero otherwise. The results in Table 8 indicate that classifying countries as having unbalanced financial systems does not help explain industrial growth patterns across countries. While the interaction terms of all our indicators of financial development enter significantly at the five percent level, none of the interaction terms with the indicators of unbalanced financial systems enters significantly. 13 Alternatively, we could use these legal indicators as instruments to thus extract the exogenous component of financial development explained by these legal rights and their enforcement. The results are similar to the ones reported here. 14 Austria, Chile, Denmark, Finland, Italy and Portugal are classified as having unbalanced bank-based systems. 15 Australia, Brazil, India, Norway, New Zealand and Sweden are classified as having unbalanced market-based systems. 16 4.4 Financial Structure and the Sources of Industry Growth We can decompose the industry growth rates into two components: the growth in the number of establishments and the growth in the average size of establishments. The creation of new establishments is more likely to depend on external funds than the expansion of existing establishments, which can be financed with internal resources. The decomposition of industry growth therefore allows us both a robustness test of the previous results and a more detailed exploration of the mechanism through which financial development and potentially financial structure determine industrial growth patterns across countries. The results in Table 9 indicate that financial development increases the growth in the number of establishments in industries that are dependent on external finance, whereas financial structure does not explain industry patterns in the growth in the number of establishments across countries. The results in Table 10 indicate that neither financial development nor structure can explain industry patterns in the growth rate of the average size of establishments across countries.16 Table 11 gives evidence that the legal determinants of financial development can explain industry patterns in the growth in the number of establishments, but not in the growth in the average size of establishments across countries. The interaction terms with financial structure are again insignificant. The results in Table 12 show that unbalanced financial system are at a disadvantage when it comes to the growth in the number of establishments in externally dependent industries. The interaction term of Unbalanced enters significantly negative at the five percent level in all regressions. Table 13 indicates that unbalanced system might be at an advantage when it comes to the growth in the average size of establishments in externally dependent industries. Since there is no theoretical literature about the effects of balanced versus unbalanced financial system, we can only speculate about these results. Unbalanced bank-based systems might exacerbate the problems that powerful banks constitute for young firms. Unbalanced market-based systems might not be able to provide the necessary staged financing for young firms. The access hurdles for young firms, especially in externally dependent industries, and the resulting lower degree of 16 The results concerning financial development are consistent with the results obtained by Rajan and Zingales (1998). 17 industrial competition in unbalanced financial systems might explain the expansion of existing firms in these industries in countries with unbalanced financial systems. In sum, these results indicate that financial development and its legal determinants help externally dependent industries grow faster by enabling the start-up of new firms and not through the expansion of existing ones. This is consistent with the Schumpeterian view that financial development enhances economic growth by allowing new firms and projects to develop. These results are also consistent with previous studies that show that financial development enhances economic growth through a better resource allocation and not through capital accumulation.17 5. Conclusions This paper examined the following questions: Do industries that depend heavily on external finance grow faster in bank-based or market-based systems? Are new firms more likely to form in a bank-based or market-based financial system? Or, is it only rather the overall level of financial development and its legal determinants that explain industrial growth patterns and emergence of new firms across countries. The results do not provide support for either the bank-based or the market-based view. Differences in financial structure cannot explain industrial growth patterns across countries. Differences in financial development, in creditor rights, shareholder rights and their enforcement, however, can explain differences in industrial growth patterns across countries. Together, these findings provide support for the financial-services approach and the legal-based approach. They indicate that industries that are heavy users of external finance, do not grow faster in an economy with either a market- or bank-based system, but in countries with higher overall levels of financial development and with better protection of outside investors. It is the overall level of financial development and not a specific structure of the financial sector that allows new firms to overcome barriers to obtaining external finance. Two caveats have to be made concerning our results. The results of both this paper and the study by Rajan and Zingales (1998) depend crucially on the assumption that external dependence as measured for a sample of U.S. firms is a good proxy for the “natural” dependence of firms on external finance across countries. Given that the findings of Rajan and Zingales are robust to 17 See Beck, Levine, and Loayza (2000). 18 alternative measures of external dependence, we can be relatively confident about this assumption. The other caveat concerns the indicators of financial structure. They might be less precise than one desires. Both Structure-Activity and Structure-Size are constructed as ratios and can therefore produce large outliers in either direction. Nonetheless, many alternative measures of financial structure produce the same conclusions. Further, we obtain the same results after controlling for extreme observations. In sum, the research does not suggest that either a bank-bank or a market-based financial system is particularly conducive for particular industries or new firms creation. It is not financial structure per se, but improving the functioning of the overall financial system that is critical for boosting external finance and facilitating the establishment of new firms. The research also suggests that strengthening the legal rights of outside investors and the overall efficiency of contract enforcement are effective tools for boosting financial development and hence economic development. 19 REFERENCES Allen, Franklin and Gale, Douglas. Comparing Financial Systems. Cambridge, MA: MIT Press, 1999. Allen, Franklin. “Stock Markets and Resource Allocation”, in: C. Mayer and X. Vives (eds.): Capital Markets and Financial Intermediation, 1993, Cambridge Univesity Press, Cambridge. 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Levine, Ross. “The Legal Environment, Banks, and Long-Run Economic Growth,” Journal of Money, Credit, and Banking, August 1998. Levine, Ross. “Law, Finance, and Economic Growth”, Journal of Financial Intermediation, 1999, 8(1/2), pp. 36-67. Levine, Ross. “Napoleon, Bourses, and Growth: With A Focus on Latin America,” in Market Augmenting Government, Eds. Omar Azfar and Charles Cadwell. Washington, D.C.: IRIS, 2000a, forthcoming. Levine, Ross. “Bank-Based or Market-Based Financial Systems: Which is Better?,” mimeo 2000b. Levine, Ross; Loayza, Norman; Beck, Thorsten. “Financial Intermediation and Growth: Causality and Causes,” Journal of Monetary Economics, 2000, forthcoming. Rajan, Raghuram G. "Insiders and Outsiders: The Choice Between Informed and Arms Length Debt," Journal of Finance, September 1992, 47(4), pp. 1367-1400. Rajan, Raghuram G. and Zingales, Luigi. "Financial Dependence and Growth," American Economic Review, June 1998. Rajan, Raghuram G. and Zingales, Luigi. “Financial Systems, Industrial Structure, and Growth, mimeo 1999. Reynolds, Thomas H. and Flores, Arturo A. Foreign Law Current Sources of Codes and Legislation in Jurisdictions of the World, Fred B. Rothman & Co. (Littleton Colorado), (AALL Publication Series No. 33). 1996. Shleifer, Andrei and Vishny, Robert W. "Large Shareholders and Corporate Control," Journal of Political Economy, June 1986, 96(3), pp. 461-88. Stiglitz, Joseph E. "Credit Markets and the Control of Capital," Journal of Money, Credit and Banking, May 1985, 17(2), pp. 133-52. Stulz, Rene M. “Financial Structure, Corporate Finance, and Economic Growth,” 1999, Ohio State University mimeo. Wenger, Ekkehard and Kaserer, Christoph. “The German System of Corporate Governance: A Model Which Should Not Be Imitated,” in ” in Competition and Convergence in Financial Markets: The German and Anglo-American Models, Eds: Stanley W. Black and Mathias Moersch, New York: North –Holland Press, 1998, pp. 41-78. 21 Table 1: Measures of External Dependence Across Industries ISIC code Industrial Sector 314 361 323 3211 324 372 322 353 369 313 371 311 3411 3513 341 342 352 355 332 381 3511 331 384 354 3843 321 382 3841 390 362 383 385 3832 3825 356 3522 Tobacco Pottery Leather Spinning Footwear Nonferrous metal Apparel Petroleum refineries Nonmetal mineral products Beverages Iron and steel Food products Pulp, paper Synthetic resins Paper and paper products Printing and publishing Other chemicals Rubber products Furniture Metal products Basic industrial goods excl. fertilizers Wood products Transportation equipment Petroleum and coal products Motor vehicles Textile Machinery Ships Other industries Glass Electric machinery Professional and scientific goods Radios Office and computing products Plastic products Drugs External dependence -0.45 -0.15 -0.14 -0.09 -0.08 0.01 0.03 0.04 0.06 0.08 0.09 0.14 0.15 0.16 0.18 0.20 0.22 0.23 0.24 0.24 0.25 0.28 0.31 0.33 0.39 0.40 0.45 0.46 0.47 0.53 0.77 0.96 1.04 1.06 1.14 1.49 External dependence is defined as capital expenditures (Compustat # 128) minus cash flow from operations divided by capital expenditures. Cash flow from operations is broadly defined as the sum of Comustat funds from operations(items # 110), decreases in inventories, decreases in receivables, and increases in payables. Source: Rajan and Zingales (1998) Table 2: Financial Development and Structure Across Countries Summary Statistics Finance-Activity Finance-Size Finance-Aggregate Finance-Dummy Structure-Activity Mean Median Standard Deviation Maximum Minimum Observations 4.85 5.00 2.09 8.80 0.74 34 4.14 4.29 0.73 5.38 2.70 34 0.00 0.07 1.00 1.84 -1.87 34 0.50 0.50 0.51 1.00 0.00 34 Structure-Size Structure-Aggregate Structure-Dummy -2.50 -2.47 1.24 -0.76 -5.09 34 -0.92 -0.85 0.87 0.88 -2.80 34 0.00 -0.08 1.00 1.46 -1.86 34 0.50 0.50 0.51 1.00 0.00 34 Correlations Finance-Activity Finance-Size Finance-Aggregate Finance-Dummy Structure-Activity Finance-Activity Finance-Size Finance-Aggregate Finance-Dummy Structure-Activity Structure-Size Structure-Aggregate Structure-Dummy Structure-Size Structure-Aggregate Structure-Dummy 1 0.90 (0.001) 0.98 (0.001) 0.78 (0.001) 0.79 (0.001) 0.39 (0.021) 0.65 (0.001) 0.50 (0.003) 1 0.98 (0.001) 0.82 (0.001) 0.51 (0.002) 0.33 (0.057) 0.46 (0.007) 0.32 (0.066) 1 0.82 (0.001) 0.66 (0.001) 0.37 (0.031) 0.57 (0.001) 0.42 (0.013) 1 0.42 (0.013) 0.11 (0.537) 0.29 (0.096) 0.29 (0.091) 1 0.68 (0.001) 0.92 (0.001) 0.79 (0.001) 1 0.92 (0.001) 0.78 (0.001) 1 0.85 (0.001) 1 p-values are reported in parentheses Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Finance-Dummy = Dummy variable that takes the value 0 if total value traded as share of GDP and claims on private sector by financial intermediaries as share of GDP are less than the respective sample mean, 0 otherwise Structure-Activity = log(Total value traded divided by claims on private sector by commercials banks) Structure-Size = log(Market capitalization divided by claims on private sector by commercials bank) Structure-Aggregate = First principal components of Structure-Activity and Structure-Size Structure-Dummy = Dummy variable that takes the value 1 if Structure-Aggregate is above the median, 0 otherwise Table 3: Industry Growth Across Countries Summary Statistics Industry's real growth Industry's growth in Industry's growth in number of firms average size of firms Mean Median Standard Deviation Maximum Minimum Observations 3.00 2.73 7.17 33.00 -44.71 1052 0.89 0.60 6.93 75.86 -33.68 926 2.61 2.76 8.65 41.03 -52.05 883 Correlations Industry's real growth Industry's growth in Industry's growth in number of firms average size of firms Industry's real growth 1 Industry's growth in number of firms 0.26 (0.001) 1 Industry's growth in average size of firms 0.64 (0.001) -0.57 (0.001) 1 Industry's real growth = annual compounded growth rate in real value added for 1980-90. Industry's growth in number of firms = log-difference between number of establishments in 1990 and 1980 Industry's growth in average size of firms = log-difference between industry's value added divided by number of establishments in 1990 and 1980 Table 4: Financial Development and Industry Growth OLS Regressions Finance-Activity Finance-Size Finance-Aggregate Finance-Dummy Interaction (external dependence x Finance-Activity) 0.721 (0.003) Interaction (external dependence x Finance-Size) 1.867 (0.017) Interaction (external dependence x Finance-Aggregate ) 1.474 (0.006) Interaction (external dependence x Finance-Dummy ) 3.274 (0.001) R2 0.314 0.313 0.314 0.315 Number of observations 1016 1016 1016 1016 Differential in real growth rate 0.810 0.844 0.879 1.205 TSLS Regressions Finance-Activity Finance-Size Finance-Aggregate Interaction (external dependence x Finance-Activity) 0.878 (0.010) Interaction (external dependence x Finance-Size) 2.964 (0.005) Interaction (external dependence x Finance-Aggregate ) 1.944 (0.007) Number of observations 1016 1016 1016 Differential in real growth rate 0.986 1.339 1.159 The dependent variable is the annual compounded growth rate in real value added for 1980-90 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. The differential in real growth rate indicates how much faster an industry at the 75th percentile of external dependence grows with respect to an industry at the 25th percentile level in a country at the 75th percentile of the respective measure of financial development compared to a country at the 25th percentile. We use the British, French and German legal origin dummies as instruments for financial development in the TSLS regressions. Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Finance-Dummy = Dummy variable that takes the value 0 if total value traded as share of GDP and claims on private sector by financial intermediaries as share of GDP are less than the respective sample mean, 0 otherwise Table 5: Financial Structure and Industry Growth OLS Regressions Structure-Activity Structure-Size Structure-Aggregate Structure-Dummy Interaction (external dependence x Structure-Activity) 0.887 (0.033) Interaction (external dependence x Structure-Size) 0.698 (0.144) Interaction (external dependence x Structure-Aggregate ) 0.914 (0.046) Interaction (external dependence x Structure-Dummy ) 1.101 (0.233) R2 0.311 0.309 0.310 0.309 Number of observations 1016 1016 1016 1016 TSLS Regressions Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) 1.407 (0.064) Interaction (external dependence x Structure-Size) 1.119 (0.246) Interaction (external dependence x Structure-Aggregate ) Number of observations 1.415 (0.121) 1016 1016 1016 The dependent variable is the annual compounded growth rate in real value added for 1980-90 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. We use the British, French and German legal origin dummies as instruments for financial structure in the TSLS regressions. Structure-Activity = log(Total value traded divided by claims on private sector by commercials banks) Structure-Size = log(Market capitalization divided by claims on private sector by commercials bank) Structure-Aggregate = First principal components of Structure-Activity and Structure-Size Structure-Dummy = Dummy variable that takes the value 1 if Structure-Aggregate is above the median, 0 otherwise Table 6: Financial Development, Financial Structure, and Industry Growth Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) -1.314 (0.308) Interaction (external dependence x Structure-Size) -0.103 (0.892) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Activity) Number of observations -0.416 (0.640) 1.350 (0.033) 0.719 (0.018) 0.842 (0.022) 1016 1016 1016 Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) -0.868 (0.435) Interaction (external dependence x Structure-Size) -0.175 (0.825) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Size) Number of observations -0.441 (0.628) 3.659 (0.029) 2.494 (0.010) 2.843 (0.014) 1016 1016 1016 Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) -1.137 (0.346) Interaction (external dependence x Structure-Size) -0.151 (0.845) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Aggregate) Number of observations -0.461 (0.609) 2.742 (0.029) 1.629 (0.013) 1.899 (0.016) 1016 1016 1016 The dependent variable is the annual compounded growth rate in real value added for 1980-90 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. All regressions are TSLS. We use the British, French and German legal origin dummies and the share of Catholic, Muslim and Protestant population in total population as instruments for financial development and financial structure. Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Structure-Activity = log(Total value traded divided by claims on private sector by commercials banks) Structure-Size = log(Market capitalization divided by claims on private sector by commercials bank) Structure-Aggregate = First principal components of Structure-Activity and Structure-Size Table 7: Financial Structure, the Legal Environment, and Industry Growth Structure-Activity Interaction (external dependence x Structure-Activity) Structure-Size Structure-Aggregate -1.494 (0.124) Interaction (external dependence x Structure-Size) -0.543 (0.695) Interaction (external dependence x Structure-Aggregate ) -1.651 (0.243) Interaction (external dependence x Creditor) 0.229 (0.687) 0.300 (0.614) 0.181 (0.756) Interaction (external dependence x Anti-Director) 1.327 (0.078) 0.598 (0.594) 1.455 (0.178) Interaction (external dependence x Rule of Law) 1.179 (0.001) 0.818 (0.001) 1.059 (0.001) F-test Creditor, Anti-Director and Rule of Law 4.77 (0.003) 4.95 (0.002) 4.92 (0.002) 1016 1016 1016 Number of observations The dependent variable is the annual compounded growth rate in real value added for 1980-90 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. All regressions are TSLS. We use the British, French and German legal origin dummies and the share of Catholic, Muslim and Protestant population in total population as instruments for financial structure and the legal determinants. Structure-Activity = log(Total value traded divided by claims on private sector by commercials banks) Structure-Size = log(Market capitalization divided by claims on private sector by commercials bank) Structure-Aggregate = First principal components of Structure-Activity and Structure-Size Creditor = index of secured creditor rights Anti-director = index of minority shareholder rights Rule of Law = Measure of the law and order tradition of a country. Table 8: Financial Development, Unbalanced Financial Systems, and Industry Growth Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) -0.528 (0.552) Interaction (external dependence x Unbalanced-Bank ) 0.788 (0.402) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Activity) Number of observations -1.861 (0.137) 0.855 (0.014) 0.879 (0.009) 0.913 (0.009) 1016 1016 1016 Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) -0.805 (0.379) Interaction (external dependence x Unbalanced-Bank ) 0.171 (0.860) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Size) Number of observations -1.614 (0.179) 2.939 (0.008) 2.844 (0.009) 3.276 (0.003) 1016 1016 1016 Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) -0.656 (0.466) Interaction (external dependence x Unbalanced-Bank ) 0.498 (0.599) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Aggregate) Number of observations -1.764 (0.150) 1.905 (0.011) 1.901 (0.009) 2.095 (0.005) 1016 1016 1016 The dependent variable is the annual compounded growth rate in real value added for 1980-90 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. All regressions are TSLS. We use the British, French and German legal origin dummies as instruments for financial development. Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Unbalanced-Bank = 1 if a country has a value of Bank Credit above the sample median and a value of Value Traded below the sample median, 0 otherwise Unbalanced-Market = 1 if a country has a value of Bank Credit below the sample median and a value of Value Traded above the sample median, 0 otherwise Unbalanced = 1 if either Unbalanced-Bank or Unbalanced-Market equals 1, 0 otherwise Table 9: Financial Development, Financial Structure, and the Growth in Number of Firms Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) 0.127 (0.905) Interaction (external dependence x Structure-Size) 0.729 (0.310) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Activity) Number of observations 0.571 (0.474) 0.659 (0.227) 0.572 (0.015) 0.521 (0.092) 903 903 903 Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) 0.275 (0.748) Interaction (external dependence x Structure-Size) 0.786 (0.282) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Size) Number of observations 0.609 (0.427) 1.969 (0.169) 1.914 (0.014) 1.746 (0.074) 903 903 903 Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) 0.179 (0.852) Interaction (external dependence x Structure-Size) 0.747 (0.302) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Aggregate) Number of observations 0.574 (0.465) 1.400 (0.193) 1.268 (0.014) 1.163 (0.081) 903 903 903 The dependent variable is the log difference between the number of establishments in 1990 and 1980 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. All regressions are TSLS. We use the British, French and German legal origin dummies and the share of Catholic, Muslim and Protestant population in total population as instruments for financial development and financial structure. Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Structure-Activity = log(Total value traded divided by claims on private sector by commercials banks) Structure-Size = log(Market capitalization divided by claims on private sector by commercials bank) Structure-Aggregate = First principal components of Structure-Activity and Structure-Size Table 10: Financial Development, Financial Structure, and the Growth in Average Size of Firms Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) -1.929 (0.136) Interaction (external dependence x Structure-Size) -1.364 (0.104) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Activity) Number of observations -1.548 (0.102) 1.050 (0.092) 0.349 (0.243) 0.615 (0.089) 883 883 883 Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) -1.322 (0.212) Interaction (external dependence x Structure-Size) -1.314 (0.125) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Size) Number of observations -1.349 (0.144) 2.430 (0.131) 1.166 (0.221) 1.805 (0.103) 883 883 883 Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) -1.610 (0.170) Interaction (external dependence x Structure-Size) -1.347 (0.112) Interaction (external dependence x Structure-Aggregate ) Interaction (external dependence x Finance-Aggregate) Number of observations -1.462 (0.118) 1.934 (0.111) 0.774 (0.230) 1.283 (0.094) 883 883 883 The dependent variable is the log difference between the average size of establishments in 1990 and 1980 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. All regressions are TSLS. We use the British, French and German legal origin dummies and the share of Catholic, Muslim and Protestant population in total population as instruments for financial development and financial structure. Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Structure-Activity = log(Total value traded divided by claims on private sector by commercials banks) Structure-Size = log(Market capitalization divided by claims on private sector by commercials bank) Structure-Aggregate = First principal components of Structure-Activity and Structure-Size Table 11: Financial Structure, the Legal Environment, and the Sources of Industry Growth Growth of the Number of Firms Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) -0.858 (0.329) Interaction (external dependence x Structure-Size) 0.104 (0.926) Interaction (external dependence x Structure-Aggregate ) -0.564 (0.650) Interaction (external dependence x Creditor) 0.749 (0.138) 0.788 (0.118) 0.749 (0.137) Interaction (external dependence x Anti-Director) 1.175 (0.126) 0.440 (0.069) 0.928 (0.343) Interaction (external dependence x Rule of Law) 0.719 (0.012) 0.472 (0.010) 0.588 (0.024) F-test Creditor, Anti-Director and Rule of Law 2.49 (0.059) 3.05 (0.028) 2.39 (0.067) 903 903 903 Number of observations Growth of the Average Size of Firms Structure-Activity Structure-Size Structure-Aggregate Interaction (external dependence x Structure-Activity) -1.033 (0.365) Interaction (external dependence x Structure-Size) -1.323 (0.331) Interaction (external dependence x Structure-Aggregate ) -1.814 (0.259) Interaction (external dependence x Creditor) -0.271 (0.636) -0.308 (0.609) -0.336 (0.575) Interaction (external dependence x Anti-Director) 0.163 (0.853) 0.157 (0.887) 0.675 (0.578) Interaction (external dependence x Rule of Law) 0.587 (0.101) 0.421 (0.072) 0.623 (0.055) F-test Creditor, Anti-Director and Rule of Law 1.57 (0.195) 1.30 (0.273) 1.70 (0.166) 883 883 883 Number of observations The dependent variable is the log difference in the number of establishment (average size of establishments) between 1990 and 1980 in the top panel (bottom panel) for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. All regressions are TSLS. We use the British, French and German legal origin dummies and the share of Catholic, Muslim and Protestant population in total population as instruments for financial structure and the legal determinants. Structure-Activity = log(Total value traded divided by claims on private sector by commercials banks) Structure-Size = log(Market capitalization divided by claims on private sector by commercials bank) Structure-Aggregate = First principal components of Structure-Activity and Structure-Size Creditor = index of secured creditor rights Anti-director = index of minority shareholder rights Rule of Law = Measure of the law and order tradition of a country. Table 12: Financial Development, Unbalanced Financial Systems, and the Growth in Number of Firms Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) -2.787 (0.008) Interaction (external dependence x Unbalanced-Bank ) -0.951 (0.303) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Activity) Number of observations -3.099 (0.039) 1.110 (0.002) 0.947 (0.002) 1.077 (0.003) 903 903 903 Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) -3.160 (0.004) Interaction (external dependence x Unbalanced-Bank ) -1.724 (0.074) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Size) Number of observations -2.766 (0.051) 3.659 (0.001) 3.094 (0.002) 3.496 (0.002) 903 903 903 Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) -2.963 (0.006) Interaction (external dependence x Unbalanced-Bank ) -1.312 (0.160) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Aggregate) Number of observations -2.949 (0.043) 2.427 (0.001) 2.058 (0.002) 2.344 (0.002) 903 903 903 The dependent variable is the log difference in the number of establishments in 1990 and 1980 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. All regressions are TSLS. We use the British, French and German legal origin dummies as instruments for financial development. Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Unbalanced-Bank = 1 if a country has a value of Bank Credit above the sample median and a value of Value Traded below the sample median, 0 otherwise Unbalanced-Market = 1 if a country has a value of Bank Credit below the sample median and a value of Value Traded above the sample median, 0 otherwise Unbalanced = 1 if either Unbalanced-Bank or Unbalanced-Market equals 1, 0 otherwise Table 13: Financial Development, Unbalanced Financial Systems, and the Growth in Average Size of Firms Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) 2.143 (0.027) Interaction (external dependence x Unbalanced-Bank ) 1.692 (0.091) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Activity) Number of observations 1.442 (0.254) -0.079 (0.822) 0.073 (0.828) 0.006 (0.986) 883 883 883 Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) 2.115 (0.033) Interaction (external dependence x Unbalanced-Bank ) 1.617 (0.094) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Size) Number of observations 1.369 (0.260) -0.111 (0.921) 0.297 (0.785) 0.281 (0.804) 883 883 883 Unbalanced Unbalanced-Bank Unbalanced-Market Interaction (external dependence x Unbalanced ) 2.134 (0.029) Interaction (external dependence x Unbalanced-Bank ) 1.661 (0.089) Interaction (external dependence x Unbalanced-Market ) Interaction (external dependence x Finance-Aggregate) Number of observations 1.398 (0.260) -0.127 (0.867) 0.177 (0.808) 0.098 (0.899) 883 883 883 The dependent variable is the log difference in the average size of establishments in 1990 and 1980 for each industry in each country. The p-values for heteroskedasticity robust standard errors are reported in parentheses. All regressions also include the industry's share of total value added in manufacturing in 1980. All regressions are TSLS. We use the British, French and German legal origin dummies as instruments for financial development. Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Unbalanced-Bank = 1 if a country has a value of Bank Credit above the sample median and a value of Value Traded below the sample median, 0 otherwise Unbalanced-Market = 1 if a country has a value of Bank Credit below the sample median and a value of Value Traded above the sample median, 0 otherwise Unbalanced = 1 if either Unbalanced-Bank or Unbalanced-Market equals 1, 0 otherwise Table A1: Financial Development, Financial Structure and the Legal Environment Across Countries Country Australia Austria Belgium Brazil Canada Chile Colombia Denmark Egypt Finland France Germany Greece India Israel Italy Japan Malaysia Mexico Netherlands New Zealand Norway Pakistan Peru Philippines Portugal South Africa Spain Sri Lanka Sweden Turkey UK US Zimbabwe Finance-Activity Finance-Size Finance-Aggregate Finance-Dummy Structure-Activity 6.76 5.23 4.34 4.72 6.77 4.23 1.95 4.70 1.70 4.99 6.01 7.26 2.59 4.48 6.37 5.01 8.80 6.55 3.50 7.31 5.34 5.75 2.59 1.40 4.09 4.23 6.03 5.71 0.74 6.68 0.98 7.14 8.11 2.86 4.77 4.48 3.87 3.49 4.76 4.24 3.34 4.09 3.46 4.28 4.65 4.67 3.92 3.51 4.30 4.09 5.38 4.87 2.81 4.99 4.37 4.56 3.34 2.70 3.64 4.31 5.23 4.43 3.23 4.83 2.83 4.72 5.15 3.32 0.91 0.34 -0.32 -0.48 0.91 -0.08 -1.27 -0.07 -1.24 0.14 0.64 0.97 -0.71 -0.53 0.49 0.00 1.84 0.93 -1.27 1.21 0.28 0.52 -1.12 -1.85 -0.53 -0.03 1.05 0.42 -1.64 0.93 -1.87 0.97 1.51 -1.06 1 1 0 0 1 0 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 1 0 0 0 1 1 1 0 1 0 1 1 0 Finance-Activity = log(Total value traded as share of GDP * Claims on private sector by financial institutions as share of GDP) Finance-Size = log(Market capitalization and claims on private sector by financial institutions as share of GDP) Finance-Aggregate = First principal component of Finance-Activity and Finance-Size Finance-Dummy = Dummy variable that takes the value 0 if total value traded as share of GDP and claims on private sector by financial intermediaries as share of GDP are less than the respective sample mean, 0 otherwise Structure-Activity = log(Total value traded divided by claims on private sector by commercials banks) Structure-Size = log(Market capitalization divided by claims on private sector by commercials bank) Structure-Aggregate = First principal components of Structure-Activity and Structure-Size Structure-Dummy = Dummy variable that takes the value 1 if Structure-Aggregate is above the median, 0 otherwise Creditor = index of secured creditor rights Anti-director = index of minority shareholder rights Rule of Law = Measure of the law and order tradition of a country. -1.19 -3.55 -2.27 -0.98 -1.35 -3.46 -3.86 -2.80 -4.82 -3.10 -2.83 -1.64 -4.47 -2.04 -1.32 -2.79 -0.77 -1.68 -1.27 -1.65 -1.39 -2.44 -3.75 -2.84 -2.49 -4.26 -2.09 -2.71 -5.09 -1.60 -4.40 -0.76 -0.86 -2.60 Structure-Size 0.05 -2.80 -0.27 -0.30 -0.06 -0.75 -1.47 -0.90 -1.85 -1.33 -1.73 -1.59 -1.62 -1.53 -0.56 -1.57 -0.35 0.11 -0.81 -0.75 0.62 -1.38 -1.70 -0.46 -1.17 -2.66 0.88 -1.55 -0.97 -0.30 -2.10 0.15 -0.24 -0.47 Structure-Aggregate 1.19 -1.64 0.51 1.06 1.05 -0.31 -0.94 -0.12 -1.60 -0.52 -0.65 -0.04 -1.30 -0.17 0.75 -0.53 1.12 1.01 0.62 0.49 1.46 -0.26 -1.03 0.14 -0.15 -1.86 1.32 -0.48 -1.17 0.79 -1.57 1.45 1.15 0.24 Structure-Dummy Creditor Anti-director Rule of Law 1 0 1 1 1 0 0 0 0 0 0 1 0 0 1 0 1 1 1 1 1 0 0 1 0 0 1 0 0 1 0 1 1 1 1 3 2 1 1 2 0 3 4 1 0 3 1 4 4 2 2 4 0 2 3 2 4 0 0 1 3 2 3 2 2 4 1 4 4 2 0 3 5 5 3 2 2 3 3 1 2 5 3 1 4 4 1 2 4 4 5 3 3 3 5 4 3 3 2 5 5 3 10 10 10 6.32 10 7.02 2.08 10 4.17 10 8.98 9.23 6.18 4.17 4.82 8.33 8.98 6.78 5.35 10 10 10 3.03 2.5 2.73 8.68 4.42 7.8 6.25 10 5 8.57 10 3.68