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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
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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.
Beck, Thorsten; Demirgüç-Kunt, Asli; Levine, Ross. “A New Database on Financial
Development and Structure” Washington, D.C.: World Bank Policy Research Working
Paper 2146, 1999.
Beck, Thorsten; Levine, Ross; Loayza, Norman. “Finance and the Sources of Growth,” Journal
of Financial Economics, 2000, forthcoming.
Demirgüç-Kunt, Asli and Levine, Ross. “Financial Structures Across Countries: Stylized Facts”
Washington, D.C.: World Bank Policy Research Working Paper 2143, 1999.
Demirgüç-Kunt, Asli and Maksimovic, Vojislav. "Law, Finance, and Firm Growth," Journal of
Finance, December 1998, 53(6), pp.2107-2137.
Grossman, Sanford, and Hart, Oliver. “Takeover Bids, the Free-Rider Problem, and the Theory
of the Corporation,” Bell Journal of Economics, 1980, 11, 42-64.
Hellwig, Martin. “Banking, Financial Intermediation, and Corporate Finance,” in: A. Giovanni
and C. Mayer (eds.) European Financial Intermediation, 1991, Cambridge University
Press, Cambridge, pp.35-63.
Hellwig, Martin. “On the Economics and Politics of Corporate Finance and Corporate Control,”
working paper, Univesity of Mannheim, 1998.
Laporta, Rafael; Lopez-de-Silanes, Florencio; Shleifer, Andrei; and Vishny, Robert W. “Investor
Protection and Corporate Governance,” mimeo, 1999b.
Laporta, Rafael; Lopez-de-Silanes, Florencio; Shleifer, Andrei; and Vishny, Robert W. “The
Quality of Government,” Journal of Law, Economics, and Organization, 1999a, 15(1),
pp. 222-279.
Laporta, Rafael; Lopez-de-Silanes, Florencio; Shleifer, Andrei; and Vishny, Robert W. "Law and
Finance," Journal of Political Economy, 1998, 106(6), pp. 1113-1155
Laporta, Rafael; Lopez-de-Silanes, Florencio; Shleifer, Andrei; and Vishny, Robert W. “Legal
Determinants of External Finance,” Journal of Finance, July 1997, 52(3), pp. 1131-1150.
Levine, Ross. “Financial Development and Economic Growth: Views and Agenda,” Journal of
20
Economic Literature, June 1997, 3592), pp. 688-726.
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