Explore the link between Financial Structures and Economic Growth

Journal of Financial Economics 65 (2002) 337–363

Funding growth in bank-based and market-based financial systems: evidence from firm-level data$

Aslı Demirg.u-c-Kunt a, Vojislav Maksimovicb,*

aThe World Bank, 1818 H St. N.W., Washington, DC 20433, USA bRobert. H. Smith School of Business, University of Maryland, Van Munching Hall, College Park,

MD 20742, USA

Received 24 July 2000; accepted 22 June 2001

Abstract

We investigate whether firms’ access to external financing to fund growth differs in market- based and bank-based financial systems. Using firm-level data for 40 countries, we compute the proportion of firms in each country relying on external finance and examine how that proportion differs across financial systems. We find that the development of a country’s legal system predicts access to external finance, and stock markets and the banking system affect access to external finance differently. However, we find no evidence that firms’ access to external financing is predicted by several proxies for relative development of stock markets to the development of the banking system. r 2002 Elsevier Science B.V. All rights reserved.

JEL classificaion: G21; G30; K20

Keywords: Financial system; Firm growth; Law; Financial institutions

1. Introduction

A key question in development economics is the relation between a country’s financial system and its economic development. Historians such as Gerschenkron (1962) have sought to explain a perceived relation between the differences in the

$We would like to thank Ross Levine and Thorsten Beck for useful discussions. The views expressed here are the authors’ own and not necessarily those of the World Bank or its member countries. *Corresponding author. Tel.: +1-301-405-2125; fax: +1-301-314-9157. E-mail addresses: [email protected] (A. Demirg.u-c-Kunt), [email protected]

(V. Maksimovic).

0304-405X/02/$ - see front matter r 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 0 4 - 4 0 5 X ( 0 2 ) 0 0 1 4 5 - 9

pattern of economic development between Britain and the Continental European economies and the differences between bank-based and market-based financial systems. More recently, the differences in the relative performance of the Japanese and the US economies have led observers to conclude that bank-based and market- based financial systems may produce different growth patterns.1 La Porta et al. (1997, 1998) challenge this view, and argue that a country’s legal system is a primary determinant of the effectiveness of its financial system. This hypothesis implies that the distinction between market-based and bank-based financial systems is not primarily important for policy.

In this paper we use firm-level data from a panel of 40 countries to analyze how a country’s legal and financial systems affect firms’ access to external finance to fund growth. For each country we predict a financial system based on the country’s legal environment. We use our estimates to ask: Does the financial system have an effect independent of the legal system? Is the use of external financing different in market- based and bank-based systems? Do the market-based and bank-based systems differ in the provision of long-term and short-term funds?

We find that the use of external financing by firms is positively related to the development of both the predicted banking system and the securities markets in each country. However, in our sample we do not find evidence that variations in the development of the financial system that are unrelated to the legal system affect access to external finance. In particular, we find no evidence that firms use external financing differently if they are in countries classified as bank-based or market- based, on the basis of the development of their banking sector relative to their securities markets.

These results are consistent with the LLSV (1998) approach that stresses the primacy of the legal system. The policy implication that flows from the results is that the way to improve access to external finance is to aid in the development of a country’s legal system, and then to let firms and investors contract either directly (as in a market-based system) or through the intermediation of banks.

We also find that securities markets and bank development have a different effect on the type of external finance firms obtain, particularly at relatively low levels of financial development. In those countries where the legal contracting environment predicts a high level of development for securities markets, more firms grow at rates requiring long-term external finance. We do not find the same effect for predicted bank development. Thus, especially for countries with lower levels of financial development, differences in contracting environments that affect the relative development of the stock market and the banking system can have implications for which firms and projects obtain financing.

There exists a growing literature on the effect of financial sector development on economic development. King and Levine (1993a, b) highlight the importance of financial development for macroeconomic growth. Recently Levine and Zervos

1For a critical examination of the effect of the legal and market environment on corporate finance see Stulz (1999). Allen (1993) and Allen and Gale (1999) provide analyses of the relative benefits of market- based and bank-based financial systems.

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363338

(1998), Rajan and Zingales (1998), and Demirg.u-c-Kunt and Maksimovic (1998) explore the relation between financial development and growth of countries, industries and firms, respectively. Wurgler (2000) provides an analysis of capital allocation efficiency in a sample of countries.

The importance of the legal system for corporate finance was first explored by LLSV (1998). Modigliani and Perotti (1999) argue that in the absence of a strong legal system that can protect the rights of external investors, financial transactions are intermediated through institutions or concentrated among agents who have sufficient bargaining power to enforce their rights privately. Demirg.u-c-Kunt and Maksimovic (1996) and Booth et al. (2001) examine whether theories advanced to explain firms’ capital structures in developed countries can explain financing choices in countries with less developed financial markets. Empirical evidence on the effect of legal effectiveness on firm growth and financing is provided by Demirg.u-c-Kunt and Maksimovic (1998, 1999, 2001), and on growth at more aggregated levels by Beck et al. (2000) and Levine (2000). This paper extends the methodology of Demirg.u-c- Kunt and Maksimovic (1998) to address differences in bank-based and market-based systems in firm growth.

The rest of the paper is organized as follows. Section 2 briefly discusses reasons that bank-based and market-based systems perform differently and our approach to testing those differences empirically. Section 3 introduces the data and summary statistics. Our principal results are reported in Section 4 and Section 5 concludes.

2. Bank-based and market-based financial systems

A financial system’s major tasks include mobilizing resources for investment, selecting investment projects to be funded, and providing incentives for the monitoring of the performance of the funded investments. A large body of theoretical and empirical research analyzes how these tasks are performed in a market-based system, and how they are performed in a system where banks and other financial intermediaries play a major role. This research identifies significant differences in incentives to monitor firms. These differences raise the possibility that a bank-based or a market-based system is inherently superior and that economic performance can be enhanced by adopting the superior system.

A second approach, identified by LLSV (1998), stresses the importance of the legal system in determining the enforceable contracts between firms and investors. According to this view, the relevant differences between countries is in the extent to which their financial systems protect investor rights. The distinction between bank- based and market-based systems is seen as secondary.

In our examination of the differences between bank-based and market-based financial systems we adopt a hypothesis that has elements of both these approaches. We posit that there exist significant differences in outcomes between systems in which financial intermediaries (like banks) play the dominant role and those where they do not. For example, as explored by Allen and Gale (1999), banks and stock markets can have a comparative advantage in selecting different types of investment

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 339

projects. Banks can also have a comparative advantage in providing short-term financing.

In common with the legal approach, we posit that the absolute quality of the banks and securities markets in a country depends on the legal system’s ability to enforce contracts. However, we argue that the legal systems in different countries can have a comparative advantage in supporting a quality banking system or quality securities markets. Thus, for example, a country with an inefficient legal system can have a low-quality financial system. However, a country can, through a combination of administrative regulation of the banking system and strong banks with bargaining power vis-"a-vis their customers, partially compensate for the effect of the deficiency of the legal system on banks. It can be more difficult to compensate for the effect of poor legal protections on securities markets. Thus, while the level of development of a country’s legal system can determine the quantity of financial services supplied, the comparative advantage in supporting intermediaries and markets determines the optimal mix of banks versus markets.

These considerations suggest the following hypotheses:

H1. For each country there is a ‘‘warranted’’ level of development of the banking sector and of stock markets, as a function of the level of development of the contracting environment. The provision of external financing to firms is greater, the higher the warranted level of development of these sectors.

H2. The expansion of one of the sectors, banks or securities markets beyond the levels warranted by the contracting environment, is unlikely to produce an improved allocation of resources.

H3. Because the banking system and securities markets have a comparative advantage in providing different services, cross-country differences in the warranted development levels of markets and banking sectors affects the type of financial constraints faced by firms.

2.1. Testing for differences in performance between the systems

Differences between outcomes in market-based and bank-based systems should, if they exist, be observable at the country, industry, or firm levels. In principle, a test would relate a performance measure, usually the growth rate, to the financial system or legal system characteristics. While this results in straightforward applications at the country level, there exists a potential selection bias when this procedure is applied at lower levels of aggregation, such as the industry and firm levels.

The selection bias arises because the way in which production is organized in different countries depends on their legal and financial systems. Thus, the firms observed are adapted to the financial system of that country. Analyzing growth rates of those firms does not take into account the possibility that a different financial system might induce a different mix of firms and that the different mix might increase wealth.

To fix ideas, consider an example involving two countries, B and M. Country B has a bank-based financial system (perhaps because its legal system favors that type

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363340

of contracting). Country M has a market-based system. Assume that the two financial systems have different comparative advantages in supplying financing. In particular, assume that market-based systems are superior at providing long-term financing. Consider entrepreneurs in each country starting firms in the same industry. Entrepreneurs in country M have a greater choice of technology and organizational forms since they have greater access to long-term financing. As a result, economy M is better off. However, once the initial investment is made, each individual firm, and the industry as a whole, can grow at the same rate in country B and in country M. Indeed, firms in country B may grow faster because they can switch to a superior technology as they accumulate enough funds over time to self- finance its acquisition. In this case, a comparison of firm or industry growth rates across countries may not identify the benefits of a market-based financial system.

An alternative approach, developed in Demirg.u-c-Kunt and Maksimovic (1998), is to test for differences between financial systems by testing whether the proportion of firms growing at rates that exceed the rate that they can self-finance, or finance using short-term instruments only, differs across different financial or legal systems. This approach would identify the financial system in economy M above as being superior. This is the approach we employ below, using firm-specific data to determine whether each firm in the sample is constrained.

While the use of firm-specific data brings advantages, it also entails two potential costs. First, the firms for which data is available are likely to be a relatively small number of the largest publicly traded firms in each economy. While such firms are of independent interest Beck et al. (2001) show that the financial and legal constraints they face are not fully representative of firms in the economy. However, industry- level data can suffer from the opposite bias: many of the firms included in industry statistics are very small and would not qualify for significant external financing under any financial system. Second, as discussed by Ball et al. (2000), the quality of firm- level financial data differs across countries. Thus, the findings of firm-level and industry-level studies need to be assessed jointly.

3. Data and summary statistics

The firm-level data consist of financial statements for the largest publicly traded manufacturing firms in 40 countries (SIC codes 2000-3999). Our sample of firms contains 45,598 annual observations over the period 1989–1996. The sample is from Worldscope and contains data from both developed and developing countries as listed in the appendix. For each of the countries we also use data on financial-system development compiled by Beck et al. (1999).

In Table 1 we present pertinent facts about the level of economic and institutional development in the sample countries. The countries are arranged from highest to lowest average per capita Gross Domestic Product (RGDPPC) in 1990 dollars. They range from Switzerland, with a per capita income of $26,972 to Pakistan, with a per capita income of $319. As an indicator of the ability of firms to enter into financial contracts, we use a commercial index of experts’ evaluations of the state’s efficiency

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 341

T a b le

1 C o u n tr ie s in

th e sa m p le

a n d th ei r le g a l a n d fi n a n ci a l in d ic a to rs

G D P /C

A P is th e re a l G D P p er

ca p it a in

1 9 9 0 U S $ . L a w

a n d o rd er

in d ic a to r, p ro d u ce d b y In te rn a ti o n a l C o u n tr y R is k ra ti n g a g en cy , re fl ec ts

th e d eg re e to

w h ic h th e ci ti ze n s o f a co u n tr y a re

w il li n g to

a cc ep t th e es ta b li sh ed

in st it u ti o n s to

m a k e a n d im

p le m en t la w s a n d a d ju d ic a te

d is p u te s. It is sc o re d b et w ee n ze ro

a n d si x w it h h ig h er

sc o re s in d ic a ti n g so u n d p o li ti ca l in st it u ti o n s a n d a st ro n g co u rt sy st em

. L o w er

sc o re s in d ic a te

a tr a d it io n o f d ep en d in g o n p h y si ca l fo rc e o r

il le g a l m ea n s to

se tt le

cl a im

s. C o m m o n -l a w

D u m m y ta k es

th e v a lu e o n e fo r co m m o n -l a w

co u n tr ie s a n d th e v a lu e ze ro

fo r o th er s. C re d it o r ri g h ts

is a n in d ex

th a t ra n g es

fr o m

ze ro

to fo u r a n d a g g re g a te s cr ed it o r ri g h ts a n d S h a re h o ld er

ri g h ts is a n in d ex

th a t ra n g es

fr o m

ze ro

to fi v e a n d a g g re g a te s sh a re h o ld er

ri g h ts

a s d es cr ib ed

in th e te x t. T h es e th re e v a ri a b le s a re

o b ta in ed

fr o m

L a P o rt a et

a l. (1 9 9 8 ). T u rn o v er

is th e to ta l v a lu e o f sh a re s tr a d ed

in th e st o ck

ex ch a n g e

d iv id ed

b y m a rk et

ca p it a li za ti o n . S to ck

m a rk et

d a ta

a re

fr o m

IF C ’s E m er g in g M a rk et

D a ta

B a se . B a n k /G

D P is th e to ta l a ss et s o f th e d ep o si t m o n ey

b a n k s

d iv id ed

b y G D P . It is o b ta in ed

fr o m

IM F , In te rn a ti o n a l F in a n ci a l S ta ti st ic s. M a rk et

is a v a ri a b le th a t ta k es

o n th e v a lu e 1 fo r m a rk et -b a se d fi n a n ci a l sy st em

s a n d 0 fo r b a n k -b a se d sy st em

s a s d efi n ed

in D em

ir g .u -c- K u n t a n d L ev in e (1 9 9 9 ). A ll v a lu es

a re

1 9 8 9 – 1 9 9 6 a v er a g es .

G D P /C

A P

(U S $ )

L a w

a n d o rd er

in d ic a to r

C o m m o n -l a w

D u m m y

C re d it o r

ri g h ts

in d ex

S h a re h o ld er

ri g h ts

in d ex

T u rn o v er

B a n k /G

D P

M a rk et

S w it ze rl a n d

2 6 9 7 2

6 .0 0

0 1

2 0 .7 4

1 .7 4

0 Ja p a n

2 3 4 6 7

5 .4 4

0 2

4 0 .4 3

1 .3 1

0 N o rw

a y

2 2 1 6 2

6 .0 0

0 2

4 0 .5 2

0 .7 1

0 D en m a rk

2 1 4 4 7

6 .0 0

0 3

2 0 .4 2

0 .5 1

0 U n it ed

S ta te s

1 9 9 9 8

6 .0 0

1 1

5 0 .7 1

0 .7 5

1 S w ed en

1 9 5 8 2

6 .0 0

0 2

3 0 .4 2

0 .5 5

1 F in la n d

1 8 5 2 1

6 .0 0

0 1

3 0 .3 2

0 .7 9

0 G er m a n y

1 7 8 0 4

5 .7 5

0 3

1 1 .2 5

1 .1 9

0 F ra n ce

1 7 5 8 8

5 .5 0

0 0

3 0 .4 7

1 .0 1

0 A u st ri a

1 7 4 3 3

6 .0 0

0 3

2 0 .6 1

1 .2 5

0 N et h er la n d s

1 6 7 4 4

6 .0 0

0 2

2 0 .5 5

1 .1 0

1 C a n a d a

1 6 2 4 3

6 .0 0

1 1

5 0 .4 4

0 .6 2

1 B el g iu m

1 6 1 0 4

6 .0 0

0 2

0 0 .1 5

1 .0 7

0 It a ly

1 4 7 8 3

5 .0 0

0 2

1 0 .3 9

0 .7 2

0 A u st ra li a

1 3 8 7 3

6 .0 0

1 1

4 0 .4 1

0 .7 3

1

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363342

U n it ed

K in g d o m

1 3 0 6 7

5 .3 1

1 4

5 0 .5 0

1 .1 3

1 Ir el a n d

1 2 0 3 4

5 .0 0

1 1

4 0 .6 2

0 .3 6

0 S in g a p o re

1 1 7 0 7

5 .1 9

1 4

4 0 .4 7

0 .9 3

1 N ew

Z ea la n d

1 1 3 3 2

6 .0 0

1 3

4 0 .2 5

0 .7 6

0 Is ra el

9 7 8 7

3 .3 1

1 4

3 0 .6 5

0 .9 5

0 H o n g K o n g

9 5 6 5

4 .6 9

1 4

5 0 .5 0

1 .4 9

1 S p a in

9 5 0 6

5 .0 0

0 2

4 0 .5 7

0 .9 5

0 G re ec e

5 2 5 7

4 .2 5

0 1

2 0 .3 0

0 .4 2

0 K o re a

4 7 8 5

3 .6 9

0 3

2 1 .2 1

0 .5 3

1 P o rt u g a l

4 6 2 0

5 .1 9

0 1

3 0 .3 3

0 .7 6

0 A rg en ti n a

3 6 2 3

3 .5 6

0 1

4 0 .3 6

0 .2 1

0 M a la y si a

2 7 0 8

3 .6 9

1 4

4 0 .4 4

0 .7 9

1 S o u th

A fr ic a

2 2 8 7

2 .6 9

1 3

5 0 .0 8

0 .6 3

0 C h il e

2 2 4 3

4 .1 9

0 2

5 0 .1 0

0 .4 6

1 B ra zi l

2 0 3 4

3 .7 5

0 1

3 0 .5 5

0 .3 2

1 M ex ic o

1 8 2 4

3 .0 0

0 0

1 0 .4 1

0 .2 2

1 T u rk ey

1 6 2 6

3 .1 9

0 2

2 0 .8 6

0 .1 9

1 T h a il a n d

1 5 1 7

4 .3 1

1 3

2 0 .7 7

0 .7 7

1 C o lo m b ia

1 3 2 1

1 .1 9

0 0

3 0 .0 9

0 .1 7

0 P er u

7 7 5

1 .6 9

0 0

3 0 .3 0

0 .1 1

1 P h il ip p in es

6 1 9

2 .1 3

0 0

3 0 .2 6

0 .3 4

1 In d o n es ia

6 1 0

3 .0 0

0 4

2 0 .4 0

0 .4 5

0 In d ia

4 0 5

2 .5 0

1 4

5 0 .4 0

0 .3 4

0 P a k is ta n

3 1 9

1 .8 8

1 4

5 0 .2 9

0 .3 6

0

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 343

in enforcing property rights within each country. This measure, produced by the International Country Risk-Rating Agency, reflects the degree to which the citizens of a country are willing to accept the established institutions to make and implement laws and adjudicate disputes. It is scored on a zero to six scale, with higher scores indicating sound political institutions and a strong court system. Lower scores indicate a tradition of depending on physical force or illegal means to settle claims. This indicator has been used in previous studies comparing institutions in different countries (e.g., Knack and Keefer, 1995; Demirg.u-c-Kunt and Maksimovic, 1998).

We place more weight on this indicator than on a comparison of specific differences in the legal codes across countries. Such a comparison can be misleading, because firms can compensate for the absence of specific legal protections by altering the provisions of contracts. It is likely to be more difficult to compensate for the systemic failures of the legal system to adjudicate claims captured by the law and order indicator. In Demirg.u-c-Kunt and Maksimovic (1999), the index is a good predictor of the use of long-term debt by large firms. By contrast, they find less evidence that the indicators of specific legal protections identified by LLSV (1998) predict the use of long-term debt. However, for completeness we also present indicators obtained by LLSV (1998). Common-Law Dummy takes the value one for common-law countries and the value zero for others. As argued by LLSV, common- law legal systems are more likely to offer protections to outside investors than civil- law systems. Creditor rights is an index that ranges from zero to four and aggregates creditor rights, while shareholder rights is an index that ranges from zero to five and aggregates shareholder rights as described in the text. The creditor and shareholder rights variables are described in LLSV (1998).

Table 1 shows that our sample contains countries with legal systems of very diverse levels of effectiveness. It contains highly effective common-law legal systems (such as the United States and Canada) and less effective legal systems (such as India and Pakistan), as well as highly effective civil-law systems (such as Switzerland) and less effective civil-law systems (such as Columbia and Peru).

For each country we also present three indicators of financial-system develop- ment. As an indicator of whether the financial system is bank-based or market- based, we use a dummy variable, MARKET1, defined in Demirg.u-c-Kunt and Levine (1999). The variable classifies countries as market-based when they have larger, more active, and efficient stock markets compared to banks. MARKET 1 is a dummy that takes the value one for higher than mean values of an aggregate Structure index, also caculated in Demirg.u-c-Kunt and Levine (1999). Structure index is computed as the means-removed average of relative size, relative activity, and relative efficiency measures. Relative size is given by the ratio of stock market capitalization to total assets of deposit money banks; relative activity is defined as the total value of stocks traded divided by bank credit to the private sector; and finally relative efficiency is given by the product of total value traded on the stock market and average overhead costs of banks in the country. Demirg.u-c-Kunt and Levine (1999) provide a discussion of alternative ways of defining market-based and bank-based systems.

We also present two other measures of the development of the market and the banking sector separately. We measure the level of activity of the stock market by its

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363344

turnover. As argued by Grossman and Stiglitz (1976), markets on which stocks trade actively provide greater incentives for investors to become informed and are therefore more informationally efficient. Turnover, TOR, is the total value of shares traded in the stock exchange divided by market capitalization. Stock market data are from IFC’s Emerging Market Data Base.2 Bank/GDP is the total assets of the deposit-money banks divided by GDP. It is obtained from IMF, International Financial Statistics. Both variables have been used in our previous firm-level studies (Demirg.u-c-Kunt and Maksimovic, 1998, 1999).

Countries scoring high on TOR include East Asian economies which were experiencing a market boom at this time, the United States, and the United Kingdom. Countries with low scrores include Latin American countries such as Chile, Columbia, and Peru, as well as European countries such as Greece and Portugal. Countries with a large banking sector include Switzerland, Japan, Germany, and Hong Kong, whereas Mexico, Turkey, and Columbia have small banking sectors relative to their GDP.

3.1. Measures of firm growth

To measure whether firms’ growth in an economy is financially constrained we adopt the approach of Demirg.u-c-Kunt and Maksimovic (1998). For each firm in an economy we estimate a rate at which it can grow, relying only on its internal funds or on short-term borrowing. We then compute the proportion of firms that grow at rates that exceed each of these two estimated rates each year. We then examine whether the proportions of firms growing faster than each of the two estimated rates differ between bank-based and market-based financial systems and whether they are affected by the level of development of the legal system.

Our estimate of the firm’s growth rate is based on the standard ‘‘percentage of sales’’ financial planning model (Higgins, 1977). This model relates a firm’s growth rate to its need for external funds. The external financing need at time t of a firm growing at gt percent a year is given by

EFNt ! gt Assetst " #1 $ gt%Earningst & bt; #1%

where EFNt is the external financing need and bt; is the proportion of the firm’s earnings that are retained for reinvestment at time t: Earnings are calculated after interest and taxes. The first term on the right-hand side is the required investment for a firm growing at gt percent. The second term is the internally available capital for investment, taking the firm’s retention ratio as given.

The financial planning model makes several implicit assumptions about the relation between the firm’s growth rate and the EFNt. First, the ratio of assets used in production to sales is assumed constant. Thus, the required total investment

2An alternative measure, used in Levine (2000), is the ratio of total value traded to GDP. Since our sample consists of firms that are already listed on the stock exchange, the ratio of value traded to market capitalization provides a measure of the activity levels of the financial markets that is more relevant to these firms.

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 345

increases in proportion to the firm’s growth in sales. Second, the firm’s profit rate per unit of sales is constant.3 Third, we assume that the economic depreciation of existing assets equals that reported in the financial statements.

We use two estimates of each firm’s attainable growth rate. The internally financed growth rate IGt is the maximum growth rate that can be financed if a firm relies only on its internal resources and maintains its dividend. IGt is obtained by assuming that the firm retains all its earnings (i.e., bt ! 1), equating EFNt to zero and solving Eq. (1) for gt; and is given by

IGt ! ROAt=#1 " ROAt%; #2%

where ROAt is the firm’s return on assets, or the ratio of earnings after taxes and interest to total assets. IGt is increasing in the firm’s return on assets. Thus, more profitable firms can finance higher growth rates internally.

The short-term financed growth rate SGRt is an estimate of the maximum growth rate that can be attained if the firm uses only short-term external financing. SGRt is obtained by using only the value of assets that are not financed by new short-term credit in place of total assets in Eq. (1). The assets not financed by short-term debt are termed ‘‘long-term capital’’ ROLTCt and are obtained by multiplying total assets by one minus the ratio of short-term liabilities to total assets. More specifically, SFGt is given by

SFGt ! ROLTCt=#1 " ROLTCt%: #3%

The use of the current realized ratio of short-term borrowing to assets to calculate SFGt ensures that the estimate is feasible and does not assume levels of short-term credit that are so costly that firms would not choose them.

The estimates of IGt and SFGt are conservative in several ways. First, each estimated maximum growth rate assumes that a firm utilizes the unconstrained sources of finance no more intensively than it is currently doing. In the case of IG the unconstrained source of finance is trade credit. In the calculation of SFG the unconstrained sources are trade credit and short-term borrowing. Second, firms with spare capacity do not need to invest and can grow at a faster rate than predicted by the financial planning model. We attempt to mitigate the potential problem posed by spare capacity by using each firm’s maximum constrained growth rates averaged over the second half of the sample period in our tests below. Third, the financial planning model abstracts from technical advances that reduce the requirements for investment capital. Thus, it may overstate the cost of growth and underestimate the maximum growth rate attainable using unconstrained sources of finance.

For each country in the sample we compute the proportion of firms whose mean annual real growth rate of sales exceeds the means of the two maximum constrained growth rates defined above. Thus, taking IG as an example, for each firm f in each country c and for each year t we estimate IGfct. We form a dummy variable for each firm f which takes on the value one if the firm inflation-adjusted realized growth rate

3This assumption was examined in Demirg.u-c-Kunt and Maksimovic (1998). The results in that paper were not sensitive to different assumptions about the rate of return on marginal sales.

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363346

exceeds the predicted rate, and zero otherwise: dfct ! 1 if gfct > IGfct and is 0 otherwise. Finally, for each country and each year we obtain STCOUNTct, the proportion of firms that grow at average rates exceeding the IGfct rate in year t; Sf dfct=nct; where nct is the number of firms in each country in year t: We repeat the same calculations with SFG in place of IG to obtain LTCOUNTct, the proportion of firms that grow at average rates exceeding the SFGfct rate in year t: Thus, LTCOUNTct is an estimate of the proportion of firms that obtain long-term financing (debt and/or equity) by issuing public or privately placed securities or by borrowing from the financial sector.

Our final variable is DCOUNTct, the proportion of firms in a country that grow at a rate that exceeds IGt but does not exceed SFGt. Thus, this variable measures the proportion of firms that have access to short-term financing but not necessarily access to long-term financing. Thus, DCOUNT proxies for the relative availability of short-term financing compared to the availability of long-term financing.

Our implementation of the financial growth model implicitly assumes that there exists a positive correlation between firms’ profits and their future investment opportunities. Some firms may have high profits from their assets in place, but poor investment opportunities. Such firms present potential problems for methodologies, such as our approach and methodologies based on Tobin’s q; that infer future investment opportunies from current valuations.

Cash-rich firms that do not have good investment opportunities and pay out their excess funds to shareholders are classified as growing at a rate that does not require external financing. However, since the existence of such firms does not have any implications for the availability of external financing, there exists the potential that such firms bias our conclusions about the proportion of firms with access to external fiance finance in different financial systems. Such bias can occur if the proportion of highly profitable firms without good investment opportunities depends on a country’s financial system. To minimize potential bias, in the regressions below we control for differences in growth opportunities across countries using economy-wide growth rates in GDP.

Table 2 shows the country averages for LTCOUNTct, STCOUNTct and DCOUNTct. The table also presents three descriptors of the firms in each country: The net fixed assets divided by total assets NFATA, the net sales divided by net fixed assets NSNFA, and SIZE, the total assets of the firm divided by the GDP of the country.

The table shows interesting variation in the proportion of firms obtaining external financing. Thus, for example, approximately half the US firms in our sample grow at rates exceeding IGt, but only 20% of the South African firms do so.

The variation in the proportion of firms obtaining external financing can be driven by differences in legal and financial systems. However, they can also be caused by differences in firm characteristics. For example, firms with a higher average ratio of net fixed assets to total assets may require more long-term financing than firms with a lower ratio. This may be one of the reasons why we observe a relatively high LTCOUNT for a country like Peru. Also, firms that are larger relative to their economy can enjoy better access to the available external financing than smaller

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 347

Table 2 The proportions of firms relying on external finance in each country and their characteristics LTCOUNT is the proportion of firms in a country whose mean growth of real sales exceeds their mean maximum short-term financed growth rate (SFG). STCOUNT is the proportion of firms whose mean growth of real sales exceeds their mean internally financed growth rate (IG). DCOUNT is given by (STCOUNT"LTCOUNT)/STCOUNT. NFATA is the net fixed assets divided by total assets. NSNFA is the net sales divided by net fixed assets. SIZE is the total assets of the firm divided by the GDP of the country. The data set, obtained from WorldScope, consists of 45,598 annual firm level observations over the period 1989–1996. These are the largest publicly traded manufacturing firms in 40 countries. All values are 1989–1996 averages.

LTCOUNT STCOUNT DCOUNT NFATA NSNFA SIZE

Argentina 0.41 0.45 0.11 0.49 2.36 2.60 Australia 0.44 0.49 0.13 0.36 3.88 2.90 Austria 1.00 1.00 0.00 0.30 4.87 2.57 Belgium 0.52 0.58 0.11 0.27 5.39 3.65 Brazil 0.42 0.43 0.01 0.56 1.63 3.34 Canada 0.53 0.57 0.07 0.39 4.51 1.66 Chile 0.30 0.38 0.34 0.52 1.60 8.62 Colombia 0.24 0.26 0.14 0.29 3.04 9.20 Denmark 0.42 0.50 0.17 0.36 4.07 1.96 Finland 0.51 0.57 0.11 0.36 4.01 13.60 France 0.41 0.50 0.20 0.22 6.79 1.75 Germany 0.91 0.93 0.02 0.29 6.35 0.67 Greece 0.35 0.45 0.25 0.33 4.11 1.13 Hong Kong 0.47 0.49 0.06 0.38 2.84 5.77 Indonesia 0.50 0.59 0.15 0.39 3.33 1.30 Indonesia 0.43 0.59 0.29 0.41 3.41 0.80 Ireland 0.40 0.52 0.21 0.38 3.47 11.90 Israel 0.68 0.75 0.12 0.30 4.64 6.46 Italy 0.42 0.48 0.12 0.26 4.87 0.99 Japan 0.48 0.55 0.14 0.29 4.02 0.35 Korea 0.69 0.75 0.08 0.39 2.66 4.92 Malaysia 0.51 0.58 0.14 0.46 2.26 3.60 Mexico 0.49 0.53 0.09 0.61 1.37 3.81 Netherlands 0.37 0.47 0.23 0.38 4.56 3.76 New Zealand 0.40 0.42 0.04 0.39 3.44 11.60 Norway 0.46 0.51 0.12 0.31 5.53 5.74 Pakistan 0.28 0.39 0.28 0.37 8.66 0.75 Peru 0.46 0.50 0.10 0.53 1.83 2.30 Philippines 0.28 0.34 0.17 0.44 2.84 2.50 Portugal 0.47 0.51 0.09 0.44 2.76 2.56 Singapore 0.46 0.55 0.19 0.34 3.37 7.62 South Africa 0.11 0.20 0.51 0.35 6.13 5.39 Spain 0.37 0.42 0.17 0.39 3.69 1.41 Sweden 0.44 0.52 0.18 0.33 4.16 7.68 Switzerland 0.48 0.53 0.12 0.37 3.81 8.36 Taiwan 0.37 0.47 0.21 0.40 2.29 5.85 Thailand 0.32 0.48 0.35 0.43 3.10 1.34 Turkey 1.00 1.00 0.00 0.33 6.03 2.39 United Kingdom 0.35 0.44 0.26 0.36 4.85 0.62 United States 0.46 0.51 0.11 0.29 6.20 0.17

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363348

firms in the same country. To the extent that the firms in our sample from the less- developed economies are larger (relative to their economy) than firms in more- developed economies, Table 2 overstates access to external financing in less- developed economies. Finally, inflation adjustment in calculating real sales growth may lead to additional problems in high inflation countries, as in the case of Turkey. In our regressions, we try to control for firm characteristics and macro variables. We also test the sensitivity results to outliers.

3.2. Summary statistics

We treat each date/country combination as a separate observation and analyze the resulting panel. Table 3 presents the summary statistics for our sample. Panel A presents the univariate statistics.

The correlation matrix is presented in Panel B. Inspection of Panel B shows that the measures of the availability of external financing LTCOUNT and STCOUNT are highly positively correlated with the level of development of the legal system. Consistent with Demirg.u-c-Kunt and Maksimovic (1998), a larger proportion of firms in countries with good legal systems grow at rates requiring external financing. More firms also use external financing in economies that are growing fast, and in economies with higher per capita incomes.

The firm characteristics associated with external financing are firm size and a low ratio of net fixed assets to total assets. However, the interpretation of the pairwise correlation is unclear. The ratio of net fixed assets to total assets is highly negatively correlated with the efficiency of the legal system, the GDP per capita, and with the size of the banking system, and highly positively correlated with the inflation rate.

The pairwise correlations between LTCOUNT and STCOUNT and our descriptors of financial structure are weak. STCOUNT is positively related to TOR and to MARKET, a dummy variable which takes a value of one when the ratio of TOR to BANK/GDP exceeds the sample median, and zero otherwise. However, LTCOUNT is not significantly correlated with either. BANK/GDP is not significantly correlated with STCOUNT or LTCOUNT.

DCOUNT is strongly negatively correlated with LAW and GDP per capita. Thus, in countries with efficient legal systems and high incomes, a smaller proportion of firms has access to short-term financing but grows at rates below those requiring long-term financing. By contrast, in countries in which firms have a high ratio of sales to assets, firms are more likely to rely on short-term rather than long-term financing.4

An interesting finding is that the firms in our sample in common-law countries are less likely to grow at rates requiring external financing than firms in civil-law countries. A positive correlation between DCOUNT and the common-law dummy

4Inflation is also negatively correlated with DCOUNT. However, in view of the potential effect of inflation on firm growth rates we treat inflation as a control variable in the regressions and do not interpret it directly.

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 349

T a b le

3 S u m m a ry

st a ti st ic s a n d th e co rr el a ti o n m a tr ix

o f th e v a ri a b le s

L T C O U N T is th e p ro p o rt io n o f fi rm

s in

a co u n tr y w h o se

m ea n g ro w th

o f re a l sa le s ex ce ed s th ei r m ea n m a x im

u m

sh o rt -t er m

fi n a n ce d g ro w th

ra te

(S F G ).

S T C O U N T

is th e p ro p o rt io n o f fi rm

s w h o se

m ea n g ro w th

o f re a l sa le s ex ce ed s th ei r m ea n in te rn a ll y fi n a n ce d g ro w th

ra te

(I G ).

D C O U N T

is g iv en

b y

(S T C O U N T " L T C O U N T )/ S T C O U N T . L A W

& O R D E R , sc o re d o n e to

si x , is a n in d ic a to r o f th e d eg re e to

w h ic h th e ci ti ze n s o f a co u n tr y a re

a b le to

u ti li ze

th e ex is ti n g le g a l sy st em

to m ed ia te

d is p u te s a n d en fo rc e co n tr a ct s. G R O W T H

is th e g ro w th

ra te

o f th e re a l G D P p er

ca p it a . IN

F L A T IO

N is th e in fl a ti o n ra te

o f th e G D P d efl a to r. S IZ

E is g iv en

b y to ta l a ss et s d iv id ed

b y co u n tr y G D P . N F A T A

is th e n et

fi x ed

a ss et s d iv id ed

b y to ta l a ss et s. N S N F A

is n et

sa le s d iv id ed

b y n et

fi x ed

a ss et s. M A R K E T is a d u m m y v a ri a b le th a t ta k es

th e v a lu e o n e fo r v a lu es

o f T O R /( B A N K /G

D P ) th a t a re

h ig h er

th a n th e sa m p le m ed ia n a n d ze ro

o th er w is e. C O M M O N

is a d u m m y th a t ta k es

th e v a lu e 1 fo r co m m o n la w co u n tr ie s a n d th e v a lu e ze ro

fo r o th er s. B A N K /G

D P is th e to ta l a ss et s o f th e d ep o si t

m o n ey

b a n k s d iv id ed

b y G D P . T O R

is st o ck

m a rk et tu rn o v er

d efi n ed

a s th e to ta l v a lu e o f sh a re s tr a d ed

d iv id ed

b y m a rk et ca p it a li za ti o n . G D P /C

A P is th e re a l

G D P p er

ca p it a in

th o u sa n d s o f U S $ . A ll co u n tr y le v el v a ri a b le s a re

a n n u a l fi g u re s, a v er a g ed

o v er

th e 1 9 8 9 – 1 9 9 6 p er io d . A ll fi rm

-l ev el v a ri a b le s a re

a v er a g ed

o v er

fi rm

s in

ea ch

co u n tr y a n d o v er

th e 1 9 8 9 – 1 9 9 6 p er io d . P a n el

A p re se n ts

th e su m m a ry

st a ti st ic s fo r th e co u n tr ie s li st ed

in T a b le

1 . P a n el

B re p o rt s

co rr el a ti o n co ef fi ci en ts .

P a n el

A : S u m m a ry

st a ti st ic s

N M ea n

S td . d ev

M in im

u m

M a x im

u m

L T C O U N T

3 8 9

0 .4 6 7

0 .2 7 9

0 1

S T C O U N T

3 8 9

0 .5 3 1

0 .2 6 0

0 1

D C O U N T

3 8 3

0 .1 5 2

0 .1 7 6

0 1

L A W

& O R D E R

3 3 6

4 .5 4 6

1 .5 7 9

1 6

G R O W T H

3 8 8

0 .0 2 6

0 .0 3 6

" 0 .1 3 5

0 .1 1 4

IN F L A T IO

N 4 1 7

0 .1 7 0

0 .5 1 1

" 0 .0 0 1

4 .3 2 8

S IZ

E 4 0 7

0 .0 0 7

0 .0 2 3

0 .0 0 0

0 .1 9 9

N F A T A

4 1 1

0 .3 7 6

0 .0 9 3

0 .1 5 1

1 N S N F A

3 9 4

3 .9 2 9

1 .9 6 3

1 .0 0 0

1 9 .6 2 7

M A R K E T

3 8 7

0 .5 0 1

0 .5 0 1

0 1

C O M M O N

4 2 0

0 .3 3 3

0 .4 7 2

0 1

B A N K /G

D P

4 0 5

0 .7 2 2

0 .3 9 7

0 .0 5 8

1 .8 1 8

T O R

4 0 2

0 .5 5 2

0 .6 0 7

0 .0 0 4

5 .2 7 7

G D P /C

A P

3 9 6

1 0 .1 6 5

8 .1 8 7

0 .2 4 2

2 7 .8 2 8

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363350

P a n el

B : C o rr el a ti o n m a tr ix

L T C O U N T

S T C O U N T

D C O U N T

L A W

G R O W T H

IN F L .

S IZ

E N F A T A

N S N F A

M A R K E T

C O M M O N

B A N K /

G D P

T O R

S T C O U N T

0 .9 6 4 * * *

D C O U N T

" 0 .5 7 0 * * *

" 0 .3 8 0 * * *

L A W

0 .1 7 8 * * *

0 .1 6 1 * * *

" 0 .2 4 3 * * *

G R O W T H

0 .1 4 5 * * *

0 .1 9 4 * * *

0 .0 0 6

0 .0 5 8

IN F L A T IO

N 0 .0 5 1

0 .0 0 8

" 0 .1 4 0 * *

" 0 .3 1 3 * * *

" 0 .1 5 5 * * *

S IZ

E 0 .1 0 1 * *

0 .0 7 3

" 0 .1 2 3 * *

0 .1 5 0 * * *

0 .0 5 9

" 0 .0 4 1

N F A T A

" 0 .1 2 6 * *

" 0 .1 5 1 * * *

" 0 .0 2 8

" 0 .3 3 5 * * *

" 0 .0 0 2

0 .4 2 3 * * *

" 0 .0 0 5

N S N F A

0 .0 5 3

0 .0 8 9 *

0 .1 4 5 * * *

0 .0 8 3

" 0 .1 3 0 * * *

" 0 .2 2 2 * * *

" 0 .1 6 5 * * * " 0 .6 7 2 * * *

M A R K E T

0 .0 6 9

0 .0 9 2 *

" 0 .0 1 8

" 0 .2 2 3 * * *

0 .1 4 7 * * *

0 .1 4 0 * * *

" 0 .1 5 6 * * *

0 .1 7 7 * * *

" 0 .1 1 4 * *

C O M M O N

" 0 .1 4 5 * * *

" 0 .1 0 6 *

0 .1 7 1 * * *

" 0 .0 3 5

0 .0 0 3

" 0 .1 5 4 * * *

" 0 .0 8 7 *

" 0 .0 0 9

" 0 .1 6 2 * * *

" 0 .0 8 5 *

B A N K /G

D P

0 .0 7 8

0 .0 7 5

" 0 .0 4 5

0 .0 5 5 2 * * *

" 0 .0 2 4

" 0 .3 2 1 * * *

" 0 .0 9 0 *

" 0 .3 5 4 * * *

0 .1 4 3 * * *

" 0 .2 5 8 * * *

" 0 .0 1 9

T O R

0 .0 7 7

0 .1 1 3 * *

0 .0 0 5

0 .1 0 9 *

0 .1 1 9 * *

" 0 .0 4 8

" 0 .1 3 1 * * * " 0 .0 1 3

" 0 .0 2 9

0 .4 6 0 * * *

" 0 .1 0 8 * *

0 .3 0 7 * * *

G D P /C

A P

0 .1 5 7 * * *

0 .1 4 3 * * *

" 0 .1 6 1 * * *

0 .7 7 4 * * *

" 0 .0 9 3 *

" 0 .2 7 9 * * *

0 .1 9 2 * * * " 0 .5 0 1 * * *

0 .2 9 9 * * *

" 0 .1 8 8 * * *

" 0 .0 9 9 * *

0 .6 0 9 * * *

0 .0 5 2

* , * * , a n d * * * in d ic a te

si g n ifi ca n ce

le v el s o f 1 0 % , 5 %

a n d 1 % , re sp ec ti v el y .

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 351

also suggests that in common-law countries a larger proportion of firms that require external financing grow at rates that do not require access to long-term financing.

The pairwise correlation results must be interpreted with caution. Inspection of Panel B shows that firm size (relative to its country’s GDP) is positively correlated with the efficiency of the legal system. Firms are larger in civil-law countries than in common law countries. Firm descriptors NFATA and NSNFA are also correlated with the efficiency of the legal system and legal origin. We control for those firm effects in our multivariate analysis.

4. Excess growth of firms and financial structure

We analyze the effect of a country’s financial system on firm growth in three stages. First, we regress our financial system indicators, TOR and BANK/GDP, on descriptors of the contracting environment. These regressions yield the estimates of the securities markets activity level and the size of the banking sector predicted by the level of development and characteristics of the legal system. Next regress our excess-growth variables STCOUNT, LTCOUNT, and DCOUNT on these predicted values and on control variables. These regressions allow us to test whether the legal system influences excess growth by affecting the development of the financial system. Finally, we augment these regressions by indicators of the relative development of the stock markets to the banking system. These regressions allow us to test whether market-based or bank-based systems perform differently.

We instrument for TOR and BANK/GDP variables used in the second stage using variables that proxy for the contracting environment in each country. This choice is motivated by the hypotheses that the development of the legal system can be taken as exogenous and that financial system development depends primarily on the ability of investors or financial intermediaries and firms to enter into effective contracts.

We use the LAW & ORDER indicator of legal effectiveness as a proxy for the contracting environment. As suggested by LLSV (1998) we also use a legal-origin variable, the common-law dummy, and the specific indices of shareholder and creditor rights. Finally, as a proxy for the ability to enter into financial contracts, we use the rate of inflation.

In the second stage we regress the dependent variables on the predicted values of TOR and BANK/GDP and several control variables. In the case of STCOUNT, for example, the estimated equation is

STCOUNT ! g1 $ g2 TOR $ g3 BANK=GDP $ g4 GROWTH $ g5 INFLATION $ g6 SIZE $ g7 GDP=CAP $ g8 LAW & ORDER $ e: #4%

We interpret these predicted financial-sector variables as the stock-market activity levels and the size of the banking sector that is predicted by a country’s contracting environment, respectively. We also include LAW & ORDER separately. Doing so

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363352

tests for the additional channels, independent of the financial system, by which the contracting environment can affect the firms’ access to financing.

We also include several control variables.5 GROWTH controls for the possibility that the firms’ desire to grow at rates that require external financing depends on the rate of growth of the economy. If the economy is growing fast, the rate of profit is likely to be high. This will also tend to increase the rates IG and SGR, permitting faster growth without access to external financing. The variable GROWTH allows for the possibility of additional effects of the growth in the economy. INFLATION controls for the possibility that in economies with high inflation the growth rates of firms will be overstated. SIZE measures the average size of the firms in each country as a proportion of their GDP. We hypothesize that large firms have more access to the country’s financial markets and institutions. Thus, this variable controls for the differences in sample selection across countries.

Differences can exist in access to financing that are related to the level of development but not specifically related to the development of the legal system. We include GDP per capita in the equation to serve as a proxy for these differences.

Our regression is estimated as a year-country unbalanced panel using a random- effects estimator. This methodology allows us to include dummy variables, which are constant across countries in our specifications. The use of random-effects panel estimators is also indicated when the explanatory variables are subject to measurement error (Moulton, 1987).

Table 4 presents the second-stage regression results. In Panel A the dependent variable is STCOUNT. Thus, the panel investigates the proportion of the firms in each country growing at a rate that requires external financing. The basic specification is given in Eq. (1).

The proportion of firms growing at rates requiring outside financing is higher in countries with high predicted TOR and BANK/GDP. Thus, a larger proportion of firms obtain outside financing when the contracting environment is conducive to the development of a large banking sector and an active stock market. This is in line with the implications of previous studies. The two control variables GROWTH and INFLATION are also significantly positive.

We do not identify any effects of average firm size relative to GDP or of the general level of development measured by GDP per capita on financing. We also do not identify any additional effects of the efficiency of the legal system not already accounted for in the development of the financial system.

Column (2) augments Eq. (1) with a variable which takes the value one for those observations where the ratio of TOR to BANK/GDP exceeds the sample median, and zero otherwise. The MARKET dummy identifies market-based economic environments. Inspection of column (2) reveals that there is no evidence that the relative ratio of market activity to the size of the banking sector affects the proportion of firms that obtain external financing.

5Additional firm-specific variables NFATA and NSNFA were included in unreported runs. They were not significant and did not affect the reported results.

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 353

Table 4 Constraints on the growth of firms and financial systems

Panel A: Constraints on short-term and long-term external financing. The regression equation estimated is: STCOUNT=a $b1 TOR+b2 BANK/GDP+b3 GROWTH+b4 INFLATION+b5 SIZE+b6 GDP/CAP +b7 LAW & ORDER+b8 MARKET+b9 ETOR $ b10 EBANK=GDP: The sample consists of 45,598 manu- facturing firms in 40 countries over the period 1989–1996. Firm-level variables are averaged for each coun- try, each year. Dependent variable is the proportion of firms whose mean growth of real sales exceeds their mean internally financed growth rate (IG). TOR is stock market turnover defined as the total value of shares divided by market capitalization. BANK/GDP is the total assets of the deposit money banks divided by GDP. GROWTH is the growth rate of the real GDP per capital. INFLATION is the inflation rate of the GDP deflator. SIZE is total assets of firms divided by GDP of the country, in thousands. GDP/ CAP is real GDP per capita in thousands of US$. NFATA is net fixed assets divided by total assets. LAW & ORDER, scored one to six, is an indicator of the degree to which citizens of a country are able to utilize the existing legal system to mediate disputes and enforce contracts. MARKET is a dummy variable that takes the value one for values of TOR/(BANK/GDP) that are higher than the sample median and zero otherwise. TOR and BANK/GDP used in estimation are the predicted values obtained from the follow- ing regressions: TOR=a $ b1 LAW & ORDER+b2 COMMON"LAW DUMMY+b3 INFLATION+ b4 SHAREHOLDER RIGHTS and BANK/GDP=a $ b1 LAW & ORDER+b2 COMMON"LAW DUMMY+b3 INFLATION+b4 CREDITOR RIGHTS. SHAREHOLDER RIGHTS is an index that ranges from zero to five and aggregates shareholder rights and CREDITOR RIGHTS is an index that ranges from zero to 4.5 and aggregates creditor rights as described in the text. COMMON"LAW DUMMY takes the value one for common law countries and the value zero for others. ETOR and EBANK=GDP are residuals from the above regressions. Regressions are estimated using panel data with random effects. Standard errors are given in parentheses.

(1) (2) (3)

CONS. "0.082 "0.068 "0.060 (0.185) (0.174) (0.162)

TOR 0.735** 0.692*** 0.720*** (0.220) (0.291) (0.266)

BANK/GDP 0.357* 0.376** 0.327* (0.220) (0.206) (0.192)

GROWTH 1.702*** 1.589*** 1.425*** (0.468) (0.479) (0.482)

INFLATION 0.061** 0.094*** 0.087 (0.032) (0.032) (0.033)

SIZE 2.475 0.216 "0.838 (6.125) (5.947) (5.584)

GDP/CAP 0.001 0.002 0.005 (0.004) (0.004) (0.004)

LAW & ORDER "0.019 "0.024 "0.024 (0.023) (0.022) (0.021)

MARKET 0.026 (0.034)

EBANK=GDP "0.130* (0.079)

ETOR 0.046 (0.055)

R2 within 0.06 0.07 0.06 R2 between 0.24 0.25 0.32 No. of observations 283 267 267

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363354

Panel B: Constraints on long-term external financing. The regression equation estimated is: LTCOUNT=a $ b1 TOR+b2 BANK/GDP+ b3 GROWTH+b4 INFLATION+b5 SIZE+b6 GDP/ CAP+b7 LAW & ORDER+b8 MARKET+b9 ETOR $ b10 EBANK=GDP: The sample consists of 45,598 manufacturing firms in 40 countries over the period 1989–1996. Firm-level variables are averaged for each country, each year. Dependent variable is the proportion of firms whose mean growth of real sales exceeds their mean maximum short-term financed growth rate (SFG). TOR is stock market turnover defined as the total value of shares divided by market capitalization. BANK/GDP is the total assets of the deposit money banks divided by GDP. GROWTH is the growth rate of the real GDP per capital. INFLATION is the inflation rate of the GDP deflator. SIZE is total assets of firms divided by GDP of the country, in thousands. GDP/CAP is real GDP per capita in thousands of US$. NFATA is net fixed assets divided by total assets. LAW & ORDER, scored one to six, is an indicator of the degree to which citizens of a country are able to utilize the existing legal system to mediate disputes and enforce contracts. MARKET is a dummy variable that takes the value one for values of TOR/(BANK/GDP) that are higher than the sample median and zero otherwise. TOR and BANK/GDP used in estimation are the predicted values obtained from the following regressions: TOR=a $ b1 LAW & ORDER+b2 COMMON"LAW DUMMY+b3 INFLATION+b4 SHARE HOLDER RIGHTS and BANK/GDP=a $ b1 LAW & ORDER+b2 COMMON"LAW DUMMY+b3 INFLATION+b4 CREDITOR RIGHTS. SHARE- HOLDER RIGHTS is an index that ranges from zero to five and aggregates shareholder rights and CREDITOR RIGHTS is an index that ranges from zero to 4.5 and aggregates creditor rights as described in the text. COMMON"LAW DUMMY takes the value one for common law countries and the value zero for others. ETOR and EBANK=GDP are residuals from the above regressions. Regressions are estimated using panel data with random effects. Standard errors are given in parentheses.

(1) (2) (3)

CONS. "0.176 "0.133 "0.144 (0.208) (0.200) (0.184)

TOR 0.843*** 0.819*** 0.830*** (0.360) (0.338) (0.307)

BANK/GDP 0.261 0.230 0.202 (0.249) (0.237) (0.220)

GROWTH 1.738*** 1.704*** 1.517*** (0.496) (0.510) (0.514)

INFLATION 0.089*** 0.124*** 0.118*** (0.034) (0.036) (0.035)

SIZE 3.904 1.864 0.866 (6.789) (6.728) (6.305)

GDP/CAP 0.001 0.002 0.006 (0.005) (0.005) (0.005)

LAW & ORDER "0.014 "0.018 "0.019 (0.024) (0.024) (0.023)

MARKET 0.011 (0.037)

EBANK=GDP "0.137* (0.089)

ETOR 0.024 (0.060)

R2 within 0.07 0.08 0.08 R2 between 0.19 0.18 0.25 No. of observations 283 267 267

Table 4. (Continued ).

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 355

Panel C: Proportion of firms that grow at rates faster than can be financed internally but do not require long- term financing. The regression equation estimated is: DCOUNT=a$b1 TOR+b2 BANK/GDP+ b3 GROWTH+b4 INFLATION+b5 SIZE+b6 GDP/CAP+b7 LAW & ORDER+b8 MARKET+ b9 ETOR $ b10EBANK=GDP: The sample consists of 45,598 manufacturing firms in 40 countries over the period 1989–1996. Firm-level variables are averaged for each country, each year. Dependent variable is give by (STCOUNT"LTCOUNT)/STCOUNT, the proportion of firms in a country whose growth of real sales exceeds the mean internally financed growth rate (IG) but does not exceed the mean short-term financed growth rate (SFG). TOR is stock market turnover defined as the total value of shares divided by market capitalization. BANK/GDP is the total assets of the deposit money banks divided by GDP. GROWTH is the growth rate of the real GDP per capital. INFLATION is the inflation rate of the GDP deflator. SIZE is total assets of firms divided by GDP of the country, in thousands. GDP/CAP is real GDP per capita in thousands of US$. NFATA is net fixed assets divided by total assets. LAW & ORDER, scored one to six, is an indicator of the degree to which citizens of a country are able to utilize the existing legal system to mediate disputes and enforce contracts. MARKET is a dummy variable that takes the value one for values of TOR/(BANK/GDP) that are higher than the sample median and zero otherwise. TOR and BANK/GDP used in estimation are the predicted values obtained from the following regressions: TOR=a $ b1 LAW & ORDER+b2 COMMON-LAW DUMMY+b3 INFLATION+b4 SHARE HOLDER RIGHTS and BANK/GDP=a$b1 LAW & ORDER+ b2 COMMON-LAW DUMMY+b3 INFLATION+b4 CREDITOR RIGHTS. SHAREHOLDER RIGHTS is an index that ranges from zero to five and aggregates shareholder rights and CREDITOR RIGHTS is an index that ranges from zero to 4.5 and aggregates creditor rights as described in the text. COMMON-LAW DUMMY takes the value one for common law countries and the value zero for others. ETOR and EBANK=GDP are residuals from the above regressions. Regressions are estimated using panel data with random effects. Standard errors are given in parentheses.

(1) (2) (3)

CONS. 0.465*** 0.343*** 0.346*** (0.131) (0.119) (0.118)

TOR "0.411** "0.400** "0.403** (0.224) (0.197) (0.196)

BANK/GDP 0.148 0.231* 0.234* (0.156) (0.140) (0.140)

GROWTH "0.674** "0.557* "0.542* (0.332) (0.313) (0.317)

INFLATION "0.084*** "0.076*** "0.075*** (0.024) (0.022) (0.022)

SIZE "0.981 "0.853 "0.875 (4.314) (3.985) (3.974)

GDP/CAP 0.002 "0.000 "0.001 (0.003) (0.003) (.003)

LAW & ORDER "0.038*** "0.024* "0.023* (0.016) (0.014) (0.014)

MARKET "0.001 (0.023)

EBANK/GDP 0.020 (0.056)

ETOR "0.000 (0.037)

R2 within 0.08 0.07 0.06 R2 between 0.25 0.24 0.25 No. of observations 279 264 264

*, **, and *** indicate significance levels of 10%, 5% and 1% respectively.

Table 4. (Continued ).

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In column (3) we augment the basic estimating equation with the residuals from the first-stage regressions. ETOR is the component of the market activity level not predicted by the legal environment. EBANK=GDP is the difference between the ratio of actual BANK/GDP and the level BANK/GDP predicted by the country’s contracting environment. Positive coefficients for these variables would suggest that there is a benefit to market activity and or a large banking sector respectively, independently of the legal system.

The coefficients of ETOR and EBANK=GDP are not significant at the 5% level, suggesting that there is little identifiable benefit to having a larger financial sector than that predicted by the legal contracting environment. If anything, the marginal significance of EBANK=GDP hints that an overexpansion of the banking sector beyond the predicted level evidences that resources are being misallocated. However, this result is sensitive to outliers in our sample. If we drop countries such as Peru and Turkey from the estimation, EBANK=GDP is not even marginally significant and BANK/GDP becomes significant at 5% in all specifications.

Panel B presents analogous regressions for LTCOUNT. Thus in this panel we explain the proportion of firms growing at rates that require additional long-term external financing. The results in Panel B are analogous to those presented in Panel A, with one exception. The coefficient for BANK/GDP, while remaining positive throughout, is no longer statistically significant. Dropping outliers does not make BANK/GDP significant in LTCOUNT regressions although EBANK/GDP loses significance as in STCOUNT regressions. Thus, we find less evidence that the size of the banking sector is an important determinant of the availability of long-term financing for the firms in our sample. This is consistent with the lack of significance of the MARKET indicator in column (2).

The dependent variable in Panel C is DCOUNT, the proportion of firms that obtain external financing but do not grow at rates that require additional long-term capital. This proportion is likely to be high when the financial system is able to supply short-term financing efficiently, but is not able to supply long-term financing.

Inspection of all three specifications in Panel C shows that DCOUNT is negatively related to TOR and positively related to BANK/GDP. Firms that require external financing in economies with strong securities markets are more likely to obtain long-term financing. By contrast, firms that require external financing in economies with a strong banking sector are less likely to grow at rates that require long-term financing. This is consistent with the notion that well-developed securities markets facilitate long-term financing, whereas a well-developed banking sector facilitates short-term financing. Interestingly, LAW & ORDER also has a strong negative effect on DCOUNT independent of its effect through TOR. Dropping outliers makes TOR less significant but LAW & ORDER more significant. The financial structure variables MARKET of ETOR and EBANK=GDP are again not significant.

The coefficients of the control variables GROWTH and INFLATION are significant in the expected directions. In high-growth economies a larger proportion of firms requiring external financing grows at rates that require long-term financing.

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In economies with high inflation rates, a higher proportion of externally financed firms grows at rate that exceeds the predicted rates IG and SFG.

We also investigated possible nonlinearities in the way financial variables can affect firm growth rates by including squared TOR and BANK/GDP terms into all specifications in Table 4. The squared TOR and BANK/GDP terms enter the DCOUNT regressions significantly with positive and negative signs, respectively. TOR and BANK/GDP terms also remain significant with their initial signs. This indicates that the positive impact of bank development on short-term financing and stock market development on long-term financing are especially important at lower levels of financial development. The squared terms do not develop significant coefficients in STCOUNT regressions. In LTCOUNT regressions only the squared TOR is marginally significant in some specifications with a negative sign.

This finding raises the possibility that relative development of banks versus markets may be particularly important at lower levels of development. To test this, we added an interaction term of MARKET with GDP per capita to column (2) in all panels of Table 4. However, this variable failed to develop a significant coefficient. Another possibility is that financial structure is only important if the underlying legal structure is inadequate. This can occur since markets in general require a better developed legal system to function efficiently. However, an interaction term of MARKET with LAW & ORDER variable does not develop a significant sign in any of the regressions in Table 4.

Wurgler (2000) argues that the responsiveness of investment to changes in value added in an industry is a measure of the efficiency with which resources are allocated. He calculates this responsiveness for manufacturing industries in a sample of countries. As a check we estimate the correlations between our variables TOR and BANK/GDP and the responsiveness variable reported in Wurgler. Although the sample period in Wurgler does not correspond to our sample period, the country specific variables we estimate are unlikely to change significantly over short periods.

For the 34 countries for which data is available, the correlation between the Wurgler’s allocation-efficiency measure and our variables TOR and BANK/GDP are 0.27 and 0.62, respectively. The former is significant at 10%, while the latter is significant at the 1% level. Thus, there is a significant positive relation between our measures of financial development and the measure of efficiency in Wurgler. However, our financial structure measure (MARKET) and Wurgler’s measure is not significantly correlated. Indeed, if we were to regress Wurgler’s measure on TOR, BANK/GDP, and MARKET, BANK/GDP develops a positive and highly significant coefficient, while MARKET is insignificant. Thus, efficiency of capital allocation appears to be strongly correlated with financial development, but not structure. Wurgler observes this in his paper when he notes that the four most studied financial systems all fall in the top quintile of his sample when ranked by his measure of the efficiency of capital allocation despite significant institutional differences (p. 199).

Further support for our findings come from Beck and Levine (2002) who investigate the same questions using industry-level data and the methodology

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363358

developed in Rajan and Zingales (1998). Indeed, they find that industry growth is highly correlated with financial development, but not financial structure. Further- more, Levine (2000) investigates the issue at the macro level, using standard cross- country growth regressions. Again, he finds that overall financial development is highly correlated with long-run economic growth, whereas there is no evidence of any correlation between growth and financial structure.

It is possible that our classification of market-based and bank-based financial does not capture essential differences between financial systems. To check this, we re- estimated the regressions in Table 4 Panels A, B, and C, including two additional proxies for the extent to which the financial system is market based. The first proxy is the percentage of assets of the ten largest banks in each country owned by the government as a share of total assets of these banks. The variable is drawn from La Porta et al. (2002). The second variable measures the ability of banks to own and control nonfinancial firms. This variable is compiled by Barth et al. (2001). Our specification was re-estimated first with these variables added to separately, and then both together. None of the additional coefficients were significant, indicating that these variables do not provide additional explanation of the use of external financing.

It is also possible is that the legal efficiency variable does not adequately represent the extent to which private property rights are safeguarded in the countries in our sample. As a broader measure of adherence to legal norms, we have used the index of political freedom calculated by Freedom House in our specifications.6 We first augment the specifications in Table 4 with this variable. It proved insignificant in every case. We further experimented with this indicator in additional specifications and did not obtain significant results. Thus, the LAW&ORDER variable that we use, which focus directly on the efficiency of each country’s legal system, appears a better indicator of the ability to enter into long-term contracts.7

It is unlikely that the available indicators can capture all the theoretically relevant nuances in the organization of financial markets or of the legal systems. However, taken together, the additional regressions suggest that in Table 4 we are using appropriate, albeit, coarse, proxies. In sum, Table 4 yields several results:

First, we have no evidence that the relative level of the development of the securities markets and the size of the banking sector, by itself, affect firms’ access to external financing. Thus, there is no evidence that the development of a market- based or bank-based financial system per se affects access to financing.

Second, the securities markets and the banking system affect firms’ ability to obtain financing in different ways, especially at lower levels of financial development. While the development of both improves access to external financing, the development of securities markets is more related to long-term financing, whereas the development of the banking sector is more related to the availability of short- term financing. Thus, differences in contracting environments that affect the relative

6We are grateful to the anonymous referee for this suggestion. 7In unreported regressions we have replaced our LAW&ORDER variable by the value of legal

efficiency at the beginning of the sample period. The results remain qualitatively unchanged.

A. Demirg.u-c-Kunt, V. Maksimovic / Journal of Financial Economics 65 (2002) 337–363 359

development of the stock market and the banking system can have implications for which firms and projects obtain financing.

Third, the effect of the securities markets and banking system development is closely tied to the level of development of the country’s contracting environment. Differences in the activity level of the securities markets not predicted by the contracting environment are not significantly related to the ability of firms do obtain external financing. This is consistent with the emphasis in LLSV (1998) on the importance of the legal system on financing.

Fourth, the proportion of firms that grow at rates that cannot be self-financed is positively related to the development of both the securities markets and the banking system. This is consistent with the findings of Demirg.u-c-Kunt and Maksimovic (1998).

5. Conclusion

The relative development of banks versus markets varies considerably across countries. The financial systems of some countries, such as the US, are market- based, whereas the financial systems of other economies, such as Japan, are bank- based. In this paper we investigate whether this difference in the organization of financial systems affects firms’ ability to obtain external financing for growth.

Our initial finding that that the proportion of firms that grow at rates that cannot be self-financed is positively related to the development of both the securities markets and the banking system. This is consistent with the findings of Demirg.u-c- Kunt and Maksimovic (1998), and with parallel findings of Levine and Zervos (1998), at the country level, and Rajan and Zingales (1998), at the industry level.

Our results show that the effects of the stock market and banking system development on firms’ growth is closely tied to the level of development of the country’s contracting environment. Development of the financial system beyond that predicted by the contracting environment are not significantly related to the ability of firms to obtain external financing. This is consistent with the emphasis on the importance of the legal system in LLSV (1998) on financing.

Using several proxies, we find no evidence that the relative levels of development of the securities markets compared to that of the banking sector, affect firms’ access to external financing. Thus, there is no evidence that the development of a market- based or bank-based financial system per se affects access to financing.

Finally, the securities markets and the banking system affect firms’ ability to obtain financing in different ways, especially at lower levels of financial development. While the development of both, if predicted by the contracting environment, improves access to external financing, the development of securities markets is more related to long-term financing, whereas the development of the banking sector is more related to the availability of short-term financing. Thus, for these countries differences in contracting environments that affect the relative development of the stock market and the banking system may have implications for which firms and which projects obtain financing.

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Appendix A

The number of firm-level observations from both developed and developing countries is listed in Table 5.

Table 5 Number of firm-level observations in each country

Number of firm observations

Argentina 93 Australia 452 Austria 382 Belgium 370 Brazil 514 Canada 1133 Chile 173 Colombia 68 Denmark 700 Finland 480 France 2506 Germany 2717 Greece 363 Hong Kong 385 India 1219 Indonesia 366 Ireland 105 Israel 91 Italy 866 Japan 9411 Korea 825 Malaysia 774 Mexico 251 Netherlands 727 New Zealand 109 Norway 330 Pakistan 339 Peru 72 Philippines 121 Portugal 230 Singapore 341 South Africa 442 Spain 468 Sweden 661 Switzerland 771 Taiwan 503 Thailand 620 Turkey 222 United Kingdom 4475 United States 10706

The data source for firm level variables is WorldScope.

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