77122 THE WORLD BANK ECONOMIC REVIEW, VOL 10, NO. 2: 291-321 Stock Market Development and Financial Intermediaries: Stylized Facts Ash Demirgiic-Kunt and Ross Levine World stock markets are booming, and emerging stock markets account for a dis- proportionate share of this growth. Yet economists lack a common concept or mea- sure of stock market development. This article collects and compares a broad array of indicators of stock market and financial intermediary development, using data from forty-four developing and industrial countries during the period from 1986 to 1993. The empirical results exhibit wide cross-country differences for each indicator as well as intuitively appealing correlations between various indicators. The article constructs aggregate indexes and analyzes them to document the relationship be- tween the emergence of stock markets and the growth of financial intermediaries. It produces a set of stylized facts that facilitates and stimulates research into the links among stock markets, economic development, and corporate financing decisions. The growth and globalization of emerging stock markets are impressive. In 1994, emerging market capitalization was $1.9 trillion, compared to $0.2 trillion in 1985. Similarly, $39 billion flowed into emerging equity markets from abroad in 1994, compared with $0.1 billion in 1985.' These developments have at- tracted the attention of academics, practitioners, and policymakers. Several stud- ies focus on measuring the benefits of holding a globally diversified portfolio (for example, see Harvey 1995 and De Santis 1993); and many countries are reforming regulations and laws to foster capital market development and at- tract foreign portfolio flows. Yet, economists have neither a common concept nor a common measure of stock market development. This article gives empirical content to the phrase "stock market development" by collecting and comparing a broader array of empirical indicators of stock market development than any previous study. Using data on forty-four develop- ing and industrial countries from 1986 to 1993, we examine different measures of stock market size, market liquidity, market concentration, market volatility, institutional development, and integration with world capital markets. Since each indicator suffers from statistical and conceptual shortcomings, we use a variety of indicators, which provide a more accurate depiction of stock markets 1. One billion is 1,000 million; one trillion is 1,000 billion. Asli Demirguc-Kunt and Ross Levine are with the Policy Research Department at the World Bank. This article was originally prepared for the World Bank conference on Stock Markets, Corporate Finance, and Economic Growth, held in Washington, D.C., February 16-17,1995. © 1996 The International Bank for Reconstruction and Development/THE WORLD BANK 291 292 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 than any single measure. Furthermore, stock market development—like the level of economic development—is a complex and multifaceted concept. No single measure will capture all aspects of stock market development. Thus, our goal is to produce a set of stylized facts about various indicators of stock market devel- opment that facilitates and stimulates research into the links among stock mar- kets, economic development, and corporate financing decisions. After describing each of the stock market development indicators, we exam- ine the relationships among them. We find enormous cross-country variation in the stock market indicators. For example, five countries have market capitaliza- tion to gross domestic product (GDP) ratios greater than 1, and five countries have market capitalization to GDP ratios less than 0.10. We find attractive cor- relations among the indicators. For example, large stock markets are more liq- uid, less volatile, and more internationally integrated than smaller markets; coun- tries with strong information disclosure laws, internationally accepted accounting standards, and unrestricted international capital flows tend to have larger and more liquid markets; countries with markets concentrated in a few stocks tend to have smaller, less liquid, and less internationally integrated markets; and in- ternationally integrated markets are less volatile. Although many stock market development indicators are significantly corre- lated in an intuitively plausible fashion, the individual indicators produce differ- ent country rankings. Thus, to produce an assessment of the overall level of stock market development across countries, we produce indexes of stock mar- ket development that average together the information contained in the indi- vidual indicators. Developing aggregate indexes that summarize the extent of a country's stock market development in a single figure is especially helpful for analysts who are interested in making comparisons across countries. These in- dexes can be used in empirical studies linking stock market development and other economic phenomena, as in Levine and Zervos (1996) and Demirgiic- Kunt and Maksimovic (1996). We find that from 1986 to 1993 the most devel- oped stock markets in the world are in Japan, the United States, and the United Kingdom, and the most underdeveloped markets are in Colombia, Venezuela, Nigeria, and Zimbabwe. The data suggest that Hong Kong, Singapore, the Re- public of Korea, Switzerland, and Malaysia have highly developed stock mar- kets; Turkey, Greece, Argentina, and Pakistan have underdeveloped markets. Furthermore, although richer countries generally have more developed stock markets than poorer countries, many markets labeled emerging are more devel- oped than those in France, the Netherlands, Australia, Canada, Sweden, and Norway. We use the assortment of stock market indicators to evaluate which stock markets have been developing fastest over the last eight years. Using measures of size, liquidity, and international integration, Indonesia, Turkey, Portugal, and Venezuela stand out as the most rapidly developing markets in the world. This article documents the relationship between the various stock market indicators and measures of financial intermediary development. Since debt and Demirgiif-Kunt and Levine 293 equity are frequently viewed as alternative sources of corporate finance, stock markets and banks are sometimes viewed as alternative vehicles for financing corporate investments (see Demirgiig-Kunt and Maksimovic 1996). Conse- quently, we document the cross-country ties between stock market develop- ment and financial intermediary development. We use measures of the size of the banking system, the amount of credit going to private firms, the size of nonbank financial corporations, and the size of private insurance and pension companies. We find that most stock market indicators are highly correlated with the development and efficient functioning of banks, nonbank financial cor- porations, and private insurance companies and pension funds. Countries with well-developed stock markets tend to have well-developed financial intermedi- aries. Section I presents indicators of stock market development and describes their theoretical relevance. Section II ranks countries using the different indicators of stock market development and studies the correlations among the indicators. Section III examines which countries have the fastest-developing stock markets. Section IV analyzes the links between stock market development and financial intermediary development. Section V summarizes the results. I. INDICATORS OF STOCK MARKET DEVELOPMENT A growing theoretical literature examines the relationship between particular attributes of stock markets and both economic growth and firms' financing de- cisions. For example, Devereux and Smith (1994) and Obstfeld (1994) show that by facilitating risk sharing, internationally integrated stock markets affect saving decisions, the allocation of capital, and long-run economic growth rates. Greater risk diversification and liquidity have theoretically ambiguous effects on saving rates, however, because saving rates could fall sufficiently for en- hanced liquidity and risk diversification to lead to slower economic growth. Levine (1991) and Bencivenga, Smith, and Starr (1996) emphasize that stock market liquidity—the ability to easily trade securities—facilitates investments in longer-run, higher-return projects that involve more transactions. On stock market size, Pagano (1993) studies the increased risk-sharing benefits of larger stock markets due to thick market externalities. Besides stock market size, li- quidity, and integration with world capital markets, theorists have examined stock return volatility. For example, DeLong and others (1989) argue that ex- cess volatility in the stock market can hinder investment, and therefore growth, although there is considerable disagreement over the existence of excess volatil- ity in stock returns (see Shiller 1981). In terms of corporate finance, some theo- ries link stock market functioning with firms' financing and investment deci- sions. Pagano (1993) models the ties between risk-diversification and corporate financing decisions, while Boyd and Smith (1996) analyze complementarities between debt and equity financing for capital investments. Yet, as Demirguc,- Kunt and Maksimovic (1996) discuss, the effect of stock market development 294 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 on firms' financing decisions is theoretically inconclusive. Thus, theory provides a rich array of channels through which stock markets—market size, liquidity, integration with world capital markets, and volatility—may be linked to eco- nomic growth and corporate financing decisions. There is very little empirical evidence on the links among stock markets, eco- nomic development, and firms' corporate financing decisions. To facilitate em- pirical research, this article collects and compares a broad array of stock market indicators motivated by the above theoretical studies and constructs aggregate indexes of overall stock market development. Demirgiic-Kunt and Maksimovic (1996) and Levine and Zervos (1996) use these indexes to examine the empiri- cal relationship among stock market development, firms' financing decisions, and long-run economic growth. The rest of this section presents and discusses an array of stock market devel- opment indicators. We focus on indicators identified by existing theoretical stud- ies. We describe measures of market size, market liquidity, market volatility, market concentration, asset pricing efficiency, regulatory and institutional de- velopment, and conglomerate indexes that aggregate the information contained in the individual measures. For developing countries, we use data from the In- ternational Finance Corporation's (lFC's)Emerging Markets Data Base. For in- dustrial countries, data are from Morgan Stanley Capital International (MSCl). We also use macroeconomic data from IMF (various issues). The data cover the period from 1986 to 1993 for up to forty-four developing and industrial coun- tries. The appendix provides details of data construction and discusses cross- country comparability issues. Stock Market Size The market capitalization ratio equals the value of listed shares divided by GDP. Analysts frequently use the ratio as a measure of stock market size. In the rest of the article, we refer to this measure as market capitalization. In terms of economic significance, the assumption behind market capitalization is that mar- ket size is positively correlated with the ability to mobilize capital and diversify risk. For example, Pagano (1993) motivates his theoretical model by observing the great variation in market capitalization and in the number of listed compa- nies in different economies. As indicated in table 1, South Africa, Hong Kong, Malaysia, Japan, and Singapore all had market capitalization ratios greater than 1 from 1986 to 1993, while Nigeria, Argentina, Indonesia, Colombia, and Tur- key all had market capitalization ratios of less than 0.10 during the same period. We include statistics on the number of listed companies as an additional mea- sure of market size. Although marginal differences in the number of listed com- panies are uninformative, extreme values can be useful. It is not very interesting that Australia averaged 1,184 listed companies and Canada averaged 1,118 listed companies during the period from 1986 to 1993. But the fewer than 70 listed companies for Finland and Zimbabwe suggest that these countries have very limited markets (table 1). Similarly, the fact that in Indonesia, Turkey, and Por- Demirgii(-Kunt and Levine 295 tugal the number of listed companies grew at over 20 percent a year from 1986 to 1993 suggests rapid stock market development (see table 3 in section HI). Liquidity Although economists advance many theoretical definitions of liquidity, ana- lysts generally use the term to refer to the ability to easily buy and sell securities. Since liquidity allows investors to alter their portfolios quickly and cheaply, it makes investment less risky and facilitates longer-term, more profitable invest- ments. Liquidity is an important attribute of stock market development because theoretically liquid markets improve the allocation of capital and enhance pros- pects of long-term economic growth. A comprehensive measure of liquidity would quantify all the costs associated with trading, including the time costs and un- certainty of finding a counterpart and settling the trade. Because we want to compare liquidity across countries and because data are very limited, we simply use two measures of realized stock trading. Total value traded/GDP equals total shares traded on the stock market ex- change divided by GDP. The total value traded ratio measures the organized trading of equities as a share of national output, and should therefore positively reflect liquidity on an economywide basis. Japan, Hong Kong, Malaysia, the United States, and the United Kingdom all had total value traded/GDP ratios above 0.40, while in Pakistan, Zimbabwe, Colombia, and Nigeria, the total value traded/GDP ratio was about 0.01 from 1986 to 1993. The total value traded/ GDP ratio complements the market capitalization ratio. Although market capi- talization may be large, there may be little trading. For example, South Africa and Chile had above-average market capitalization but below-average total value traded/GDP (table 1). Together, market capitalization and total value traded/GDP inform us about market size and liquidity. A second measure of liquidity is the turnover ratio. Turnover equals the value of total shares traded divided by market capitalization. High turnover is often used as an indicator of low transactions costs. Korea and Germany (largely reflecting massive trading around reunification) had turnover ratios above 0.90, while Nigeria, Zimbabwe, and South Africa had turnover ratios below 0.05. The turnover ratio complements market capitalization. A small but active mar- ket will have small market capitalization but high turnover. For example, Nor- way and India had below-average market capitalization but above-average turn- over (table 1). Alternatively, South Africa's market capitalization to GDP ratio was the highest in the world, but its turnover ratio was one of the smallest. Turnover also complements total value traded/GDP. Although total value traded/ GDP captures trading compared with the size of the economy, turnover measures trading relative to the size of the stock market. Put differently, a small, liquid market will have a high turnover ratio but a small total value traded/GDP ratio. For example, there was not much equity trading in Brazil relative to the size of its economy, but Brazil's turnover ratio was high, reflecting a small but active stock market. By contrast, Malaysia had the third-highest market capitalization Table 1. Indicators of Stock Market Development, 1986-93 (annual average)i Market Total value Number of listed Market Institutional APT ICAPM capitalization' tradedJGDP* companies0 Turnover6 Volatility' concentration1 development* pricing error** pricing errorh Economy Rank Value Rank Value Rank Value Rank Value Rank Value Rank Value Rank Value Rank Value Rank Value Argentina 40 0.06 34 0.02 26 187 19 0.34 37 0.34 15 0.64 10 1.16 14 4.98 24 11.58 Australia 10 0.54 12 0.17 5 1,184 21 0.31 11 0.04 13 4.94 12 4.14 Austria 35 0.10 22 0.07 39 90 5 0.69 14 0.05 Belgium 18 0.36 28 0.04 27 182 35 0.12 6 0.04 Brazil 34 0.11 26 0.05 9 579 11 0.48 36 0.25 7 0.26 4 1.54 24 7.26 23 6.92 Canada 13 0.48 13 0.15 6 1,118 20 0.31 5 0.04 8 0.27 Chile 11 0.52 30 0.04 21 225 37 0.08 25 0.06 19 0.50 5 1.52 17 5.56 13 4.25 Colombia 38 0.07 40 0.01 40 87 38 0.07 23 0.06 26 0.74 11 1.16 19 5.62 15 4.82 Denmark 19 0.28 23 0.07 17 267 23 0.24 Finland 26 0.19 27 0.04 42 62 30 0.21 13 0.05 France 20 0.27 18 0.09 8 641 16 0.35 15 0.05 6 0.26 Germany 22 0.24 8 0.35 11 551 1 1.47 10 0.04 15 0.41 Greece 32 0.12 37 0.02 34 126 34 0.13 31 0.10 17 0.47 18 0.77 16 5.29 19 5.23 Hong Kong 2 1.36 2 0.59 14 318 12 0.44 India 31 0.16 25 0.06 2 4,614 9 0.50 24 0.06 3 0.22 8 1.34 7 3.33 7 2.89 Indonesia 39 0.06 36 0.02 38 91 27 0.23 17 0.96 9 3.68 8 3.03 Ireland 21 0.06 Israel 25 0.21 15 0.11 15 312 3 0.72 18 0.06 Italy 29 0.16 29 0.04 19 227 24 0.24 20 0.06 Japan 4 1.08 1 0.62 3 2,027 8 0.54 12 0.04 2 0.19 1 2.39 4 2.26 Jordan 9 0.57 14 0.13 36 103 29 0.22 7 0.04 23 0.59 12 1.16 2 2.55 1 2.05 Korea, Rep. of 15 0.40 6 0.37 10 576 2 0.93 30 0.08 9 0.28 3 1.55 10 3.73 9 3.18 Luxembourg 23 205 Malaysia 3 1.28 3 0.46 16 291 26 0.24 17 0.05 12 0.36 1 1.63 11 3.90 5 2.45 Mexico 24 0.22 19 0.09 25 193 7 0.56 32 0.10 10 0.36 2 1.61 21 5.94 21 5.77 Netherlands 12 0.49 11 0.21 18 239 14 0.41 3 0.03 New Zealand 16 0.39 24 0.06 20 226 32 0.17 16 0.05 Nigeria 41 0.04 41 0.00 33 127 41 0.01 21 0.51 20 0.64 8 3.66 11 3.72 Norway 27 0.19 17 0.09 35 126 10 0.48 27 0.07 Pakistan 33 0.11 38 0.01 12 487 36 0.08 1 0.03 5 0.25 13 1.09 3 2.59 2 2.15 Philippines 23 0.24 31 0.04 30 152 28 0.23 29 0.08 22 0.52 9 1.32 15 5.26 16 4.90 Portugal 30 0.16 32 0.03 29 162 31 0.20 4 0.03 14 0.41 6 1.37 12 4.02 20 5.28 Singapore 5 1.04 7 0.35 31 147 18 0.34 South Africa 1 1.54 21 0.08 7 700 39 0.05 Spain 21 0.25 20 0.08 13 383 17 0.35 19 0.06 Sweden 14 0.46 16 0.10 32 133 25 0.24 22 0.06 Switzerland 7 0.77 9 0.31 28 176 15 0.39 8 0.04 20 0.50 Taiwan (China) 24 197 34 0.15 13 0.40 16 0.98 20 5.68 14 4.54 Thailand 17 0.36 10 0.22 22 210 4 0.70 26 0.07 11 0.36 7 1.36 6 3.12 10 3.18 Turkey 37 0.08 33 0.03 37 91 22 0.28 35 0.17 18 0.50 14 1.06 22 6.38 22 6.66 United Kingdom 6 0.92 5 0.41 4 1,932 13 0.44 9 0.04 4 0.24 5 2.94 6 2.56 United States 8 0.64 4 0.41 1 7,087 6 0.65 2 0.03 1 0.14 4 2.71 3 2.24 Venezuela 36 0.10 35 0.02 41 82 33 0.15 33 0.13 24 0.63 15 1.00 23 6.67 17 5.15 Zimbabwe 28 0.18 39 0.01 43 57 40 0.03 28 0.07 16 0.44 19 0.66 18 5.57 18 5.18 Average 0.41 0.15 627 0.36 0.08 0.40 1.19 4.49 4.34 Number of economies 41 41 43 41 37 26 20 24 24 Note: For each indicator, the stock market development of each economy is ranked from high to low. Thus, for market capitalization, total value traded/GDP, number of listed companies, turnover, and institutional development, the ranking by value of the indicator is from high to low. For volatility, market concentration, APT pricing error, and 1C AP M pricing error, the ranking by value of the indicator is from low to high. a. Market capitalization is the value of stocks divided by GDP. b. Total value traded/GDP is total value of traded shares divided by GDP. c. Number of companies listed represents the number of shares listed on the exchange. d. Turnover is given by total value traded divided by market capitalization. e. Volatility is the twelve-month rolling standard deviation estimate based on market returns. f. Market concentration is the share of market capitalization held by the ten largest stocks. g. Institutional development is an average of institutional indicators as described in the text. h. APT and ICAPM pricing errors are obtained from Korajczyk (1994). Source: Authors' calculations and Korajczyk (1994). 298 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 and total value traded/GDP ratios from 1986 to 1993, but it had below-average turnover (table 1). Thus, incorporating information on market capitalization, total value traded/GDP, and turnover provides a more comprehensive picture of development than any single indicator can provide. Concentration In some countries a few companies dominate the market. High concentration is not desirable because it may adversely affect the liquidity of the market. To measure the degree of market concentration, we compute the share of market capitalization accounted for by the ten largest stocks and call this measure concen- tration. The United States and Japan have very low concentration. The ten larg- est stocks account for less than 20 percent of the markets. In Venezuela, Argen- tina, and Colombia, where the concentration ratio averaged above 0.60 in the period from 1986 to 1993 (table 1), concentration is three times larger than that in the United States and Japan. Volatility We include a measure of stock market volatility, because volatility of stock returns is another attribute that has received significant attention in the litera- ture and is of great interest to practitioners. This indicator is a twelve-month, rolling, standard-deviation estimate based on market returns. We cleanse the return series of monthly means and twelve months of autocorrelations using a procedure defined by Schwert (1989). Greater volatility is not necessarily a sign of more or less stock market development. Indeed, high volatility could be an indicator of development, so far as revelation of information implies volatility in a well-functioning market (see, for example, Bekaert and Harvey 1995). Here we refer to "less volatility" as reflecting "greater stock market development" for simplicity. As with the other indicators, there are great cross-country differ- ences in volatility. Volatility in Pakistan, the United States, and the Netherlands averaged about 0.03 from 1986 to 1993; volatility in Brazil and Argentina was above 0.25. Asset Pricing Academic researchers and market practitioners have devoted prodigious resources to measuring the degree of integration between national stock markets and the world market and to gauging whether markets price risk efficiently (see Bonser-Neal and others 1990; Cho, Eun, and Senbet 1986; Claessens, Dasgupta, and Glen 1995; Errunza and Losq 1989,1985a, 1985b; Errunza and Senbet 1981; Errunza, Losq, and Padmanabhan 1992; Gultekin, Gultekin, and Penati 1989; Jorion and Schwartz 1986; Korajczyk and Viallet 1989; Solnik 1974; Stehle 1977; and Wheatley 1988). Although a market need not be integrated into the world capital markets to be developed, ana- lysts generally refer to countries that are more integrated and that price risk more efficiently as more developed. Demirgiif-Kunt and Levine 299 To measure asset pricing efficiency, we use estimates of asset pricing errors computed by Korajczyk (1994,1996). Unfortunately, the data only permit com- putation of these pricing errors for twenty-four countries. As argued in Korajczyk and Viallet (1989), the capital asset pricing model (CAPM) and arbitrage pricing model imply that the expected return on each asset is linearly related to a bench- mark portfolio or linear combination of benchmark portfolios. In domestic ver- sions of these asset pricing models the benchmark portfolios include only secu- rities traded on the local exchange, but in the international versions the portfolios include all securities. If the models are correct, then the benchmark portfolio, or combination of portfolios, should explain all of the systematic expected returns on assets above the risk-free interest rate.2 Thus, we term systematic deviations of expected returns as pricing errors under the maintained hypothesis that the model is correct. Using different asset pricing models, Korajczyk (1994) com- putes the systematic deviation between actual returns and those implied by the models. The asset pricing theory (APT) and international capital asset pricing model (ICAPM) compute pricing errors using an international arbitrage pricing model and international capital asset pricing model, respectively. Korajczyk (1994) computes the extent of pricing error under the maintained hypothesis that the models are correct. We take the average of the absolute value of the pricing errors for the stocks in a country as a measure of capital market integration. Thus, under the maintained hypothesis, greater values of the APT and ICAPM measures reflect less international integration. Greater pricing errors may reflect poor information about firms, high transactions costs, and official barriers to international asset trading. We refer to greater pric- ing errors as indicating less stock market development. The APT and ICAPM pricing errors give similar country rankings. Brazil, Turkey, and Mexico had relatively large pricing errors, but the United States, Japan, Jordan, and Pa- kistan yielded lower pricing errors, which suggest a high level of interna- tional integration. These two pricing-error estimates—APT and ICAPM—rely on the success of equilibrium models of asset pricing that investigators sometimes have rejected as good representations of the pricing of risk. However, these measures allow us to incorporate indicators, albeit imperfect indicators, of the ability of agents to diversify risk domestically and internationally. Furthermore, we analyze the evolution of the degree of integration between each domestic market and the world market over time. Regulatory and Institutional Indicators Regulatory and institutional factors may influence the functioning of stock markets (see Pagano 1993). For example, mandatory disclosure of reliable in- formation about firms and financial intermediaries may enhance investor par- 2. Since no asset is riskless in real terms, Korajczyk and Viallet (1989) test the restrictions implied by a zero-beta asset. 300 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 ticipation in equity markets. Regulations that instill investor confidence in bro- kers and other capital-market intermediaries should encourage investment and trading in the stock market. To measure the institutional development of emerging stock markets, we use information provided by the IFC and construct seven regulatory-institutional in- dicators. The first indicator shows whether the firms that are listed in a stock market publish price-earnings information. We give a value of 0 or 1, where 1 indicates that the information is comprehensive and published internationally. The second indicator measures accounting standards. We assign values of 0, 1, or 2, for countries with poor, adequate, or good (internationally accepted) ac- counting standards. The third indicator measures the quality of investor protec- tion laws as judged by the IFC, where 0, 1, and 2 are used to indicate poor, adequate, or good investor protection laws. The fourth indicator shows whether the country has a securities and exchange commission. The fifth, sixth, and sev- enth indicators measure restrictions on dividend repatriation by foreign inves- tors, capital repatriation by foreign investors, and domestic investments by for- eigners. We assign values of 0, 1, and 2, indicating whether capital flows are restricted, have some restrictions, or are free, respectively. We compute an aver- age institutional development indicator, which simply averages the seven regu- latory-institutional indicators. These indicators are available on an annual basis from 1986'to 1993 for twenty developing countries. There is substantial variation across countries and indicators. For example, Jordan freely allowed international capital flows to cross its borders, but did not publish regular price-earnings information and had poor accounting standards. India had accounting standards of internationally accepted quality, but restricted capital inflows and the repatriation of capital and dividends. Nigeria tightly restricted capital flows over most of the period and did not publish price- earnings information on firms in a comprehensive and internationally accepted manner. In contrast, Malaysia, Mexico, Korea, Brazil, and Chile had very high institutional development indicators overall (table 1). Correlations between Various Indicators of Stock Market Development Many stock market indicators are significantly correlated in an intuitively plausible fashion.3 First, market size is significantly positively correlated with total value traded/GDP and the average institutional indicator, and significantly negatively correlated with pricing error and volatility. Countries with big stock markets have less volatile, more efficient stock markets with a high volume of trading relative to GDP. Second, countries with highly concentrated markets have markets that are underdeveloped. Market concentration is significantly nega- tively correlated with market size and market liquidity, and significantly posi- tively correlated with pricing error. Third, countries that have stock markets which are more integrated internationally—as measured by low APT and ICAPM 3. We do not report the actual values here due to space constraints. For these and for more detailed statistics throughout the article, see Demirguc-Kunt and Levine (1995). Demirguf-Kunt and Leirine 301 values—have less volatile stock returns. Fourth, countries with well-developed regulatory and institutional systems, as defined by the IFC, tend to have large, liquid stock markets. Although many stock market development indicators are significantly cor- related in intuitively attractive ways, the correlation coefficients are frequently below 0.60. The correlations suggest that the different indicators capture different aspects of stock market development. For example, the correlation between the two measures of market liquidity, total value traded/GDP and turnover is only 0.50. Thus, although the degree of trading relative to the size of the economy is significantly correlated with the degree of trading relative to the size of the market, the two liquidity measures do not move one for one. Instead, they provide complementary information about stock market liquidity. Therefore, to measure how well stock markets function in general, that is, to compute an index of overall stock market development, we need to incorporate the information contained in a broad selection of these indicators. II. WHICH STOCK MARKETS ARE MOST DEVELOPED? Which stock markets are most developed overall? To answer this question, we construct four conglomerate indexes of stock market development that aggregate the information contained in the individual indicators. We then use these conglom- erate indexes to rank countries in terms of overall stock market development. The Indexes To compute the conglomerate indexes of stock market development, we average the means-removed values of particular stock market development indicators. To construct each index, we follow a two-step procedure. iNDEXl aggregates information on market capitalization, total value traded/GDP, and turnover. First, for each country, /', we compute the means-removed market capitalization, total value traded/GDP, and turnover ratios. We define the means-removed value of variable X for country / as X(i)m = [X(i) - mean(X)] / [ABS[ mean(X)]}, where the term in the denominator is the absolute value of the average value of X across all countries from 1986 to 1993. For the pricing-error measures (APT and ICAPM) and the market concentration measure, where larger numbers refer to less stock market development, we multiply the indicator num- bers by negative 1 before computing the means-removed values. Second, we take a simple average of the means-removed market capitalization, total value traded, and turnover ratios to obtain an overall index of stock market devel- opment, INDEXl.4 INDEXl is calculated for forty-one countries (see table 2). INDEX2 is constructed in the same way. It aggregates information on the three 4. We computed principal components indexes of the indicators, which allow the data to choose the weights rather than talcing a simple average. However, we do not report these indexes because the rankings they produce are very highly correlated with the indexes we report. 302 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 Table 2. Aggregate Indexes of Stock Market Development, 1986-93 INDEXl' INDEX2b INDEX3C INDEX4* Economy Rank Value Rank Value Rank Value Rank Value Argentina 32 -0.59 15 -0.47 23 -0.87 15 -0.50 Australia 13 0.19 7 0.12 7 0.15 Austria 19 -0.15 Belgium 28 -0.47 Brazil 24 -0.29 11 -0.38 12 -0.37 10 -0.23 Canada 14 0.09 Chile 27 -0.46 12 -0.40 11 -0.34 13 -0.37 Colombia 40 -0.88 23 -0.71 22 -0.68 21 -0.73 Denmark 26 -0.37 Finland 30 -0.53 France 21 -0.21 Germany 3 1.38 Greece 36 -0.73 18 -0.61 17 -O.60 16 -0.52 Hong Kong 2 2.01 India 23 -0.26 9 -0.13 9 -0.11 7 -0.01 Indonesia 35 -0.71 17 -0.52 14 -0.48 Israel 15 0.08 Italy 29 -0.51 Japan 1 2.02 1 1.63 1 1.63 1 1.41 Jordan 16 -0.08 8 0.04 8 0.07 8 -0.06 Korea, Rep. of 6 1.05 4 0.84 4 0.85 4 0.73 Malaysia 8 0.90 5 0.72 5 0.79 5 0.60 Mexico 18 -0.14 10 -0.16 10 -0.17 9 -0.11 Netherlands 12 0.32 New Zealand 25 -0.33 Nigeria 41 -0.96 20 -0.67 21 -0.67 19 -0.59 Norway 20 -0.18 Pakistan 39 -0.82 16 -0.51 16 -0.49 11 -0.33 Philippines 31 -0.54 14 -0.43 13 -0.42 14 -0.40 Portugal 33 -0.61 13 -0.42 15 -0.49 12 -0.34 Singapore 7 1.04 South Africa 10 0.48 Spain 22 -0.25 Sweden 17 -0.10 Switzerland 9 0.75 Thailand 11 0.38 6 0.36 6 0.36 6 0.31 Turkey 34 -0.61 19 -0.61 19 -0.62 17 -0.54 United Kingdom 4 1.23 3 1.01 3 1.02 3 0.89 United States 5 1.21 2 1.01 2 1.03 2 0.94 Venezuela 37 -0.74 22 -0.68 18 -0.61 20 -0.66 Zimbabwe 38 -0.81 21 -0.67 20 -0.66 18 -0.56 Average 0.02 -0.07 -0.07 -0.05 Number of economies 41 23 23 21 Note: Details of the calculation of the indexes are discussed in the text. Definitions of the indicators are given in table 1. The ranking order, by index, is from high to low. The indexes represent averages during the period from 1986 to 1993. a. rNDExl is the average of market capitalization, total value traded/GDP, and turnover. b. INDEX2 adds APT pricing error to INDEXl. c INDEX3 adds ICAPM pricing error to INDEXl. d. INDEX4 adds market concentration to INDEX2. Source: Authors' calculations. Demirgiif-Kunt and Levine 3 03 indicators used in iNDEXl and APT pricing error to obtain an overall indicator of stock market development that incorporates international integration. INDEX2 includes only the twenty-three countries with APT estimates. INDEX3 combines INDEX 1 with the ICAPM pricing error. INDEX3 includes only the twenty-three coun- tries with ICAPM pricing-error estimates. INDEX4 averages the means-removed values of market capitalization, total value traded/GDP, turnover, APT pricing error, and market concentration. We compute this index only for the twenty- one countries with data on all five underlying indicators. Rankings of Stock Market Development Table 2 gives the country-by-country values and rankings for the four aggre- gate indexes. Although there are variations in country rankings, the indexes are very highly correlated, with correlation coefficients of 0.96. Thus, the various conglomerate indexes give very similar country rankings. Here we briefly sum- marize the results from table 2. Consider first INDEX4, which aggregates the largest number of individual stock market development indicators but has the fewest countries. The INDEX4 vari- able says that Japan, the United States, the United Kingdom, and Korea have the most developed stock markets when aggregating information on market size, liquidity, international integration, and market concentration. Colombia, Ven- ezuela, Nigeria, and Zimbabwe have the four lowest rankings in this twenty- one-country sample. Next, consider INDEXl, which aggregates the least information but includes the most economies (forty-one) with data on all the underlying indicators. INDEXl ranks Japan, Hong Kong, Germany, the United Kingdom, the United States, Korea, Singapore, and Malaysia as having very highly developed stock markets when aggregating information on market size and liquidity. INDEXl implies that Nigeria, Colombia, Pakistan, and Zimbabwe have the least developed stock markets. As noted above, Germany's high ranking is strongly influenced by the tumultuous years surrounding reunification when there was an explosion of eq- uity transactions. If Germany's two years of exceptionally high trading are re- moved in computing its averages during the period from 1986 to 1993, Ger- many falls from the top ten. Although it is difficult to answer unambiguously the question of which stock markets are most developed, our evaluation of the indexes presented in table 2 suggests that the three most developed markets are in Japan, the United States, and the United Kingdom. The most underdeveloped markets are in Colombia, Venezuela, Nigeria, and Zimbabwe. Furthermore, the data suggest that Hong Kong, Singapore, Korea, Switzerland, and Malaysia have highly developed stock markets, and Turkey, Greece, Argentina, and Pakistan have underdeveloped markets. Note that there is a close correspondence between income per capita and stock market development. Poorer countries have lower stock market development than richer countries on average. Also note that there are important exceptions. Fre- 304 THE WORLD BANK ECONOMIC REVIEW, VOL 10, NO. 2 quently, many markets termed emerging—such as Korea, Malaysia, and Thailand— are uniformly ranked higher than markets termed developed—such as France, the Netherlands, Australia, Canada, Sweden, and many other European countries. III. WHICH STOCK MARKETS ARE DEVELOPING MOST RAPIDLY? Which stock markets are developing most rapidly? To answer this question, we rank countries according to the growth rates of the individual indicators of stock market development. Growth Rates of Individual Indicators of Stock Market Development Table 3 presents the average annual growth rates of the individual indicators of stock market development from 1986 to 1993. Here we highlight three points. First, in terms of market size, Indonesia and Turkey boomed over this period, growing at average annual rates of more than 100 percent a year. As a bench- mark, market capitalization in the United States grew at 4 percent annually. At the other extreme, Finland, Japan, Germany, Sweden, New Zealand, and Italy saw their market capitalization ratios shrink from 1986 to 1993. Using another measure of market size, Indonesia, Turkey, Portugal, and Thailand saw the num- ber of listed companies grow at an annual rate of over 18 percent. Second, as measured by total value traded/GDP, Indonesia, Portugal, Turkey, Venezuela, and Greece experienced rapid liquidity growth (more than 200 per- cent), while Japan and Italy weathered rapid declines (-12 and -14 percent, respectively). As with total value traded/GDP, the turnover measure of liquidity identifies Indonesia as the fastest-growing market in terms of liquidity. Third, some cross-country quandaries emerge from studying stock market growth. Consider, for example, the cases of Mexico and Portugal. Both coun- tries liberalized their capital markets and privatized public enterprises, and both countries experienced very rapid improvements in international integration (as measured by the APT pricing error). In terms of market volatility, Mexico saw rapid declines in return volatility as it liberalized its economy and privatized state enterprises. In contrast, stock return volatility in Portugal exploded as it liberalized its capital markets and privatized its public enterprises. Another note- worthy difference between the two countries is that while market concentration grew dramatically in Mexico, it shrunk steadily in Portugal. Growth Rates of Aggregate Indexes of Stock Market Development Using individual stock market development indicators, we found it diffi- cult to assess which markets experienced the most rapid overall develop- ment. Thus, we now evaluate the growth rate of overall indexes of stock market development. In section II, the goal was to compare the level of stock market development across countries. Here, however, we seek to measure the growth rate of each country's level of overall stock market development. Consequently, we now use the growth rate of each country's stock market Demirgiif-Kunt and Levine 305 indicator. We average these growth rates to compute an overall index of stock market development. We construct iNDEXGl, which aggregates information on market capitaliza- tion, total value traded/GDP, and turnover, by computing the average annual growth rate for each indicator for each country. We then take a simple average of the growth rates to obtain an overall index of stock market development for each country. This index allows us to examine the growth rate of each country's overall level of stock market development. INDEXG2 combines the growth rates of market capitalization, total value traded/ GDP, turnover, and the APT pricing-error measure. INDEXG2 includes only coun- tries with APT pricing-error estimates. INDEXG3 is similar to INDEXG2, except that INDEXG3 uses the ICAPM pricing-error estimates instead of the APT pricing- error estimates. Finally, INDEXG4 averages the annual growth rates of market capitalization, total value traded/GDP, turnover, APT pricing error, and market concentration. We compute this index only for the twenty-five countries with data on all five underlying indicators for the period from 1986 to 1993. Table 4 reports the aggregate indexes of overall stock market growth. The main findings are straightforward. Regardless of the index, Indonesia, Turkey, Portugal, and Venezuela experienced the most rapid overall stock market devel- opment over the eight years. Although these countries began the period with underdeveloped markets, other countries with similarly underdeveloped stock markets—such as Colombia, Pakistan, and Zimbabwe—did not enjoy the ex- plosive development experienced by Indonesia, Turkey, Portugal, and Venezuela. We investigated whether stock markets that were initially underdeveloped grew faster. There is some evidence in support of convergence. Markets that were initially small and illiquid grew faster and became more liquid. Markets that initially were volatile and priced risk poorly tended to grow larger but not necessarily more liquid. IV. Is STOCK MARKET DEVELOPMENT LINKED TO THE REST OF THE FINANCIAL SYSTEM? Do countries with well-developed stock markets have well-developed banks and nonbank financial intermediaries? To address this question, we discuss four types of measures of financial intermediary development: financial system, banks, nonbank financial corporations, and insurance and pension companies. We look at correlations among the indicators. We then construct aggregate indexes of financial intermediary development, which we use to examine the correlation between stock market development and financial intermediary development. Indicators of Financial Intermediary Development Here we discuss the size of the financial system, the size and efficiency of the banking system, the size of nonbank financial corporations, and the size of pri- vate insurance and private pension funds. Table 3. Growth Rates of Indicators of Stock Market Development, 1986-93 Number Market Total value of listed Market Institutional APT ICAPM capitalization traded/GDP companies Turnover Volatility concentration development pricing error pricing error Economy Rank Value Ranii Value Raniz Value Rank Value Ranii Value Rank Value Rank Value Raniz Value Ranii Value Argentina 3 0.87 8 1.18 41 -0.03 21 0.17 31 0.09 22 0.08 6 0.09 18 0.14 24 0.43 Australia 31 0.02 34 0.08 32 0.00 29 0.06 5 -0.02 8 -0.01 10 0.01 Austria 12 0.37 6 1.48 13 0.06 5 0.91 26 0.04 Belgium 33 0.00 37 0.01 38 -0.02 3 1.54 8 -0.02 Brazil 16 0.30 21 0.34 37 -0.01 42 -0.11 24 0.04 21 0.07 14 0.04 5 -0.03 13 0.05 Canada 35 0.00 38 0.01 30 0.01 32 0.05 22 0.03 25 0.09 Chile 19 0.27 23 0.27 25 0.03 43 -0.11 16 0.01 15 0.02 16 0.03 11 0.00 14 0.06 Colombia 11 0.42 15 0.54 35 -0.01 37 -0.03 35 0.15 18 0.05 10 0.05 17 0.09 23 0.27 Denmark 24 0.06 14 0.55 34 -0.01 13 0.38 Finland 36 -0.02 28 0.19 23 0.03 18 0.24 27 0.05 France 23 0.07 32 0.09 16 0.05 30 0.06 33 0.10 19 0.06 Germany 38 -0.03 24 0.26 26 0.02 15 0.30 2 -0.05 8 -0.02 Greece 9 0.51 5 2.50 17 0.05 11 0.43 29 0.08 10 0.00 2 0.22 23 0.19 18 0.13 Hong Kong 26 0.06 22 0.31 9 0.09 17 0.25 India 15 0.32 29 0.16 29 0.02 40 -0.08 32 0.09 12 0.00 17 0.02 4 -0.06 8 0.00 Indonesia 1 1.89 1 17.74 1 0.37 1 1.82 20 -0.06 19 0.14 1 -0.26 Ireland 21 0.03 Israel 7 0.53 16 0.50 5 0.15 7 0.54 25 0.04 Italy 41 -0.10 41 -0.14 19 0.05 22 0.16 6 •-0.02 Japan 37 -0.03 40 -0.12 27 0.02 39 -0.07 28 0.06 2 -0.09 3 -0.10 3 -0.07 Jordan 20 0.12 12 0.58 33 0.00 19 0.24 7 -0.02 5 -0.05 12 0.04 24 0.26 20 0.16 Korea, Rep. of 17 0.28 18 0.43 8 0.09 36 -0.01 18 0.01 24 0.09 15 0.03 12 0.03 9 0.01 Luxembourg 6 0.12 2 1.66 Malaysia 14 0.34 7 1.31 10 0.09 12 0.40 3 -0.05 3 -0.08 19 0.01 14 0.04 5 -0.02 Mexico 10 0.49 11 0.62 22 0.04 34 0.01 1 -0.06 26 0.23 13 0.04 1 -0.15 4 -0.07 Netherlands 32 0.01 31 0.13 21 0.04 4 1.39 12 -0.01 New Zealand 40 -0.05 26 0.20 43 -0.11 24 0.10 4 -0.03 Nigeria 21 0.10 25 0.23 12 0.08 35 -0.01 9 0.00 4 0.11 9 -0.01 15 0.06 Norway 25 0.06 10 0.67 39 -0.03 9 0.45 23 0.03 Pakistan 18 0.27 19 0.40 11 0.08 41 -0.09 11 -0.01 23 0.08 7 0.09 21 0.16 22 0.25 Philippines 5 0.61 13 0.57 18 o.os 38 -0.06 17 0.01 20 0.07 9 0.06 13 0.04 6 0.00 Portugal 8 0.51 2 3.25 3 0.20 14 0.35 37 0.85 7 -0.03 18 0.02 2 -0.14 2 -0.26 Singapore 29 0.04 20 0.34 15 0.06 10 0.43 South Africa 28 0.04 30 0.13 20 0.04 27 0.08 Spain 34 0.00 33 0.09 24 0.03 25 0.10 20 0.03 Sweden 39 -0.05 39 -0.02 42 -0.05 26 0.09 30 0.08 Switzerland 22 0.07 35 0.05 14 0.06 16 0.29 19 0.02 17 0.02 Taiwan (China) 7 0.12 20 0.17 10 -0.02 6 -0.03 8 0.09 16 0.05 17 0.12 Thailand 6 0.57 9 0.76 4 0.18 31 0.05 15 0.01 1 -0.12 11 0.04 22 0.17 16 0.09 Turkey 2 1.02 3 2.87 2 0.23 6 0.65 34 0.13 13 0.01 1 0.29 20 0.14 19 0.14 ^ United Kingdom 30 0.03 27 0.20 40 -0.03 23 0.10 14 0.00 14 0.02 7 -0.02 7 0.00 5 United States 27 0.04 36 0.04 36 -0.01 33 0.02 9 -0.02 16 0.02 6 -0.02 11 0.01 Venezuela 4 0.66 4 2.77 31 0.01 8 0.48 36 0.27 11 0.00 3 0.17 15 0.04 21 0.24 Zimbabwe 13 0.35 17 0.45 28 0.02 28 0.06 13 0.00 4 -0.07 5 0.11 10 -0.01 12 0.04 Average 0.27 1.02 0.05 0.31 0.05 0.02 0.07 0.04 0.06 Number of economies 41 41 43 43 37 26 20 24 24 Note: Growth rates are the average annual growth rates. Definitions of the indicators are given in table 1. For each indicator, economies are ranked by the rate of growth of stock market development, from high to low. Thus, for market capitalization, total value tradedVGDP, number of listed companies, turnover, and institutional development, the ranking by value of the indicator is from high to low. For volatility, market concentration, AFT pricing error, and ICAPM pricing error, the ranking by value of the indicator is from low to high. Source: Authors' calculations. 308 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 Table 4. Growth Rates of Aggregate Indexes of Stock Market Development, 198&-93 INDEXC1 1NDEXG2 INDEXG3 INDEXG4 Economy Rank Value Rank Value Rank Value Rank Value Argentina 7 0.74 6 0.52 7 0.45 5 0.54 Australia 36 0.05 21 0.04 21 0.04 Austria 6 0.92 Belgium 10 0.52 Brazil 24 0.18 15 0.14 15 0.12 16 0.12 Canada 38 0.02 24 -0.01 Chile 26 0.14 18 0.11 17 0.09 17 0.10 Colombia 18 0.31 12 0.21 14 0.17 12 0.22 Denmark 16 0.33 Finland 28 0.14 France 34 0.07 22 0.04 Germany 25 0.17 14 0.14 Greece 5 1.15 5 0.81 5 0.83 4 0.86 Hong Kong 22 0.20 India 29 0.14 16 0.12 16 0.10 18 0.10 Indonesia 1 7.15 1 5.33 1 5.43 Israel 9 0.52 Italy 40 -0.03 Japan 41 -0.07 23 -0.03 23 -0.04 25 -0.03 Jordan 17 0.31 13 0.17 12 0.19 9 0.25 Korea, Rep. of 21 0.23 14 0.17 13 0.17 13 0.15 Malaysia 8 0.68 7 0.50 6 0.52 6 0.53 Mexico 14 0.37 8 0.32 9 0.30 11 0.22 Netherlands 11 0.51 New Zealand 33 0.09 Nigeria 31 0.11 20 0.08 20 0.06 20 0.08 Norway 13 0.39 Pakistan 23 0.20 17 0.11 18 0.08 15 0.13 Philippines 15 0.37 10 0.27 10 0.28 8 0.26 Portugal 3 1.37 3 1.06 3 1.09 2 1.04 Singapore 20 0.27 South Africa 32 0.09 Spain 35 0.06 Sweden 39 0.01 Switzerland 27 0.14 19 0.10 Thailand 12 0.46 9 0.30 8 0.32 7 0.37 Turkey 2 1.51 2 1.10 2 1.10 1 1.13 United Kingdom 30 0.11 19 0.09 19 0.08 21 0.08 United States 37 0.03 22 0.03 22 0.02 23 0.02 Venezuela 4 1.30 4 0.97 4 0.92 3 0.98 Zimbabwe 19 0.29 11 0.22 11 0.21 10 0.23 Average 0.53 0.55 0.54 0.31 Number of economies 41 23 23 25 Note: Growth rates of indexes are obtained by averaging the growth rates of different stock market indicators, depending on the index. Indexes are defined in table 2. The ranking, by growth rate of each index, is from high to low. Source: Authors* calculations. Demirgiif-Kunt and Levine 309 FINANCIAL SYSTEM. On the basis of work by King and Levine (1993), we use three measures of financial system development. The ratio of liquid liabilities of the financial intermediaries to GDP is M3 money supply divided by GDP. The ratio is a measure of the overall size of the formal financial system. If the size of the financial system is positively related to the provision of financial services, then this ratio should be a good indicator of the provision of financial intermediary services. The ratio of quasi-liquid liabilities to GDP is M3 money supply minus M l , divided by GDP. It subtracts narrow money from the liquid liabilities measure of financial intermediary size. Analysts sometimes use the quasi-liquid measure instead of liquid liabilities because Ml/GDP represents highly liquid bank depos- its and therefore may not be as closely associated with efficient financial inter- mediation as longer-term investments in financial intermediaries. The quasi- liquid measure focuses on longer-term liabilities. Liquid and quasi-liquid liabilities that finance government deficits may not reflect the provision of efficient financial intermediary services (such as acquir- ing information about firms, monitoring managers, and facilitating transactions and risk diversification). Therefore, we compute a third variable, domestic credit to private firms divided by GDP. Unfortunately, although IMF (various issues) classifies credit as "claims on the private sector," some of these claims in some countries include credit to public enterprises. Table 5 indicates that Hong Kong, Japan, and Switzerland had well-devel- oped financial systems as measured by liquid and quasi-liquid liabilities to GDP and domestic credit to private firms. In contrast, Argentina, Brazil, Mexico, Colombia, and Nigeria had underdeveloped financial systems as revealed by these three indicators. BANKS. TO measure the level of development of the banking system, we use the ratio of the total claims of deposit money banks to GDP. The three countries with the largest values for this indicator were Switzerland, Luxembourg, and Japan. At the other extreme, Nigeria, Argentina, and Venezuela had the lowest ratio of bank credit to GDP during the period from 1986 to 1993. We compute a measure of banking efficiency, which we call spread, that equals the difference between bank lending and borrowing rates. This measure may not accurately capture banking efficiency because the interest rate data may not accurately reflect borrowing and lending costs. The spread indicator will not provide accurate information on how well banks monitor firm managers, nor will it capture government intervention in the banking system in a very informa- tive way. But the spread indicator is widely used and available across countries. We include it for completeness. For better measures of financial repression for a few select countries see Giovannini and De Melo (1993). According to the spread indicator, the banking systems of Switzerland, Canada, and the United King- dom were among the most efficient, whereas Argentina, Israel, and Turkey had the least efficient banks. Table 5. Indicators of Financial Intermediary Development, 1986-93 (annual average) Assets of private Assets of private Quasi-liquid Domestic credit Total claims nonbank financial insurance and Liquid liabilities liabilities to private sector of deposit corporations to pension funds to*GDP' to GDP* to GDP banks to GDP Spread0 GDP to GDP Economy Rank Value Rank Value Rank Value Rank Value Rank Value Rank Value Rank Value Argentina 44 0.23 41 0.15 39 0.26 41 0.37 38 45.28 Australia 24 1.13 19 0.89 16 1.07 22 1.19 28 6.28 5 0.45 8 035 Austria 9 1.72 7 1.44 11 1.36 4 2.39 Belgium 31 0.94 33 0.55 29 0.61 20 1.20 26 5.70 Brazil 43 0.26 42 0.14 38 0.29 36 0.51 Canada 21 1.27 14 ' 0.97 24 0.86 28 0.93 2 1.38 6 0.42 6 0.48 S- Chile 36 0.72 28 0.61 22 0.93 29 0.90 30 6.96 0 Colombia 41 0.47 38 0.28 40 0.25 33 9.70 21 0.06 18 0.03 Denmark 23 1.19 27 0.62 21 0.98 21 1.20 23 5.35 15 0.12 5 0.54 Finland 25 1.10 21 0.82 8 1.60 14 1.60 12 3.55 12 0.21 9 0.33 France 16 1.36 20 0.87 6 1.77 8 2.00 34 10.57 10 0.28 11 0.20 Germany 17 1.34 15 0.94 5 1.80 5 2.16 22 5.15 10 0.33 Greece 12 1.54 9 1.21 33 0.45 27 0.95 31 7.19 Hong Kong 1 3.91 1 3.53 India 33 0.87 31 0.57 32 0.51 33 0.68 8 3.00 Indonesia 37 0.65 35 0.44 28 0.66 34 0.65 16 4.23 22 0.02 Ireland 32 0.88 26 0.64 31 0.52 30 0.87 21 5.10 Israel 20 1.30 10 1.19 17 1.01 7 2.07 37 20.95 Italy 13 1.47 23 0.75 27 0.71 24 1.01 32 7.34 9 0.33 17 0.06 Japan 2 3.57 2 3.00 2 2.27 3 2.58 11 3.31 7 0.43 Jordan 4 2.40 8 1.41 15 1.24 16 1.52 24 5.56 17 0.08 16 0.07 Korea, Rep. of 29 0.96 22 0.78 19 0.99 25 1.00 6 2.90 3 0.55 12 0.14 Luxembourg 6 2.36 2 2.59 4 2.31 Malaysia 8 1.89 5 1.51 12 1.33 13 1.61 5 2.68 8 0.39 14 0.10 Mexico 42 0.42 37 0.29 37 0.29 38 0.48 35 13.76 18 0.08 19 0.02 Netherlands 10 1.61 11 1.16 9 1.53 9 1.97 29 6.92 25 0.00 1 1.08 New Zealand 27 1.03 29 0.61 23 0.92 23 1.10 17 4.49 Nigeria 40 0.48 40 0.23 42 0.24 42 0.33 19 4.60 19 0.08 Norway 22 1.26 30 0.61 14 1.27 15 1.57 15 4.21 Pakistan 35 0.79 39 0.25 30 0.55 32 0.70 23 0.01 22 0.00 Philippines 38 0.63 34 0.48 36 0.34 37 0.48 20 5.04 20 0.07 20 0.01 Portugal 14 1.47 16 0.93 25 0.84 17 1.49 27 5.96 Singapore 7 2.26 4 1.80 7 1.64 12 1.87 9 3.02 2 0.84 13 0.11 South Africa 26 1.06 24 0.72 26 0.74 31 0.78 10 3.20 Spain 15 1.44 18 0.90 13 1.31 11 1.89 18 4.59 11 0.24 15 0.08 Sweden 30 0.96 20 0.98 18 1.41 25 5.68 1 0.89 4 0.56 Switzerland 3 2.83 3 2.26 1 3.14 1 3.26 1 0.87 Taiwan (China) 5 2.38 6 1.49 4 1.80 6 2.10 Thailand 19 1.31 12 1.12 18 0.99 19 1.23 13 3.60 13 0.15 21 0.01 Turkey 39 0.61 36 0.41 35 0.36 35 0.54 36 19.50 24 0.01 United Kingdom 11 1.59 17 0.92 3 1.97 10 1.97 3 1.82 16 0.08 2 0.92 United States 18 1.33 13 0.99 10 1.42 26 0.99 7 3.00 4 0.53 3 0.67 Venezuela 34 0.80 32 0.55 34 0.40 40 0.45 7 0.40 Zimbabwe 28 0.96 25 0.70 41 0.24 39 0.45 14 3.90 14 0.13 Average 1.33 0.95 1.01 1.31 6.81 0.26 0.30 Number of economies 44 42 42 42 38 25 22 Note: The financial intermediary development of each economy is ranked from high to low. This ranking is shown by ranking the value of the indicator from high nonbanks to GDP, and assets of private insurance and pension funds to GDP; for spread, the ranking by value of the indicator is from low to high. a. Liquid liabilities of the financial system are the M3 definition of money. b. Quasi-liquid liabilities are M3 minus Ml money. c. The spread is the difference between bank lending and borrowing rates. Source: Authors' calculations. 312 THE WORLD BANK ECONOMIC REVIEW, VOL- 10, NO. 2 NONBANK FINANCIAL CORPORATIONS. We use the ratio of assets of private nonbank financial intermediaries to GDP to measure the size of nonbank financial corporations, such as finance companies, mutual funds, and brokerage houses. The four economies with the largest values for this indicator were Sweden, Singapore, Korea, and the United States. Indonesia, Pakistan, Turkey, and the Netherlands had very low values.5 INSURANCE AND PENSION COMPANIES. Finally, we use the ratio of assets of private insurance companies and pension funds to GDP to measure the size of private insurance and pension companies. The three countries with the largest values for this indicator were the Netherlands, the United Kingdom, and the United States. The Philippines, Thailand, and Pakistan had very low values. Correlations between Various Indicators of Financial Intermediary Development The measures of financial system size—the liquid, quasi-liquid, and domestic credit to private firms indicators—are very highly correlated. The correlation coefficients are 0.79 or higher and significant at the 0.01 level. The correlations between the indicators of the size of the financial system and indicators of the size of banks, private nonbank financial corporations, and private insurance and pension companies are not as strong. Although all of the correlations are positive, many are not significant. Furthermore, the correlation coefficient of those that are significant is frequently below 0.50. The different financial intermediary indicators give different country rankings of financial intermediary development. These differences reflect financial struc- tures across countries, that is, different combinations of financial intermediar- ies and financial markets that compose a country's financial system. Differences in financial structure may reflect legal differences. For example, countries with universal banking, as distinct from the more segregated legal and regulatory impediments of the United States, may develop different combinations of finan- cial intermediaries. The overall size of the financial system across countries with different financial structures, however, may be similar, as may be the provision of financial services to investors. For example, countries with big financial sys- tems have big banks and nonbank financial corporations, but the correlation between financial system size and private insurance and pension companies is not strong. Aggregate Indexes of Financial Intermediary Development Because we want to compare an overall measure of financial intermediary development with our aggregate indicators of stock market development, we construct conglomerate indexes of financial intermediary development. Using 5. We collected data on private nonbank financial corporations, insurance companies, and pension funds from individual country reports, including documents published by ministries of finance, central banks, and regulatory agencies. Demirgiif-Kunt and Levine 313 the same procedure for constructing conglomerate indexes discussed above, this section constructs three financial intermediary indexes. FINDEXl averages the means-removed values of the ratio of liquid liabilities to GDP and the ratio of domestic credit to the private sector to GDP. FINDEX2 averages the means- removed values of the ratio of liquid liabilities to GDP, the ratio of domestic credit to the private sector to GDP, the ratio of assets of private nonbank finan- cial corporations to GDP, and the ratio of assets of private insurance and pension funds to GDP. FINDEX3 combines the means-removed values of the ratio of total claims of deposit banks to GDP, the ratio of assets of private nonbank financial corporations to GDP, and the ratio of assets of private insurance and pension funds to GDP. Table 6 provides the country rankings and the values of these indexes from 1986 to 1993. The aggregate indexes of financial intermediary development are highly correlated, with correlation coefficients above 0.73 and P-values less than 0.01. The results in table 6 on FINDEX3—which aggregates information on banks, private nonbank financial corporations, and private insurance companies and pension funds—suggest that the top five economies with the most developed financial intermediaries were Switzerland, Sweden, Luxembourg, Australia, and Singapore. The five countries with the least developed financial intermediaries were Colombia, Pakistan, the Philippines, Turkey, and Mexico. We prefer FINDEX3 to the other financial intermediary indexes because it combines information on particular financial intermediaries: banks, nonbank financial corporations, and insurance companies and pension funds. The other aggregate indexes mix infor- mation on particular intermediaries with information on liabilities that span across different types of intermediaries. Stock Market Development and Financial Intermediary Development Do countries with well-developed stock markets have well-developed banks and nonbank financial intermediaries? Table 7 presents the correlations between individual indicators of stock market development and individual indicators of financial intermediary development. Here we highlight three points. First, stock market size (market capitalization) and liquidity (as measured by total value traded/GDP) are positively correlated with all of the indicators of financial intermediary development. They are significantly correlated with all of the indicators of financial intermediary development except the ratio of the as- sets of private insurance and pension companies to GDP. Second, volatility is significantly negatively correlated with all the indicators of financial intermedi- ary development except the ratio of assets of private nonbank financial corpora- tions to GDP. Thus, countries with well-developed financial intermediaries, large banks, and large private insurance companies and pension funds tend to have less volatile stock markets. Third, APT and ICAPM pricing errors are negatively correlated with indicators of financial intermediary development. Countries with stock markets that are internationally integrated tend to have larger financial systems and banks than countries with less internationally integrated markets. 314 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 Table 6. Aggregate Indexes of Financial Intermediaries, 1986-93 FINDEX1' FlNDEX2b FINDEX3' Economy Rank Value Rank Value Rank Value Argentina 42 -0.79 37 -0.72 Australia 11 0.23 4 0.75 Austria 20 -0.12 7 0.23 12 0.34 Belgium 29 -0.35 23 -0.06 Brazil 41 -0.75 34 -0.58 Canada 17 -0.06 6 0.27 13 0.32 Chile 28 -0.29 28 -0.32 Colombia 40 -0.72 20 -0.78 43 -0.82 Denmark 21 -0.12 12 -0.02 19 0.01 Finland 13 0.12 10 0.03 20 0.01 France 8 0.31 9 0.09 18 0.06 Germany 9 0.30 14 0.31 Greece 26 -0.23 27 -0.30 India 30 -0.44 33 -0.48 Indonesia 32 -0.46 36 -0.72 Ireland 31 -0.45 29 -0.36 Israel 19 -0.07 10 0.54 Italy 22 -0.13 15 -0.17 26 -0.23 Japan 2 1.31 7 0.62 Jordan 6 0.42 14 -0.16 31 -0.45 Korea, Rep. of 24 -0.21 11 0.02 17 0.08 Luxembourg 3 0.94 Malaysia 10 0.29 8 0.10 21 0.00 Mexico 39 -0.71 19 -0.77 39 -0.77 Netherlands 7 0.34 4 0.53 6 0.65 New Zealand 23 -0.20 25 -0.19 Nigeria 38 -0.71 38 -0.72 Norway 15 0.03 15 0.16 Pakistan 33 -0.46 17 -0.72 42 -0.81 Philippines 37 -0.61 18 -0.73 41 -0.78 Portugal 18 -0.06 16 0.11 Singapore 4 0.56 1 0.70 5 0.68 South Africa 27 -0.23 30 -0.39 Spain 14 0.11 13 -0.15 24 -0.14 Sweden 25 -0.21 2 0.67 2 1.04 Switzerland 1 1.45 1 1.39 Taiwan (China) 3 0.64 11 0.51 Thailand 16 -0.02 16 -0.36 32 -0.48 Turkey 36 -0.59 40 -0.78 United Kingdom 5 0.45 5 0.53 9 0.55 United States 12 0.14 3 0.59 8 0.60 Venezuela 35 -0.52 22 -0.06 Zimbabwe 34 -0.52 35 -0.59 Average -0.08 -0.00 -0.02 Number of economies 42 20 43 Note: Details of the calculation of the indexes are discussed in the text. The ranking order, by growth rate of each index, is from high to low. a. FINDEXl is the average of the ratio of liquid liabilities (M3 money) to GDP and the ratio of domestic credit to the private sector to GDP. b. FINDEX2 is the average of the ratio of liquid liabilities (M3 money) to GDP, the ratio of domestic credit to the private sector to GDP, the ratio of the assets of private nonbank institutions to GDP, and the ratio of assets of private insurance and pension funds to GDP. c. F1NDEX3 is the average of the ratio of total claims of deposit banks to GDP, the ratio of the assets of private nonbank institutions to CDP, and the ratio of the assets of private insurance and pension funds to GDP. FINDEX3 does not include the last two terms if data are not available. Source: Authors' calculations. Demirguc-Kunt and Levine 315 Table 7. Correlations between Indicators of Financial Intermediary and Stock Market Development, 1986-93 Financial intermediary indicator Total Domestic Assets of claims of credit to Quasi- Assets private Liquid deposit private liquid of private insurance liabilities banks to sector liabilities nonbanks and pension Stock market indicator to GDP1 GDP to GDP to GDPh to GDP funds to GDP Market capitalization Correlation 0.66 0.40 0.52 0.67 0.47 0.29 [0.00] [0.01] [0.00] [0.00] [0.02] [0.20] Number of observations 41 40 40 40 25 22 Total value traded/GDP Correlation 0.75 0.58 0.70 0.78 0.46 0.33 [0.00] [0.00] [0.00] [0.00] [0.02] [0.14] Number of observations 41 40 40 40 25 22 Turnover Correlation 0.18 0.42 0.38 0.22 0.27 0.11 [0.25] [0.01] [0.01] [0.16] [0.20] [0.61] Number of observations 41 40 40 40 25 22 APT pricing error Correlation -0.49 -0.48 -0.54 -0.45 -0.06 -0.40 [0.01] [0.02] [0.01] [0.03| [0.84] [0.20] Number of observations 24 24 24 24 16 12 ICAPM pricing error Correlation -0.51 -0.47 -0.55 -0.46 -0.23 -0.38 [0.01] [0.02] [0.01] [0.02] [0.39] [0.22] Number of observations 24 24 24 24 16 12 Volatility Correlation -0.41 -0.42 -0.40 -0.37 -0.12 -0.52 [0.01] [0.01] [0.01] [0.03] [0.60] [0.02] Number of observations 37 37 37 36 21 20 Market concentration Correlation -0.24 -0.28 -0.32 -0.24 -0.42 -0.56 [0.24] [0.16] [0.11] [0.23] [0.11] [0.04] Number of observations 26 26 26 26 16 14 Institutional development Correlation -0.05 0.21 0.26 0.04 0.42 0.51 [0.84] [0.37] [0.27] [0.86] [0.15] [0.20] Number of observations 20 20 20 20 13 8 Note: P-values are in brackets. Indicators of stock market development are defined in table 1. a. Liquid liabilities are the M3 definition of money. b. Quasi-liquid liabilities are M3 minus Ml money. Source: Authors' calculations. 316 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 Table 8. Correlations between Aggregate Indexes of Financial Intermediary and Stock Market Development, 1986-93 Stock market index Financial intermediary index INDEX1 1NDEX2 1NDEX3 1NDEX4 F1NDEX1 Correlation 0.72 0.83 0.84 0.81 [0.00] [0.00] [0.00] [0.00] Number of observations 40 23 23 21 FINDEX2 Correlation 0.67 0.89 0.89 0.92 [0.00] [0.001 [0.00] [0.00] Number of observations 20 11 11 10 FINDEX3 Correlation 0.62 0.79 0.79 0.80 [0.00] [0.00] [0.00] [0.00] Number of observations 40 23 23 21 Note: P-values are in brackets. The stock market indexes are defined in table 2, and the financial intermediary indexes are defined in table 6. Details of the calculation of the indexes are discussed in the text. Source: Authors' calculations. Using the conglomerate indexes of stock market development and the con- glomerate indexes of financial intermediary development, the strong positive correlation between stock market development and financial intermediary de- velopment emerges even more strongly. As shown in table 8, the aggregate in- dexes of stock market development are all significantly correlated with the ag- gregate indexes of financial intermediary development at the 0.01 level. Furthermore, measures of stock market pricing errors, as represented by APT and ICAPM, are positively correlated with banking inefficiency as measured by the interest rate spread (table 9). Stock market development (including mea- sures of pricing errors) and financial intermediary development (including mea- sures of banking efficiency) go hand in hand. These results are consistent with Boyd and Smith's (1996) model, where there is a role for both banking and equity markets as economies develop. Thus, with increases in per capita income and wealth, stock markets emerge and complement (but not replace) bank lend- ing. As economies develop, their financial systems display a wide array of insti- tutions and markets. V. SUMMARY This article collected and summarized information on a wide assortment of indicators of stock market and financial intermediary development. To describe different characteristics of equity market development, we used measures of stock market size, liquidity, integration with world capital markets, volatility, Demirgiif-Kunt and Levine 317 Table 9. Correlations between Stock Market Pricing Errors and Financial Intermediary Inefficiency, 1986-93 APT ICAPM Indicator Spread' pricing error pricing error Spread Correlation 1.00 0.20 0.81 [0.00] [0.39] [0.00] Number of observations 39 21 21 APT pricing error Correlation 1.00 0.68 [0.00] [0.00] Number of observations 24 24 ICAPM pricing error Correlation 1.00 [0.00] Number of observations 24 Note: P-values are in brackets. a. The spread is the difference between bank lending and borrowing rates. Source: Authors' calculations. concentration, and features of the regulatory system. To describe the develop- ment and structure of financial intermediaries, we used measures of the overall size of the financial intermediary sector, the allocation of credit, the spread be- tween borrowing and lending interest rates, and the size of particular types of financial intermediaries, such as banks, insurance companies, and pension funds. No single measure is the correct measure of stock market or financial interme- diary development. Indeed, each indicator may be the appropriate measure for a particular question. Consequently, this article's major contribution is the collec- tion and comparison of a wide variety of indicators. The article constructs ag- gregate indexes of stock market and financial intermediary development that combine the information reflected in several individual indicators. There are enormous cross-country differences for each indicator of stock market development. For example, the ratio of market capitalization to GDP is greater than 1 in five countries and less than 0.10 in five countries. Even so, there are intuitively appealing correlations among the individual stock market indicators and between the stock market indicators and measures of financial intermediary development. Big markets, for example, tend to be less volatile, more liquid, and less concentrated in a few stocks; internationally integrated markets tend to be less volatile; and institutionally developed markets tend to be large and liquid. Moreover, we find that across countries the level of stock mar- ket development is highly correlated with the development of banks, nonbank financial corporations, and insurance companies and private pension funds. When we compute conglomerate indexes of overall stock market develop- ment, plausible and educational patterns emerge. We find that the three most 318 THE WORLD BANK ECONOMIC REVIEW, VOL. 10, NO. 2 developed markets are Japan, the United States, and the United Kingdom. The most underdeveloped markets are Colombia, Venezuela, Nigeria, and Zimbabwe. The data suggest that Korea, Switzerland, and Malaysia have highly developed stock markets, while Turkey, Greece, Argentina, and Pakistan have underdevel- oped markets. Furthermore, although richer countries generally have more de- veloped stock markets than poorer countries, many markets labeled emerging— such as Korea, Malaysia, and Thailand—are systematically more developed than markets labeled developed—such as France, the Netherlands, Australia, Canada, Sweden, and Norway. During the period from 1986 to 1993, some markets exhibit very rapid devel- opment in terms of size, liquidity, and international integration. Indonesia, Tur- key, Portugal, and Venezuela have experienced explosive development. Future case studies into the underlying causes of and the economic consequences of this rapid development could yield valuable insights. In this article, the goal has not been to test specific hypotheses rigorously. Rather, our objectives have been to compile and compare different indicators of stock market development, highlight some important correlations, and, most important, stimulate future research into the links between stock market devel- opment and economic development. APPENDIX. THE CROSS-COUNTRY COMPARABILITY OF STOCK MARKET DATA The IFC began calculating emerging market indexes in 1981. IFC selects stocks for inclusion in the indexes on the basis of three criteria: size, liquidity, and industry. The indexes include the largest and most actively traded stocks in each market, targeting 60 percent of total market capitalization at the end of each year. The index targets 60 percent of trading volume during the year. Size is measured by market capitalization, and liquidity is measured by the total value of shares traded during the year. Selection criteria used by Morgan Stanley Capital International (MSCI) in creating industrial country stock indexes are comparable to those of the IFC. In constructing the MSCI indexes, 60 percent coverage of the total market capitalization of each market is the primary objective. In contrast to the IFC indexes, MSCI indexes have no secondary objective regarding volume of trading. Instead, they try to replicate the industrial composition of the local market and take a representative sample of large, medium, and small capitaliza- tion stocks. MSCI uses liquidity as a consideration in choosing among the me- dium and small capitalization stocks. The IFC indexes represent value-weighted portfolios of the stocks in each market. Each stock is weighted by its market capitalization in the same way in which the MSCI country indexes are formed, using the chained Paasche method. Most of the stock market indicators compiled in this study are constructed using complete market information, and are fully comparable. For example, the market capitalization ratio is the value of all listed shares in the stock exchange divided by GDP in all countries. 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