Stock market development

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The determinants of stock market development in the Middle-Eastern and North African region

Stock market development


Samy Ben Naceur Faculty of Economics and Business, Universite´ Libre de Tunis, Tunis, Tunisia

Samir Ghazouani Institut Supe´rieur de Comptabilite´ & d’Administration des Entreprises (ISCAE), Campus Universitaire de Manouba, Manouba, Tunisia, and

Mohamed Omran College of Management and Technology, Arab Academy of Science and Technology, Alexandria, Egypt Abstract Purpose – The purpose of this study is to investigate the role of stock markets in economic growth and to shed some light on the macroeconomic determinants which must have an important influence on stock markets development. Design/methodology/approach – The empirical study is conducted using an unbalanced panel data from 12 Middle Eastern and North African (MENA) region countries. Econometric issues are based on estimation of some fixed and random effects specifications. Findings – It is found that saving rate, financial intermediary, stock market liquidity and the stabilization variable are the important determinants of stock market development. In addition, it is found that financial intermediaries and stock markets are complements rather than substitutes in the growth process. Practical implications – This paper has some policy implications to MENA region countries. In order to promote stock market development in the region, it is important to encourage savings by appropriate incentives, to improve stock market liquidity, to develop financial intermediaries and to control inflation. Originality/value – Since it is unclear whether emerging markets in the MENA region respond, similarly, to economic and political shocks like other emerging markets and/or developed markets. This paper fills this gap by making an in-depth analysis of 12 MENA capital markets in order to assess how they can improve their capital markets, and hence, benefit the global investor. Keywords Stock markets, Capital markets, Middle East, North Africa Paper type Research paper

1. Introduction Even though most Middle-Eastern and North African (MENA) countries have embarked on economic reform and structural adjustment programs, the Asian crisis of 1997 shifted the focus of such programs to financial markets. However, the lack of institutional development is a powerful obstacle to an increased access to MENA capital markets. Additionally, the region witnessed, and still, wars, political turmoil and economic instability. Consequently, MENA countries have not yet emerged as economic powers, which might explain the lack of academic research on MENA capital markets. In fact, it is unclear whether emerging markets in the MENA region respond,

Managerial Finance Vol. 33 No. 7, 2007 pp. 477-489 # Emerald Group Publishing Limited 0307-4358 DOI 10.1108/03074350710753753

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similarly, to economic and political shocks like other emerging markets and/or developed markets. Hence, the purpose of this paper is to fill this void in the literature and make an in-depth analysis of 12 MENA capital markets in order to assess how they can improve their capital markets, and hence, benefit the global investor. More precisely, the paper addresses the issue of the impact of macroeconomic variables on stock market development in 12 MENA markets. The measurement of stock market development is important because it is the precept for predicting economic growth and therefore, the principle for country selection by foreign investors. Thus, the results of this paper are expected to contribute to the paradigm of global asset allocation strategies in emerging markets. The paper is organized as follows. In section 2, the outlines which characterize the evolution of the financial systems in the MENA region countries, especially those considered in the empirical study, are presented. Section 3 Identifies organic relationships between stock market development and economic growth by means of some main macroeconomic determinants. Section 4 outlines the data and the adopted econometric methodology. The findings are reported in section 5 and the paper concludes with a summary and policy implications. 2. Evolution of financial systems in the MENA region Most of the Middle-Eastern countries have engaged in implementing economic reform and structural adjustment programs in recent decades. The core of the abovementioned programs is the reform in the financial sector that have enabled most of MENA countries to establish or resurrect their stock markets. As a result, stock exchanges in these countries and other emerging economies became very important to the world’s economy and their role in the international financial system witnessed a significant increase. As seen from Table I, Panel A, over the nine years between 1990 and 1999, the market capitalization of emerging stock markets rose from $604 billion to $3,074 billion. In the meantime, the value of trade represented by the emerging markets also increased significantly from $613 billion in 1990 to $2,867 billion in 1999, a more than fourfold Years 1990


Panel A: Developed and emerging markets performance between 1990 and 1999 Stock market indicators Value Percentage Value DM EM DM EM DM EM Market capitalization (billion of US$) 8,795 604 93.5 6.5 32,956 3,074 Value traded (billion of US$) 4,406 613 88 12 28,154 2,867 Number of listed companies 16,504 8,920 65 35 23,326 26,314

Percentage DM EM 91.5 8.5 91.8 9.2 47 53

Panel B: Weight of Middle-Eastern markets in the S&P/IFCGCI between 1990 and 1999 Latin America 15.8% 21.3% Asia 73.3% 50.7% Europe 9.7% 14% Middle East and North Africa 1.2% 14% Table I. Some indicators for emerging markets over the period [1990-1999]

Notes: DM, Developed Markets; EM, Emerging Markets; S&P/IFCGCI, Standard and Poor and International Finance Corporation Global Composite Index, respectively Source: International Finance Corporation (2000)

increase in their level of activities. In addition, the emerging stock markets’ participation in the number of listed companies throughout the world jumped from only 35 per cent in 1990 to 53 per cent in 1999, suggesting that these markets are seen to grow much faster than developed markets. However, because of major changes in the economic and financial environment in the MENA countries, emerging equity markets in this region have been the focus of much attention recently from international investors. As a result, the weighting of these markets in the Standard and Poor/International Finance Corporation Global Composite Index surged substantially from below 2 per cent in 1990 to around 14 per cent in 1999 (Table I, Panel B). Nevertheless, the latest development in the stock market in MENA countries varies across countries as seen in Table II. Jordan, Kuwait and Qatar seem to outperform other countries as they achieved very strong progress between 1999 and 2002. On the other hand, Morocco, Turkey and Saudi Arabia come at the end of the list. On average, it is clear from the table that the whole sample countries achieved high level of performance between 1999 and 2002. The only negative indicator is the market capitalization that decreased by 21.6 per cent, but the main reason here is Turkey because of the huge depreciation in its currency[1].


Bahrain Egypt Iran Jordan Kuwait Lebanon Morocco Oman Qatar Saudi Arabia Tunisia Turkey Total



% change 2002 [1999-2002]


Market capitalization (billions of US$) 7.16 6.62 6.60 7.72 7.76 41 33.04 30.79 24.31 26.34 20.28 1,033 21.86 7.54 9.70 14.34 34.38 295 5.83 4.94 6.31 7.09 21.46 152 19.60 19.85 26.66 35.10 79.09 85 1.92 1.58 1.25 1.40 27.38 13 13.70 10.88 9.03 8.56 37.49 54 4.30 3.52 2.63 5.27 22.42 140 5.50 5.17 7.30 10.57 92.13 21 60.95 67.17 73.20 74.85 22.80 72 2.64 2.81 2.23 2.13 19.43 44 114.27 69.51 47.69 34.40 69.89 285 290.78 230.37 216.92 227.76 21.67 2,235

Value traded (billions of Bahrain 0.44 0.25 0.25 0.21 Egypt 9.73 11.80 5.91 6.44 Iran 2.27 1.08 1.10 2.21 Jordan 0.55 0.41 0.93 1.33 Kuwait 6.00 4.21 11.71 22.12 Lebanon 0.09 0.12 0.05 0.11 Morocco 2.52 1.21 0.84 1.44 Oman 0.71 0.55 0.42 0.58 Qatar 0.34 0.24 0.41 0.88 Saudi Arabia 15.09 17.31 22.22 30.97 Tunisia 0.46 0.69 0.34 0.25 Turkey 84.03 181.93 80.40 70.76 Total 122.24 219.79 124.60 137.31

US$) 53.59 33.75 2.82 142.96 268.66 26.93 42.95 18.57 159.73 105.31 46.10 15.80 12.33

6.21 29.44 10.39 9.41 30.62 4.71 18.43 16.60 6.18 24.75 17.33 73.54 42.04




Stock market development


% change [1999-2002]

Number of listed companies 41 42 40 1,071 1,110 1,150 304 316 327 163 161 158 86 88 95 13 14 13 54 55 55 131 96 140 22 22 25 75 76 68 44 45 46 315 310 288 2,319 2,335 2,405

2.44 11.33 10.85 3.95 11.76 0.00 1.85 0.00 19.05 5.56 4.55 1.05 7.61

Turnover ratio 3.71 3.79 2.67 38.32 24.32 24.46 14.30 11.33 15.39 8.21 14.80 18.83 21.20 43.93 63.03 7.45 4.24 8.24 11.13 9.31 16.82 15.67 15.94 11.04 4.64 5.67 8.36 25.78 30.36 41.38 24.45 15.34 11.60 261.75 168.59 205.68 95.41 57.44 60.29

56.93 16.89 48.09 100.03 105.86 74.80 8.72 33.49 35.18 67.19 33.10 179.69 43.41

Table II. Selected indicators of stock market performance [1999-2002]

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On the other hand, most of our sample countries embarked on institutional setting and regulations such as establishing security market regulation, investors protections, trading rules based on shared regulatory responsibility, etc. Additionally, except for Gulf countries and Iran, foreign investors are allowed to participate in stock market activities with nearly no limitation[2]. Given the importance of these markets to the global financial system, this paper empirically investigates the impact of several macroeconomic indicators on stock market development. 3. Stock market development, economic growth and macroeconomic factors The financial system is essential to an economy because it is responsible for resource allocation. Well-working financial intermediaries may affect positively the economic development through four main channels which consist in reducing information and transactions costs, improving the allocation of resources (through fund pooling, risk diversification, liquidity management, screening and monitoring), increasing saving rates and promoting the development of markets and instruments that enable risk sharing organic relationships between stock market development and economic growth are identified[3]. Conversely, the financial crisis literature points to the destabilizing effect of financial liberalization as it leads to over-lending. Over-lending would appear through several channels, including a limited monitoring capacity of regulatory agencies, the inability of banks to discriminate good projects during investment booms, and the existence of an explicit or implicit insurance against banking failures (Aghion et al., 1999). Empirical investigations provide evidence of a positive relationship between finance and economic growth. The first evidence that financial sector development promotes growth was reported by Goldsmith (1969) in a paper covering 35 countries over the period (1860-1963). However, his work did neither control for initial conditions and country characteristics, nor did it permit any conclusions on causality or the relative strength of the transmission channels. Recent years have witnessed a vivid interest in empirical research on the relationship between financial sector development and economic growth. The relationship was found to be bi-directional, that is financial development is crucial for economic growth and economic growth can also promote financial development. The evidence deals with this causal relationship along three lines: .

Financial development accelerates economic growth or is conducive to growth slowdowns. The financial sector increases savings and allocates them to more productive investments. Thereby financial development can spur economic growth. For instance, recent findings in King and Levine (1993), Rousseau and Wachtel (1998), Levine and Zervos (1998), Levine et al. (2000), Beck et al. (2000a, b), and Rousseau and Sylla (2001). Conversely, the banking and currency crisis literature find that monetary aggregates, such as domestic credit, are among the best predictors for crises (e.g. Demirgu¨c¸-Kunt and Degatriache, 1998, 2000; Gourinchas et al., 1999). Since banking crises usually lead to recessions, an expansion of domestic credit would then be associated to growth slowdowns.


Economic growth promotes financial development. According to this hypothesis, financial development appears as a consequence of the overall economic

expansion. It has a passive role and adapts itself to the financing needs of the real sector (Gurley and Shaw, 1967; Goldsmith, 1969). .

The reciprocal relationship. Economic growth makes the development of financial system profitable and the establishment of an efficient financial sector contributes to stimulate economic development. Luintel and Khan (1999) reveal evidence for bi-directional causality from a sample of ten developing countries. Shan et al. (2001) confirm this finding from a sample of nine OECD countries.

Most of the evidence quoted above uses banks-based measures of financial development such as total lending by non-bank public per capita, bank credit to GDP (Shan et al., 2001) and broad money to GDP (Rousseau and Sylla, 2001). Banks dominate financing in many places and even in the most developed countries. Stock markets are only a small part of the overall financial system[4]. However, the existence of an equity market is important because it provides investors with an exit mechanism, it attracts foreign capital inflows, it provides important information that improves the efficiency of the financial system and it provides the valuation of companies. Not until recently has the focus increasingly shifted to stock market indicators, due to the increasing contribution of financial markets in economies. Ajte and Jonanovic (1993) show that trading volume (stock market development indicator) has a strong incidence on economic growth while bank credit does not. Similarly, Levine and Zervos (1996, 1998) and Singh (1997) find evidence on a positive relationship between stock market development and long-run economic growth. In addition, Levine and Zervos (1996) show that stock market liquidity is positively and robustly associated with long-run economic growth after controlling for economic and political variables. In the same vein, Rousseau and Wachtel (2000) use two measures of stock market development, that is the ratio of market capitalization to GDP and the ratio of total value traded to GDP. Both have a positive coefficient, but only the latter is significant. The results show that the development of a liquid and highly capitalized equity market accelerates growth. They also make an important contribution to the literature by using panel techniques with annual data. Finally, Garcia and Liu (1999) empirically explored the determinants of stock market development, particularly market capitalization. They also examined the association between financial intermediary development and stock market development using a sample of fifteen industrial and developing countries from 1980 to 1995. They concluded that real income level, saving rate, financial intermediary development, and stock market liquidity are important predictors of market capitalization, while macroeconomic stability does not have any explaining power. They confirmed that banks and markets are complement instead of substitutes. 4. Data and econometric modeling 4.1 Data sources Data were extracted from various sources. Arab Monetary Fund was a main source for data on Arab countries. We consult the capital market unit database to collect stock market indicators from 1994, and the economic and technical department database for other economic data series. As for the stock market data prior to 1994, we collect them from world development indicators and local stock markets. With regard to Iran and Turkey, world development indicators was the main source for both economic and stock market data.

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Our original intention was to cover all countries in the MENA region, but given that some countries have not yet established stock markets (for example, Iraq, Libya, Sudan, Syria and Yemen), and other countries established stock markets only in the past couple of years (United Arab Emirates), the sample countries included only 12 countries, in which ten countries are from the Arab world. Of course, data were not available for a uniform period for each country, and many countries have no stock market until recently. Consequently, it is expected that the number of observations varies across our sample countries leading to conduct estimations over an incomplete panel data. The number of time observations ranges from three annual observations for Qatar to 21 observations for Jordan. For the most other countries, the periods of observations cover mainly the 1980s and 1990s (see Appendix 1). This paper focuses on the determinants of stock market capitalization – defined as the total market value of all listed shares divided by GDP – as a proxy for financial market growth[5]. Besides, we use the following indicators as explanatory variables (Garcia and Liu, 1999): .

Income. We use real GDP in US dollars to measure the income level. As income increases, its cyclical component should have a positive incidence on the size of the stock market. In addition, higher income means better education, better business environment and wealthy citizens. We expect to have a positive impact on stock market development.


Saving rate. The saving rate is calculated as the ratio of gross saving to gross disposable income. Like banks, stock markets convey saving to investment projects. Usually, the larger the saving rate, the higher the flow of capital to stock markets. We expect a positive effect of the saving rate on the stock market size.


Investment rate. The investment rate is calculated as the ratio of gross fixed capital to gross disposable income. As investment rate depends on saving rate, we expect investment to be important determinants of stock market capitalization.


Credit to private sector. We use the domestic credit to the private sector divided by GDP to account for financial intermediary development. Since both banks and stock markets intermediate savings towards investment projects, they can be either complements or substitutes. Boyd and Smith (1996) suggest that banks and stock markets may behave as complements rather than as substitutes. Empirically, Demirgu¨c¸-Kunt and Levine (1996a) show that the degree of stock market development is positively related to bank development. Conversely, Garcia (1986) finds that central banks may generate a negative correlation between bank growth and stock market development.


M3. Another indicator for bank development is the ratio of broad money supply M3 to GDP. This ratio is a measure of the size of the banking sector in relation to the economy as a whole whereas credit to private sector measures the role of financial intermediaries in provision of longer-run financing of investment projects by private corporations.



Stock market liquidity. We measure the stock market liquidity using two indicators. The first variable is the value traded which is the ratio of total value traded to GDP and it measures the value of stock transactions relative to the size of the economy. The second variable is the Turnover ratio calculated as the ratio of the total value traded by stock market capitalization (It often measures the value of equity transactions relative to the size of the stock exchange). Liquid stock market enables investors to modify their portfolios quickly and cheaply. It facilitates investment projects and make them less risky (Levine, 1991; Bencivenga et al., 1996). Therefore, we expect liquidity to have a positive impact on stock market capitalization because larger amount of savings are channeled through stock markets. Macroeconomic instability. To measure the incidence of macroeconomic instability on stock market development, we use inflation change. We expect that the higher the volatility of the economy (inflation change) the less incentive companies and investors would have to put their money in the stock exchange (stock market development).

4.2 Econometric modeling According to the available data, the treatment of incomplete panels is imperative. Indeed, the available panel dataset for the twelve MENA region countries is unbalanced since each variable is observed over varying time period length. In this study, fixed effects as well as random effects models are considered. The fixed effects model is more simple to conduct and is defined according to the following regression model: yit ¼ i þ 0 Xit þ "it ;

i ¼ 1; . . . ; N ; t ¼ 1; . . . ; Ti


yit indicates the dependent variable while Xit determines the vector of k explanatory variables. i, i ¼ 1, . . . , N, are constant coefficients specific to each country. Their presence assumes that differences across the considered countries appear by means of differences in the constant term. These individual coefficients are estimated together with the vector of coefficients . In order to validate the fixed effects specification, the question is to prove, according to the empirical application, that the individual coefficients i, i ¼ 1, . . . , N, are not all equal. This corresponds to the following joint null hypothesis: H0 : 1 ¼    ¼ N ¼ 


It is rather the acceptation of the alternative hypothesis which is interesting if we want to differentiate between the situation in each country considered in the sample and confirm the existence of significant heterogeneity across countries. The appropriate statistic of the test is a Fisher distributed one with (N  1, Ni¼1 Ti  N  k) degrees of freedom under the null hypothesis and is defined as follows: SSR0  SSR1 F¼ SSR1



Ti  N  k N 1


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where SSR0 and SSR1 are, respectively, the sum of squared residuals provided by the estimation of the constrained model (under the null hypothesis that is no individual specific coefficients are considered) and the sum of squared residuals relative to the fixed effects model (equation (1)). In the random effects case, the model is defined as follows: yit ¼ 0 Xit þ "it ;


i ¼ 1; . . . ; N ; t ¼ 1; . . . ; Ti


where "it ¼ i þ it reflect the error component disturbances. The individual specific effects are random and distributed normally (i ! IIN(0, 2 )). They are independent of the residual terms it which are also distributed normally (it ! IIN(0, 2 )). The estimation of the model is conducted by the feasible generalized least squares method. First, convergent estimates of the variances 2 and 2 are needed. They are obtained by the following formulae:  PN PT i  ^i 2 ^it   i¼1 t¼1  ^2 ¼ P ð5Þ N i¼1 Ti  N  k


N  2 1  1 X i0  ^  yi  b Xi  ^2 ¼ N  k i¼1 Ti


^it are the residuals issued from the estimation of the fixed effects model (equation (1)) ^i are individual means of these residuals over each time period relative to each and  country. Next, the first term in equation (6) indicates the residuals issued from the estimation of the unit means regression where ^ ib are called the between estimators. The second stage consists in the estimation by ordinary least squares of the following transformed regression model: qffiffiffiffi  qffiffiffiffi   qffiffiffiffi   0 ^ ^ ^ i  1 yi ¼  Xit þ i  1 Xi þ "it þ i  1 "i ð7Þ yit þ with ^i ¼


^2 ; þ Ti ^2

i ¼ 1; . . . ; N


Finally, a Hausman specification test is conducted in order to compare the two categories of specifications. It is proven that, under the null hypothesis, the two estimates (equations (1) and (7)) could not differ systematically since they are both consistent. So, the test can be based on the difference. Under the null hypothesis, the Hausman statistic is asymptotically distributed as chi-square with k degrees of freedom and is written down as follows:  0     1   ^ ^F  V ^ ^GLS V ^GLS  ^F ð9Þ H ¼ ^GLS  ^F where ^F and ^GLS are, respectively, the estimates of the fixed effects and ^ ðÞ are the corresponding variance–covariance matrices of random effects models. V these estimated coefficients.

5. Empirical results The estimation of fixed effects as well as random effects specifications was carried out using the econometric methodology presented in section 4[6]. First, the F-test (equation (3)) led to the validation of the fixed effects specification, that is the presence of individual effects which are not equal. So the heterogeneity across countries is confirmed. On the other hand, the Hausman test also led, for this application, to the acceptation of the null hypothesis according to which the estimates issued from each type of model are equivalent. For all the specifications, the estimated values for the statistics of the test (equation (9)) are below the corresponding critical values of chi-square at the 5 per cent level (see Appendix 2 for random effects results). Indeed and from a purely practical point of view, it is difficult to make a real distinction between fixed and random effects models in such situation because each one have some technical and conceptual advantages and drawbacks. Since we need to consider heterogeneity across countries, we adopt the fixed effects specifications. Table III shows the results of regressions on determinants of stock market capitalization from a sample of twelve MENA countries using the fixed effects specifications. The results from column (1) display that last year’s saving rate, domestic credit to private sector and last year’s value traded to GDP ratio have a positive and significant effect on stock market capitalization. Conversely, last year’s income has no significant impact on market capitalization meaning that high income growth does not promote development in the stock market. On the other hand, growth in revenues is conveyed to other vehicles, such as real investment, bank sector and foreign direct investment (specially Gulf countries), rather than stock markets.

Regressions Income Saving rate

(1) 0.00167 (1.205) 0.402 (2.377)

Investment rate Credit to private 0.846 sector (9.112) M3 Value traded

0.283 (3.434)

Turnover ratio




0.00163 0.00246 0.00197 (1.125) (1.379) (1.334) 0.174 0.471 (0.767) (2.686) 0.0684 (0.382) 0.83 0.942 (8.407) (10.077) 0.268 (2.557) 0.31 0.543 (3.676) (5.575) 0.0406 (1.0896)

0.0012 (0.866) 0.424 (2.529)

(6) 0.00183 (1.0037) 0.341 (1.555)

0.798 (8.388) 0.311 (3.758)

(7) 0.00213 (1.364)

134 0.925 75.442

134 0.885 48.032

134 0.922 69.66


(8) 0.00127 (0.873)

0.00883 0.0405 (0.0469) (0.226) 0.947 0.791 (9.47) (7.854)

0.254 (2.497) 0.557 (5.758)

0.335 (3.939) 0.041 (1.0582)

0.247 (1.913)

Inflation change No. observations 134 R2 0.929 Statistic F 75.294


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134 0.931 74.726

134 0.887 52.723

134 0.918 68.179

0.222 (1.67)

Table III.

134 0.927 74.951

Fixed effects specifications of determinants of market capitalization

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To test the effect of the investment rate on stock development, column (2) includes last year’s investment rate instead of saving rate. The results reached in the first regression are confirmed. However, the investment rate is not a good predictor of market capitalization since its coefficient is insignificant. This confirms the void relationship between the real economy and the financial market since we found in the first regression no link between last year’s income and stock market capitalization. Such issue could be explained by the smallness of the stock markets in the MENA region. To test the incidence of another measure of financial intermediary development on stock market capitalization, column (3) contains M3 to GDP ratio instead of domestic credit to private sector. This confirms the positive impact of financial intermediary growth on development of stock market. Comparing regressions (1) and (3), we record that domestic credit to private sector seems to be a better measure of financial intermediary and a better predictor of stock market development. This is consist with our expectation. To test the incidence of another measure of stock market liquidity, regression (4) includes least year’s turnover ratio instead of the ratio of value traded to GDP. Comparing with regression (1), we notice that the value traded plays a more important role in explaining stock market capitalization since the coefficient of least year’s turnover ratio is not significant. In addition, inflation change is introduced to control for the macroeconomic stability. In regression (5), the coefficient of this variable have the expected negative sign and is significant which indicate that macroeconomic stability does play a considerable role in determining stock market capitalization. Finally, to test the hypothesis that saving rate is better than investment rate to predict stock market capitalization development, we compare regressions (3)-(5) with regressions (6)-(8), respectively. The results prove the predominance of saving rate as a good predictor stock market capitalization. 6. Conclusions Using a sample of twelve MENA region countries over a varying period, this study tries to identify the main macroeconomic determinants of stock market development. It also examines the impact of financial intermediary development on stock market capitalization. We find that saving rate, financial intermediary (specially credit to private sector), stock market liquidity (specially the ration of value traded to GDP) and the stabilization variable (inflation change) are the important determinants of stock market development, while income as well as investment do not prove to be significant. In addition, we find that financial intermediaries and stock markets are complements rather than substitutes in the growth process. This paper also has some policy implications to MENA region countries. In order to promote stock market development in the region, it is important to encourage savings by appropriate incentives, to improve stock market liquidity, to develop financial intermediaries and to control inflation. Notes 1. If we eliminate Turkey, the market capitalization indicator would be increased by 1 per cent instead. 2. Gulf countries in this paper are Bahrain, Kuwait, Oman, Qatar and Saudi Arabia. 3. For more detailed descriptions, see King and Levine (1993), Levine (1997), Pagano (1993) and Wachtel (2003).

4. The literature omits measures of stock market development because measures of stock market development for a 20-year period are only available for about 40 countries. 5. This definition of stock market development is used here rather than a composite index of stock market development because it is a good proxy for general development and individual measures and indexes of stock market development are strongly associated (Demirgu¨c¸-Kunt and Levine, 1996a). 6. An appropriate algorithm was written on TSP.43 software. References Aghion, P., Bacchetta, P. and Banerjee, A. (1999), ‘‘Capital markets and the instability of open economies’’, mimeo. Atje, R. and Jovanovic, B. (1993), ‘‘Stock markets development’’, European Economic Review, Vol. 37, pp. 632-40. Beck, T., Demirgu¨c¸-Kunt, A. and Levine, R. (2000a), ‘‘A new database on financial development and structure’’, World Bank Economic Review, Vol. 14, pp. 597-605. Beck, T., Levine, R. and Loayza, N. (2000b), ‘‘Finance and the sources of growth’’, Journal of Financial Economics, Vol. 58, pp. 261-300. Bencivenga, V., Smith, B. and Starr, R. (1996), ‘‘Equity markets, transaction costs, and capital accumulation: an illustration’’, World Bank Economic Review, Vol. 10, pp. 241-65. Boyd, J. and Smith, B. (1996), ‘‘The coevolution of the real and financial sectors in the growth process’’, World Bank Economic Review, Vol. 10, pp. 371-96. Demirgu¨c¸-Kunt, A. and Degatriache, G. (1998), ‘‘The determinants of banking crises in developing and developed countries’’, IMF Staff Papers, Vol. 45, pp. 81-109. Demirgu¨c¸-Kunt, A. and Degatriache, G. (2000), ‘‘Banking sector fragility: a multivariate logit approach’’, World Bank Economic Review, Vol. 14, pp. 287-307. Demirgu¨c¸-Kunt, A. and Levine, R. (1996a), ‘‘Stock markets, corporate finance, and economic growth: an overview’’, World Bank Economic Review, Vol. 10, pp. 223-39. Garcia, V.F. (1986), A Critical Inquiry Into Argentine Economic History [1946-1970], Garland Publishing Co., New York, NY. Garcia, V. and Liu, L. (1999), ‘‘Macroeconomic determinants of stock market development’’, Journal of Applied Economics, Vol. 2, pp. 29-59. Goldsmith, R.W. (1969), Financial Structure and Development, Yale University Press, New Haven, CT. Gourinchas, P.O., Landerretche, O. and Valdes, R. (1999), ‘‘Lending booms: some stylized facts’’, mimeo. Gurley, J. and Shaw, E. (1967), ‘‘Financial structure and economic development’’, Economic Development and Cultural Change, Vol. 34, pp. 333-46. International Finance Corporation (2000), Emerging Stock Market Fact Book 2000, Washington, DC. King, R.G. and Levine, R. (1993). ‘‘Finance and growth: Schumpeter might be right’’, Quarterly Journal of Economics, Vol. 108, pp. 717-38. Levine, R. (1991), ‘‘Stock markets, growth and tax policy’’, Journal of Finance, Vol. 46, pp. 1445-65. Levine, R. (1997), ‘‘Financial development and economic growth: views and agenda’’, Journal of Economic Literature, Vol. 35, pp. 688-726. Levine, R. and Zervos, S. (1996), ‘‘Stock markets, banks, and economic growth’’, working paper No. 1690, World Bank Policy Research. Levine, R. and Zervos, S. (1998), ‘‘Stock markets, banks and economic growth’’, American Economic Review, Vol. 88, pp. 537-58.

Stock market development


MF 33,7


Levine, R., Loayza, N. and Beck, T. (2000), ‘‘Financial intermediation and growth: causality and causes’’, Journal of Monetary Economics, Vol. 46, pp. 31-77. Luintel, and Khan, M. (1999), ‘‘A quantitative reassessment of the finance-growth nexus: evidence from a multivariate VAR’’, Journal of Development Economics, Vol. 60, pp. 381-405. Pagano, M. (1993), ‘‘Financial markets and growth: an overview’’, European Economic Review, Vol. 37, pp. 613-22. Rousseau, P.L. and Sylla, R. (2001), ‘‘Financial systems, economic growth and globalization’’, NBER working paper No. 8323. Rousseau, P.L. and Wachtel, P. (1998), ‘‘Financial intermediation and economic performance: Historical evidence from five industrial countries’’, Journal of Money, Credit, and Banking, Vol. 30, pp. 657-78. Rousseau, P.L. and Wachtel, P. (2000), ‘‘Equity markets and growth: cross country evidence on timing and outcomes’’, Journal of Banking and Finance, Vol. 24, pp. 1933-57. Shan, J.Z., Morris, A.G. and Sun, F. (2001), ‘‘Financial development and economic growth: an egg and chicken problem?’’, Review of International Economics, Vol. 9, pp. 443-54. Singh, A. (1997), ‘‘Financial liberalisation stock markets and economic development’’, The Economic Journal, Vol. 107, pp. 771-82.

Further reading Baltagi, B.H. (1995), Econometric Analysis of Panel Data, John Wiley & Sons, New York, NY. Baltagi, B.H. and Chang, Y.J. (1994), ‘‘Incomplete panels: a comparative study of alternative estimators for the unbalanced one-way error component regression model’’, Journal of Econometrics, Vol. 62, pp. 67-89. Demirgu¨c¸-Kunt, A. and Levine, R. (1996b), ‘‘Stock market development and financial intermediaries: stylized facts’’, World Bank Economic Review, Vol. 10, pp. 291-21. Sevestre, P. (2002), Econome´trie des donne´es de panel, Dunod, Paris. Wachtel, P. (2003), ‘‘How much do we really know about growth and finance?’’, Economic Review, Vol. 88, pp. 33-48.

Appendix 1

Table AI. Sample description

Bahrain Egypt Iran Jordan Kuwait Lebanon Morocco Oman Qatar Saudi Arabia Tunisia Turkey

[1989-1999] [1981-1999] [1993-1999] [1979-1999] [1993-1999] [1995-1999] [1983-1999] [1989-1999] [1997-1999] [1991-1999] [1987-1999] [1988-1999]

Stock market development

Appendix 2






Jordan Egypt Tunisia Morocco Saudi Arabia Kuwait Qatar Oman Bahrain Lebanon Turkey Iran

3.581 26.765 47.706 21.504 9.727 26.917 45.578 20.606 33.669 47.374 24.994 45.968

1.58 18.832 35.61 12.638 4.373 16.477 26.0718 7.722 50.933 50.384 14.779 32.884

19.225 19.73 12.765 11.776 2.539 32.396 39.545 4.754 49.104 32.836 10.39 10.251

8.419 31.205 54.998 25.687 15.229 28.53 57.793 26.196 25.507 54.268 29.0707 52.836




Regressions Income



1.723 31.322 21.753 7.256 43.53 2.337 18.817 0.518 5.894 14.771 18.508 12.334 34.514 9.66 17.0393 10.00778 39.0471 69.416 40.333 21.32 4.555 3.468 36.825 4.188






9.753 24.532 44.316 17.751 1.964 20.355 41.739 14.0221 41.599 62.197 19.55 40.702

1.976 14.898 32.463 10.696 7.359 9.945 17.346 4.885 55.246 45.653 30.637 25.115



Table AII. Constants from the fixed effects regressions


0.00165 (1.74) 0.43 (2.679)

0.00189 0.00162 0.00187 (1.918) (1.66) (1.883) 0.261 0.497 (1.305) (2.988) 0.0859 (0.491) 0.836 0.811 0.932 (9.248) (8.442) (10.255) 0.243 (2.674) 0.287 0.316 0.546 (3.562) (3.822) (5.739) 0.0431 (1.2)

0.00125 0.00161 0.00227 0.00156 (1.284) (1.496) (2.239) (1.521) Saving rate 0.451 (2.833) 0.361 0.0367 0.0539 Investment rate (1.715) (0.2) (0.31) Credit to private 0.787 0.924 0.774 sector (8.522) (9.492) (7.91) M3 0.237 (2.56) Value traded 0.316 0.558 0.341 (3.914) (5.952) (4.104) Turnover ratio 0.0433 (1.162) Inflation change 0.248 0.22 (2.0383) (1.751) Constant 23.952 13.748 3.878 29.363 17.113 10.169 20.437 8.445 (2.229) (1.115) (0.346) (2.663) (1.5) (0.709) (1.632) (0.645) Nb. observations 134 R2 0.568 2 ^v 70.761 ^u2 772.978 Statistic H 0.416

134 0.545 74.061 806.503 0.865

134 0.322 114.223 561.481 2.487

134 0.531 77.06 823.437 0.347

134 0.582 69.206 821.932 0.416

134 0.328 112.486 811.618 0.223

134 0.497 81.77 801.1 1.354

134 0.557 72.958 923.479 0.704

Corresponding author Samy Ben Naceur can be contacted at: [email protected], [email protected]

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Table AIII. Random effects specifications of determinants of market capitalization

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