and explanatory variables and the methodology we use, then present the regression results, and finally discuss some robustness tests.

# **3.1 Data and Methodology**

For the empirical analysis of stock markets, we follow Claessens, Klingebiel, and Schmukler (2006), who analyze the factors driving domestic stock market development and internationalization. We use three measure of domestic stock market development: market capitalization, value traded, and capital raised, all as a percentage of GDP.<sup>16</sup> The data on market capitalization and value traded on the major local stock exchanges come from the Standard & Poor’s Global Stock Markets Factbook and cover the period 1975-2004 for 117 countries. The amount of equity capital raised by domestic firms in the local stock market comes from the World Federation of Exchanges and covers the period 1982-2004 for 46 countries.

In terms of explanatory variables, we include several factors found to be important in the literature on stock market development. First, since more developed countries tend to have deeper domestic stock markets (see, for example, La Porta, Lopez de Silanes, and Shleifer, 2006, La Porta et al., 1997, and Rajan and Zingales, 2003) we use GDP per capita as a measure of countries’ overall economic development. Higher income countries also tend to have better institutional and legal environments, which have been found to matter for financial development (see Beck and Levine, 2005).<sup>17</sup> To further address this issue, we include an index of the strength of minority shareholder rights from Djankov et al. (2005).<sup>18</sup> The regressions include two alternative indicators of macroeconomic soundness, the annual inflation rate and the government deficit over GDP, given that a better macroeconomic environment promotes financial development (see Bencivenga and Smith, 1992, Boyd, Levine, and Smith, 2001, and Huybens and Smith, 1999).

We include three alternative variables to control for the extent of financial openness and liberalization, as that has been found to affect stock market development (see Bekaert and Harvey, 2000, 2003, Edison and Warnock, 2003, Henry, 2000, and Levine and Zervos, 1998). First, we include a “de jure” measure of capital account liberalization constructed by Chinn and Ito (2006). Second, as we are analyzing stock markets, we also use a “de jure” indicator of stock market liberalization. Our data for dating the

> 16 We also estimated regressions using turnover (defined as value traded over market capitalization) and obtained results similar to those reported below.

> 17 GDP per capita is highly correlated with different measures of the institutional environment. For our sample, the correlation between GDP per capita and indices of bureaucratic quality, corruption, and law and order reported by the International Country Risk Guide (ICRG) service is 0.73, 0.67 and 0.71, respectively and in all cases it is significant at the one percent level. All the results reported in the paper are robust to replacing GDP per capita with any of these measures of the institutional environment.

> 18 Djankov et al. (2005) present revised estimates of the anti-director rights index from La Porta et al. (1998) and expand the sample of countries covered. All the results reported in the paper are robust to replacing this updated index with the original measure from La Porta et al. (1998).

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