factor for the development of liquid, well-functioning securities markets. See, for example, McCauley and Remolona (2000) and Shah and Thomas (2001).

Finally, to test whether the level of stock market development in Latin America differs from that predicted from fundamentals, we include a Latin American dummy variable, which takes the value one if the country is located in Latin America and the Caribbean and zero otherwise.<sup>24</sup> If stock market development in Latin America is close to the level predicted by the region’s fundamentals, this dummy should not be significant.

After removing outliers, countries with missing data on the independent variables, and countries with less than five annual observations, we are left with a sample of 95 countries covering the period 1975-2004.<sup>25</sup> The sample includes 18 Latin American countries, which account on average for 17 percent of the observations used in the regressions.<sup>26</sup> In all cases, we pool the data over time and across countries. Regarding the estimation technique, we use least squares estimators adjusting the standard errors for clustering at the country-level.<sup>27</sup>

# **3.2 Regression Results**

The results for stock market capitalization over GDP, value traded over GDP, and capital raised over GDP are presented in Tables 1, 2, and 3, respectively. The tables provide in the first column the results for a regression with GDP per capita, inflation, and capital account liberalization as the only explanatory variables. The tables then report a regression with government deficit over GDP instead of inflation, since these two constitute alternative indicators of macroeconomic soundness and stability. To keep the size of the tables manageable, we just continue to use one of the macro variables, government deficit over GDP.<sup>28</sup> In the third and fourth column, the tables report regressions with the stock market liberalization index and equity flows as a percentage of GDP respectively replacing the capital account liberalization dummy. In the fifth and sixth columns, the shareholder rights index is introduced. In the sixth column, we include the growth opportunities measure. In the seventh and eight columns, we control for GDP instead of GDP per capita. We do not include GDP and GDP per capita in the same specification as these variables are highly correlated.<sup>29</sup> Note, however, that all our results

> 24 For defining this dummy we consider the World Bank regional classification, which includes Latin American and Caribbean countries. We also estimated all the regressions excluding the Caribbean countries and obtained similar results.

> 25 We also estimated the regressions constraining the sample to countries with at least three annual observations and without imposing any restrictions on the number of observations and obtained results similar to those reported in the paper in both cases.

> 26 See Appendix Table 1 for the list of countries covered.

> 27 We also estimated all the regressions using panel feasible generalized least squared (FGLS), allowing for heteroskedastic error structures and different autocorrelation coefficients within countries, and obtained similar results.

> 28 We choose this variable because inflation is not statistically significant in most regressions. We obtained results similar to those reported in the paper when controlling for both inflation and fiscal deficit.

> 29 The correlation between the logarithm of GDP per capita and the logarithm of GDP is 0.54 for our sample of countries and is significant at the one percent level.

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