Amparo Castelló-Climent, Universidad Carlos III de Madrid ... - Ivie

Table 2 provides the results of the cross-section and pool estimations where
no fixed effects are taking into account (equation (1)). In order to increase the
number of observations, the dependent variable in the cross-section regressions
(Columns (1)-(4)) is the average growth rate over the period 1975-2000. 10 The
explanatory variables include the naturally log of per capita income (lny), the
income Gini coefficient (Gini y ), the human capital Gini coefficient (Gini h ),
the average years of secondary schooling in the female population (Educf ), the
average years of secondary schooling in the male population (Educm) andthe
current price level of investment (pi). All the explanatory variables are measured
in 1975.
Column (1) shows the results obtained in the literature that analyses the
effectsofinequalityongrowthestimatingcross-section regressions. In line with
these studies, the coefficient of the income Gini index is negative and statistically
significant, suggesting a negative effect on growth from higher initial income inequality.
However, as pointed out by Castello and Domenech (2002), this result
is not robust to the inclusion of regional dummies. When we include dummies
for Latin America and the East Asian regions, as it is displayed in column (2),
the coefficient of the income Gini index stops being statistically significant. On
the contrary, even controlling for regional dummies the coefficient of the human
capital Gini index is negative and statistically significant at the standard levels
(column (3)). When both inequality indicators are included in the equation
neither the coefficient of the income Gini index nor the coefficient of the human
capital Gini index are statistically significant. This may be due to the fact that
we are including too many controls in a sample with very few countries.
We can increase the number of observation by extending the data in their
temporal dimension. Columns (5) to (7) show the results of the OLS pool regressions
for the whole period 1965-2000. These regressions also include time
dummies to diminish the possible incidence of business cycles in the estimated
coefficients. The results are quite similar to the ones obtained in the crosssection
regressions. On the one hand, the coefficient of the income Gini index
is negative but not statistically significant. On the other hand, the relationship
between human capital inequality and economic growth is negative with
acoefficient that is statistically significant in all cases. With regard to the
other controls, one surprising result could be that whereas male education has
a positive effect on the growth rate, the coefficient of the female education is
negative and statistically significant. The explanation given in the literature for
the negative coefficient is that lower levels of female education is an indication
of backwardness and, therefore, a greater potential growth through the convergenceprocess.
Thecoefficient of the investment price is negative, as expected,
and also statistically significant.
10 We choose 1975 as the starting period because it is the closest period to 1965 with a
greaternumberofobservations.
14