conflicting results for its existence. While many studies offer support for the empirical existence of a Kuznets curve, such as Barro ( 2000 , 2008 ), and Acemoglu and Robinson (2002) , others have shown that controlling for country-specific effects can lead to the rejection of the hypothesis ( Deininger and Squire, 1998 ; Higgins and Williamson, 1999 ; Savvides and Stengos, 2000 ). 11 However, most of these latter studies have been criticized for the inconsistent income inequalitydataused.
In this Section, we take a fresh look at this controversial issue. For the
Income inequality in Latin America has declined during the last decade, in contrast to the experience in many other emerging and developed regions. However, Latin America remains the most unequal region in the world. This study documents the declining trend in income inequality in Latin America and proposes various reasons behind this important development. Using a panel econometric analysis for a large group of emerging and developing countries, we find that the Kuznets curve holds. Notwithstanding the limitations in the dataset and of cross-country regression analysis more generally, our results suggest that almost two-thirds of the recent decline in income inequality in Latin America is explained by policies and strong GDP growth, with policies alone explaining more than half of this total decline. Higher education spending is the most important driver, followed by stronger foreign direct investment and higher tax revenues. Results suggest that policies and to some extent positive growth dynamics could play an important role in lowering inequality further.
The paper examines empirically the question of whether more unequal societies spend more on income redistribution than their more egalitarian counterparts. Theoretical arguments on this issue are inconclusive. The political economy literature suggests that redistributive spending is higher in unequal societies due to median voter preferences. Alternatively, it can be argued that unequal societies may spend less on redistribution because of capital market imperfections. Based on different data sources, the cross-country evidence reported in this paper suggests that more unequal societies do spend less on redistribution.
Milanovic (2000) .
5 Notwithstanding the improvement in the quality of data on income distribution, researchers have also recently criticized the data complied by Deininger and Squire (1996) . See also Panizza (1999) .
6 The inequalitydataused in the empirical section below, based on the distribution of income/expenditures by quintiles, do not allow for testing the “soak-the-rich” hypothesis put forward by Bassett, Burkett, and Putterman (1999) or to measure inequality based on the relative position of the median and decisive voters in the income
This paper draws on existing empirical literature and an original theoretical model to argue that globalization and skill supply affect the extent to which technology adoption in developing countries favors skilled workers. Developing countries are experiencing technical change that is skill-biased because skill-biased technologies are becoming relatively cheaper. Increased skill supply further biases technical change in favor of skilled labor. Free trade induces technology that favors skilled workers in skill-abundant developing countries and that favors unskilled workers in skill-scarce developing countries, and therefore amplifies the predicted wage effects of trade liberalization. These features aid our understanding of the observed rises in inequality within developing countries and the absence of a significant downward effect of expanded educational attainment on skill premia. They also help account for the large and differential effects of trade liberalization on inequality. These findings are pertinent for the Middle East and North Africa because of its recent increase in trade openness and remarkable rise in educational attainment.
education and technology ( Tinbergen, 1975 ), recipients of expanded education may be able to adapt to SBTC, but this may not reduce inequality and would not help those who remain unskilled.
Data and Methodological Description
The inequalitydataused in three of the linear projections in Table 1 is the EHII, which is an index from 0–100 of household income inequality from 1963 to 2003. More information on the data, which is also used in Table 2 and is constructed by the University of Texas Inequality Project (UTIP), is available at http