اثر نوسانات درآمد بر توزیع درآمد: شواهدی از داده های سطح دولتی در ایالات متحده On the Effects of Income Volatility on Income Distribution: Asymmetric Evidence from State Level Data in the U.S.

I. Introduction The inverted-U hypothesis, introduced by Kuznets (1955), basically identifies the level of economic activity as the main determinant of income inequality. More precisely, it asserts that at the early stages of economic growth, income inequality worsens and it only improves at the later stages. Empirical support for the hypothesis is rather mixed, mostly rejecting the hypothesis.1 Another strand of the literature, however, argues that income or output volatility as a measure of uncertainty can worsen income inequality. Hausmann and Gavin (1997) is perhaps the first study that alludes us to the adverse effects of income volatility on income distribution by arguing that poorer members of society are not well equipped to absorb economic shocks or uncertainties relative to richer members. Using cross-sectional data from 56 countries in Latin America and industrial economies, they found that while neither GDP growth nor inflation had any significant effects on income inequality, the volatility of real GDP had significantly adverse effects on income inequality. The same is supported by Caroli and Garcia-Penalosa (2001), who looked at the effects of volatility of wages on wage differentials between low skilled and high skilled workers. Similar arguments are extended to the distribution of human capital rather than distribution of income by Checchi and Garcia-Penalosa (2004) who develop a theoretical model, showing that aggregate production risk determines the average level of education and its distribution. The higher the production risk, the higher the educational inequality. Other cross-sectional studies that support the adverse impact of output volatility on income distribution are Breen and Garcia-Penalosa (2005) and Laursen and Mahajan (2005). While the above studies have used cross-sectional data from different countries, two studies have used panel data across countries and over time. Calderon and Yeyati (2009) uses data from 75 countries over the 1970-2005 (5-year period observations) to show that even in a panel model, output volatility has adverse effects on income inequality measured by GINI coefficient. Their findings do not seem to be sensitive to different measures of volatility, nor to different measures of income inequality. They also assess asymmetric effects of output fluctuations by assigning dummy variables to output drops and output jumps to show that output volatility has asymmetric effects on income distribution.