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One of the key features of research on income inequality is the search for a Kuznets curve. Two curvilinear relationships in particular have been documented in the literature: one between inequality and income and the other between inequality and environmental factors. More recently, inequality and its link to trade liberalisation has received a good deal of attention, not least because it is among the major controversies provoked by the globalisation process. The outcomes for developing countries of greater openness do not fit neatly with the predictions of standard trade theory. Given this, it is natural to ask whether the relationship between trade openness and inequality may be better understood in terms of the Kuznets hypothesis. To this end, the study tests the Kuznets hypothesis in the context of trade liberalisation using data for Latin America. The evidence is new and is consistent with the Kuznets hypothesis: inequality increases with trade openness until a critical level of openness is reached after which inequality begins to fall. The curvilinear relationship between openness and inequality suggests that Latin American countries should continue with trade liberalisation measures but also introduce redistribution policies to ease the (initial) adverse consequences of liberalisation. [ABSTRACT FROM AUTHOR]

Most Latin American economies ended the twentieth century further behind the United States (in terms of productivity) than they had been in 1950. We investigate whether this reflects the effect of occasional economic setbacks or a systematic tendency to fall behind the United States. This is done using a time-series approach that allows for up to two structural breaks in a series. We find evidence that relative productivity is a (broken) trend-stationary process for most of the 18 countries considered but that only one, Chile, shows evidence of catching up with the United States at the century’s close. [ABSTRACT FROM AUTHOR]

The roles played by differences in study design and methodology in influencing the estimates of β-convergence have been hinted at in narrative reviews of the empirical convergence literature. While such reviews are useful, they only provide informal evidence as to the reasons for the study-to-study variation in reported convergence rates. In contrast, meta-regression analysis is a way of formally measuring the roles played by study design and methodology in influencing β-convergence. In cross-national studies, convergence rates are found to be higher when panel estimation methods are used, and when human capital development, investment rates and spatial factors are controlled for. The longer the time span covered by the estimation, the lower the rates. In intra-national studies, β-convergence is higher when the investment rate is included as a conditioning variable and when GMM estimation methods are used. Rates are found to be lower in studies of developing countries. [ABSTRACT FROM AUTHOR]