This paper investigates the distribution of well being among world citizens during the last two centuries. The estimates show that inequality of world distribution of income worsened from the beginning of the 19th century to World War II and after that seems to have stabilized or to have grown more slowly. In the early 19th century most inequality was due to differences within countries; later, it was due to differences between countries. Inequality in longevity, also increased during the 19th century, but then was reversed in the second half of the 20th century, perhaps mitigating the failure of income inequality to improve in the last decades.
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JEL Codes: D31, D63, J62Abstract: This paper proposes a method to decompose earnings inequality into a component due to unequal opportunities and a residual term. Drawing on the distinction between 'circumstance' and 'effort' variables in John Roemer's work on equality of opportunity, we associate inequality of opportunities with the inequality attributable to circumstances which lie beyond the control of the individual -such as her family background, her race and the region where she was born. We interpret the decomposition as establishing a lower bound on the contribution of opportunities to earnings inequality. We further decompose the effect of opportunities into a direct effect on earnings and an indirect component which works through the "effort" variables. The decomposition is applied to the distributions of male and female earnings in Brazil, in 1996. While the residual term is large, observed circumstances nevertheless account for around a quarter of the value of the Theil index. Parental education is by far the most important circumstance affecting earnings, dwarfing the effects of race and place of birth.
This survey presents the set of methods available in the literature on selection bias correction, when selection is specified as a multinomial logit model. It contrasts the underlying assumptions made by the different methods and shows results from a set of Monte Carlo experiments. We find that, in many cases, the approach initiated by Dubin and MacFadden (1984) as well as the semi-parametric alternative recently proposed by Dahl (2002) are to be preferred to the most commonly used Lee (1983) method. We also find that a restriction imposed in the original Dubin and MacFadden paper can be waived to achieve more robust estimators. Monte Carlo experiments also show that selection bias correction based on the multinomial logit model can provide fairly good correction for the outcome equation, even when the IIA hypothesis is violated.
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