The pro-poorness, growth and inequality nexus: Some findings from a simulation study

A widely accepted criterion for pro-poorness of an income growth pattern is that it should reduce a (chosen) measure of poverty by more than if all incomes were growing equiproportionately. Inequality reduction is not generally seen as either necessary or sufficient for pro-poorness. As shown in Lambert (2010), in order to conduct nuanced investigation of the pro-poorness, growth and inequality nexus, one needs at least a 3-parameter model of the income distribution. In this paper, we explore in detail the properties of inequality reduction and pro-poorness, using the Watts poverty index and Gini inequality index, when income growth takes place within each of the following models: the displaced lognormal, Singh-Maddala and Dagum distributions. We show by simulation, using empirically relevant parameter estimates, that distributional change preserving the form of each of these income distributions is, in the main, either pro-poor and inequality reducing, or pro-rich and inequality exacerbating. Instances of pro-rich and inequality reducing change do occur, but we find no evidence that distributional change could be both pro-poor and inequality exacerbating.