A Non-Parametric Measure of Poverty Elasticity

Title: A Non-Parametric Measure of Poverty Elasticity
Format: Journal Article
Publication Date: 2011

We estimate the growth elasticity of poverty (GEP) using recently developed non-parametric panel methods and the most up-to-date and extensive poverty data from the World Bank, which exceeds 500 observations in size and represents more than 96 percent of the developing world’s population. Unlike previous studies which rely on parametric models, we employ a non-parametric approach which captures the non-linearity in the relationship between growth, inequality, and poverty. We find that the growth elasticity of poverty is higher for countries with fairly equal income distributions, and declines in nations with greater income disparities. Moreover, when controlling for differences in estimation technique, we find that the reported values of the GEP in the literature (based on the World Bank’s now-defunct 1993-PPP based poverty data) are systematically larger in magnitude than estimates based on the latest 2005-PPP based data.

External Contributors: Dustin Chambers

Chambers, Dustin and Shatakshee Dhongde. "A Non-Parametric Measure of Poverty Elasticity" Review of Income and Wealth 57.4 (2011): 683-703.

  • Development Economics
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  • School of Economics