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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.

This study is the first to measure the impact of federal regulations on consumer prices. By combining consumer expenditure and pricing data from the Bureau of Labor Statistics, industry supply-chain data from the Bureau of Economic Analysis, and industry-specific regulation information from the Mercatus CenterÕs RegData database, we determine that regulations promote higher consumer prices, and that these price increases have a disproportionately negative effect on low-income households. Specifically, we find that the poorest households spend larger proportions of their incomes on heavily regulated goods and services prone to sharp price increases. While the literature explores other specific costs of regulation, noting that higher consumer prices are a probable consequence of heavy regulation, this study is the first to provide a thorough empirical analysis of that relationship across industries. Irrespective of the reasons for imposing new regulations, these results demonstrate that in the aggregate, the negative consequences are significant, especially for the most vulnerable households.