We analyze the performance of kernel density methods applied to grouped data to estimate poverty (as applied in Sala …-i-Martin, 2006, QJE). Using Monte Carlo simulations and household surveys, we find that the technique gives rise to biases in poverty … estimates, the sign and magnitude of which vary with the bandwidth, the kernel, the number of datapoints, and across poverty …

Current estimates of global poverty vary substantially across studies. In this paper we undertake a novel sensitivity … analysis to highlight the importance of methodological choices in estimating global poverty. We measure global poverty using … different data sources, parametric and nonparametric estimation methods, and multiple poverty lines. Our results indicate that …