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...

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...

Vietnam is widely regarded as a success story for its impressive economic growth and poverty reduction in the last few decades. Yet, recent evidence indicates that the country's economic growth has not been uniform. Compiling and analyzing new extensive province-level data from the Vietnam...