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 …

techniques, in particular kernel density estimation, in estimating poverty from grouped data. Using Monte Carlo simulations, we … show that kernel density estimation gives rise to nontrivial biases in estimated poverty levels that depend on the … bandwidth, kernel, poverty indicator, size of the dataset, and data generating process. Furthermore, the empirical bias in the …

Kernel density estimation (KDE) has been prominently used to measure poverty from grouped data (Sala-i-Martin, 2006 … distributions and unit data from several household surveys, we compare KDE-based poverty estimates with their true and survey … counterparts. We find that the technique gives rise to biases in poverty estimates the sign and magnitude of which vary with the …

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 …

inequality and poverty. The first kind of social planner, SPε , comprises averters to income inequality as measured by the … versa. The inequality-entangled SPv and SPε evaluate inequality, social welfare and poverty consistently. This paper offers … social welfare, inequality and poverty for 27 European Union member countries in 2021. …