inform policy by complementing the analysis of standard macro-level measures of inequality and poverty with a household …-level analysis of subjective perceptions of poverty. We find that many more people appear to feel poor than are classified as such …

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 …

Regressions in a number of recent papers written by staff members of the World Bank and the IMF rely on an interaction … variable (IAV) to establish the effects of foreign aid on economic growth or the reduction of poverty. The common assumption in …

Using micro-data from household expenditure surveys, we document the evolution of consumption poverty in the United … poverty has not declined materially since the 1980s and even increased for the young. We then analyze which social and … economic factors help explain the extent of poverty in the U.S. using probit, tobit, and machine learning techniques. Our …

, which be associated with an increase in poverty of about 75 million people. Policy responses more effective than those in …

satellite-recorded nighttime lights as an additional measurement of true GDP per capita, we provide a statistical framework, in … results for measurement error models to identify and estimate the nonlinear relationship between nighttime lights and true GDP …