Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross Sections

Panel data are rarely available for developing countries. Departing from traditional pseudo-panel methods that require multiple rounds of cross-sectional data to study poverty mobility at the cohort level, we develop a procedure that works with as few as two survey rounds and produces point estimates of transitions along the welfare distribution at the more disaggregated household level. Validation using Monte Carlo simulations and real cross-sectional and actual panel survey data – from several countries, spanning different income levels and geographical regions – perform well under various deviations from model assumptions. The method could also inform investigation of other welfare outcome dynamics.