Recovering income distributions from aggregated data via micro-simulations

Abstract

For the studies of wealth, inequality and poverty, the analysis of income distribution of the individuals is a crucial issue. In practice, however, only aggregated data are available, either in groups or as a few quantiles of the distribution. To perform counterfactual exercises, it is desirable to generate samples of micro income data corresponding to the same population structure. This method serves also for the imputation of income densities corresponding to the observed grouped data. This work introduces a method of density estimation from grouped data. Small sample properties and two empirical examples are delivered.