Recovering income distributions from aggregated data via micro-simulations
2019
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.
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