Abstract
AbstractThe incomes of top earners are typically top‐coded in survey data. I show that the accuracy of imputed income values for top earners in longitudinal surveys can be improved significantly by incorporating information from multiple time periods into the imputation process in a simple way. Moreover, I introduce an innovative, nonparametric empirical Bayes imputation method that further improves imputation quality. I show that the empirical Bayes imputation method reduces the RMSE of imputed income values by 19–51% relative to standard approaches in the literature. I also illustrate the benefits of the empirical Bayes method for investigating multi‐year income inequality.
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