Abstract

For many analyses concerning wages, such as the gender wage gap we have to solve the problem of censored wages at the upper limit of the social security system. We treat this problem as a missing data problem. We regard the missingness mechanism as not missing at random (NMAR, according to Little an Rubin, 1987, 2002) as well as missing by design. The censored wages are multiply imputed by draws of a random variable from a truncated distribution. The multiple imputation is based on Markov chain Monte Carlo (MCMC) technique, and a new algorithm is derived.