Evaluation of Alternative Income Imputation Methods for a Longitudinal Survey

Abstract

This article evaluates various methods for imputing income in a household-based longitudinal survey. Eight longitudinal methods are evaluated in a simulation study using five waves of data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The quality of the imputed data is evaluated by considering eleven criteria that measure the predictive, distributional and estimation accuracy of the cross-sectional estimates and the estimates of change between waves. Many of the imputation methods perform well cross-sectionally, but when the methods are placed in a longitudinal context their strengths and weaknesses are more apparent. The method that combines the Little and Su method with the population carryover method performs the best overall.