A Comparison of Imputation Methods under Large Samples and Different Censoring Levels (PowerPoint)

Several imputation approaches using a large sample and different levels of censoring are compared and contrasted following a multiple imputation methodology. The study not only discusses these imputation approaches, but also quantifies differences in price variability before and after price imputation, evaluates the performance of each method, and estimates and compares parameters and elasticities from a complete demand system. The study’s findings reveal that small variability among the mean prices from the various imputation approaches may result in relatively larger variability among the underlying parameter estimates of interest and the ultimately desired measures. This suggests that selection bias may be avoided by validating the imputation approaches and choosing the imputation method based on an analysis of the ultimately desired measures.