| Summary: | 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 or reduced by validating the imputation approaches and choosing the
imputation method based on an analysis of the ultimately desired measures.
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