A Comparison of Price Imputation Methods under Large Samples and Different Levels of Censoring
Jose Antonio Lopez
Abstract
Open-access reader
Jose Antonio Lopez
Abstract
Open-access reader
Several imputation approaches under a large sample and different levels of censoring are compared and contrasted by using a multiple imputation methodology. The study not only discusses 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 from a complete demand system. The study’s findings reveal that even when there is small variability among different price imputation approaches, there may be large variability among the underlying parameter estimates of interest and the ultimately desired measures. This suggests that a multiple imputation approach may be preferred over a comparison of mean prices among various imputation approaches.
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Several imputation approaches under a large sample and different levels of censoring are compared and contrasted by using a multiple imputation methodology. The study not only discusses 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 from a complete demand system. The study’s findings reveal that even when there is small variability among different price imputation approaches, there may be large variability among the underlying parameter estimates of interest and the ultimately desired measures. This suggests that a multiple imputation approach may be preferred over a comparison of mean prices among various imputation approaches.
Key concepts: Imputation (statistics), Censoring (clinical trials), Econometrics, Statistics, Computer science, Missing data, Mathematics