Hedonic Imputation versus Time Dummy Hedonic Indexes (with a commentary by Jan de Haan)

Statistical offices try to match item models when measuring inflation between two periods. However, for product areas with a high turnover of differentiated models, the use of hedonic indexes is more appropriate since they include the prices and quantities of unmatched new and old models. The two main approaches to hedonic indexes are hedonic imputation (HI) indexes and dummy time hedonic (HD) indexes. This study provides a formal analysis of the difference between the two approaches for alternative implementations of an index that uses weighting that is comparable to the weighting used by the Tornqvist superlative index in standard index number theory. This study shows exactly why the results may differ and discusses the issue of choice between these approaches. An illustrative study for desktop PCs is provided.