Chained, exact and superlative hedonic price changes: estimates from microdata

Abstract

Scanner data are used to calculate chained, exact (and superlative) hedonic price indexes for television sets. The data source is available for a wide range of goods, the application providing an example of how this method can be more widely applied. The indexes correspond to constant utility, hedonic cost-of-living indexes. The approach improves on the existing direct method, which takes its estimates directly from the coefficients on time dummies in a hedonic regression. It also improves on the matched model method used by statistical agencies. The differences between actual price changes and exact hedonic quality-adjusted price changes are found to be substantial. Base-period and current-period weighted exact hedonic indexes are similar, thus providing good approximations to a superlative index. Estimates from the direct, dummy variable approach were compared to the superlative indexes. The disparities between the results argue for caution in the use of the direct, dummy variable approach to estimating quality-adjusted price changes.