Estimating Quality‐adjusted Price Changes: Method and Application to VCRs

This paper uses scanner data to generate estimates of quality‐adjusted price changes for video‐recorders. We use hedonic regressions to derive estimates of the changing worth of each quality component. These are then applied to weighted changes in the mix of quality attributes of products to derive estimates of quality‐adjusted price (QAP) changes. The data source used is electronic‐point‐of‐sale (EPOS) scanner data that are available for a wide range of goods. This study provides an example of how such methods can be more widely applied. The estimates of QAP changes correspond to constant‐utility, (hedonic) cost‐of‐living indexes defined in economic theory as the ratio of expenditure functions at constant utility allowing for changing prices and characteristics of goods. This method is proposed as an improvement on the existing direct method, which takes its estimates directly from the coefficients associated with ‘time dummies’ in a hedonic regression. We finally undertake a matching process, akin to that used by statistical offices, and compare the results. Direct comparisons with RPI estimates and these hedonic approaches are not easy since the approaches use quite different data sets. Our replication of a procedure akin to that used for the RPI on the scanner data set provides insights into sources of potential bias.