The Product Life Cycle and Sample Representativity Bias in Price Indexes

Official price indexes are usually calculated using matched samples of products. If products exhibit systematic price trends at different points in their life cycle then matched sample methods may introduce bias if the life cycle movement in the sample does not adequately reflect that in the population. This article explores the extent of these life cycle pricing effects and then examines the bias it can introduce in measured inflation. A large US supermarket scanner data set for 6 cities and 6 products over 12 years is used. Using hedonic methods we find that the life cycle component of price change is important across a range of products and cities. To explore the bias introduced by these movements we use simulations which construct indexes with different sample update frequency. For indexes which are never completely re-sampled we find an annual bias of 0.88 and 0.59 percentage points depending upon whether we use the actual prices or prices imputed from our hedonic model. This compares with absolute biases of 0.24 and 0.08 percentage points for the corresponding cases for samples which are re-selected annually. Thus our results provide strong support for more frequently updating index samples