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 six cities and six 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 that construct indexes with different sample update frequency. For indexes that are never completely resampled, we find an annual absolute 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 0.34 and 0.10 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.     

The age-dependent value of time: a life cycle analysis

A life cycle framework is developed to examine how the value of time (VOT) changes as one ages. We consider two risk-sharing schemes, the Tonti scheme under which wealth is actuarially insured, and the Robinson Crusoe scheme under which insurance institution is entirely absent. For the first time in the literature, we characterize the condition, in terms of key parameters for valuating VOT, under which VOT may increase, decline, or even display more complicated profiles, as one ages. Our analysis reveals the crucial role played by the relative magnitude of the market interest rate to other parameters (including the parameter of time preference, the age-specific mortality and the wage growth rate) in determining the age profile of VOT, and the difference in VOT that is caused by the insurance scheme.