Estimating Variances for a Scanner-based Consumer Price Index

This paper presents estimates of the sampling variance of price change for an experimental scannerbased Consumer Price Index for cereal for the New York Consolidated Metropolitan Statistical Area. Variances are presented for 1-, 2-, 6-, and 12-month price change lags, using a stratified jackknife methodology. In section one the official CPI and scanner-based geometric price index estimators are described. Section two presents the construction of jackknifed replicates and gives the sampling variance estimator for the scanner index series. Section three presents computational results and contrasts scanner variances with variance estimates for the published price index for cereal for the same area. Sources of price change variability are identified and discussed. Section four contrasts variance estimates in which missing prices are imputed independently for each jackknifed replicate with those in which this step is not taken. Conclusions are given in section five.