SCANNER DATA, PRICE INDICES AND THE CPI CHAIN DRIFT BIAS

Scanner data mean transaction data that specify product prices and their expenditures obtained from supermarkets' IT systems by scanning bar codes (i.e. GTIN or SKU). Scanner data are a relatively new and cheap data source for the calculation of the Consumer Price Index (CPI) and the main advantage of using scanner data is the fact that they provide full information about products even on the lowest data aggregation level. One of main challenges while using scanner data is the choice of the appropriate price index formula. The list of potential price indices, which could be used in the scanner data case, is quite wide, i.e. bilateral and multilateral indices are used in practice. For instance, some countries use the chain Jevons price index formula while some other countries prefer the multilateral GEKS index or the Geary-Khamis method. One of the most important criterions in selecting index formula for scanner data case is the potential reduction of the chain drift bias. The chain drift occurs if the index differs from unity when prices revert back to their base level. In the paper we present some simulation results which show the situations on the market leading to the serious chain drift bias.