REVEALING THE PECULIARITIES OF PRICING USING DATA ON ONLINE RETAILERS IN MOSCOW

Abstract

In this study, using online data on prices of retailers in Moscow, we analyzed the correspondence of price behavior to certain pricing models. The present study complements previous estimates of price rigidity in the context of identifying empirical signs of certain pricing models based on Russian data. The empirical analysis is based on data about Moscow online retailers collected on a daily basis from February 2019 to June 2020. The data cover 33 food categories, 54 non-food categories and seven service categories. The work obtained the following empirical results, which, with some degree of convention, may be inherent in the Russian economy as a whole. The work did not reveal an explicit dependence of the size of the price change on the duration of the period of price unchanged. The Golosov-Lucas model turned out to be the closest in terms of coincidence of stylized factors for Moscow online retailers in the studied time period, but no complete coincidence was found. Pricing behavior of Russian retailers refers to hybrid pricing models which include pricing elements that depend both on the state of the economy and on time. Decomposition of inflation into intensive (average size of price changes) and extensive (the share of goods whose prices have changed in a given period) components indicates a significant contribution of the intensive component to the price dynamics based on Russian data. A similar result is typical for inflation dispersion in which the contribution of the intensive component to the dispersion decomposition turns out to be the highest. The results obtained are not fully stable in relation to the period under consideration and can be adjusted as the sample expands.