Affiliation:
1. Russian Presidential Academy of National Economy and Public Administration
Abstract
Modern information technologies make it possible to aggregate and study a significant amount of data on the prices of online retailers. Online data has the advantages of high frequency and real-time monitoring. Based on daily granular micro data on prices since September 2020 to May 2023 (including), we test theoretical and empirical drivers of price stickiness using a logistic regression approach. The heterogeneity of the data leads us to conduct estimates on two sub-periods: before and after February 2022. In the first sub-period we found that the use of attractive prices by online retailers contributed to increased price rigidity, while the probability of price change was higher as the more productscompetitors adjusted prices. Price changes ranged from one to four weeks. In the second sub-period, the factors of market size and attractive prices became insignificant for the pricing of online retailers. Price changes continued to be periodic and dependent on the behavior of competitors but to a lesser extent than in 2020—2021.
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