Working Paper: NBER ID: w20819
Authors: Yuriy Gorodnichenko; Viacheslav Sheremirov; Oleksandr Talavera
Abstract: Using a unique dataset of daily U.S. and U.K. price listings and the associated number of clicks for precisely defined goods from a major shopping platform, we shed new light on how prices are set in online markets, which have a number of special properties such as low search costs, low costs of monitoring competitors' prices, and low costs of nominal price adjustment. We document that although online prices are more flexible than offline prices, they continue to exhibit relatively long spells of fixed prices, large size and low synchronization of price changes, considerable cross-sectional dispersion, and low sensitivity to predictable or unanticipated changes in demand conditions. Qualitatively these patterns are similar to those observed for offline prices, which calls for more research on the sources of price rigidities and dispersion.
Keywords: Price Setting; Online Markets; E-commerce; Price Rigidity; Price Dispersion
JEL Codes: E3
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| online prices with a high number of clicks (D49) | more flexible than those in conventional stores (L81) |
| frequency of price changes (E30) | higher in more competitive markets (L13) |
| higher competition (L13) | smaller price adjustments (D49) |
| low synchronization of price changes across sellers (D43) | prices are adjusted independently (P22) |
| online prices (P22) | do not significantly respond to predictable changes in demand (C69) |