Dynamic Competition in the Era of Big Data

by Patrick J. Kehoe, Brad Larsen, Elena Pastorino
Monday, February 14, 2022

Economics Working Paper 22102

Abstract: The advent of rich and highly–detailed information on individual web–browsing and purchase histories— an instance of so–called Big Data—has begun to make feasible sophisticated forms of personalized pricing, heretofore considered too informationally demanding to implement. We argue these pricing strategies are especially relevant in markets for differentiated experience goods. Taking the view that this ability to price discriminate both intertemporally and interpersonally will become increasingly relevant in the future, here we investigate its implications on the dynamics of prices and on efficiency in such markets. In particular, we derive a simple characterization of the equilibrium pricing rule that shows how prices contain a variety– specific dynamic component that depends on the relative informativeness of competing varieties about consumers’ tastes. Over time, this pricing rule leads to discontinuous price changes that take the form of fluctuating price discounts for a given consumer. We provide evidence on the gains associated with these sophisticated forms of price discrimination using data on individual consumers’ purchases of Apple and Samsung products over time. We estimate primitives in the setting in which firms use the uniform pricing rule we observe in the data and then simulate the counterfactual world with first-degree price discrimination. We find that a significant fraction of consumers are better off under price discrimination relative to uniform pricing, as price discrimination intensifies competition for each individual consumer. Consumers worse off under price discrimination are those who are a good match for only Apple or Samsung. Firm profits from these consumers are correspondingly higher under price discrimination.

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