On the limitations of data-based price discrimination

Haitian Xie (), Ying Zhu () and Denis Shishkin ()
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Haitian Xie: Guanghua School of Management, Peking University
Ying Zhu: Department of Economics, University of California San Diego
Denis Shishkin: Department of Economics, University of California San Diego

Theoretical Economics, 2025, vol. 20, issue 1

Abstract: The classic third degree price discrimination (3PD) model requires the knowledge of the distribution of buyer valuations and the covariate to set the price conditioned on the covariate. In terms of generating revenue, the classic result shows that 3PD is at least as good as uniform pricing. What if the seller has to set a price based only on a sample of observations from the underlying distribution? Is it still obvious that the seller should engage in 3PD? This paper sheds light on these fundamental questions. In particular, the comparison of the revenue performance between 3PD and uniform pricing is ambiguous overall when prices are set based on samples. This finding is in the nature of statistical learning under uncertainty: a curse of dimensionality, but also other small sample complications.

Keywords: Price discrimination; empirical revenue maximization; information theory; prior-independent pricing; optimal rate of convergence (search for similar items in EconPapers)
JEL-codes: C14 C44 D42 D82 (search for similar items in EconPapers)
Date: 2025-01-28
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