Behavior-Based Price Discrimination and Data Protection in the Age of Algorithms
39 Pages Posted: 31 Oct 2022 Last revised: 10 Jan 2023
Date Written: October 20, 2022
The legal literature on price discrimination focuses primarily on consumers’ immutable features, like when higher interest rates are offered to black borrowers and higher prices to women at car dealerships. This paper examines a different type of discriminatory pricing practice: behavior-based pricing (BBP), where prices are set based on consumers’ behavior, most prominently their prior purchasing decisions. The increased use of artificial intelligence and machine learning algorithms to set prices has facilitated the growing penetration of BBP in various markets. Unlike race-based and sex-based discrimination, with BBP, consumers can strategically adjust their behavior to impact the prices they will be offered in the future. Sellers, in turn, can adjust prices in early periods to influence consumers’ purchasing decisions so as to increase the informational value of these decisions and thereby maximize profits. This paper analyzes possible legal responses to BBP and arrives at two counterintutive policy implications: First, even if BBP is desirable, the economic literature teaches us that mandating its disclosure may reduce overall welfare even though this would reduce informational asymmetry in the market. Second, by expanding the model to consider the regulation of BBP using data protection laws, and specifically a right to be forgotten (erasure) and a right to opt-out of data collection (cookies), we find that these rules create informational effects that have eluded the literature on data protection and may be desirable as a response to BBP even though they increase informational asymmetry.
Keywords: Price Discrimination, Data Protection, Consumer Protection, Disclosure Mandates, Right to Be Forgotten, Law and Technology
JEL Classification: D42, K12
Suggested Citation: Suggested Citation