Optimal Nonlinear Pricing with Data-Sensitive Consumers
American Economic Journal: Microeconomics
vol. 15,
no. 2, May 2023
(pp. 80-108)
Abstract
We study monopolistic screening when some consumers are data sensitive and incur a privacy cost if their purchase reveals information to the monopolist. The monopolist discriminates between data-sensitive and classical consumers using privacy mechanisms that consist of a direct mechanism and a privacy option. A privacy mechanism is optimal for large privacy costs and leaves classical consumers better off than data-sensitive consumers with the same valuation. When privacy preferences become public information, data-sensitive consumers and the monopolist gain, whereas classical consumers lose. Our results are relevant for policies targeting consumers' data awareness, such as the European General Data Protection Regulation.Citation
Krähmer, Daniel, and Roland Strausz. 2023. "Optimal Nonlinear Pricing with Data-Sensitive Consumers." American Economic Journal: Microeconomics, 15 (2): 80-108. DOI: 10.1257/mic.20210190Additional Materials
JEL Classification
- D11 Consumer Economics: Theory
- D42 Market Structure, Pricing, and Design: Monopoly
- D82 Asymmetric and Private Information; Mechanism Design
- D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- L12 Monopoly; Monopolization Strategies
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