Optimal Nonlinear Pricing with Data-Sensitive Consumers

Daniel Krähmer and Roland Strausz

American Economic Journal: Microeconomics, 2023, vol. 15, issue 2, 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.

JEL-codes: D11 D42 D82 D83 L12 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Working Paper: Optimal Non-Linear Pricing with Data-Sensitive Consumers (2021)
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DOI: 10.1257/mic.20210190

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