Too Much Data: Prices and Inefficiencies in Data Markets

Daron Acemoglu, Ali Makhdoumi, Azarakhsh Malekian and Asuman Ozdaglar

No 26296, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: When a user shares her data with an online platform, she typically reveals relevant information about other users. We model a data market in the presence of this type of externality in a setup where one or multiple platforms estimate a user’s type with data they acquire from all users and (some) users value their privacy. We demonstrate that the data externalities depress the price of data because once a user’s information is leaked by others, she has less reason to protect her data and privacy. These depressed prices lead to excessive data sharing. We characterize conditions under which shutting down data markets improves (utilitarian) welfare. Competition between platforms does not redress the problem of excessively low price for data and too much data sharing, and may further reduce welfare. We propose a scheme based on mediated data-sharing that improves efficiency.

JEL-codes: D62 D83 L86 (search for similar items in EconPapers)
Date: 2019-09
New Economics Papers: this item is included in nep-big, nep-com, nep-ict, nep-mic and nep-pay
Note: EFG IO LE PE
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (45)

Published as Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asu Ozdaglar, 2022. "Too Much Data: Prices and Inefficiencies in Data Markets," American Economic Journal: Microeconomics, vol 14(4), pages 218-256.

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Journal Article: Too Much Data: Prices and Inefficiencies in Data Markets (2022)
Working Paper: Too Much Data: Prices and Inefficiencies in Data Markets (2019)
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