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Too Much Data: Prices and Inefficiencies in Data Markets

Author

Listed:
  • Daron Acemoglu
  • Ali Makhdoumi
  • Azarakhsh Malekian
  • Asuman Ozdaglar

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.

Suggested Citation

  • Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asuman Ozdaglar, 2019. "Too Much Data: Prices and Inefficiencies in Data Markets," NBER Working Papers 26296, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:26296
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    Cited by:

    1. Dirk Bergemann & Alessandro Bonatti & Tan Gan, 2019. "The Economics of Social Data," Cowles Foundation Discussion Papers 2203, Cowles Foundation for Research in Economics, Yale University.

    More about this item

    JEL classification:

    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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