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Buying Data from Consumers: The Impact of Monitoring Programs in U.S. Auto Insurance

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  • Yizhou Jin
  • Shoshana Vasserman

Abstract

New technologies have enabled firms to elicit granular behavioral data from consumers in exchange for lower prices and better experiences. This data can mitigate asymmetric information and moral hazard, but it may also increase firms’ market power if kept proprietary. We study a voluntary monitoring program by a major U.S. auto insurer, in which drivers accept short-term tracking in exchange for potential discounts on future premiums. Using a proprietary dataset matched with competitor price menus, we document that safer drivers self-select into monitoring, and those who opt in become yet 30% safer while monitored. Using an equilibrium model of consumer choice and firm pricing for insurance and monitoring, we find that the monitoring program generates large profit and welfare gains. However, large demand frictions hurt monitoring adoption, forcing the firm to offer large discounts to induce opt-in while preventing the unmonitored pool from unraveling given the competitive environment. A counterfactual policy requiring the firm to make monitoring data public would thus further reduce the firm’s incentive to elicit monitoring data, leading to less monitoring and lower consumer welfare in equilibrium.

Suggested Citation

  • Yizhou Jin & Shoshana Vasserman, 2021. "Buying Data from Consumers: The Impact of Monitoring Programs in U.S. Auto Insurance," NBER Working Papers 29096, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29096
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    Cited by:

    1. Martin Eling & Irina Gemmo & Danjela Guxha & Hato Schmeiser, 2024. "Big data, risk classification, and privacy in insurance markets," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 49(1), pages 75-126, March.
    2. Tesary Lin, 2022. "Valuing Intrinsic and Instrumental Preferences for Privacy," Marketing Science, INFORMS, vol. 41(4), pages 663-681, July.
    3. Siqi Liu & Bhoomija Ranjan & Benjamin Reed Shiller, 2020. "Are Coarse Ratings Fine? Applications to Crashworthiness Ratings," Working Papers 132, Brandeis University, Department of Economics and International Business School.

    More about this item

    JEL classification:

    • L0 - Industrial Organization - - General

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