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Potential social value from data: an application of discrete choice analysis

Author

Listed:
  • Diane Coyle
  • Annabel Manley

Abstract

There is great interest in understanding the value of data. However, its non-rivalry and externalities imply that private markets and market prices (if they exist) will not reflect social value. What's more, the value of any given data depends on the uses to which it can be put. This paper applies a form of discrete choice analysis widely used in marketing to elicit users' preferences and the marginal value of data. Given the widely-acknowledged importance of data in the economy, public data sets are an important part of the national economic infrastructure, we selected a prominent open data set. The method delivers estimates that could be used by public bodies for purposes such as estimating the social return to the data they provide or setting prices for 'freemium' access in cases where they are required to recover some of their costs.

Suggested Citation

  • Diane Coyle & Annabel Manley, 2021. "Potential social value from data: an application of discrete choice analysis," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-17, Economic Statistics Centre of Excellence (ESCoE).
    • Handle: RePEc:nsr:escoed:escoe-dp-2021-17
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    References listed on IDEAS

    as
    1. Richard Carson & Nicholas Flores & Norman Meade, 2001. "Contingent Valuation: Controversies and Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 19(2), pages 173-210, June.
    2. Heather Rolfe & Johnny Runge & Sylaja Srinivasan, 2020. "The Value of Economic Statistics: Baseline Report," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-05, Economic Statistics Centre of Excellence (ESCoE).
    3. Hunt Allcott & Luca Braghieri & Sarah Eichmeyer & Matthew Gentzkow, 2020. "The Welfare Effects of Social Media," American Economic Review, American Economic Association, vol. 110(3), pages 629-676, March.
    4. Erik Brynjolfsson & Avinash Collis & W. Erwin Diewert & Felix Eggers & Kevin J. Fox, 2020. "Measuring the Impact of Free Goods on Real Household Consumption," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 25-30, May.
    5. Daniel Ker & Emanuele Mazzini, 2020. "Perspectives on the value of data and data flows," OECD Digital Economy Papers 299, OECD Publishing.
    6. Richard Carson & Nicholas Flores & Norman Meade, 2001. "Contingent Valuation: Controversies and Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 19(2), pages 173-210, June.
    7. Diane Coyle & David Nguyen, 2020. "Free goods and economic welfare," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-18, Economic Statistics Centre of Excellence (ESCoE).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    data; discrete choice; non-rival; social welfare;
    All these keywords.

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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