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Do-it-yourself digital: the production boundary and the productivity puzzle

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  • Diane Coyle

Abstract

Part of the debate about the ‘productivity puzzle’ concerns the potential mismeasurement of digital activities. Specific measurement adjustments explored in previous research appear not to make a quantitatively large difference to real GDP or productivity growth estimates. However, although these potential adjustments may be small individually, taken together they could be wide in scope and quantitatively significant. This paper sets out a taxonomy of the range of potential measurement artefacts arising from digital innovations. It also specifically considers digitally-enabled substitutions in activity across the production boundary. I argue that these, along with other substitutions occurring within the production boundary, go beyond the effects of digital considered in earlier research; and may be making a meaningful contribution to the productivity puzzle as measured on existing statistical definitions.

Suggested Citation

  • Diane Coyle, 2017. "Do-it-yourself digital: the production boundary and the productivity puzzle," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2017-01, Economic Statistics Centre of Excellence (ESCoE).
    • Handle: RePEc:nsr:escoed:escoe-dp-2017-01
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    References listed on IDEAS

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    1. Greenstein, Shane & Nagle, Frank, 2014. "Digital dark matter and the economic contribution of Apache," Research Policy, Elsevier, vol. 43(4), pages 623-631.
    2. Josh Lerner & Jean Tirole, 2005. "The Economics of Technology Sharing: Open Source and Beyond," Journal of Economic Perspectives, American Economic Association, vol. 19(2), pages 99-120, Spring.
    3. Robert J. Gordon, 2016. "Perspectives on The Rise and Fall of American Growth," American Economic Review, American Economic Association, vol. 106(5), pages 72-76, May.
    4. Coyle, Diane, 2017. "Precarious and Productive Work in the Digital Economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 240, pages 5-14, May.
    5. David M. Byrne & John G. Fernald & Marshall B. Reinsdorf, 2016. "Does the United States Have a Productivity Slowdown or a Measurement Problem?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(1 (Spring), pages 109-182.
    6. Nadim Ahmad & Paul Schreyer, 2016. "Are GDP and Productivity Up to the Challenges of the Digital Economy?," International Productivity Monitor, Centre for the Study of Living Standards, vol. 30, pages 4-27, Spring.
    7. Chad Syverson, 2017. "Challenges to Mismeasurement Explanations for the US Productivity Slowdown," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 165-186, Spring.
    8. Coyle, Diane, 2017. "Precarious and Productive Work in the Digital Economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 240, pages 5-14, May.
    9. Diane Coyle, 2014. "GDP: A Brief but Affectionate History," Economics Books, Princeton University Press, edition 1, number 10183.
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    Cited by:

    1. Eric J. Bartelsman, 2019. "From New Technology to Productivity," European Economy - Discussion Papers 113, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    2. Richard Heys & Josh Martin & Walter Mkandawire, 2019. "GDP and Welfare: A spectrum of opportunity," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-16, Economic Statistics Centre of Excellence (ESCoE).
    3. Crafts, Nicholas & Mills, Terence C., 2020. "Is The Uk Productivity Slowdown Unprecedented?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 251, pages 47-53, February.

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    More about this item

    Keywords

    digital; production boundary; productivity;
    All these keywords.

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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