IDEAS home Printed from https://ideas.repec.org/p/oec/ecoaaa/1723-en.html
   My bibliography  Save this paper

The value of data in digital-based business models: Measurement and economic policy implications

Author

Listed:
  • Carol Corrado
  • Jonathan Haskel
  • Massimiliano Iommi
  • Cecilia Jona-Lasinio

Abstract

A defining aspect of the digital age is data and its business use. Data have become an important input for firms (e.g., to train artificial intelligence algorithms) but data use is neither accounted for in macroeconomic statistics nor part of business contracts for goods and services provided to customers.This paper puts data and data investments in a framework amenable to measurement and policy analysis aimed at sharpening our understanding of the modern economies. Data is conceptualized as an intangible asset: a storable, nonrival (yet excludable) factor input that is only partially captured in existing macroeconomic and financial statistics. We provide experimental estimates of data investment designed to encompass data and data intelligence for six major European countries (France, Germany, Italy, Spain, and the United Kingdom) and we found an average value of 5 to 6.5 percent of market sector gross value added in 2010-2018 (Corrado et al, 2022). We also develop a simulation exercise to test the potential growth contribution of data capital, and we find that even limited diffusion of data capital could raise labor productivity growth as much as ½ percentage point per year, but outcomes are highly dependent on factors influenced by policy settings.

Suggested Citation

  • Carol Corrado & Jonathan Haskel & Massimiliano Iommi & Cecilia Jona-Lasinio, 2022. "The value of data in digital-based business models: Measurement and economic policy implications," OECD Economics Department Working Papers 1723, OECD Publishing.
    • Handle: RePEc:oec:ecoaaa:1723-en
    DOI: 10.1787/d960a10c-en
    as

    Download full text from publisher

    File URL: https://doi.org/10.1787/d960a10c-en
    Download Restriction: no
    File URL: https://libkey.io/10.1787/d960a10c-en?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Erdsiek, Daniel & Rost, Vincent, 2022. "Datenbewirtschaftung in deutschen Unternehmen: Umfrageergebnisse zu Status-quo und mittelfristigem Ausblick," ZEW Expert Briefs 22-09, ZEW - Leibniz Centre for European Economic Research.

    More about this item

    Keywords

    data; innovation; intangible capital; productivity growth;
    All these keywords.

    JEL classification:

    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oec:ecoaaa:1723-en. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/edoecfr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.