IDEAS home Printed from https://ideas.repec.org/p/oec/ecoaaa/1709-en.html

A new macroeconomic measure of human capital exploiting PISA and PIAAC: Linking education policies to productivity

Author

Listed:
  • Balázs Égert
  • Christine de la Maisonneuve
  • David Turner

Abstract

This paper provides a new measure of human capital using PISA and PIAAC surveys, and mean years of schooling. The new measure is a cohort-weighted average of past PISA scores (representing the quality of education) of the working age population and the corresponding mean years of schooling (representing the quantity of education). In contrast to the existing literature, the relative weights of each component are not imposed or calibrated but directly estimated. The paper finds that the elasticity of the stock of human capital with respect to the quality of education is three to four times larger than for the quantity of education. The new measure has a strong link to productivity with the potential for productivity gains being much greater from improvements in the quality than quantity component of human capital. The magnitude of these potential gains in MFP is comparable to a similarly standardised improvement in product market regulation, but the effects materialise with much longer lags. The paper demonstrates through the example of pre-primary education, how to simulate the impact of a particular reform to education policy on human capital and productivity.

Suggested Citation

  • Balázs Égert & Christine de la Maisonneuve & David Turner, 2022. "A new macroeconomic measure of human capital exploiting PISA and PIAAC: Linking education policies to productivity," OECD Economics Department Working Papers 1709, OECD Publishing.
    • Handle: RePEc:oec:ecoaaa:1709-en
    DOI: 10.1787/a1046e2e-en
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

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


    Cited by:

    1. D’Andrea, Sara & D’Andrea, Silvia & Di Bartolomeo, Giovanni & D’Imperio, Paolo & Infantino, Giancarlo & Meacci, Mara, 2024. "The macroeconomic impact of structural reforms: The case of Italy," Journal of Policy Modeling, Elsevier, vol. 46(5), pages 946-963.
    2. Marites M. Cuyos, Mbm & John Michael P. Castino, Dm, Lpt, 2025. "Feasibility Study on the Offering of Bachelor of Science in Business Administration Major in Human Resource Management (BSBA-HRM) Program at Cronasia Foundation College, Inc," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(3s), pages 3736-3762, May.
    3. Wang, Jiabin & Qiao, Li & Zhu, Guofen & Di, Kaisheng & Zhang, Xihui, 2025. "Research on the driving factors and impact mechanisms of green new quality productive forces in high-tech retail enterprises under China's Dual Carbon Goals," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
    4. Balázs Égert & Christine de la Maisonneuve, 2024. "The impact of the war on human capital and productivity in Ukraine," Policy Studies, Taylor & Francis Journals, vol. 45(3-4), pages 282-292, May.
    5. Izabela Sobiech Pellegrini & Rafał Chmura & Jakub Sawulski & Tymoteusz Mętrak, 2025. "Can the improvements in human capital quality mitigate the negative impact of ageing on growth? Evidence from selected EU countries," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 33(2), pages 253-274, April.
    6. Ángel de la Fuente & Rafael Doménech, 2024. "Cross‐country data on skills and the quality of schooling: A selective survey," Journal of Economic Surveys, Wiley Blackwell, vol. 38(1), pages 3-26, February.
    7. Pfeiffer, Philipp & Varga, Janos & in 't Veld, Jan, 2024. "Unleashing potential: Model-based reform benchmarking for EU Member States," European Journal of Political Economy, Elsevier, vol. 83(C).
    8. Bughin, Jacques, 2025. "Corporate AI play and short term skill-biased AI change," Technology in Society, Elsevier, vol. 82(C).
    9. Christine de la Maisonneuve & Balázs Égert & David Turner, 2023. "Quantifying the Macroeconomic Impact of COVID-19-Related School Closures through the Human Capital Channel," Economies, MDPI, vol. 11(12), pages 1-14, November.
    10. Raphaël Martin & Thomas Renault & Baptiste Roux, 2022. "Baisse de la productivité en France : échec en « maths » ?," Post-Print hal-04084079, HAL.
    11. Jarmila Botev & Balazs Egert & David Turner, 2022. "The Effect of Structural Reforms: Do They Differ between GDP and Adjusted Household Disposable Income?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 14(12), pages 1-55, December.
    12. DI PIETRO Giorgio & KARPINSKI Zbigniew, 2024. "Teaching mathematics for success: A data-driven review and analysis of best practices," JRC Research Reports JRC140539, Joint Research Centre.
    13. Arpaia Alfonso, 2025. "How Skills Can Drive Competitiveness," Intereconomics: Review of European Economic Policy, Sciendo, vol. 60(1), pages 18-27.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • I20 - Health, Education, and Welfare - - Education - - - General
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

    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:1709-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.