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Using Web Data to Measure the Demand for Skills

Author

Listed:
  • Kea Tijdens
  • Brian Fabo

Abstract

In the post-Fordist economy, a skilled workforce is crucial for maintaining competitiveness in the global economy. Nevertheless, how to measure the demand for skills remains a puzzle. The main issue discussed in this paper is how can online based surveys serve researchers and policy makers as a tool for determining the demand for skills on the labour market. The paper begins by an overview of the literature to make a case for the importance of measuring skills for the public policy. Following the introductory part, different approaches to measuring demand for skills are evaluated. Special attention is paid to the role of the Internet as a source of the relevant data. Measurement of frequency in which various tasks are being performed is proposed as an indicator for measuring skills associated with the specific occupation. The paper closes by a demonstration of the practical implementation of the questions measuring frequency of performance of different tasks in more than 400 occupations in the environment of the global WageIndicator survey.

Suggested Citation

  • Kea Tijdens & Brian Fabo, 2014. "Using Web Data to Measure the Demand for Skills," Discussion Papers 21, Central European Labour Studies Institute (CELSI).
    • Handle: RePEc:cel:dpaper:21
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    File URL: https://celsi.sk/media/discussion_papers/DP21.pdf
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    References listed on IDEAS

    as
    1. Peter Elias, 1997. "Occupational Classification (ISCO-88): Concepts, Methods, Reliability, Validity and Cross-National Comparability," OECD Labour Market and Social Policy Occasional Papers 20, OECD Publishing.
    2. Gary S. Becker, 1975. "Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education, Second Edition," NBER Books, National Bureau of Economic Research, Inc, number beck75-1, January.
    3. Theodore W. Schultz, 1960. "Capital Formation by Education," Journal of Political Economy, University of Chicago Press, vol. 68(6), pages 571-571.
    4. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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    Cited by:

    1. Mamertino, Mariano & Sinclair, Tara M., 2019. "Migration and online job search: A gravity model approach," Economics Letters, Elsevier, vol. 181(C), pages 51-53.
    2. Beblavý, Miroslav & Fabo, Brian & Lenaerts, Karolien, 2016. "Demand for Digital Skills in the US Labour Market: The IT Skills Pyramid," CEPS Papers 12055, Centre for European Policy Studies.
    3. Tara Sinclair & Mariano Mamertino, 2016. "Online Job Search and Migration Intentions Across EU Member States," Working Papers 2016-5, The George Washington University, Institute for International Economic Policy.
    4. repec:aia:aiaswp:wp161 is not listed on IDEAS
    5. Stefano Visintin & Kea Tijdens & Maarten van Klaveren, 2015. "Skill mismatch among migrant workers: evidence from a large multi-country dataset," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-34, December.
    6. Brian Fabo & Martin Kahanec, 2020. "The Role of Computer Skills on the Occupation Level," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 6(2), pages 87-99.
    7. Kureková, Lucia Mýtna & Beblavy, Miroslav & Thum, Anna-Elisabeth, 2014. "Using Internet Data to Analyse the Labour Market: A Methodological Enquiry," IZA Discussion Papers 8555, IZA Network @ LISER.

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    Keywords

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    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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