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Text analysis of job offers for mismatch of educational characteristics to labour market demands

Author

Listed:
  • Maciej Beręsewicz

    (University of Economics and Business
    Statistical Office in Poznań)

  • Herman Cherniaiev

    (University of Information Technology and Management in Rzeszów)

  • Andrzej Mantaj

    (University of Information Technology and Management in Rzeszów)

  • Robert Pater

    (University of Information Technology and Management in Rzeszów
    Educational Research Institute)

Abstract

Nowadays, the traditional ways of job seeking have become less popular than digital methods. Recruitment websites are more attractive to job seekers since they provide easy, convenient access to a greater number of job vacancies. The biggest disadvantage, however, is that job vacancies published online are often unstructured and confusing. Studies related to online job vacancies are usually restricted to a short duration and a small number of recruitment websites. Such studies frequently use proxies for skills and occupations, or aggregate them into wider groups. The aim of our research is to provide full educational characteristics of job vacancies in Poland and calculate a complete list of educational mismatches. We introduce an approach that includes stages of source selection; data collection; and extraction of occupations, qualifications, and skills. We describe difficulties with data scraping and ways to overcome them. Thanks to our large dataset, we are able to determine and describe the labour demand. We also show the results of a survey that estimates educational traits of the labour supply. To measure mismatch between education and labour supply and demand, we use structural compliance indices. The paper also offers a case study for chosen occupational groups. Our findings reveal the greatest mismatch is in education and job-related skills, with the least mismatch occurring between geographic regions.

Suggested Citation

  • Maciej Beręsewicz & Herman Cherniaiev & Andrzej Mantaj & Robert Pater, 2024. "Text analysis of job offers for mismatch of educational characteristics to labour market demands," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(2), pages 1799-1825, April.
    • Handle: RePEc:spr:qualqt:v:58:y:2024:i:2:d:10.1007_s11135-023-01707-7
    DOI: 10.1007/s11135-023-01707-7
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    References listed on IDEAS

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    1. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    2. Pietro Giorgio Lovaglio & Mario Mezzanzanica & Emilio Colombo, 2020. "Comparing time series characteristics of official and web job vacancy data," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 85-98, February.
    3. Brad Hershbein & Lisa B. Kahn, 2018. "Do Recessions Accelerate Routine-Biased Technological Change? Evidence from Vacancy Postings," American Economic Review, American Economic Association, vol. 108(7), pages 1737-1772, July.
    4. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2020. "AI and Jobs: Evidence from Online Vacancies," Working Papers 279, Princeton University, Department of Economics, Center for Economic Policy Studies..
    5. Ioana Marinescu & Ronald Wolthoff, 2020. "Opening the Black Box of the Matching Function: The Power of Words," Journal of Labor Economics, University of Chicago Press, vol. 38(2), pages 535-568.
    6. Marianna Kudlyak & Murat Tasci & Didem Tuzemen, 2019. "Minimum Wage Increases and Vacancies," Working Papers 19-30R, Federal Reserve Bank of Cleveland, revised 21 Apr 2022.
    7. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.
    8. David J Deming & Kadeem Noray, 2020. "Earnings Dynamics, Changing Job Skills, and STEM Careers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(4), pages 1965-2005.
    9. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2020. "AI and Jobs: Evidence from Online Vacancies," Working Papers 279, Princeton University, Department of Economics, Center for Economic Policy Studies..
    10. Forsythe, Eliza & Kahn, Lisa B. & Lange, Fabian & Wiczer, David, 2020. "Labor demand in the time of COVID-19: Evidence from vacancy postings and UI claims," Journal of Public Economics, Elsevier, vol. 189(C).
    11. David Deming & Lisa B. Kahn, 2018. "Skill Requirements across Firms and Labor Markets: Evidence from Job Postings for Professionals," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 337-369.
    12. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    13. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
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