IDEAS home Printed from https://ideas.repec.org/a/ers/journl/vxxivy2021ispecial1p787-809.html
   My bibliography  Save this article

The Gender Polarization of Education and Employment in the European Union Countries (in 2005-2019): Practical Implications

Author

Listed:
  • Malgorzata Michalcewicz-Kaniowska
  • Bartosz Mickiewicz
  • Anna Murawska
  • Monika Odlanicka-Poczobutt
  • Małgorzata Zajdel

Abstract

Purpose: The main purpose of this article is to define the level of education of the European Union citizens and to determine the gaps in this scope between men and women. Design/Approach/Methodology: The analyzed indicators are percentage of the population with tertiary education (X1), percentage of early school leavers (X2), the participation rate in pre-school education (X3), and adult participation in learning (X4). What was also analyzed were such indicators as the percentage of employed graduates (Y1) and general employment level (Y2). The source of empirical data was the information collected by the European Statistical Office (Eurostat) about 28 member states of in the years 2005-2019. Findings: In recent years, the EU's education (28) member states citizens have been growing steadily. However, according to ISCED, more women than men improve their knowledge and gain an education at the education level of 5-8, and the gap in this scope is getting wider, to the detriment of men. This diversification can be observed particularly in such countries as Estonia, Lithuania, and Latvia. Practical Implications: In recent years, one could observe that the EU member states that recent graduates' employment rate remained stable at a high level and that the total employment rate increased steadily. This applies both to men and women. Originality/Value: For women, education and qualifications raising on the labor market should be important as the research indicated significant correlations between the indicators that characterize the differences in the level of education of women in the EU (28) countries and the differences in their employment, which was not observed in case of men.

Suggested Citation

  • Malgorzata Michalcewicz-Kaniowska & Bartosz Mickiewicz & Anna Murawska & Monika Odlanicka-Poczobutt & Małgorzata Zajdel, 2021. "The Gender Polarization of Education and Employment in the European Union Countries (in 2005-2019): Practical Implications," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 787-809.
  • Handle: RePEc:ers:journl:v:xxiv:y:2021:i:special1:p:787-809
    as

    Download full text from publisher

    File URL: https://ersj.eu/journal/2074/download
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Maarten Goos & Alan Manning & Anna Salomons, 2009. "Job Polarization in Europe," American Economic Review, American Economic Association, vol. 99(2), pages 58-63, May.
    2. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    3. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
    4. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    5. Grossman, Michael, 2000. "The human capital model," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 7, pages 347-408, Elsevier.
    6. Anna Murawska, 2017. "Influence of population’s education level on the employment and unemployment rates in the European Union countries," Ekonomia i Prawo, Uniwersytet Mikolaja Kopernika, vol. 16(2), pages 171-184, June.
    7. Wojciech Hardy & Roma Keister & Piotr Lewandowski, 2016. "Do entrants take it all? The evolution of task content of jobs in Poland," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 47.
    8. Anna Murawska & Bartosz Mickiewicz & Małgorzata Zajdel & Małgorzata Michalcewicz-Kaniowska, 2020. "Multidimensional Analysis of the Relationship between Sustainable Living Conditions and Long and Good Health in the European Union Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 716-735.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Adriana Barone & Cristian Barra, 2022. "Gender differences in weight status and early school leaving in Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(3), pages 644-666, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zilian, Laura S. & Zilian, Stella S. & Jäger, Georg, 2021. "Labour market polarisation revisited: evidence from Austrian vacancy data," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-7.
    2. Thomsen, Stephan L, 2018. "Die Rolle der Computerisierung und Digitalisierung für Beschäftigung und Einkommen," Hannover Economic Papers (HEP) dp-645, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Prettner, Klaus & Strulik, Holger, 2020. "Innovation, automation, and inequality: Policy challenges in the race against the machine," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 249-265.
    4. Hensvik, Lena & Skans, Oskar Nordström, 2023. "The skill-specific impact of past and projected occupational decline," Labour Economics, Elsevier, vol. 81(C).
    5. Guendalina Anzolin, 2021. "Automation and its Employment Effects: A Literature Review of Automotive and Garment Sectors," JRC Working Papers on Labour, Education and Technology 2021-16, Joint Research Centre.
    6. Usabiaga, Carlos & Núñez, Fernando & Arendt, Lukasz & Gałecka-Burdziak, Ewa & Pater, Robert, 2022. "Skill requirements and labour polarisation: An association analysis based on Polish online job offers," Economic Modelling, Elsevier, vol. 115(C).
    7. Martina Bisello & Eleonora Peruffo & Enrique Fernandez-Macias & Riccardo Rinaldi, 2019. "How computerisation is transforming jobs: Evidence from the European Working Conditions Survey," JRC Working Papers on Labour, Education and Technology 2019-02, Joint Research Centre.
    8. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2016. "ELS issues in robotics and steps to consider them. Part 1: Robotics and employment. Consequences of robotics and technological change for the structure and level of employment," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 146501.
    9. Fierro, Luca Eduardo & Caiani, Alessandro & Russo, Alberto, 2022. "Automation, Job Polarisation, and Structural Change," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 499-535.
    10. Azio Barani, 2021. "Innovazione tecnologica e lavoro: automazione, occupazione e impatti socio-economici," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 0(114), pages 51-79.
    11. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    12. Anderton, Robert & Jarvis, Valerie & Labhard, Vincent & Morgan, Julian & Petroulakis, Filippos & Vivian, Lara, 2020. "Virtually everywhere? Digitalisation and the euro area and EU economies," Occasional Paper Series 244, European Central Bank.
    13. Christian Dippel & Robert Gold & Stephan Heblich & Rodrigo Pinto, 2017. "Instrumental Variables and Causal Mechanisms: Unpacking the Effect of Trade on Workers and Voters," CESifo Working Paper Series 6816, CESifo.
    14. Colombo, Emilio & Mercorio, Fabio & Mezzanzanica, Mario, 2019. "AI meets labor market: Exploring the link between automation and skills," Information Economics and Policy, Elsevier, vol. 47(C), pages 27-37.
    15. Gries, Thomas & Naudé, Wim, 2020. "Artificial Intelligence, Income Distribution and Economic Growth," IZA Discussion Papers 13606, Institute of Labor Economics (IZA).
    16. Armanda Cetrulo & Dario Guarascio & Maria Enrica Virgillito, 2020. "Anatomy of the Italian occupational structure: concentrated power and distributed knowledge," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(6), pages 1345-1379.
    17. Christine Mayrhuber & Julia Bock-Schappelwein, 2018. "Dimensionen plattformbasierter Arbeit in Österreich und Europa. Implikationen für die soziale Sicherheit," WIFO Studies, WIFO, number 61667, April.
    18. Gaetano Basso, 2020. "The Evolution of the Occupational Structure in Italy, 2007–2017," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(2), pages 673-704, November.
    19. Krenz, Astrid & Prettner, Klaus & Strulik, Holger, 2021. "Robots, reshoring, and the lot of low-skilled workers," European Economic Review, Elsevier, vol. 136(C).
    20. Beier, Grischa & Matthess, Marcel & Shuttleworth, Luke & Guan, Ting & de Oliveira Pereira Grudzien, David Iubel & Xue, Bing & Pinheiro de Lima, Edson & Chen, Ling, 2022. "Implications of Industry 4.0 on industrial employment: A comparative survey from Brazilian, Chinese, and German practitioners," Technology in Society, Elsevier, vol. 70(C).

    More about this item

    Keywords

    Education level; employment diversification; education of men and women; labor market qualifications.;
    All these keywords.

    JEL classification:

    • A2 - General Economics and Teaching - - Economic Education and Teaching of Economics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

    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:ers:journl:v:xxiv:y:2021:i:special1:p:787-809. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Marios Agiomavritis (email available below). General contact details of provider: https://ersj.eu/ .

    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.