IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp16845.html
   My bibliography  Save this paper

Do Recruiters Penalize Men Who Prefer Low Hours? Evidence from Online Labor Market Data

Author

Listed:
  • Kopp, Daniel

    (ETH Zurich)

Abstract

Part-time work is a popular way to reconcile work and family responsibilities. This study investigates how easy it is for men and women to get part-time jobs. To assess this question, I first analyze the hiring decisions of recruiters who screen jobseekers on an online recruiting platform and estimate contact penalties for men and women seeking part-time jobs. Second, I relate the number of hours advertised in online job postings to firms' confidentially reported gender preferences. I find that recruiters prefer full-time over part-time workers, and that part-time penalties are more pronounced for men than for women. Differences in job or workplace characteristics cannot explain these results. Instead, the preponderance of evidence points to bias due to gender stereotypes.

Suggested Citation

  • Kopp, Daniel, 2024. "Do Recruiters Penalize Men Who Prefer Low Hours? Evidence from Online Labor Market Data," IZA Discussion Papers 16845, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp16845
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp16845.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tito Boeri & Herbert Bruecker, 2011. "Short-time work benefits revisited: some lessons from the Great Recession [‘Reversed roles? Wage and employment effects of the current crisis’]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 26(68), pages 697-765.
    2. Becker, Sascha O. & Fernandes, Ana & Weichselbaumer, Doris, 2019. "Discrimination in hiring based on potential and realized fertility: Evidence from a large-scale field experiment," Labour Economics, Elsevier, vol. 59(C), pages 139-152.
    3. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    4. Garnero, Andrea & Kampelmann, Stephan & Rycx, François, 2013. "Part-time Work, Wages and Productivity: Evidence from Belgian Matched Panel Data," IZA Discussion Papers 7789, Institute of Labor Economics (IZA).
    5. Forrest Briscoe, 2007. "From Iron Cage to Iron Shield? How Bureaucracy Enables Temporal Flexibility for Professional Service Workers," Organization Science, INFORMS, vol. 18(2), pages 297-314, April.
    6. Edward Shepard & Thomas Clifton, 2000. "Are longer hours reducing productivity in manufacturing?," International Journal of Manpower, Emerald Group Publishing Limited, vol. 21(7), pages 540-553, November.
    7. Uschi Backes-Gellner & Yvonne Oswald & Simone N. Tuor, 2011. "Part-time work and employer-provided training: boon to women and bane to men?," Economics of Education Working Paper Series 0058, University of Zurich, Department of Business Administration (IBW).
    8. repec:oup:ecpoli:v:26:y:2011:i:68:p:697-765 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    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. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
    2. Basso, Gaetano & Boeri, Tito & Caiumi, Alessandro & Paccagnella, Marco, 2020. "The New Hazardous Jobs and Worker Reallocation," IZA Discussion Papers 13532, Institute of Labor Economics (IZA).
    3. Konle-Seidl, Regina, 2020. "Short-time Work in Europe: Rescue in the Current COVID-19 Crisis?," IAB-Forschungsbericht 202004_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. Daniel Paravisini & Veronica Rappoport & Philipp Schnabl & Daniel Wolfenzon, 2015. "Dissecting the Effect of Credit Supply on Trade: Evidence from Matched Credit-Export Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(1), pages 333-359.
    5. Reamonn Lydon & Thomas Y. Mathä & Stephen Millard, 2019. "Short-time work in the Great Recession: firm-level evidence from 20 EU countries," IZA Journal of Labor Policy, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 8(1), pages 1-29, December.
    6. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    7. repec:hum:wpaper:sfb649dp2016-005 is not listed on IDEAS
    8. Taisuke Otsu & Myung Hwan Seo, 2014. "Asymptotics for maximum score method under general conditions," STICERD - Econometrics Paper Series 571, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    9. Sauvenier, Mathieu & Van Bellegem, Sébastien, 2023. "Direction Identification and Minimax Estimation by Generalized Eigenvalue Problem in High Dimensional Sparse Regression," LIDAM Discussion Papers CORE 2023005, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2017. "Econom\'etrie et Machine Learning," Papers 1708.06992, arXiv.org, revised Mar 2018.
    11. repec:hal:wpspec:info:hdl:2441/2ju03cb3kc9a3986bsibii70hd is not listed on IDEAS
    12. Chen, Daniel L. & Levonyan, Vardges & Yeh, Susan, 2016. "Policies Affect Preferences: Evidence from Random Variation in Abortion Jurisprudence," IAST Working Papers 16-58, Institute for Advanced Study in Toulouse (IAST).
    13. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
    14. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP77/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Everding, Jakob & Marcus, Jan, 2020. "The effect of unemployment on the smoking behavior of couples," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29(2), pages 154-170.
    16. Michael Christl & Silvia Poli & Tine Hufkens & Andreas Peichl & Mattia Ricci, 2023. "The role of short-time work and discretionary policy measures in mitigating the effects of the COVID-19 crisis in Germany," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(4), pages 1107-1136, August.
    17. Florentino Felgueroso & Marcel Jansen, 2020. "Una valoraciónde los ERTEpara hacer frente a la crisis del COVID-19 en basea la evidencia empírica y desde una perspectiva comparada," Policy Papers 2020-06, FEDEA.
    18. Ivan A Canay & Magne Mogstad & Jack Mount, 2024. "On the Use of Outcome Tests for Detecting Bias in Decision Making," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(4), pages 2135-2167.
    19. repec:spo:wpmain:info:hdl:2441/4urlmja10p80kqireg3ejlnogi is not listed on IDEAS
    20. Kruppe, Thomas & Scholz, Theresa, 2014. "Labour hoarding in Germany : employment effects of short-time work during the crises," IAB-Discussion Paper 201417, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    21. Jill Rubery & Isabelle Bi-Swinglehurst & Anthony Rafferty, 2024. "Part-time work and productivity," Insight Papers 031, The Productivity Institute.
    22. Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
    23. Andersen, Signe Hald & Özcan, Berkay, 2021. "The effects of unemployment on fertility," LSE Research Online Documents on Economics 109007, London School of Economics and Political Science, LSE Library.

    More about this item

    Keywords

    recruitment; part-time; gender equality; hiring; online labor markets;
    All these keywords.

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions

    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:iza:izadps:dp16845. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.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.