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Gender Differences in Returns to Beauty

Author

Listed:
  • Kimberly Scharf

    (University of Nottingham)

  • Oleksandr Talavera

    (University of Birmingham)

  • Linh Vi

    (Aston University)

Abstract

We employ a sample of nearly 40,000 gender-targeted online job vacancies in Vietnam from February 2019 to July 2020 to investigate gender differences in returns to physical attractiveness. In particular, we compare the monthly offered wage in matched vacancies with and without beauty preferences of the same characteristics among job ads directed at men and women separately. We find evidence that better-looking women enjoy a wage premium of 3.7 percentage points, whereas better-looking men do not. Further analysis shows that the gender differences in returns to beauty are mainly driven by gender role attitudes and the perceived lack of fit rather than productivity-enhancing effect or employers' negligence in job postings.

Suggested Citation

  • Kimberly Scharf & Oleksandr Talavera & Linh Vi, 2023. "Gender Differences in Returns to Beauty," Discussion Papers 23-08, Department of Economics, University of Birmingham.
  • Handle: RePEc:bir:birmec:23-08
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    References listed on IDEAS

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    1. 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.
    2. Lennart Ziegler, 2020. "Skill Demand and Posted Wages. Evidence from Online Job Ads in Austria," Vienna Economics Papers vie2002, University of Vienna, Department of Economics.
    3. Boris Hirsch & Elke J. Jahn & Alan Manning & Michael Oberfichtner, 2022. "The Urban Wage Premium in Imperfect Labor Markets," Journal of Human Resources, University of Wisconsin Press, vol. 57(S), pages 111-136.
    4. Marianne Bertrand, 2018. "Coase Lecture – The Glass Ceiling," Economica, London School of Economics and Political Science, vol. 85(338), pages 205-231, April.
    5. Hamermesh, Daniel S & Biddle, Jeff E, 1994. "Beauty and the Labor Market," American Economic Review, American Economic Association, vol. 84(5), pages 1174-1194, December.
    6. Anita Staneva & G Arabsheibani, 2014. "Is there an informal employment wage premium? Evidence from Tajikistan," IZA Journal of Labor & Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 3(1), pages 1-24, December.
    7. Marianne Bertrand & Matilde Bombardini & Raymond Fisman & Brad Hackinen & Francesco Trebbi, 2021. "Hall of Mirrors: Corporate Philanthropy and Strategic Advocacy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(4), pages 2413-2465.
    8. Peter Kuhn & Kailing Shen, 2013. "Gender Discrimination in Job Ads: Evidence from China," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(1), pages 287-336.
    9. Eleonora Patacchini & Giuseppe Ragusa & Yves Zenou, 2015. "Unexplored dimensions of discrimination in Europe: homosexuality and physical appearance," Journal of Population Economics, Springer;European Society for Population Economics, vol. 28(4), pages 1045-1073, October.
    10. Deryugina, Tatyana & Shurchkov, Olga, 2015. "Now you see it, now you don’t: The vanishing beauty premium," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 331-345.
    11. repec:wyi:journl:002164 is not listed on IDEAS
    12. Cavapozzi, Danilo & Francesconi, Marco & Nicoletti, Cheti, 2021. "The impact of gender role norms on mothers’ labor supply," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 113-134.
    13. David H. Autor & Michael J. Handel, 2013. "Putting Tasks to the Test: Human Capital, Job Tasks, and Wages," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 59-96.
    14. Pfann, Gerard A. & Biddle, Jeff E. & Hamermesh, Daniel S. & Bosman, Ciska M., 2000. "Business success and businesses' beauty capital," Economics Letters, Elsevier, vol. 67(2), pages 201-207, May.
    15. Michael French, 2002. "Physical appearance and earnings: further evidence," Applied Economics, Taylor & Francis Journals, vol. 34(5), pages 569-572.
    16. 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.
    17. Eva O. Arceo-Gomez & Raymundo M. Campos-Vazquez & Raquel Y. Badillo & Sergio Lopez-Araiza, 2022. "Gender stereotypes in job advertisements: What do they imply for the gender salary gap?," Journal of Labor Research, Springer, vol. 43(1), pages 65-102, March.
    18. Panggih Kusuma Ningrum & Tatdow Pansombut & Attachai Ueranantasun, 2020. "Text mining of online job advertisements to identify direct discrimination during job hunting process: A case study in Indonesia," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-29, June.
    19. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2012. "Causal Inference without Balance Checking: Coarsened Exact Matching," Political Analysis, Cambridge University Press, vol. 20(1), pages 1-24, January.
    20. Jobu Babin, J. & Hussey, Andrew & Nikolsko-Rzhevskyy, Alex & Taylor, David A., 2020. "Beauty Premiums Among Academics," Economics of Education Review, Elsevier, vol. 78(C).
    21. Alberto Alesina & Paola Giuliano & Nathan Nunn, 2013. "On the Origins of Gender Roles: Women and the Plough," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(2), pages 469-530.
    22. Ehrmann, Michael & Talmi, Jonathan, 2020. "Starting from a blank page? Semantic similarity in central bank communication and market volatility," Journal of Monetary Economics, Elsevier, vol. 111(C), pages 48-62.
    23. Lucia Kureková & Miroslav Beblavý & Anna Thum-Thysen, 2015. "Using online vacancies and web surveys to analyse the labour market: a methodological inquiry," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-20, December.
    24. Francesconi, Marco & Nicoletti, Cheti & Cavapozzi, Danilo, 2021. "The Impact of Gender Role Norms on Mothers’ Labor Supply," CEPR Discussion Papers 15957, C.E.P.R. Discussion Papers.
    25. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    26. Lennart Ziegler, 2020. "Skill Demand and Posted Wages. Evidence from Online Job Ads in Austria," Vienna Economics Papers 2002, University of Vienna, Department of Economics.
    27. Dan-Olof Rooth, 2009. "Obesity, Attractiveness, and Differential Treatment in Hiring: A Field Experiment," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    28. M. Christl & Monika Köppl–Turyna, 2020. "Gender wage gap and the role of skills and tasks: evidence from the Austrian PIAAC data set," Applied Economics, Taylor & Francis Journals, vol. 52(2), pages 113-134, January.
    29. Philip K. Robins & Jenny F. Homer & Michael T. French, 2011. "Beauty and the Labor Market: Accounting for the Additional Effects of Personality and Grooming," LABOUR, CEIS, vol. 25(2), pages 228-251, June.
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    More about this item

    Keywords

    FinTech; physical attractiveness; online vacancies; gender; beauty premium;
    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
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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