IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp13225.html
   My bibliography  Save this paper

Collaboration, Alphabetical Order and Gender Discrimination – Evidence from the Lab

Author

Listed:
  • Wiborg, Vegard Sjurseike

    (University of Oslo)

  • Brekke, Kjell Arne

    (University of Oslo)

  • Nyborg, Karine

    (University of Oslo)

Abstract

If individual abilities are imperfectly observable, statistical discrimination may affect hiring decisions. In our lab experiment, pairs of subjects solve simple mathematical problems. Subjects then hire others to perform similar tasks. Before choosing whom to hire, they receive information about the past scores of pairs, not of individuals. We vary the observability of individuals' abilities by ordering pair members either according to performance, or alphabetically by nickname. We find no evidence of gender discrimination in either treatment, however, possibly indicating that gender stereotypes are of limited importance in the context of our study.

Suggested Citation

  • Wiborg, Vegard Sjurseike & Brekke, Kjell Arne & Nyborg, Karine, 2020. "Collaboration, Alphabetical Order and Gender Discrimination – Evidence from the Lab," IZA Discussion Papers 13225, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp13225
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp13225.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Alice H. Wu, 2018. "Gendered Language on the Economics Job Market Rumors Forum," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 175-179, May.
    2. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    3. Jonathan Guryan & Kerwin Kofi Charles, 2013. "Taste‐based or Statistical Discrimination: The Economics of Discrimination Returns to its Roots," Economic Journal, Royal Economic Society, vol. 123(11), pages 417-432, November.
    4. Kenneth J. Arrow, 1998. "What Has Economics to Say about Racial Discrimination?," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 91-100, Spring.
    5. Heather Sarsons, 2017. "Recognition for Group Work: Gender Differences in Academia," American Economic Review, American Economic Association, vol. 107(5), pages 141-145, May.
    6. Steven D. Levitt & John A. List, 2007. "What Do Laboratory Experiments Measuring Social Preferences Reveal About the Real World?," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 153-174, Spring.
    7. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    8. Lane, Tom, 2016. "Discrimination in the laboratory: A meta-analysis of economics experiments," European Economic Review, Elsevier, vol. 90(C), pages 375-402.
    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. Banerjee, Ritwik & Mustafi, Priyoma, 2020. "Using Social Recognition to Address the Gender Difference in Volunteering for Low Promotability Tasks," IZA Discussion Papers 13956, Institute of Labor Economics (IZA).

    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. Achard, Pascal & Suetens, Sigrid, 2023. "The Causal Effect of Ethnic Diversity on Support for Redistribution and the Role of Discrimination," Other publications TiSEM a5e6e0cd-5e07-4a24-a15c-a, Tilburg University, School of Economics and Management.
    2. Ravetti, Chiara & Sarr, Mare & Munene, Daniel & Swanson, Tim, 2019. "Discrimination and favouritism among South African workers: Ethnic identity and union membership," World Development, Elsevier, vol. 123(C), pages 1-1.
    3. Francisco B. Galarza, 2017. "Trust and Trustworthiness in College: An Experimental Analysis," Working Papers 17-03, Centro de Investigación, Universidad del Pacífico.
    4. Cacault, Maria Paula & Grieder, Manuel, 2019. "How group identification distorts beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 63-76.
    5. Achard, Pascal & Suetens, Sigrid, 2023. "The Causal Effect of Ethnic Diversity on Support for Redistribution and the Role of Discrimination," Discussion Paper 2023-013, Tilburg University, Center for Economic Research.
    6. Dickinson, David L. & Masclet, David & Peterle, Emmanuel, 2018. "Discrimination as favoritism: The private benefits and social costs of in-group favoritism in an experimental labor market," European Economic Review, Elsevier, vol. 104(C), pages 220-236.
    7. Batsaikhan, Mongoljin & He, Tai-Sen & Li, Yupeng, 2021. "Accents, group identity, and trust behaviors: Evidence from Singapore," China Economic Review, Elsevier, vol. 70(C).
    8. Batsaikhan, Mongoljin & Gørtz, Mette & Kennes, John & Lyng, Ran Sun & Monte, Daniel & Tumennasan, Norovsambuu, 2021. "Discrimination and Daycare Choice: Evidence from a Randomized Survey," IZA Discussion Papers 14874, Institute of Labor Economics (IZA).
    9. Jan Feld & Edwin Ip & Andreas Leibbrandt & Joseph Vecci, 2022. "Identifying and Overcoming Gender Barriers in Tech: A Field Experiment on Inaccurate Statistical Discrimination," CESifo Working Paper Series 9970, CESifo.
    10. Bronchal, Adrià, 2023. "Better the devil you know: The effects of group identity uncertainty on coordination efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 634-656.
    11. Élisabeth Tovar & Matthieu Bunel, 2019. "Profit vs morality: how unfair is labor market discrimination? Results from a survey experiment," EconomiX Working Papers 2019-25, University of Paris Nanterre, EconomiX.
    12. Mongoljin Batsaikhan & Mette Gørtz & John Kennes & Ran Sun Lyng & Daniel Monte & Norovsambuu Tumennasan, 2019. "Daycare Choice and Ethnic Diversity: Evidence from a Randomized Survey," Economics Working Papers 2019-02, Department of Economics and Business Economics, Aarhus University.
    13. Sevilla, Almudena, 2020. "Gender Economics: An Assessment," IZA Discussion Papers 13877, Institute of Labor Economics (IZA).
    14. José J. Domínguez & Natalia Montinari, 2021. "Gender Quotas and Task Assignment in Organizations," ThE Papers 21/13, Department of Economic Theory and Economic History of the University of Granada..
    15. Bajzíková, Stanislava & Cingl, Lubomír, 2023. "Measuring stereotypes in effort tasks: A multiple-price list approach," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 105(C).
    16. Élisabeth Tovar & Matthieu Bunel, 2019. "Profit vs morality: how unfair is labor market discrimination? Results from a survey experiment," Working Papers hal-04141860, HAL.
    17. Zenou, Yves & Islam, Asad & Pakrashi, Debayan & Wang, Liang Choon, 2018. "Determining the Extent of Statistical Discrimination: Evidence from a field experiment in India," CEPR Discussion Papers 12955, C.E.P.R. Discussion Papers.
    18. Mario L. Small & Devah Pager, 2020. "Sociological Perspectives on Racial Discrimination," Journal of Economic Perspectives, American Economic Association, vol. 34(2), pages 49-67, Spring.
    19. Bouma, J.A. & Nguyen, Binh & van der Heijden, Eline & Dijk, J.J., 2018. "Analysing Group Contract Design Using a Lab and a Lab-in-the-Field Threshold Public Good Experiment," Discussion Paper 2018-049, Tilburg University, Center for Economic Research.
    20. Claudia Keser & David Masclet & Claude Montmarquette, 2020. "Labor Supply, Taxation, and the Use of Tax Revenues: A Real-Effort Experiment in Canada, France, and Germany," Public Finance Review, , vol. 48(6), pages 714-750, November.

    More about this item

    Keywords

    discrimination; collaboration; alphabetic; gender;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • A13 - General Economics and Teaching - - General Economics - - - Relation of Economics to Social Values
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    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:dp13225. 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.