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The Inelastic Demand for Affirmative Action

Author

Listed:
  • Getik, Demid

    (Department of Economics, Lund University)

  • Islam, Marco

    (Department of Economics, Lund University)

  • Samahita, Margaret

    (School of Economics, University College Dublin)

Abstract

We study the origins of support for gender-related affirmative action (AA) in two pre-registered online experiments (N = 1, 700). Participants act as employers who decide whether to use AA in hiring job candidates. We implement three treatments to disentangle the preference for AA stemming from i) perceived gender differences in productivity, ii) beliefs about AA effects on productivity, or iii) other non-material motives. To test i), we provide information to employers that there is no gender gap in productivity. To test ii), we inform the candidates about the hiring rule ex-ante, allowing us to observe how AA is expected to affect productivity. To test iii), we remove the payment to the employers based on the chosen candidates’ productiv- ity, thus making AA cheaper. We do not find significant differences in AA support across treatments, despite successfully altering beliefs about expected productivity differences. Our results suggest that AA choice reflects a more intrinsic and inelastic preference for advancing female candidates.

Suggested Citation

  • Getik, Demid & Islam, Marco & Samahita, Margaret, 2021. "The Inelastic Demand for Affirmative Action," Working Papers 2021:7, Lund University, Department of Economics.
    • Handle: RePEc:hhs:lunewp:2021_007
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    References listed on IDEAS

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    1. Alberto Alesina & Armando Miano & Stefanie Stantcheva, 2023. "Immigration and Redistribution," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(1), pages 1-39.
    2. Ernst Fehr & Klaus M. Schmidt, 1999. "A Theory of Fairness, Competition, and Cooperation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(3), pages 817-868.
    3. Miguel A. Costa-Gomes & Georg Weizsäcker, 2008. "Stated Beliefs and Play in Normal-Form Games," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(3), pages 729-762.
    4. Marcela Ibanez & Gerhard Riener, 2018. "Sorting through Affirmative Action: Three Field Experiments in Colombia," Journal of Labor Economics, University of Chicago Press, vol. 36(2), pages 437-478.
    5. Edwin Ip & Andreas Leibbrandt & Joseph Vecci, 2020. "How Do Gender Quotas Affect Workplace Relationships? Complementary Evidence from a Representative Survey and Labor Market Experiments," Management Science, INFORMS, vol. 66(2), pages 805-822, February.
    6. Calsamiglia, Caterina & Franke, Jörg & Rey-Biel, Pedro, 2013. "The incentive effects of affirmative action in a real-effort tournament," Journal of Public Economics, Elsevier, vol. 98(C), pages 15-31.
    7. Mitra Akhtari & Natalie Bau & Jean-William Laliberté, 2024. "Affirmative Action and Precollege Human Capital," American Economic Journal: Applied Economics, American Economic Association, vol. 16(1), pages 1-32, January.
    8. Thomas Buser & Muriel Niederle & Hessel Oosterbeek, 2020. "Can competitiveness predict education and labor market outcomes? Evidence from incentivized choice and survey measures," Tinbergen Institute Discussion Papers 20-048/I, Tinbergen Institute.
    9. Ingar Haaland & Christopher Roth, 2023. "Beliefs about Racial Discrimination and Support for Pro-Black Policies," The Review of Economics and Statistics, MIT Press, vol. 105(1), pages 40-53, January.
    10. Muriel Niederle & Lise Vesterlund, 2007. "Do Women Shy Away From Competition? Do Men Compete Too Much?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1067-1101.
    11. Axel Ockenfels & Gary E. Bolton, 2000. "ERC: A Theory of Equity, Reciprocity, and Competition," American Economic Review, American Economic Association, vol. 90(1), pages 166-193, March.
    12. Chen, Daniel L. & Schonger, Martin & Wickens, Chris, 2016. "oTree—An open-source platform for laboratory, online, and field experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 9(C), pages 88-97.
    13. Balafoutas, Loukas & Davis, Brent J. & Sutter, Matthias, 2016. "Affirmative action or just discrimination? A study on the endogenous emergence of quotas," Journal of Economic Behavior & Organization, Elsevier, vol. 127(C), pages 87-98.
    14. Muriel Niederle & Carmit Segal & Lise Vesterlund, 2013. "How Costly Is Diversity? Affirmative Action in Light of Gender Differences in Competitiveness," Management Science, INFORMS, vol. 59(1), pages 1-16, May.
    15. Banerjee, Ritwik & Ibanez, Marcela & Riener, Gerhard & Sahoo, Soham, 2021. "Affirmative action and application strategies: Evidence from field experiments in Columbia," DICE Discussion Papers 362, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    16. Maggian, Valeria & Montinari, Natalia & Nicolò, Antonio, 2020. "Do quotas help women to climb the career ladder? A laboratory experiment," European Economic Review, Elsevier, vol. 123(C).
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    More about this item

    Keywords

    affirmative action; beliefs; gender; information; institution;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • J38 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Public Policy
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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