IDEAS home Printed from https://ideas.repec.org/p/zbw/glodps/422.html
   My bibliography  Save this paper

Job Prestige and Mobile Dating Success: A Field Experiment

Author

Listed:
  • Neyt, Brecht
  • Baert, Stijn
  • Vynckier, Jana

Abstract

Research exploiting data on classic (offline) couple formation has confirmed predictions from evolutionary psychology in a sense that males attach more value to attractiveness and women attach more value to earnings potential. We examine whether these human partner preferences survive in a context of fewer search and social frictions. We do this by means of a field experiment on the mobile dating app Tinder, which takes a central place in contemporary couple formation. Thirty-two fictitious Tinder profiles that randomly differ in job status and job prestige are evaluated by 4,800 other, real users. We find that both males and females do not use job status or job prestige as a determinant of whom to show initial interest in on Tinder. However, we do see evidence that, after this initial phase, males less frequently begin a conversation with females when those females are unemployed but also then do not care about the particular job prestige of employed females.

Suggested Citation

  • Neyt, Brecht & Baert, Stijn & Vynckier, Jana, 2019. "Job Prestige and Mobile Dating Success: A Field Experiment," GLO Discussion Paper Series 422, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:422
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/206405/1/GLO-DP-0422.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Stefan Eriksson & Dan-Olof Rooth, 2014. "Do Employers Use Unemployment as a Sorting Criterion When Hiring? Evidence from a Field Experiment," American Economic Review, American Economic Association, vol. 104(3), pages 1014-1039, March.
    2. Marianne Bertrand & Emir Kamenica & Jessica Pan, 2015. "Gender Identity and Relative Income within Households," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(2), pages 571-614.
    3. Stijn Baert & Ann-Sophie De Pauw & Nick Deschacht, 2016. "Do Employer Preferences Contribute to Sticky Floors?," ILR Review, Cornell University, ILR School, vol. 69(3), pages 714-736, May.
    4. Leonardo Bursztyn & Thomas Fujiwara & Amanda Pallais, 2017. "'Acting Wife': Marriage Market Incentives and Labor Market Investments," American Economic Review, American Economic Association, vol. 107(11), pages 3288-3319, November.
    5. Raymond Fisman & Sheena S. Iyengar & Emir Kamenica & Itamar Simonson, 2006. "Gender Differences in Mate Selection: Evidence From a Speed Dating Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 673-697.
    6. David Neumark, 2018. "Experimental Research on Labor Market Discrimination," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 799-866, September.
    7. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    8. Neyt, Brecht & Vandenbulcke, Sarah & Baert, Stijn, 2019. "Are men intimidated by highly educated women? Undercover on Tinder," Economics of Education Review, Elsevier, vol. 73(C).
    9. Gunter J. Hitsch & Ali Hortaçsu & Dan Ariely, 2010. "Matching and Sorting in Online Dating," American Economic Review, American Economic Association, vol. 100(1), pages 130-163, March.
    10. Ann-Sophie De Pauw, 2016. "Do employer preferences contribute to sticky floors ?," Post-Print hal-01772258, HAL.
    11. Abramova, Olga & Baumann, Annika & Krasnova, Hanna & Buxmann, Peter, 2016. "Gender Differences in Online Dating: What Do We Know So Far? A Systematic Literature Review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77661, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. William Greene, 2002. "The Behavior of the Fixed Effects Estimator in Nonlinear Models," Working Papers 02-05, New York University, Leonard N. Stern School of Business, Department of Economics.
    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. Afridi, Farzana & Arora, Abhishek & Dhar, Diva & Mahajan, Kanika, 2023. "Women's Work, Social Norms and the Marriage Market," IZA Discussion Papers 15948, Institute of Labor Economics (IZA).
    2. Farzana Afridi & Abhishek Arora & Diva Dhar & Kanika Mahajan, 2023. "Women’s Work, Social Norms and the Marriage Market∗," Working Papers 94, Ashoka University, Department of Economics.
    3. Beloborodova, Anna, 2023. "Political views regarding the war in Ukraine in an online dating experiment," MPRA Paper 120739, University Library of Munich, Germany.
    4. Beloborodova, Anna, 2023. "Love or politics? Political views regarding the war in Ukraine in an online dating experiment," MPRA Paper 118862, University Library of Munich, Germany.

    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. Neyt, Brecht & Vandenbulcke, Sarah & Baert, Stijn, 2019. "Are men intimidated by highly educated women? Undercover on Tinder," Economics of Education Review, Elsevier, vol. 73(C).
    2. Carlsson, Magnus & Eriksson, Stefan, 2019. "Age discrimination in hiring decisions: Evidence from a field experiment in the labor market," Labour Economics, Elsevier, vol. 59(C), pages 173-183.
    3. Valfort, Marie-Anne, 2020. "Anti-Muslim discrimination in France: Evidence from a field experiment," World Development, Elsevier, vol. 135(C).
    4. Carlsson, Magnus & Eriksson, Stefan, 2017. "The effect of age and gender on labor demand – evidence from a field experiment," Working Paper Series 2017:8, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    5. Zhang, Peilu & Zhang, Yinjunjie & Palma, Marco, 2018. "Social Norms and Competitiveness: My Willingness to Compete Depends on Who I am (supposed to be)," MPRA Paper 89727, University Library of Munich, Germany.
    6. David Neumark, 2018. "Experimental Research on Labor Market Discrimination," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 799-866, September.
    7. Ong, David & Wang, Jue, 2015. "Income attraction: An online dating field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 111(C), pages 13-22.
    8. Baert, Stijn & Norga, Jennifer & Thuy, Yannick & Van Hecke, Marieke, 2016. "Getting grey hairs in the labour market. An alternative experiment on age discrimination," Journal of Economic Psychology, Elsevier, vol. 57(C), pages 86-101.
    9. Gaddis, S. Michael, 2018. "An Introduction to Audit Studies in the Social Sciences," SocArXiv e5hfc, Center for Open Science.
    10. Ingvild Almås & Andreas Kotsadam & Espen R. Moen & Knut Røed, 2023. "The Economics of Hypergamy," Journal of Human Resources, University of Wisconsin Press, vol. 58(1), pages 260-281.
    11. Baert, Stijn, 2017. "Hiring Discrimination: An Overview of (Almost) All Correspondence Experiments Since 2005," GLO Discussion Paper Series 61, Global Labor Organization (GLO).
    12. Ong, David & Yang, Yu (Alan) & Zhang, Junsen, 2020. "Hard to get: The scarcity of women and the competition for high-income men in urban China," Journal of Development Economics, Elsevier, vol. 144(C).
    13. Giovanni Busetta & Fabio Fiorillo & Giulio Palomba, 2021. "The impact of attractiveness on job opportunities in Italy: a gender field experiment," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(1), pages 171-201, April.
    14. Baert, Stijn & De Visschere, Sarah & Schoors, Koen & Vandenberghe, Désirée & Omey, Eddy, 2016. "First depressed, then discriminated against?," Social Science & Medicine, Elsevier, vol. 170(C), pages 247-254.
    15. Cassar, Alessandra & Zhang, Y. Jane, 2022. "The competitive woman: Evolutionary insights and cross-cultural evidence into finding the Femina Economica," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 447-471.
    16. Egebark, Johan & Ekström, Mathias & Plug, Erik & van Praag, Mirjam, 2021. "Brains or beauty? Causal evidence on the returns to education and attractiveness in the online dating market," Journal of Public Economics, Elsevier, vol. 196(C).
    17. Margaret Maurer-Fazio & Sili Wang, 2018. "Does marital status affect how firms interpret job applicants’ un/employment histories?," International Journal of Manpower, Emerald Group Publishing Limited, vol. 39(4), pages 567-580, July.
    18. Farzana Afridi & Abhishek Arora & Diva Dhar & Kanika Mahajan, 2023. "Women’s Work, Social Norms and the Marriage Market∗," Working Papers 94, Ashoka University, Department of Economics.
    19. Baert, Stijn & Picchio, Matteo, 2021. "A signal of (Train)ability? Grade repetition and hiring chances," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 867-878.
    20. Stijn Baert & Sunčica Vujić, 2018. "Does it pay to care? Volunteering and employment opportunities," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(3), pages 819-836, July.

    More about this item

    Keywords

    job prestige; partner preferences; dating apps; online dating; Tinder;
    All these keywords.

    JEL classification:

    • J12 - Labor and Demographic Economics - - Demographic Economics - - - Marriage; Marital Dissolution; Family Structure
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

    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:zbw:glodps:422. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/glabode.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.