IDEAS home Printed from https://ideas.repec.org/p/fau/wpaper/wp2020_18.html
   My bibliography  Save this paper

Beauty and Productivity: A Meta-Analysis

Author

Listed:
  • Kseniya Bortnikova

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University Opletalova 26, 110 00, Prague, Czech Republic)

Abstract

The economics of beauty is now a burgeoning field of research. Not only the magnitude but also the direction of the beauty effect on labor outcomes is a matter of discussion. In this work, I conduct a quantitative synthesis of 418 estimates of the effect of beauty on worker´s productivity, as reported in 37 studies. The estimates are tested for publication selection using informal testing of the funnel plot as well as formal testing methods. The results provide substantial evidence of selective reporting: positive estimates of the beauty effect are preferred in literature. The set of 21 explanatory variables was collected to determine the sources of heterogeneity in the reported estimates. To account for the model uncertainty, I employ the Bayesian and Frequentist model averaging. The results indicate that differences in the reported estimates appear to be driven by choice of study design and sources of real heterogeneity, such as geographical regions and individual characteristics of respondents. The type of occupation and gender of respondents have no impact on the estimates of beauty effect concerning productivity. The average beauty effect is probably much lower than commonly believed based on the available empirical literature.

Suggested Citation

  • Kseniya Bortnikova, 2020. "Beauty and Productivity: A Meta-Analysis," Working Papers IES 2020/18, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jun 2020.
  • Handle: RePEc:fau:wpaper:wp2020_18
    as

    Download full text from publisher

    File URL: https://ies.fsv.cuni.cz/en/veda-vyzkum/working-papers/6257
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Havranek, Tomas & Rusnak, Marek & Sokolova, Anna, 2017. "Habit formation in consumption: A meta-analysis," European Economic Review, Elsevier, vol. 95(C), pages 142-167.
    2. Giam Pietro Cipriani & Angelo Zago, 2011. "Productivity or Discrimination? Beauty and the Exams," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(3), pages 428-447, June.
    3. Sean P. Salter & Franklin G. Mixon & Ernest W. King, 2012. "Broker beauty and boon: a study of physical attractiveness and its effect on real estate brokers’ income and productivity," Applied Financial Economics, Taylor & Francis Journals, vol. 22(10), pages 811-825, May.
    4. Hamermesh, Daniel S. & Meng, Xin & Zhang, Junsen, 2002. "Dress for success--does primping pay?," Labour Economics, Elsevier, vol. 9(3), pages 361-373, July.
    5. Havranek, Tomas & Horvath, Roman & Irsova, Zuzana & Rusnak, Marek, 2015. "Cross-country heterogeneity in intertemporal substitution," Journal of International Economics, Elsevier, vol. 96(1), pages 100-118.
    6. Markus M. Mobius & Tanya S. Rosenblat, 2006. "Why Beauty Matters," American Economic Review, American Economic Association, vol. 96(1), pages 222-235, March.
    7. repec:bla:obuest:v:62:y:2000:i:0:p:771-800 is not listed on IDEAS
    8. Amy King & Andrew Leigh, 2009. "Beautiful Politicians," Kyklos, Wiley Blackwell, vol. 62(4), pages 579-593, November.
    9. Christian Pfeifer, 2012. "Physical attractiveness, employment and earnings," Applied Economics Letters, Taylor & Francis Journals, vol. 19(6), pages 505-510, April.
    10. Berggren, Niclas & Jordahl, Henrik & Poutvaara, Panu, 2010. "The looks of a winner: Beauty and electoral success," Journal of Public Economics, Elsevier, vol. 94(1-2), pages 8-15, February.
    11. Stanley, T. D. & Jarrell, Stephen B. & Doucouliagos, Hristos, 2010. "Could It Be Better to Discard 90% of the Data? A Statistical Paradox," The American Statistician, American Statistical Association, vol. 64(1), pages 70-77.
    12. Doorley, Karina & Sierminska, Eva, 2012. "Myth or Fact? The Beauty Premium across the Wage Distribution," IZA Discussion Papers 6674, Institute of Labor Economics (IZA).
    13. Tomas Havranek & Zuzana Irsova & Olesia Zeynalova, 2017. "Tuition Fees and University Enrollment: A Meta-Analysis," Working Papers IES 2017/16, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2017.
    14. Paulo R. A. Loureiro & Adolfo Sachsida & Mário Jorge Cardoso de Mendonça, 2010. "Links Between Physical Appearance and Wage Discrimination: further evidence," Working papers - Textos para Discussao do Departamento de Economia da Universidade de Brasilia 341, Departamento de Economia da Universidade de Brasilia.
    15. Michael French, 2002. "Physical appearance and earnings: further evidence," Applied Economics, Taylor & Francis Journals, vol. 34(5), pages 569-572.
    16. Petra Valickova & Tomas Havranek & Roman Horvath, 2015. "Financial Development And Economic Growth: A Meta-Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 506-526, July.
    17. Efendic, Adnan & Pugh, Geoff & Adnett, Nick, 2011. "Institutions and economic performance: A meta-regression analysis," European Journal of Political Economy, Elsevier, vol. 27(3), pages 586-599, September.
    18. Berri, David J. & Simmons, Rob & Van Gilder, Jennifer & O'Neill, Lisle, 2011. "What does it mean to find the face of the franchise? Physical attractiveness and the evaluation of athletic performance," Economics Letters, Elsevier, vol. 111(3), pages 200-202, June.
    19. Jon Nelson, 2013. "Meta-analysis of alcohol price and income elasticities – with corrections for publication bias," Health Economics Review, Springer, vol. 3(1), pages 1-10, December.
    20. De Long, J Bradford & Lang, Kevin, 1992. "Are All Economic Hypotheses False?," Journal of Political Economy, University of Chicago Press, vol. 100(6), pages 1257-1272, December.
    21. T. D. Stanley, 2005. "Beyond Publication Bias," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 309-345, July.
    22. 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.
    23. Nicola Persico & Andrew Postlewaite & Dan Silverman, 2004. "The Effect of Adolescent Experience on Labor Market Outcomes: The Case of Height," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 1019-1053, October.
    24. López Bóo, Florencia & Rossi, Martín A. & Urzúa, Sergio S., 2013. "The labor market return to an attractive face: Evidence from a field experiment," Economics Letters, Elsevier, vol. 118(1), pages 170-172.
    25. John Karl Scholz & Kamil Sicinski, 2015. "Facial Attractiveness and Lifetime Earnings: Evidence from a Cohort Study," The Review of Economics and Statistics, MIT Press, vol. 97(1), pages 14-28, March.
    26. Parrett, Matt, 2015. "Beauty and the feast: Examining the effect of beauty on earnings using restaurant tipping data," Journal of Economic Psychology, Elsevier, vol. 49(C), pages 34-46.
    27. Jan Sauermann, 2023. "Performance measures and worker productivity," IZA World of Labor, Institute of Labor Economics (IZA), pages 260-260, April.
    28. 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.
    29. James C. Hershauer & William A. Ruch, 1978. "A Worker Productivity Model and Its Use at Lincoln Electric," Interfaces, INFORMS, vol. 8(3), pages 80-90, May.
    30. Doucouliagos, Hristos (Chris), 2011. "How large is large? Preliminary and relative guidelines for interpreting partial correlations in economics," Working Papers eco_2011_5, Deakin University, Department of Economics.
    31. Hristos Doucouliagos & T. D. Stanley, 2009. "Publication Selection Bias in Minimum‐Wage Research? A Meta‐Regression Analysis," British Journal of Industrial Relations, London School of Economics, vol. 47(2), pages 406-428, June.
    32. Daniel Hamermesh & Amy M. Parker, 2003. "Beauty in the Classroom: Professors' Pulchritude and Putative Pedagogical Productivity," NBER Working Papers 9853, National Bureau of Economic Research, Inc.
    33. Tomas Havranek & Zuzana Irsova & Olesia Zeynalova, 2018. "Tuition Fees and University Enrolment: A Meta‐Regression Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(6), pages 1145-1184, December.
    34. Fletcher, Jason M., 2009. "Beauty vs. brains: Early labor market outcomes of high school graduates," Economics Letters, Elsevier, vol. 105(3), pages 321-325, December.
    35. 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.
    36. Arunachalam Raj & Shah Manisha, 2012. "The Prostitute's Allure: The Return to Beauty in Commercial Sex Work," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 12(1), pages 1-27, December.
    37. T. D. Stanley, 2001. "Wheat from Chaff: Meta-analysis as Quantitative Literature Review," Journal of Economic Perspectives, American Economic Association, vol. 15(3), pages 131-150, Summer.
    38. Biddle, Jeff E & Hamermesh, Daniel S, 1998. "Beauty, Productivity, and Discrimination: Lawyers' Looks and Lucre," Journal of Labor Economics, University of Chicago Press, vol. 16(1), pages 172-201, January.
    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. Dilmaghani, Maryam, 2020. "Beauty perks: Physical appearance, earnings, and fringe benefits," Economics & Human Biology, Elsevier, vol. 38(C).
    2. Astghik Mavisakalyan, 2016. "Looks matter: Attractiveness and employment in the former soviet union," Bankwest Curtin Economics Centre Working Paper series WP1604, Bankwest Curtin Economics Centre (BCEC), Curtin Business School.
    3. Mavisakalyan, Astghik, 2018. "Do employers reward physical attractiveness in transition countries?," Economics & Human Biology, Elsevier, vol. 28(C), pages 38-52.
    4. Cazachevici, Alina & Havranek, Tomas & Horvath, Roman, 2020. "Remittances and economic growth: A meta-analysis," World Development, Elsevier, vol. 134(C).
    5. LIU Xing & SIERMINSKA Eva, 2014. "Evaluating the effect of beauty on labor market outcomes: A review of the literature," LISER Working Paper Series 2014-11, Luxembourg Institute of Socio-Economic Research (LISER).
    6. Ying Cao & Feng Guan & Zengquan Li & Yong George Yang, 2020. "Analysts’ Beauty and Performance," Management Science, INFORMS, vol. 66(9), pages 4315-4335, September.
    7. Babin, J. Jobu & Chauhan, Haritima S. & Kistler, Steven L., 2024. "When pretty hurts: Beauty premia and penalties in eSports," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 726-741.
    8. 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.
    9. Peng, Langchuan & Wang, Xi & Ying, Shanshan, 2020. "The heterogeneity of beauty premium in China: Evidence from CFPS," Economic Modelling, Elsevier, vol. 90(C), pages 386-396.
    10. Chan, Ho Fai & Ulrich, Fabian & Altman, Hannah & Schmidt, Sascha L. & Schreyer, Dominik & Torgler, Benno, 2022. "Beyond performance? The importance of subjective and objective physical appearance in award nominations and receptions in football," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 271-289.
    11. Eiji Yamamura & Ryohei Hayashi & Yoshiro Tsutsui & Fumio Ohtake, 2022. "Racers’ attractive looks, popularity, and performance: how do speedboat racers react to fans’ expectations?," The Japanese Economic Review, Springer, vol. 73(4), pages 597-623, October.
    12. Cazachevici, Alina & Havranek, Tomas & Horvath, Roman, 2019. "Remittances and Economic Growth: A Quantitative Survey," EconStor Preprints 205812, ZBW - Leibniz Information Centre for Economics.
    13. Havranek, Tomas & Horvath, Roman & Zeynalov, Ayaz, 2016. "Natural Resources and Economic Growth: A Meta-Analysis," World Development, Elsevier, vol. 88(C), pages 134-151.
    14. Thi Mai Lan Nguyen, 2020. "Output Effects of Monetary Policy in Emerging and Developing Countries: Evidence from a Meta-Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(1), pages 68-85, January.
    15. David Ong, 2022. "The college admissions contribution to the labor market beauty premium," Contemporary Economic Policy, Western Economic Association International, vol. 40(3), pages 491-512, July.
    16. Deng, Weiguang & Li, Dayang & Zhou, Dong, 2019. "Beauty and Job Accessibility: New Evidence from a Field Experiment," GLO Discussion Paper Series 369, Global Labor Organization (GLO).
    17. Jindrich Matousek & Tomas Havranek & Zuzana Irsova, 2022. "Individual discount rates: a meta-analysis of experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 318-358, February.
    18. Sebastian Gechert & Tomas Havranek & Zuzana Irsova & Dominika Kolcunova, 2022. "Measuring Capital-Labor Substitution: The Importance of Method Choices and Publication Bias," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 55-82, July.
    19. Ahmed, Shaker & Ranta, Mikko & Vähämaa, Emilia & Vähämaa, Sami, 2023. "Facial attractiveness and CEO compensation: Evidence from the banking industry," Journal of Economics and Business, Elsevier, vol. 123(C).
    20. Zigraiova, Diana & Havranek, Tomas & Irsova, Zuzana & Novak, Jiri, 2021. "How puzzling is the forward premium puzzle? A meta-analysis," European Economic Review, Elsevier, vol. 134(C).

    More about this item

    Keywords

    Beauty bias; productivity; discrimination; meta-analysis; publication bias;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • J7 - Labor and Demographic Economics - - Labor Discrimination
    • 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:fau:wpaper:wp2020_18. 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: Natalie Svarcova (email available below). General contact details of provider: https://edirc.repec.org/data/icunicz.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.