IDEAS home Printed from https://ideas.repec.org/p/war/wpaper/2023-06.html
   My bibliography  Save this paper

Modelling Subjective Attractiveness

Author

Listed:
  • Konrad Lewszyk

    (University of Warsaw, Faculty of Economic Sciences and Data Science Lab WNE UW)

  • Piotr Wójcik

    (University of Warsaw, Faculty of Economic Sciences and Data Science Lab WNE UW)

Abstract

Attractive people obtain greater economic and reproductive success. This article attempts to grasp individual preferences of facial attractiveness and create reliable models that will accurately predict a beauty score on a binary and quintary scale. Based on extensive research conducted on factors of attractiveness, we derive the most important facial features that have the highest impact in beauty perception. Based on a sample of 681 images of faces using facial a landmark detector. We derive various numerical features represented by face characteristics and. The application of various machine learning algorithms shows that attractiveness can be predicted accurately based on facial characteristics. In addition, we show that indeed the attractiveness is subjective as the same features have different importance for different subjects.

Suggested Citation

  • Konrad Lewszyk & Piotr Wójcik, 2023. "Modelling Subjective Attractiveness," Working Papers 2023-06, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2023-06
    as

    Download full text from publisher

    File URL: https://www.wne.uw.edu.pl/download_file/2564/0
    File Function: First version, 2023
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hamermesh, Daniel S. & Meng, Xin & Zhang, Junsen, 2002. "Dress for success--does primping pay?," Labour Economics, Elsevier, vol. 9(3), pages 361-373, July.
    2. Christian Pfeifer, 2012. "Physical attractiveness, employment and earnings," Applied Economics Letters, Taylor & Francis Journals, vol. 19(6), pages 505-510, April.
    3. Douglas W. Yu & Glenn H. Shepard, 1999. "The mystery of female beauty," Nature, Nature, vol. 399(6733), pages 216-216, May.
    4. Michael French, 2002. "Physical appearance and earnings: further evidence," Applied Economics, Taylor & Francis Journals, vol. 34(5), pages 569-572.
    5. 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.
    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. Henk Erik Meier & Michael Mutz, 2020. "Does Attractiveness Lead to or Follow From Occupational Success? Findings From German Associational Football," SAGE Open, , vol. 10(1), pages 21582440209, January.
    2. 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.
    3. Dilmaghani, Maryam, 2020. "Beauty perks: Physical appearance, earnings, and fringe benefits," Economics & Human Biology, Elsevier, vol. 38(C).
    4. 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.
    5. Mavisakalyan, Astghik, 2018. "Do employers reward physical attractiveness in transition countries?," Economics & Human Biology, Elsevier, vol. 28(C), pages 38-52.
    6. 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.
    7. 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).
    8. Guéguen, Nicolas, 2012. "Hair color and wages: Waitresses with blond hair have more fun," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 41(4), pages 370-372.
    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, 2006. "The Looks of a Winner: Beauty, Gender and Electoral Success," Ratio Working Papers 104, The Ratio Institute.
    11. Gan, Hongwu & Lu, Shengfeng & Lu, Weijie & Niu, Geng & Zhou, Yang, 2023. "Beauty and stock market participation," Journal of Banking & Finance, Elsevier, vol. 155(C).
    12. Cabane Charlotte & Lechner Michael, 2015. "Physical Activity of Adults: A Survey of Correlates, Determinants, and Effects," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(4-5), pages 376-402, August.
    13. Doorley, Karina & Sierminska, Eva, 2012. "Myth or Fact? The Beauty Premium across the Wage Distribution," IZA Discussion Papers 6674, Institute of Labor Economics (IZA).
    14. 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.
    15. Jobu Babin, J. & Hussey, Andrew & Nikolsko-Rzhevskyy, Alex & Taylor, David A., 2020. "Beauty Premiums Among Academics," Economics of Education Review, Elsevier, vol. 78(C).
    16. 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.
    17. French, Michael T. & Robins, Philip K. & Homer, Jenny F. & Tapsell, Lauren M., 2009. "Effects of physical attractiveness, personality, and grooming on academic performance in high school," Labour Economics, Elsevier, vol. 16(4), pages 373-382, August.
    18. Das, Tirthatanmoy & Polachek, Solomon, 2017. "Micro Foundations of Earnings Differences," IZA Discussion Papers 10922, Institute of Labor Economics (IZA).
    19. Oreffice, Sonia & Quintana-Domeque, Climent, 2016. "Beauty, body size and wages: Evidence from a unique data set," Economics & Human Biology, Elsevier, vol. 22(C), pages 24-34.
    20. 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).

    More about this item

    Keywords

    Attractiveness; beauty-premium; image processing; machine learning; predictive models;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

    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:war:wpaper:2023-06. 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: Marcin Bąba (email available below). General contact details of provider: https://edirc.repec.org/data/fesuwpl.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.