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When Does Beauty Pay? A Large-Scale Image-Based Appearance Analysis on Career Transitions

Author

Listed:
  • Nikhil Malik

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

  • Param Vir Singh

    (Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Kannan Srinivasan

    (Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

Abstract

We compare the career outcomes of MBA graduates with attractive and plain-looking faces. Our findings reveal that attractive MBA graduates have a higher probability of holding more desirable jobs compared with their plain-looking counterparts 15 years after obtaining their MBA degree, resulting in a 15-year attractiveness premium of 2.4%. This premium corresponds to an annual salary differential of $2,508. Additionally, we observed an “extreme” attractiveness premium of over 11% for the top 10% most attractive graduates, leading to a yearly salary differential of $5,528. Notably, this attractiveness premium is accumulated persistently over a decade. Moreover, the attractiveness premium is more pronounced among arts undergraduate graduates and those in managerial roles or the management industry, as opposed to those with IT backgrounds or working in technical jobs or the IT industry post-MBA. To achieve these results, we devised a robust methodological framework that combines custom machine learning (ML) models. These models generate a time series of an individual’s attractiveness by morphing a single profile picture and determine career success by ranking job titles based on revealed preferences in job transitions. Additionally, we employed a quasi-experiment design using propensity score matching to ensure the accuracy and reliability of our analysis.

Suggested Citation

  • Nikhil Malik & Param Vir Singh & Kannan Srinivasan, 2024. "When Does Beauty Pay? A Large-Scale Image-Based Appearance Analysis on Career Transitions," Information Systems Research, INFORMS, vol. 35(4), pages 1524-1545, December.
  • Handle: RePEc:inm:orisre:v:35:y:2024:i:4:p:1524-1545
    DOI: 10.1287/isre.2021.0559
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