When does beauty pay? An ML based measurement of beauty bias. Malik N., Singh P.V. and Srinivasan K. 

Forthcoming at Information Systems Research. 2023.

Peer Reviewed Conferences


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 to 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 ten percent 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, 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 models. These models generate a time series of an individual's attractiveness through morphing 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.