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Beauty, Productivity, and Discrimination: Lawyers' Looks and Lucre
Abstract
We propose models with an ascriptive characteristic generating earnings differentials and causing sectoral sorting, allowing us to distinguish among sources producing such differentials. We use longitudinal data on a large sample of graduates from one law school and measure beauty by rating matriculation photographs. (1) Betterlooking attorneys who graduated in the 1970s earned more than others after 5 years of practice, an effect that grew with experience. (2) Attorneys in the private sector are better‐looking than those in the public sector, differences that rise with age. These results support theories of dynamic sorting and customer behavior.
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Cited by
Kukkonen, I., Pajunen, T., Sarpila, O., & Åberg, E. (2024) · European Societies · doi:10.1080/14616696.2023.2210202 · Cited by 43
“…2011; Kanazawa and Still 2018), better negotiators (Rosenblat 2008), or whether the preferences indeed cause employees to be more productive in certain fi elds of work where, for example, customer preferences are crucial for productivity (Biddle and Hamermesh 1998; Hamer-mesh and Biddle 1994).”
BackgroundOccupational Characteristics and the Obesity Wage Penalty
Shinall, J. B. (2014) · doi:10.2139/ssrn.2379575 · Cited by 17
Metadata
- Authors
- Biddle, J. E., & Hamermesh, D. S.
- Venue
- Journal of Labor Economics
- Publisher
- University of Chicago Press
- Published
- 1998-01
- Volume
- 16
- Issue
- 1
- Pages
- 172-201
- ISSN
- 0734-306X (ISSN-L)
- 1537-5307
- OpenAlex
- W3122918631
- Cited by
- 464
- References
- 0
- FWCI
- 11.43
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Beauty, Productivity, and Discrimination: Lawyers' Looks and Lucre. https://app.cochat.ai/papers/10.1086/209886
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- Biddle, J. E., & Hamermesh, D. S. (1998). Beauty, Productivity, and Discrimination: Lawyers' Looks and Lucre. Journal of Labor Economics. https://doi.org/10.1086/209886
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
