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Where Does the Wage Penalty Bite?

In: Economic Aspects of Obesity

  • Christian A. Gregory
  • Christopher J. Ruhm

The literature examining the relationship between body mass index (BMI) and wages has fairly consistently found that BMI has a negative impact on earnings for women, and less (if any) consequences for men. In this paper, we relax the assumption -- largely unquestioned in this research -- that the conditional mean of wages is linear or piecewise linear in body mass index (BMI). Using data from the 1986 and 1999-2005 Panel Study of Income Dynamics, we estimate semi-parametric wage models that allow earnings to vary with BMI in a highly flexible manner. For women, the results show that earnings peak at levels far below the clinical threshold of "obesity" or even "overweight". For men, our main estimates suggest a reasonably flat BMI-wage profile that peaks early in the "overweight" category. However, the results of instrumental variables (IV) models or specifications focusing on long-lags of BMI are more similar to those for women. The findings for females (and the IV estimates for males) suggest that it is not obesity but rather some other factor -- such as physical attractiveness -- that produces the observed relationship between BMI and wages. We also provide non-parametric estimates of the association between BMI and health expenditures, using data from the Medical Expenditure Panel Survey. These cast further doubt on the hypothesis that the wage penalties associated with increasing BMI occur because the latter serve as an index for underlying medical costs.

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This chapter was published in:
  • Michael Grossman & Naci H. Mocan, 2011. "Economic Aspects of Obesity," NBER Books, National Bureau of Economic Research, Inc, number gros09-1, 07.
  • This item is provided by National Bureau of Economic Research, Inc in its series NBER Chapters with number 11824.
    Handle: RePEc:nbr:nberch:11824
    Contact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
    Phone: 617-868-3900
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    2. Wada, Roy & Tekin, Erdal, 2010. "Body composition and wages," Economics & Human Biology, Elsevier, vol. 8(2), pages 242-254, July.
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    4. Mobius, Markus & Rosenblat, Tanya, 2010. "Why Beauty Matters," Staff General Research Papers 32112, Iowa State University, Department of Economics.
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    9. John Cawley & Richard V. Burkhauser, 2006. "Beyond BMI: The Value of More Accurate Measures of Fatness and Obesity in Social Science Research," NBER Working Papers 12291, National Bureau of Economic Research, Inc.
    10. Susan Averett & Sanders Korenman, 1993. "The Economic Reality of the Beauty Myth," NBER Working Papers 4521, National Bureau of Economic Research, Inc.
    11. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
    12. Jeff E. Biddle & Daniel S. Hamermesh, 1995. "Beauty, Productivity and Discrimination: Lawyers' Looks and Lucre," NBER Working Papers 5366, National Bureau of Economic Research, Inc.
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    14. Bound, John, et al, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-68, July.
    15. Charles L. Baum & William F. Ford, 2004. "The wage effects of obesity: a longitudinal study," Health Economics, John Wiley & Sons, Ltd., vol. 13(9), pages 885-899.
    16. Duncan, Greg J & Hill, Daniel H, 1985. "An Investigation of the Extent and Consequences of Measurement Error in Labor-Economic Survey Data," Journal of Labor Economics, University of Chicago Press, vol. 3(4), pages 508-32, October.
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