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The Medical Care Costs of Obesity: An Instrumental Variables Approach

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  • John Cawley
  • Chad Meyerhoefer

Abstract

This paper is the first to use the method of instrumental variables (IV) to estimate the impact of obesity on medical costs in order to address the endogeneity of weight and to reduce the bias from reporting error in weight. Models are estimated using data from the Medical Expenditure Panel Survey for 2000-2005. The IV model, which exploits genetic variation in weight as a natural experiment, yields estimates of the impact of obesity on medical costs that are considerably higher than the correlations reported in the previous literature. For example, obesity is associated with $676 higher annual medical care costs, but the IV results indicate that obesity raises annual medical costs by $2,826 (in 2005 dollars). The estimated annual cost of treating obesity in the U.S. adult non-institutionalized population is $168.4 billion or 16.5% of national spending on medical care. These results imply that the previous literature has underestimated the medical costs of obesity, resulting in underestimates of the cost effectiveness of anti-obesity interventions and the economic rationale for government intervention to reduce obesity-related externalities.

Suggested Citation

  • John Cawley & Chad Meyerhoefer, 2010. "The Medical Care Costs of Obesity: An Instrumental Variables Approach," NBER Working Papers 16467, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16467
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    1. Neil Mehta & Virginia Chang, 2009. "Mortality attributable to obesity among middle-aged adults in the united states," Demography, Springer;Population Association of America (PAA), vol. 46(4), pages 851-872, November.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Jay Bhattacharya & Neeraj Sood, 2011. "Who Pays for Obesity?," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 139-158, Winter.
    4. Alberto Abadie & Joshua Angrist & Guido Imbens, 2002. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Econometrica, Econometric Society, vol. 70(1), pages 91-117, January.
    5. Finkelstein, E.A. & Trogdon, J.G., 2008. "Public health interventions for addressing childhood overweight: Analysis of the business case," American Journal of Public Health, American Public Health Association, vol. 98(3), pages 411-415.
    6. Burkhauser, Richard V. & Cawley, John & Schmeiser, Maximilian D., 2009. "The timing of the rise in U.S. obesity varies with measure of fatness," Economics & Human Biology, Elsevier, vol. 7(3), pages 307-318, December.
    7. John Komlos & Marek Brabec, 2010. "The Trend of Mean BMI Values of US Adults, Birth Cohorts 1882-1986 Indicates that the Obesity Epidemic Began Earlier than Hitherto Thought," NBER Working Papers 15862, National Bureau of Economic Research, Inc.
    8. Partha Deb & Pravin K. Trivedi, 2006. "Maximum simulated likelihood estimation of a negative binomial regression model with multinomial endogenous treatment," Stata Journal, StataCorp LP, vol. 6(2), pages 246-255, June.
    9. Schroeter, Christiane & Lusk, Jayson & Tyner, Wallace, 2008. "Determining the impact of food price and income changes on body weight," Journal of Health Economics, Elsevier, vol. 27(1), pages 45-68, January.
    10. Frazis, Harley & Loewenstein, Mark A., 2003. "Estimating linear regressions with mismeasured, possibly endogenous, binary explanatory variables," Journal of Econometrics, Elsevier, vol. 117(1), pages 151-178, November.
    11. Marquis, M. Susan & Long, Stephen H., 1995. "Worker demand for health insurance in the non-group market," Journal of Health Economics, Elsevier, vol. 14(1), pages 47-63, May.
    12. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    13. Jay Bhattacharya & Neeraj Sood, 2005. "Health Insurance and the Obesity Externality," NBER Working Papers 11529, National Bureau of Economic Research, Inc.
    14. Partha Deb & Pravin K. Trivedi, 2006. "Specification and simulated likelihood estimation of a non-normal treatment-outcome model with selection: Application to health care utilization," Econometrics Journal, Royal Economic Society, vol. 9(2), pages 307-331, July.
    15. John Cawley, 2004. "The Impact of Obesity on Wages," Journal of Human Resources, University of Wisconsin Press, vol. 39(2).
    16. Oster, G. & Thompson, D. & Edelsberg, J. & Bird, A.P. & Colditz, G.A., 1999. "Lifetime health and economic benefits of weight loss among obese persons," American Journal of Public Health, American Public Health Association, vol. 89(10), pages 1536-1542.
    17. James W. Hardin & Henrik Schmeidiche & Raymond J. Carroll, 2003. "Instrumental variables, bootstrapping, and generalized linear models," Stata Journal, StataCorp LP, vol. 3(4), pages 351-360, December.
    18. Brendan Kline & Justin L. Tobias, 2008. "The wages of BMI: Bayesian analysis of a skewed treatment-response model with nonparametric endogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 767-793.
    19. Jay Bhattacharya & M. Kate Bundorf & Noemi Pace & Neeraj Sood, 2011. "Does Health Insurance Make You Fat?," NBER Chapters, in: Economic Aspects of Obesity, pages 35-64, National Bureau of Economic Research, Inc.
    20. Jason M. Fletcher & David Frisvold & Nathan Tefft, 2010. "Can Soft Drink Taxes Reduce Population Weight?," Contemporary Economic Policy, Western Economic Association International, vol. 28(1), pages 23-35, January.
    21. Markus Frolich & Blaise Melly, 2010. "Estimation of quantile treatment effects with Stata," Stata Journal, StataCorp LP, vol. 10(3), pages 423-457, September.
    22. Steven C. Hill & G. Edward Miller, 2010. "Health expenditure estimation and functional form: applications of the generalized gamma and extended estimating equations models," Health Economics, John Wiley & Sons, Ltd., vol. 19(5), pages 608-627, May.
    23. Burkhauser, Richard V. & Cawley, John, 2008. "Beyond BMI: The value of more accurate measures of fatness and obesity in social science research," Journal of Health Economics, Elsevier, vol. 27(2), pages 519-529, March.
    24. Shiell, Alan & Gerard, Karen & Donaldson, Cam, 1987. "Cost of illness studies: An aid to decision-making?," Health Policy, Elsevier, vol. 8(3), pages 317-323, December.
    25. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
    26. Gruber, Jonathan & Washington, Ebonya, 2005. "Subsidies to employee health insurance premiums and the health insurance market," Journal of Health Economics, Elsevier, vol. 24(2), pages 253-276, March.
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    More about this item

    JEL classification:

    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • I1 - Health, Education, and Welfare - - Health

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