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Obesity and Hyperbolic Discounting: Evidence and Implications

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Abstract

Efforts to use nutrition education to combat the growing obesity problem in the USA have been largely unsuccessful. One possible reason for the persistence of the obesity problem is the presence of consumers who discount hyperbolically. To counter this phenomenon, sophisticated agents may try to employ commitment devices to protect long–term health goals from short–term consumption decisions. This study uses data from the Continuing Survey of Food Intakes by Individuals to examine the impact of hyperbolic discounting and use of commitment devices on individuals’ caloric consumption. The results suggest that obese dieters display behavior consistent with hyperbolic discounting.

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Notes

  1. It is becoming increasingly clear that rising caloric consumption is the primary mode by which obesity has increased. Cutler et. al. (2003) demonstrate that caloric intake rose by over 10% between 1977–1978 and 1994–1996, while energy expenditures remained relatively flat over this period. Similarly, Cawley et al. (2007) find that more days in physical education have no measurable effect on youth BMI.

  2. Standard economic theory suggests that each individual has a constant, exogenously determined rate of time preference. Under this theory, while different individuals might have different rates of time preference, a given individual acts based on a constant, unchanging rate of time preference that was developed in childhood. Becker and Mulligan (1997) challenged this assumption by suggesting that experiences that individuals have during adulthood might lead that individual’s rate of time preference to evolve over their lifetime. While this theory treats time preference in a manner similar to other preferences that are subject to change, it does not go so far as to assume that time preference is completely context dependent.

  3. Thaler and Benartzi (2004) note that the literature has assumed two possible types of agents: sophisticated and naïve. Sophisticated agents who seek to alter their behavior, as modeled by Laibson (1997), will overcome hyperbolic discounting by employing commitment devices. Alternatively, naïve agents will not employ these devices because they do not understand the problem they face. Thaler and Benartzi suggest that individual behavior reflects a mix of sophisticated and naïve behavior.

  4. Alternatively, that person could reward themselves with an instantaneous benefit for their healthy behavior. For example, one weight loss web site that records daily rates of food intake, exercise, weight measurements, and other relevant factors, rewards participants through a publicly visible point system and encourages members to congratulate those who successfully reach identified goals (see http://www.sparkpeople.com).

References

  • Angeletos, G.-M., Laibson, D., Repetto, A., Tobacman, J., & Weinberg, S. (2003). The hyperbolic consumption model: calibration, simulation, and empirical evaluation. In G. Loewenstein, D. Read, & R. Baumeister (Eds.), Time and decision (pp. 517–543). New York: Russell Sage Foundation.

    Google Scholar 

  • Ariely, D., & Wertenbroch, K. (2002). Procrastination, deadlines, and performance: Self-control by precommitment. Psychological Science, 13(3), 219–224.

    Article  Google Scholar 

  • Becker, G. S., & Mulligan, C. (1997). The endogenous determination of time preference. Quarterly Journal of Economics, 112(3), 728–758.

    Article  Google Scholar 

  • Bénabou, R., & Tirole, J. (2004). Willpower and personal rules. Journal of Political Economy, 112(4), 848–886.

    Article  Google Scholar 

  • Bickel, W. K., Odum, A. L., & Madden, G. J. (1999). Impulsivity and cigarette smoking: Delay discounting in current, never, and ex-smokers. Psychopharmacology, 146, 447–454.

    Article  Google Scholar 

  • Brocas, I., Carrillo, J. D., & Dewatripont, M. (2004). Commitment devices under self-control problems: An overview. In I. Brocas, & J. Carrillo (Eds.), The Psychology of economic decisions: Volume II: Reasons and choices (pp. 49–65). Oxford: Oxford University Press.

    Google Scholar 

  • Cawley, J., Meyerhoefer, C., & Newhouse, D. (2007). The impact of state physical education requirements on youth physical activity and overweight. Health Economics, 16(12), 1287–1301.

    Article  Google Scholar 

  • CDC (Centers for Disease Control and Prevention) (2006). Behavioral Risk Factor Surveillance System: Trends Data. Atlanta, GA: U.S. Department of Health and Human Services. Retrieved from http://apps.nccd.cdc.gov/brfss/Trends/TrendData.asp.

  • CDC (Centers for Disease Control and Prevention) (2007). Defining overweight and obesity. Atlanta, GA: Department of Health and Human Services, Retrieved from http://www.cdc.gov/nccdphp/dnpa/obesity/defining.htm.

  • Cutler, D., & Glaeser, E. (2005). What explains the differences in smoking, drinking, and other health-related behaviors? American Economic Review, 95(2), 238–242.

    Article  Google Scholar 

  • Cutler, D. M., Glaeser, E. L., & Shapiro, J. M. (2003). Why have Americans become more obese? Journal of Economic Perspectives, 17(3), 93–118.

    Article  Google Scholar 

  • FDA (Food and Drug Administration) (2004). Calories count. Rockville, MD: Department of Health and Human Services, Retrieved from http://www.cfsan.fda.gov/∼dms/owg-toc.html.

  • Flegal, K. M., Graubard, B. I., Williamson, D. F., & Gail, M. H. (2005). Excess deaths associated with underweight, overweight, and obesity. Journal of the American Medical Association, 293(15), 1861–1867.

    Article  Google Scholar 

  • Frederick, S., Loewenstein, G., & O’Donoghue, T. (2002). Time discounting and time preference: A critical review. Journal of Economic Literature, 40, 351–401 (June).

    Article  Google Scholar 

  • Fuchs, V. (1986). The Health Economy. Cambridge: Harvard University Press.

    Google Scholar 

  • Geier, A. B., Rozin, P., & Doros, G. (2006). Unit bias: A new heuristic that helps explain the effect of portion size on food intake. Psychological Science, 17(6), 521–525.

    Article  Google Scholar 

  • Grossman, M. (1972). On the concept of health capital and the demand for health. The Journal of Political Economy, 80(2), 223–255.

    Article  Google Scholar 

  • Henderson, J., & Low, S. (2006). Obesity: America’s economic epidemic. The Main Street Economist, 1(2), 1–5.

    Google Scholar 

  • Hersch, J. (2005). Smoking restrictions as a self-control mechanism. Journal of Risk and Uncertainty, 31(1), 5–21.

    Article  Google Scholar 

  • Just, D. R. (2006). Behavioral economics, food assistance, and obesity. Agricultural and Resource Economics Review, 35(2), 209–220.

    Google Scholar 

  • Kim, J.-Y. (2006). Hyperbolic discounting and the repeated self-control problem. Journal of Economic Psychology, 27, 344–359.

    Article  Google Scholar 

  • Kirby, K., & Herrnstein, R. (1995). Preference reversals due to myopic discounting of delayed reward. Psychological Science, 6(2), 83–89.

    Article  Google Scholar 

  • Laibson, D. (1997). Golden eggs and hyperbolic discounting. The Quarterly Journal of Economics, 112(2), 443–477.

    Article  Google Scholar 

  • Lakdawalla, D., & Philipson, T. (2002). The growth of obesity and technological change: A theoretical and empirical examination. NBER Working Paper #8946, Retrieved from http://www.nber.org/papers/w8946.

  • Lakdawalla, D., Philipson, T., & Bhattacharya, J. (2005). Welfare-enhancing technological change and the growth of obesity. American Economic Review, 95(2), 253–257.

    Article  Google Scholar 

  • Loewenstein, G., & Prelec, D. (1992). Anomalies in intertemporal choice: Evidence and an interpretation. The Quarterly Journal of Economics, 107(2), 573–597.

    Article  Google Scholar 

  • Mokdad, A., Ford, E., Bowman, B., Dietz, W., Vinicor, F., Bales, V., et al. (2003). Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. Journal of the American Medical Association, 289(1), 76–79.

    Article  Google Scholar 

  • Nayga, R. M. (2000). Schooling, health knowledge, and obesity. Applied Economics, 32, 815–822.

    Article  Google Scholar 

  • NCHS (National Center for Health Statistics) (2006). Prevalence of Overweight and Obesity among Adults: United States, 2003-2004. Hyattsville: U.S. Department of Health and Human Services. Retrieved from http://www.cdc.gov/nchs/products/pubs/pubd/hestats/obese03_04/overwght_adult_03.htm.

  • Orbell, S., Hodgkins, S., & Sheeran, P. (1997). Implementation intentions and the theory of planned behavior. Personality and Social Psychology Bulletin, 23(9), 945–954.

    Article  Google Scholar 

  • PHS (Public Health Service, Office of the Surgeon General) (2001). The Surgeon General’s Call to Action to Prevent and Decrease Overweight and Obesity. Rockville: U.S. Department of Health and Human Services.

    Google Scholar 

  • Read, D. (2001). Is time-discounting hyperbolic or subadditive? Journal of Risk and Uncertainty, 23, 5–32.

    Article  Google Scholar 

  • Read, D. (2006). Which side are you on? The ethics of self-command. Journal of Economic Psychology, 27, 681–693.

    Article  Google Scholar 

  • Samuelson, P. (1937). A note on measurement of utility. Review of Economic Studies, 4, 155–161.

    Article  Google Scholar 

  • Scharff, R. L., & Viscusi, W. K. (2009). Risk attitudes and heterogeneous rates of time preference. Economic Inquiry, in press.

  • Shapiro, J. M. (2005). Is there a daily discount rate? Evidence from the food stamp nutrition cycle. Journal of Public Economics, 89, 303–325.

    Article  Google Scholar 

  • Shiv, B., & Fedorikhin, A. (1999). Heart and mind in conflict: The interplay of affect and cognition in consumer decision making.”. Journal of Consumer Research, 26(3), 278–282.

    Article  Google Scholar 

  • Simonson, I. (2008). Will I like a “medium” pillow? Another look at constructed and inherent preferences. Journal of Consumer Psychology, 18, 155–169.

    Article  Google Scholar 

  • Smith, P. K., Bogin, B., & Bishai, D. (2005). Are time preference and body mass index associated? Evidence from the National Longitudinal Survey of Youth. Economics and Human Biology, 3, 259–270.

    Article  Google Scholar 

  • Strotz, R. (1956). Myopia and inconsistency in dynamic utility maximization. Review of Economic Studies, 23, 165–180.

    Google Scholar 

  • Ted, O. D., & Rabin, M. (1999). Doing it now or later. American Economic Review, 89(1), 103–124.

    Article  Google Scholar 

  • Thaler, R. H. (1981). Some empirical evidence on dynamic inconsistency. Economic Letters, 8, 201–207.

    Article  Google Scholar 

  • Thaler, R. H., & Benartzi, S. (2004). Save more tomorrow: Using behavioral economics to increase employee saving. Journal of Political Economy, 112(1), S164–S187.

    Article  Google Scholar 

  • Wansink, B. (2004). Environmental factors that increase the food intake and consumption volume of unknowing consumers. Annual Review of Nutrition, 24, 455–479.

    Article  Google Scholar 

Download references

Acknowledgements

I would like to thank 2007 Society for Risk Analysis conference participants and Ohio State University, Department of Consumer Sciences Seminar Series participants for their helpful comments on early drafts of this paper.

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Correspondence to Robert L. Scharff.

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Scharff, R.L. Obesity and Hyperbolic Discounting: Evidence and Implications. J Consum Policy 32, 3–21 (2009). https://doi.org/10.1007/s10603-009-9090-0

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