Department of Economics, Georgia State University
The obesity rates for both adults and children have approximately tripled over the past half century, reaching “epidemic” proportions of 35% and 17%, respectively (Ogden et al., 2014; Fryar et al., 2012). Obesity is a natural subject for economic investigation because it is the result of behaviors that can be influenced by incentives. Over the past two decades, numerous researchers have attempted to identify the specific changes in incentives that explain the rise in obesity. The literature has made substantial progress toward identifying the underlying causes of the obesity epidemic, but much remains to be learned about which policies can reverse the trend and also the welfare implications of such policies.
The literature on the economics of obesity began with a few highly influential studies in the late 1990s and early 2000s. A seminal theoretical model by Philipson and Posner (1999) characterized the rise in obesity as a rational response to falling food prices (caused by increased agricultural productivity) and the rising opportunity cost of physical activity (caused by a shift toward sedentary employment). Lakdawalla et al. (2005) provided empirical evidence to support this theory. Cutler et al. (2003) agreed with the general characterization of obesity as the consequence of otherwise welfare enhancing technological progress, but they argued for the importance of innovations related to the time cost, rather than monetary cost, of food consumption. Chou et al. (2004) estimated an econometric model of adult obesity and found that restaurants per capita, grocery food prices, restaurant prices, cigarette prices, and smoking bans explained much of the trend. Anderson et al. (2003) found evidence that increased female labor force participation – which changed the supervision arrangements of children – contributed to the rise in childhood obesity. Cawley (2004) focused on the economic consequences of obesity rather than causes, finding evidence of a wage penalty for obese women.
In subsequent years, numerous studies have built on this early literature. Some, such as instrumental variable investigations of the effect of restaurants on obesity by Dunn (2010) and Anderson and Matsa (2011), contributed by revisiting the early results using more refined methods. Others evaluated additional potential contributing factors such as the proliferation of discount big-box grocers (e.g. Courtemanche and Carden, 2011), urban sprawl (e.g. Zhao and Kaestner, 2010), falling real gasoline prices during the 1980s and 1990s (e.g. Courtemanche, 2011), and the food stamp program (see the article by Maoyong Fan and Yanhong Jin in this newsletter). Courtemanche et al. (2016) included many of the economic factors alleged by prior literature to have contributed to the rise in obesity in an econometric “horse race”. Collectively, these factors explained nearly half of the rise in obesity and an even larger percentage of the rise in severe obesity, with the proliferation of restaurants and big box grocers standing out as playing particularly substantial roles. These results suggest that economists have made considerable progress in identifying the underlying causes of the obesity epidemic.
Nonetheless, identifying the appropriate role for obesity-fighting policy interventions remains challenging. As discussed above, the overarching theme of the economic causes of obesity literature is that the rise in obesity is a side effect of technological and societal progress. In that case, simply reversing the trends in the contributing factors is not a desirable solution. Moreover, if the rise in obesity is merely the artifact of individuals’ rationally re-optimizing in response to changing economic incentives, it is not clear that any policy intervention is warranted. The case for policy intervention hinges on whether market failures, not just market forces, are at work.
Three specific market failures have emerged as possible grounds for intervention. First, for obese individuals with health insurance, their health care expenditures can lead to a negative externality in the form of increased costs for others in the risk pool. Pigouvean approaches to internalizing the externality might include premium adjustments based on weight and taxes on products that contribute to obesity, such as soda. However, there is currently very little evidence to suggest that these strategies do much to change behavior. For instance, soda taxes appear to lead to substitution to other calorie-dense beverages rather than a reduction in overall calorie intake (e.g. Fletcher et al., 2010). Broad-based taxes on nutrients such as sugar might potentially be more effective than narrow taxes on specific products like soda (Harding and Lovenheim, 2014), but such policies could be at odds with other public health objectives such as eliminating hunger. More generally, it is possible that the external costs of obesity are actually internalized, as Bhattacharya and Bundorf (2009) find evidence that the additional health care from obesity are ultimately borne by obese employees with employer-sponsored insurance in the form of lower wages.
A second market failure is imperfect information about the behaviors that contribute to obesity. One example of such misinformation is the well-documented tendency for individuals to underestimate the calories in restaurant meals (e.g. Block et al., 2013). This has led to several localities implementing mandates for chain restaurants to post calories on menus and menu boards. A national mandate, passed as part of the Affordable Care Act, is scheduled to take effect in early 2017. Some recent evidence suggests that calorie labeling mandates may lead to weight loss, but the magnitude of the effect does not appear to be large enough to lead to substantial reductions in obesity (Deb and Vargas, 2016; Yelowitz, 2016; Restrepo, forthcoming).
A third potential market failure relates to the inability of individuals to act in their own long-run best interest. The existence of a multi-billion dollar weight loss industry provides evidence of regret in eating and exercise decisions. Such “mistakes” in optimization can be incorporated into either an economic model featuring time inconsistent preferences (e.g. Courtemanche et al., 2015) or a “dual-decision” model featuring internal tension between one’s long-run utility- maximizing self and another self concerned only with immediate pleasure (Ruhm. 2012). In either case, constraining one’s future choices can actually lead to welfare gains by preventing impulsive mistakes. Conversely, the expanded choices brought about by technological progress – such as the increased array of cheap processed foods and sedentary leisure time activities – could have led to more such mistakes and therefore welfare-reducing weight gain. However, mapping these insights into specific policy recommendations remains controversial.
In short, much has been learned from nearly two decades of economic investigations into the causes of obesity, and much remains to be learned in the decades to come. For readers interested in more detailed reviews of the obesity literature – particularly the work on the causes of childhood obesity and the consequences of obesity, which were only briefly addressed here – please see Cawley and Ruhm (2012) and Cawley (2015).
Anderson, P., Butcher, K., and Levine, P. (2003): “Maternal Employment and Overweight Children.” Journal of Health Economics, 22, 477-504.
Anderson, M.L. and Matsa, D.A. (2011): “Are Restaurants Really Supersizing America?” American Economic Journal: Applied Economics, 3, 152-188.
Bhattacharya, J. and Bundorf, M.K. (2009): “The Incidence of the Healthcare Costs of Obesity.” Journal of Health Economics, 28, 649-658.
Block, J.P., Condon, S.K., Kleinman, K., Mullen, J., Linakis, S., Rifas-Shiman, S., and Gillman,
M.W. (2013): “Consumers’ Estimation of Calorie Content at Fast Food Restaurants: Cross Sectional Observational study. British Medical Journal, 346: 1-10.
Cawley, J. (2004): “The Impact of Obesity on Wages.” Journal of Human Resources, 39, 451-474.
Cawley, J. (2015): “An Economy of Scales: A Selective Review of Obesity’s Economic Causes, Consequences,
and Solutions.” Journal of Health Economics, 43, 244-268.
Cawley, J. and Ruhm, C. (2012): “The Economics of Risky Health Behaviors.” Chapter 3 in Handbook of Health Economics, Vol. 2, 95-199.
Chou, S., Grossman, M. and Saffer, H. (2004): “An Economic Analysis of Adult Obesity: Results from the Behavioral Risk Factor Surveillance System.” Journal of Health Economics, 23, 565-587.
Courtemanche, C. (2011): “A Silver Lining? The Connection between Gasoline Prices and Obesity,” Economic Inquiry, 49, 935-957.
Courtemanche, C. and Carden, W.A. (2011): “Supersizing Supercenters? The Impact of Walmart Supercenters on Body Mass Index and Obesity,” Journal of Urban Economics, 69, 165-181.
Courtemanche, C., Heutel, G., and McAlvanah, P. (2015): “Impatience, Incentives, and Obesity.” Economic Journal, 125, 1-31.
Courtemanche, C., Pinkston, J., Ruhm, C. & Wehby, G. (2016): “Can Changing Economic Factors Explain the Rise in Obesity?” Southern Economic Journal, 82, 1266-1310.
Cutler, D., Glaeser, E. and Shapiro, J. (2003): “Why Have Americans Become More Obese?” Journal of Economic Perspectives, 17, 93-118.
Deb, P. and Vargas, C. (2016): “Who Benefits from Calorie Labeling? An Analysis of its Effects on Body Mass.” National Bureau of Economic Research Working Paper No. 21992.
Dunn, R.A. (2010). “The Effect of Fast-food Availability on Obesity: An Analysis by Gender, Race, and Residential Location.” American Journal of Agricultural Economics, 92(4):1149-1164.
Fletcher, J., Frisvold, D., and Tefft, N. (2010). “The Effects of Soft Drink Taxes on Child and Adolescent Consumption and Weight Outcomes.”
Fryar, C. D., Carroll, M. D., & Ogden, C. L. (2012). “Prevalence of Obesity among Children and Adolescents: United States, Trends 1963-1965 through 2009-2010. Available at www.cdc.gov/nchs/data/hestat/obesity_child_09_10/obesity_child_09_10.pdf
Harding, M. and Lovenheim, M. (2014). “The effect of prices on nutrition: comparing the impact of product-and nutrient-specific taxes.” National Bureau of Economic Research Working Paper No. 19781.
Lakdawalla, D., Philipson, T. and Bhattacharya, J. (2005): “Welfare-Enhancing Technological Change and the Growth of Obesity,” American Economic Review Papers and Proceedings, 95, 253-257.
Ogden, C.L., Carroll, M.D., Kit, B.K., Flegal, K.M. (2014): “Prevalence of Childhood and Adult Obesity in the United States, 2011-2012.” Journal of the American Medical Association, 311, 806-14.
Philipson, T. and Posner, R. (1999): “The Long-Run Growth in Obesity as a Function of Technological Change,” National Bureau of Economic Research Working Paper No. 7423.
Restrepo, B. (forthcoming): “Calorie Labeling in Chain Restaurants and Body Weight: Evidence from New York.” Health Economics.
Ruhm, C. (2012): “Understanding Overeating and Obesity,” Journal of Health Economics, 31, 781-796.
Yelowitz, A. (2016). “Menu Mandates and Obesity: A Futile Effort.” Policy Analysis, Cato Institute, No. 789.
Zhao, Z. and Kaestner, R. (2010): “Effects of Urban Sprawl on Obesity,” Journal of Health Economics, 29, 779-787.