Health Insurance and the Obesity Externality

Bhattacharya, Jay; Sood, Neeraj

doi:10.3386/w11529

Cited by 28 publications

(23 citation statements)

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“…6 We found evidence of a slight correlation but nothing to suggest that the model cannot produce unbiased estimates of the independent effects of caloric supply and physical activity. 7 Method 2.…”

Section: Part I: Calories In or Energy Outmentioning

confidence: 88%

“…In addition, obesity is responsible for ∼6%-10% of national health expenditures in the United States and 2%-4% in other developed countries (3,8,21,46,73,75). Moreover, the lifetime medical costs related to diabetes, heart disease, high cholesterol, hypertension, and stroke among the obese are $10,000 higher than among the nonobese (6).…”

Section: Introductionmentioning

confidence: 99%

“…We first translated the actual change in food supply for a particular country into the predicted weight gain, which was then allocated proportionally across individuals within each country according to their BMI percentile. We then compared the predicted BMI gain with the actual BMI gain 6 Correlations between caloric supply and unmeasured waste will underestimate the impact of caloric supply on percent obese, causing our estimate of the coefficient for caloric supply to shrink toward zero. Correlations between caloric supply and physical activity could go in either direction.…”

Section: Part I: Calories In or Energy Outmentioning

confidence: 99%

See 2 more Smart Citations

Why Is the Developed World Obese?

Bleich

Cutler

Murray

et al. 2008

Annu. Rev. Public Health

381

284

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Obesity has risen dramatically in the past few decades. However, the relative contribution of energy intake and energy expenditure to rising obesity is not known. Moreover, the extent to which social and economic factors tip the energy balance is not well understood. This exploratory study estimates the relative contribution of increased caloric intake and reduced physical activity to obesity in developed countries using two methods of energy accounting. Results show that rising obesity is primarily the result of consuming more calories. We estimate multivariate regression models and use simulation analysis to explore technological and sociodemographic determinants of this dietary excess. Results indicate that the increase in caloric intake is associated with technological innovations as well as changing sociodemographic factors. This review offers useful insights to future research concerned with the etiology of obesity and suggests that obesity-related policies should focus on encouraging lower caloric intake. 273*This PDF amended on (4 Dec. 2008): See explanation at

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Section: Part I: Calories In or Energy Outmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Section: Part I: Calories In or Energy Outmentioning

confidence: 99%

See 1 more Smart Citation

Why Is the Developed World Obese?

Bleich

Cutler

Murray

et al. 2008

Annu. Rev. Public Health

381

284

View full text Add to dashboard Cite

show abstract

“…the intensive margin) raises BMI. Bhattacharya and Sood (2007) calculate that the welfare loss in the U.S. associated with this second channel totals $150 per capita (in 1998 dollars). In summary, the obesity related externality that operates through insurance seems to be not just a transfer from the nonobese to the obese, but to also impose deadweight loss on society by distorting decisions about purchases of insurance and about optimal investment in weight loss and prevention of weight gain.…”

Section: Discussionmentioning

confidence: 99%

The Medical Care Costs of Obesity: An Instrumental Variables Approach

2010

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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 obesityrelated externalities.

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“…The externality arises when health insurance premiums do not adjust to reflect enrollee weight, such as when the obese and the non-obese are lumped into a single risk pool. But this can be solved if insurance companies require obese people to pay higher insurance premiums and does not call for public policies (Bhattacharya & Sood, 2005;Philipson & Posner, 2008). Indeed, some employers and health insurance companies already offer incentives for employers to engage in healthier behaviors (Mello & Rosenthal, 2008).…”

Section: Obesity Externality and Time-inconsistent Preferencesmentioning

confidence: 99%

Life satisfaction, overweightness and obesity

Kuroki

2016

Intnl. J. Wellbeing

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Many economists share the view that the rise in obesity is largely the result of rational decision-making by individuals who compare risks and benefits. A dominant view among economists is that there is no economic justification for government intervention unless there is a market failure. However, recent developments in behavioral economics suggests that people often fail to make optimal decisions, and that public welfare may be improved by government interventions even when there is no externality. This paper examines the association between one's body weight and life satisfaction by utilizing data on self-reported life satisfaction, which approximates individual utility, after briefly reviewing the economics of obesity and discussing the rationale and justification of obesity-related policies. Using a large data set (N = 1,465,219), it is found that life satisfaction of people who are overweight or obese is lower. The adverse life satisfaction effect of obesity remains statistically significant, even when socioeconomic factors and obesity-related health variables are controlled. The findings suggest that many overweight and obese people may be making sub-optimal decisions when it comes to eating. While the findings are not causal and thus do not necessarily suggest that government intervention will be welfareenhancing even in the absence of negative externalities, effective anti-obesity policies may lead to higher life satisfaction among many overweight people who are struggling with self-control problems.

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Health Insurance and the Obesity Externality

Cited by 28 publications

References 0 publications

Why Is the Developed World Obese?

Why Is the Developed World Obese?

The Medical Care Costs of Obesity: An Instrumental Variables Approach

Life satisfaction, overweightness and obesity

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