Market Failure vs. The Invisible Hand:
Economic Consequences and Causes of Obesity in the United States
Alec Barlow
Spring 2010
Introduction
Obesity is often called an epidemic in the United States. Many social and economic
issues arise from its increasing prevalence, especially with regards to health care. As medical
technology advances, more treatments are being developed to help individuals that would not
have survived in previous times. While these individuals may be able to live to much older ages,
the amount of health care they consume over their lifetimes is significantly different based on
their whether or not they are obese. Obesity related conditions add $147 billion each year to
total health care expenditures in the United States, without including any possible costs affecting
other industries. Therefore, it may be in the taxpayers’ interest to have the government look into
policies that would reduce these costs. Besides creating cheaper treatments or improving the
efficiency of the health care delivery system, implementing policies aimed at reducing the
prevalence of obesity could be worthwhile. However, before determining how the government
could get involved, the causes of obesity need to be studied in order to determine if the
government even should become involved.
Previous literature remains divided on this issue. Studies that view obesity as a social
concern tend to favor government involvement in markets that may already be operating
effectively. On the other hand, studies that focus on the economic causes of obesity are reluctant
to say that government involvement is necessary because evidence for a market failure is hard to
find. This study attempts to find some supporting evidence for the existence of a market failure
by examining some unintended consequences of the Affordable Care Act of 2010. The law is
recent enough so that the literature reviewed by this study could not examine it.
This study begins by reviewing previous literature, starting with a definition of obesity
and the economic and social consequences related to it. It then looks at recent trends in the
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obese population, along with a discussion of factors that might have caused an increase in the
prevalence of obesity over time. Next, it reviews various arguments in order to determine
whether or not obesity is caused by a market failure. Finally, it develops a simple theoretical
model explaining this failure.
Literature Review
Health Risks
It is generally accepted that an individual is considered obese with a body mass index
(BMI) of at least 30. Obesity increases the risk of many complicating health conditions,
including cardiovascular disease, some cancers, and diabetes. Mortality rates resulting from
these conditions are, therefore, much higher in the obese population than in a slimmer population
(Flegal, 2007), reducing life expectancy by about 5 years (McPherson, 2008).
Economic and Social Consequences
In addition to higher morbidity and mortality risks, obesity leads to higher total health
care expenditures in the United States. Using regression models with data from the 1998 and
2006 Medical Expenditure Panel Surveys and the National Health Expenditure Accounts,
treating obesity related conditions was estimated to be $147 billion annually in 2008, half of
which is paid by the government, through Medicare and Medicaid. Per capita, obese individuals
cost 42% more than individuals of normal weight, or a difference of around $1,429 per year.
Also, it was estimated that almost 90% of the additional obesity related expenditures that
occurred between 1998 and 2006 was due to the increased prevalence of obesity, rather than the
use of more expensive treatment methods (Finkelstein, 2009).
Although obese individuals incur significant health care costs over the course of their
lifetimes, one study from the Netherlands estimated that total health expenditures were actually
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higher for healthy individuals because they lived longer; lethal diseases in obese individuals are
substituted for a greater number of non-lethal, more expensive diseases in the end-of-life years of
healthy individuals. Therefore, according to the authors, preventing obesity is not a way to
reduce health expenditures (van Baal, 2008).
While van Baal’s study comes to an interesting and, perhaps, counterintuitive conclusion,
it faces certain shortcomings. First, the results were simulated using the health care system in the
Netherlands, which had per capita health care expenditures that were almost half that of the
United States in 2007, $3,092 vs. $6,096, respectively (Infoplease.com). Expecting similar
results in a country with different demographics and health care delivery systems is not certain,
so the assumptions the authors rely on to create their simulation would probably have to be
altered, ultimately changing the results.
Obesity also has negative effects on productivity and national welfare. Productivity
losses occur in the form of premature death, health impairments, an increased risk of taking
disability pensions or worker’s compensation, and an increased risk and duration of sick leave.
Substantial weight loss in morbidly obese individuals was shown to reduce these risks. No
articles could be found that dispute these claims. However, the authors mention that their
estimates could be limited by “heterogeneity between studies” such as differing definitions of
sick leave or the study population’s demographic background (Neovius, 2008).
Obese individuals face various negative perceptions about their productive capability, as
well. A number of studies show that obese colleagues are perceived to “lack self-discipline, be
lazy, less conscientious, less competent, sloppy, disagreeable, and emotionally unstable” (Puhl,
2001). The existence of hiring prejudices, lower wages, and fewer promotion prospects relative
to non-obese employees may be the result of these perceptions (Puhl, 2001).
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Although Puhl heavily relies on self-reporting techniques, its findings provide evidence
for how the existence of obesity may hinder the ability of labor markets to optimally allocate
resources. If a perception bias against obese individuals exists, there would be a greater chance
that the obese population would be working in areas where their talents are not optimally suited
for.
Finding concrete evidence supporting this claim remains challenging, however. A
relationship between obesity and employment or wages was modeled using data from the British
National Child Development Study. With obesity as the only independent variable, a significant
wage penalty, 7.8% for men and 11.5% for women age 33, was observed, along with a lower
probability of employment, 4.5% for men and 6.1% for women age 33. After, controlling for
various other variables, including socioeconomic status, parental background, and cognitive
ability, substantially reduced these differences. The wage penalty became essentially zero for
men and 5.6% for women. The probability of employment was reduced to 2.7% for men and
4.6% for women. The authors, therefore, are unable to conclude whether obesity has a causal
effect on the labor market. Lower wages, leading to reduced total income, would tend to
increase the demand for cheaper, high-calorie, processed foods, thus creating the possibility of a
reversed relationship and complicating the author’s findings (Lindeboom, 2009).
Current trends
The results of the First National Health Examination Survey done between 1959 and
1962 showed an average BMI of 24.91 for persons over the age of 18, with just 12.73% defined
as obese. By the year 2000, however, a similar survey showed an average BMI of 27.85, along
with a dramatic increase in the percentage of obese individuals, totaling 29.57%. Much of this
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increase occurred during the 1980s and 1990s (Chou, 2004), while data taken between 2007 and
2008 showed obesity at relatively stable levels (Flegal, 2010).
Causes of Obesity
This increase in the obese population can partly be explained by factors in the labor
market starting in 1970s. When certain groups began seeing slower growth or even declines in
real income, coupled with an increase in hours worked and the labor participation rate, the
amount of time left for food preparation decreased. In turn, the demand for high-calorie,
inexpensive convenience food increased, and the per capita number of fast food and full-service
restaurants increased by 100% and 35%, respectively, between 1972 and 1997 (Chou, 2004).
The “increasing prevalence of convenience food and fast food is part of a long-term trend
away from labor-intensive preparation” (Chou, 2004) and it has paved the way for a “revolution
in the mass production of food” (Cutler, 2003) beginning in the 1980s. Yet, as technological
advances in food preservation and production have cut the amount of time spent preparing meals
from two hours in 1965 to less than one hour in 1995, certain implications have resulted.
First, the less time that is required to preparing a meal, the more meals an individual
tends to eat in a day, leading to a larger number of calories consumed (Cutler, 2003). Decreasing
preparation time lowers the “nonmonetary costs” of a meal, specifically the amount of labor
involved (Finkelstein, 2010). As stated earlier, less preparation time is also the result of trends in
the labor market requiring households to shift leisure activities to market work. This has helped
feed the growth of fast food and full-service restaurants, which tend to provide meals with high
caloric density. In addition, a reduction in the amount of time available for leisure means that
time devoted to exercise is also reduced, therefore lowering the number of calories burned in a
day (Chou, 2004).
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Second, the growth in mass produced food, with its relatively lower cost, tends to cause
individuals to consume a greater quantity of processed foods (Cutler, 2003). One measurement
of prices showed that since 1983, the price of fruit and vegetables has increased by 144%, while
the price of fats, sugars, and carbonated beverages has increased by 70%, 66%, and 32%,
respectively. As the price of processed foods decrease relative to healthier alternatives, their
quantity demanded will increase (Finkelstein, 2010).
Another article disputes these figures. It found that the consumer price index (CPI) of
fruits and vegetables has increased by 49% since 1980, while the price index of cakes, cupcakes,
and cookies has increased by only 6% during the same time. However, it is believed that the CPI
overstates the increase in price of fruits and vegetables. More specifically, quality improvements
and other factors that add value, like pre-cutting or bagging, are not taken into account by these
measurements. In fact, evidence suggests that the price trend of fresh, unprepared fruits and
vegetables has moved similarly to processed foods, making the relative cost of a healthy diet
unchanged over time (Kuchler, 2008). The increased demand of processed foods may be a
matter of shifting preferences, rather than economic constraints.
Is obesity caused by market failure?
Generally, government has a role to play when a market failure occurs. In other words,
when the private sector is unable to efficiently allocate resources on its own, the government
should consider whether it has the ability to create policies that could correct this (Finkelstein,
2010). Using this rational, if the government is responsible for reducing obesity in the
population, being obese must be the result of some type or market failure. Is this really the case?
One paper states that “obesity rates are not, in and of themselves, evidence of market
failure and may be evidence of the success of the market in producing affordable and convenient
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foods and labor saving goods and services” (Finkelstein, 2010). As stated before, the
development of processed foods has lowered the relative price of a meal and reduced the
nonmonetary costs of preparing it. Therefore, resources originally allocated to the preparation of
food can now be transferred to more productive uses.
Another paper evaluates two possible market failures that may cause obesity. The first of
these is that producers do not supply the types of food desired by consumers. This is unlikely
because a producer that ignores consumer preferences will not be viable for very long (Kuchler,
2004). The second case has to do with consumers lacking information and unintentionally
choosing to eat a poor diet. Restaurants do not have nutritional information listed for the food
they offer and they often have little incentive to disclose this information. The high fat and
calorie levels in the food they tend to produce gives the food a better flavor, and reducing these
levels, or simply disclosing them, would be a competitive disadvantage. Consumers may also
underestimate the number of calories they eat during a meal at these establishments. Evidence of
this comes from a study in 1996, which found that trained dietitians underestimated the calorie
content of restaurant meals by 37% (Kuchler, 2004). In addition, marketing campaigns may
distort information by focusing on the health benefits of consumption, like obtaining essential
vitamins, while ignoring the unhealthy ingredients (Brownwell, 2009).
It is difficult to conclude that obesity is caused by a market failure in the food industry.
In general, consumers have shifted their dietary preferences in response to societal factors, a
rational response. While it is true that some imperfect information exists, consumers generally
understand whether a certain food is healthy or not, even though they may underestimate just
how unhealthy some foods are.
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On the other hand, there could be evidence of a market failure in the way that health care
is paid for. The current system of insurance incentivizes consumers to make poor diet choices
due to time-inconsistent preferences, or decisions that provide short-term gratification but longterm harm. Therefore, the consequences of weight gain are discounted when individuals place
more value on present satisfaction because they do not bear the full costs of their decisions
(Brownwell, et al. 2009). Since insurance is pooled risk, the higher costs incurred are transferred
to others in the form of higher premiums. “Economic efficiency will be compromised if
individuals react to insurance by replacing healthy diets with…unhealthy ones” (Kuchler, 2004).
Using data from the Medical Expenditure Panel Survey, this health insurance externality was
estimated to reduce social welfare by $150 per capita in 1998 dollars. However, this cost largely
disappeared if the cost of insurance was weight dependent (Bhattacharya, 2006).
Commentary
Ultimately, the literature provides little evidence that obesity is currently caused by a
significant market failure. The literature does show that obesity probably reduces social welfare,
but without being able to target a market failure to correct, policies aimed at reducing the
prevalence of obesity, such as taxing unhealthy foods, would create inefficiencies in those
markets. However, the literature is not recent enough to account for the changes made by the
Affordable Care Act of 2010 (ACA), and the government may be exacerbating the health
insurance externality because the cost of insurance will be subsidized for certain income groups.
If these subsidies are large enough, they may increase the prevalence of obesity because the cost
burden that obese individuals bear would be reduced even further, thus providing less incentive
for one to become healthy. The next section attempts to model this externality.
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Theoretical Externality Model
The following model attempts to illustrate how a health insurance externality could
increase the prevalence of obesity. This model assumes that obese individuals have higher
medical expenditures over their lifetimes than healthy individuals, but their insurance premiums
are currently equal. It also focuses only on the cost of insurance, and by using the guidelines
given in the ACA, it assumes that this cost will remain constant each year. Finally, as a
theoretical model, numerical values are not used.
First, it is necessary to illustrate how a health insurance subsidy could increase the rates
of obesity. As stated in the literature review, individuals that do not bear all the costs of an
unhealthy diet have a greater incentive to engage in one. Figure 1 shows the reason for this.
Subsidized health insurance causes the marginal cost (MCS) of health improving behavior to
increase. In turn, individuals will cut back on this behavior from an optimal amount (Q*) to a
sub-optimal amount (QS), ultimately causing weight gain. The consequences of this lifestyle
remain, and may cause an additional increase in the size of the health insurance externality.
An increase in the size of the externality could also occur because the Affordable Care
Act fixes the private cost of insurance premiums to an individual’s income level. Figure 2
illustrates the implications of this policy. The total cost of health insurance for an individual is
shown by the curve TC. Subsidies, the size of which is shaded in blue, reduce the private cost
that an individual incurs to curve TCS. If enough individuals avoided health-seeking behavior
and became obese, the increase this would have on total health care expenditures would
inevitably shift the insurance cost curve up to TCO. With private costs fixed, the additional cost
would be absorbed by additional subsidies shaded in red. The increased subsidies would
ultimately be paid with taxes, adding to the social cost.
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Lastly, after taking into account these unintended consequences, the health insurance
externality is illustrated in Figure 3. Individuals with subsidized insurance have a private
marginal cost (PMC) curve lower than the social marginal cost (SMC) curve. The intersection of
the private marginal benefit (PMB) curve with these curves shows that at the market equilibrium
(Q1), the amount of health care consumed is greater than the socially optimal level (Q*). This
difference results in a welfare loss, shaded in red, in the form of higher taxes for those helping to
subsidize insurance costs.
Conclusion
This study examined the causes and consequences of obesity in order to find whether or
not the United States government should examine ways to reduce its prevalence. In order for the
government to get involved in an issue, markets must not be working effectively. A bias towards
the economic and social consequences of obesity can make the perceptions about solutions to
obesity differ with economic analysis. The targeting of processed or restaurant food is often
viewed favorably, but these markets remain effective and altering them would be an
irresponsible use of government resources. However, there is evidence that the system of health
insurance may cause obesity because when individuals share the cost of health care, an incentive
to engage in less healthy behavior arises. This study differed from previous literature because it
found additional evidence for this theory by modeling possible unintended consequences of the
ACA. It concludes that additional cost sharing for health care may actually increase the number
of obese individuals in the United States. If policies to reduce the prevalence were to be looked
at, they should begin with incentives within the system of insurance, not in other markets.
The results of this study were not what I had originally anticipated. I assumed that the
government could design a policy to reduce obesity levels by taxing unhealthy foods while
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subsidizing healthy ones and had planned to model the effects of such a plan. However, after
studying the previous literature, I realized that I had not considered the necessary factors that
warrant government involvement. Often, well-intentioned policies may have unanticipated
effects, so it is important that the government only become involved in markets when concrete
evidence of inefficiencies can be measured.
It would be worthwhile to do additional studies that look at obesity within the health
insurance system, particularly after the new exchanges begin in 2014. Obtaining data to test the
model developed in this study would also help to support its conclusion.
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References
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Thompson, and David S. Ludwig (Brownwell et al). “The Public Health and Economic Benefits
of Taxing Sugar-Sweetened Beverages.” New England Journal of Medicine, October 15 2009,
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Brownell, Kelly D. and Thomas R. Frieden. “Ounces of Prevention-The Public Policy Case for
Taxes on Sugared Beverages.” New England Journal of Medicine, April 30 2009, 1805 1808.
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behavioral risk factor surveillance system.” Journal of Health Economics 23, 565–587. 2004.
Cutler, D., Glaeser, E.L., & Shapiro, J.M. (2003). “Why have Americans become more obese?”
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Figures
Preference for Health seeking behavior
Figure 1: Subsidized health insurance increases the cost of
engaging in health seeking behavior.
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Cost/Benefit of Health Insurance
Figure 2: Subsidies lower the total private cost of insurance from
TC to TCS. As the prevalence of obesity increases, total cost shifts
From TC to TCO, but total private cost remains unchanged. The
original social cost of the subsidy, shaded blue, increased by the
amount shaded red.
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Social Welfare in the Health Insurance Market
Figure 3: An externality is created due to subsidized health insurance. Social
Welfare is reduced by the amount shaded in red.
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