...voluminous research in the fields of medicine, public health, and, increasingly of late, economics. The weight distribution in the United States has not only made considerable shift to the right--average adult female weight, for example, increased by 20 pounds, or 13.5%, between 1976-1980 (National Health and Nutrition Examination Survey [NHANES] II) and 1999-2000 (NHANES 99)--but the upper tail has experienced disproportionate growth: for women over the same time span, 95th-percentile weight grew 16.7%, from 215 to 251 pounds, and 99th-percentile weight increased 18.2%, from 258 to 305 pounds, as shown in Table 1 and Figure 1. (1,2) The official definition of obesity employed by the Centers for Disease Control and Prevention (CDC) and by the World Health Organization is a body mass index (BMI) value of 30 or greater, where BMI is the ratio of weight, measured in kilograms, to squared height, measured in meters. For a 5'4" woman, 175 pounds or greater classifies as obese, and for a 5'9" man, the obesity threshold is 203 pounds. (3)

A number of papers in economics have sought to explain obesity growth among American adults over varying time spans of recent history. The explanations have focused on standard economic influences, such as falling food prices and preparation time costs and reductions in physical labor on the job. (4) The theoretical models offered study representative agents and speak primarily to secular trends in average weight. Although the model of Cutler, Glaeser, and Shapiro (2003) (henceforth CGS), emphasizing self-control problems, can predict growth in upper quantile weights relative to the mean, the prediction is sensitive to the empirical variation in self-control over food intake, variation that is not well understood. The prior works abstract from biological heterogeneity--acknowledged by Cawley (1999) and Chou, Grossman, and Saffer (2004) as a major factor in weight variation--and either ignore or hold fixed social influences on weight determination. In this paper, we argue that a richer description of the social and biological determinants of weight gain--interacted with falling food prices--contributes substantially to a more complete understanding of the evolution of the weight distribution over the past 30 yr.

In our choice model, utility depends on food and nonfood consumption and on how individual weight compares with a social weight standard or norm. Extensive research in the fields of social psychology and sociobiology asserts that standards of physical appearance are powerful motivators of human behavior, although these disciplines may disagree on the forces that determine the content of such standards. (5) Previous models of weight determination have incorporated weight standards into the utility function via various exogenous constructs: Lakdawalla and Philipson (2002) refer to an "ideal weight"; Levy (2002) posits a "sociocultural weight norm"; and CGS posit a social- and health-related cost of weight gain. In contrast, we posit an endogenous social weight standard that depends on aggregate behavior in the social group. This specification generates a number of predictions that differ from those that arise when norms are held fixed, and we find that the data provide stronger support for the model with flexible, socially determined norms.

[FIGURE 1 OMITTED]

Through analytical results and calibrated simulations, we illustrate how food price declines affect the entire weight distribution and describe explicit adjustment dynamics across long-run equilibria. The metabolic model and simulations are calibrated to American women aged 30-60 yr. This demographic restriction enhances the calibration's precision, because the physiological and social processes we consider are gender and age-group specific. Consistent with the data for this demographic group, observed in the NHANES II, NHANES III, and NHANES 99 studies, we predict large increases in mean weight, and even larger gains in upper quantile weights, as the food price falls. For simulated price declines based on independently estimated trends in the full price per calorie of food, including both the money price and the time costs, the predictions match the quantitative changes in average weight and the obesity rate for this group with considerable accuracy. Counterfactual simulations in which weight norms are fixed do not explain the data as well. Depending on how rapidly the weight aspiration adjusts to changing behavior, the dynamic analysis shows that equilibrium adjustments may occur with a substantial lag, helping to explain the observations, over the past 10 yr, that food prices have been roughly flat and yet average weight and obesity rates have continued to rise.

Among a number of genetically influenced physiological factors known to affect weight and BMI, the basal metabolic rate (BMR)--the calories expended per day in the maintenance of involuntary bodily functions with the body at rest--is arguably the most important and is relatively easy (yet expensive) to measure. Using a well-known data set containing direct observations of BMRs, we estimate parametric models of metabolism in relation to body weight, including a description of its idiosyncratic component. By embedding the metabolic model into the economic choice model, we can describe complete weight distributions at each food price. More important than capturing cross-sectional weight variation (and metabolic variation appears capable of explaining a substantial portion of the latter), the metabolism model holds nonobvious consequences for the evolution of the distribution over time as prices fall: the marginal effect of calorie consumption increases, on average, as average weight grows, even with no change in the distribution of genetic endowments.

Social comparison in the model implies that individuals aspire to weigh less (by some fraction) than average weight in the population at a given time. This endogenous weight aspiration therefore increases as food prices fall, because the price decline causes average weight to increase. Although it is difficult to observe weight norms directly, this prediction agrees with the observation that the sell-reported "desired weights" of Americans increased significantly between 1994 and 2002, complicating the conventional wisdom that media images emphasizing thinness dictate weight aspirations. The data on desired weight come from the CDC's Behavioral Risk Factor Surveillance System (BRFSS), which contains self-reported desired weights and actual weights for the same individuals. (6) While the data are not longitudinal, observations from different survey years are instructive of overall trends. In 1994, average weight for an American woman was 147 pounds, and the average desired weight was 132 pounds. By 2002, the average had increased to 153 pounds, and average desired weight had increased to 135 pounds. These figures--which follow similar patterns expressed in terms of BMI--suggest a reduction in (implicit or explicit) social pressure to maintain lower weights. The recent survey of weight perception by Rand and Resnick (2000) finds that 87% of Americans, including 48% of obese Americans, believe that their body weight falls in the "socially acceptable" range.

The remainder of the paper is organized as follows. Section II describes the theoretical model. Section III analyzes the comparative static effects of price on equilibrium weights, the weight norm, and welfare. In Section IV, we simulate equilibrium weight distributions under three different price levels and simulate the dynamic adjustment paths across equilibria. We compare our results with benchmark models involving weight-linear metabolism, a fixed weight norm, and forward-looking (as opposed to myopic) behavior. In Section V, we evaluate explanations for the evolution of the weight distribution (again under falling food prices) based on variation in self-control and addiction to food. Section VI discusses policy implications and predictions on the future of obesity.

II. THEORETICAL FRAMEWORK

Agent-Based Model

The theoretical model takes an agent-based approach, positing that genetically heterogeneous individuals interact within a social group. The nature of the interaction is that each individual compares her own weight to the group's commonly held norm or "desired" weight, and this comparison enters her optimization problem. Desired weight is defined as a fraction, less than 1, of average weight in the group and is therefore subject to change over time. This specification, in which people aim to be thinner than the average person in the reference population, combines two basic assumptions: (1) in contemporary Western society, thinness (up to a point) is prized and (2) individuals assess themselves in relation to others rather than against an absolute scale. The latter assumption follows the social interactions literature in economics, as well as longstanding traditions in sociology and social psychology, in stressing the notion that people are concerned with being normal in relation to their peers. (7) This specification creates room for gaps between the prevailing white Western ideal of thinness and the de facto standards to which individuals aspire, and ours is consequently not a model of the evolution of the media ideals themselves.

The assumption of a common (relative) weight norm is admittedly highly stylized, and we recognize that individual weight aspirations are likely to exhibit idiosyncratic variation. In the BRFSS data for 30- to 60-yr-old women, the coefficient of variation of desired weight is 13.9%. However, the coefficient of variation of actual weight is significantly greater, at 23.1%. (8) In addition, race is a significant explanatory factor in desired weight for this sample. (Figure 2 plots mean desired weights against mean actual weights for various demographic groups.) These facts suggest the presence of a social component in the formation of weight aspirations. In assuming that the weight target is uniform across individuals, the model takes the stylized view that this demographic constitutes a coherent social group. (9) Thus, the model is likely to generate less variation than one with idiosyncratic preference shocks or multiple subgroup-specific weight targets. This approach therefore constitutes a conservative test of the explanatory power of social weight norms. (10)

Equilibrium is defined as a weight distribution and a norm that are mutually consistent. Each individual maximizes a myopic utility function over short-term food and nonfood consumption, taking the reference weight and prices into account. (11) Food and nonfood consumption are both good, but deviation from the reference weight is bad. A general expression of the one-period utility model is as follows:

(1) [U.sub.it][[F.sub.t], [C.sub.t]|[W.sub.t-1]] = [G.sub.i][[F.sub.it], [C.sub.it]] - J[([W.sub.it][[F.sub.it], [W.sub.i,t-1], [[epsilon].sub.i]] -[M.sub.t-1]).sup.2].

[F.sub.t], and [C.sub.t] represent food and nonfood consumption, respectively, for period t. [W.sub.t - 1] is weight at the end of period t - 1 and is a product of past actions. Individual heterogeneity is captured by [[epsilon].sub.i], which is a stationary shock to basal metabolism, described below. [G.sub.i] is the norm-independent component of utility: it is strictly increasing and strictly concave in C and strictly concave but not necessarily monotonic in F. The term J([W.sub.it][[F.sub.it], [W.sub.i,t - 1], [[epsilon].sub.i]] - [M.sub.t-1]) (2) gives the social interaction component, which is the cost of deviating from the reference weight, M. The subscript on M indicates that agents observe the value of the reference weight (M) at the end of the period t - 1 and take this as fixed in the optimization; in particular, they do not forecast the value of the reference weight (M) that will emerge as a consequence of aggregate behavior in period t. The coefficient J gives the strength of the social interactions, which is held constant across individuals. The presence of a norm has the intuitive effect of lowering the variance of weight in the population, even though not everyone conforms to the norm exactly.

The individual correctly anticipates her own end-of-period weight as a function of food intake and so takes into account the effect of current food consumption on the cost of deviating from the reference weight. This cost is symmetric--it is just as undesirable to be underweight relative to the norm as to be overweight--and is meant to capture several known types of sanctions. Stigmatization of overweight (and underweight) individuals has been documented by Myers and Rosen (1999), among others, and may entail teasing, ostracism, and discrimination in hiring. Contagion regarding eating behavior among adolescent girls has been observed by Crandall (1988). Ross (1994) finds that some overweight individuals become depressed as a direct result of negative self-perception and that these individuals tend to belong to social groups with a low incidence of overweight. Graham and Felton (2005) also find that obesity contributes to depression (while rejecting the reverse causality): however, they find that obesity does not raise depression risk significantly among African American women, a group with one of the highest obesity...

NOTE: All illustrations and photos have been removed from this article.



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