Doctoral Dissertation Research in Economics: The Health Economics of Food Consumption and Obesity

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Obesity has become a leading health concern in the United States. The increasing prevalence of the disease, combined with the growing body of medical research linking obesity with other diseases, makes understanding obesity a primary concern of health-related research. This disease provides a unique opportunity for economics to contribute to a proper understanding of health because obesity, more so than most other diseases, ultimately results from a series of individual decisions that all consumers must make. Obesity, defined as an excessive amount of body fat, is the eventual outcome of an imbalance between caloric intake, or food consumption, and caloric expenditure, including resting metabolism and exercise. This research is designed to study the link between health investments and outcomes and subsequent medical expenditures attributable to the disease. In addition, this research will study the patterns in demand for different types of food, allowing for habit formation, in order to better understand the link between individual decisions and obesity.The first goal of this research is to study how individual health investments related to obesity impact health and medical expenditures in an environment with health insurance. First, a hazard model is estimated using individual medical histories collected in the National Health and Nutrition Examination Survey (NHANES) to calculate the increased probability of disease given individual weight history. These results are then linked with comprehensive medical expenditure data from the Medical Expenditure Panel Survey to estimate the financial cost of disease for overweight and obesity and how those costs are spread across insurance groups.The second goal of this research is to provide a richer understanding of how food consumption decisions can lead to obesity. The theoretical model is adapted from the Becker and Murphy model of rational addiction by allowing for habit formation with multiple addictive goods. The model is estimated by constructing a pseudo-panel using the NHANES spanning the years 1971-2002. This data does not include prices or expenditures, so restricted access to geographic identifiers is required for merging prices. This provides economic inferences out of this rich health data set. The results of the estimation will provide insight into the relative strength of habits for different types of foods as well as insight into the effectiveness of differenttypes of public intervention.The intellectual merit of this research comes not only from the theoretical contribution to economics, but also from its novel approach to dealing with the disease from a policy standpoint. One theoretical contribution of this research is the innovation of allowing for multiple addictive goods in one model. Specifically, this model allows for 'good' habits and 'bad' habits that are substitutes for one another. Previous studies of addiction have focused on one addictive good in isolation, or two addictive goods where the goods are complimentary. But, considering addictive substitutes is likely to provide insight into the study of many other addictive goods. In addition, this research seeks to connect studies estimating the costs of obesity with policy interventions designed to cover those costs. The connection between preventable medical costs and a food tax suggests a more focused direction for public policy than simply promoting better eating becauseobesity is bad.More broadly, this research will contribute to the public debate on overweight and obesity by contributing to the public understanding of how obesity impacts health and by providing the latest estimates of their cost. Furthermore, because habits in food consumption are likely to be important, the second stage of the research will provide specific guidance for policymakers about the effectiveness of several proposed policies. This research will be disseminated to the public through publication in peer-reviewed economic journals.