Smoking, Expectations, and Health: A Dynamic Stochastic Model of Lifetime Smoking Behavior

This research discusses results obtained through formulation and estimation of a dynamic stochastic model that captures individual smoking decision making, health expectations, and longevity over the life cycle. The standard rational addiction model is augmented with a Bayesian learning process about the health marker transition technology to evaluate the importance of personalized health information in the decision to smoke cigarettes. Additionally, the model is well positioned to assess how smoking, and smoking cessation, impacts morbidity and mortality outcomes while taking into consideration the potential for dynamic selection of smoking behaviors. This research also provides a novel approach to the empirical construction of the theoretically common “smoking stock” that facilitates the estimation of investment and depreciation parameters. The structural parameters are estimated using rich longitudinal health and smoking data from the Framingham Heart Survey: Offspring Cohort. Results suggest that there exists heterogeneity across individuals in the pathways by which smoking effects health. Furthermore, upon smoking, the estimated parameters suggest a positive reinforcement effect and a negative withdrawal effect, both of which encourage future smoking. The paper also presents evidence of health selection in smoking behavior that, when not modeled, may cause an overstatement of the effect of smoking on morbidity and mortality. Finally, personalized health marker information is not found to significantly influence smoking behavior relative to chronic health shocks themselves.