Estimation of a Dynamic Model of Weight
The ongoing debate about the economic causes of obesity has focused on the changing relative prices of diet and exercise. This paper uses a model that explicitly includes time and spatially varying community-level urbanicity and price measures as instruments to obtain statistically correct measures for the endogenous effects of diet, physical activity, drinking, and smoking on weight. We apply a dynamic panel system GMM estimation model to longitudinal (1991-2006) data from China to model weight and find that among adult men in China, about 6.1% of weight gain was due to declines in physical activity and 2.9-3.8% was due to dietary changes over this period. In the long run, physical activity can account for around 6.9% of weight gain, while diet can account for 3.2-4.2% of weight gain.
Published Versions
Shu Ng & Edward Norton & David Guilkey & Barry Popkin, 2012. "Estimation of a dynamic model of weight," Empirical Economics, Springer, vol. 42(2), pages 413-443, April. citation courtesy of