Abstract
Obesity, Fast Food, and Grocery Stores: Evidence from Geo-referenced Micro Data
Susan E. Chen, Raymond J.G.M. Florax, and Samantha D. Snyder, Purdue University
Description
In this research we provide unique quantitative estimates of the
effect of proximity to fast food and grocery stores on obesity. Our
empirical model combines geo-referenced micro data on access to fast
food restaurants and grocery stores with data about salient personal
characteristics, individual behaviors, and neighborhood
characteristics such as zoning and crime. We create a “local food
environment” for every individual utilizing 1/2 mile buffers
around a person's home address. Local food landscapes are
potentially endogenous due to spatial sorting of the population and
food outlets. The BMI of individuals living close to each other are
likely (spatially) correlated because of (un)observed individual and neighborhood effects. The biases associated with endogeneity and spatial correlation are handled with spatial econometric instrumental variables and general method of moments techniques. Our policy simulations focus on reducing the density of fast food restaurants, or alternatively increasing access to grocery stores. We account for spatial heterogeneity in both the policy instruments and the home location of individuals, and consistently find small and significant effects for the hypothesized relationships between fast food and grocery store density and individual BMI values.
Download final conference paper
