Gravity model estimation with proxy variables and the impact of endogeneity on transportation planning

Abstract

This study presents an alternative method for estimating gravity models by multiple linear regression that is based on proxy variables, thus circumventing the endogeneity problems arising when least-squares estimators are used. The proxy variable approach generates consistent estimators for a gravity model without endogeneity bias. The presence of endogeneity is tested for using statistical tests developed specifically for our application. We conclude that proxy variables eliminate the endogeneity and produce consistent estimators in gravity models estimated using least squares. We also find, however, that endogeneity bias has no significant impact either on gravity model prediction or on urban transportation system planning processes based on such models.