We estimate an equilibrium sorting model of housing location and commuting mode choice with endogenous traffic congestion to evaluate the efficiency and equity impacts of a menu of urban transportation policies. Leveraging fine-scale data from household travel diaries and housing transaction data identifying residents’ home and work locations in Beijing, we recover structural estimates with rich preference heterogeneity over both travel mode and residential location decisions. Counterfactual simulations demonstrate that even when different policies reduce congestion to the same degree, their impacts on residential sorting and social welfare differ drastically. First, driving restrictions create large distortions in travel choices and are welfare reducing. Second, distance-based congestion pricing reduces the spatial separation between residences and workplaces and improves welfare for all households when it is accompanied by revenue recycling. Third, sorting undermines the congestion reduction under driving restrictions and subway expansion but strengthens it under congestion pricing. Fourth, the combination of congestion pricing and subway expansion delivers the greatest congestion relief and efficiency gains. It can also be self-financed, with the cost of subway expansion fully covered by congestion pricing revenue. Finally, eliminating preference heterogeneity, household sorting, or endogenous congestion significantly biases the welfare estimates and changes the relative welfare rankings of the policies.
DATE: Friday, October 21, 2022
TIME: 3:00-4:00 p.m.
LOCATION: Fronczak 444