Air pollution and traffic congestion are two of the most pressing urban challenges in many fast-growing economies. Various transportation policies from both the demand and supply sides including congestion pricing, driving restrictions, the gasoline tax, and the expansion of public transit have been adopted to address these issues. We develop and estimate a residential location sorting model to examine the interactions of transportation policies and household sorting. The sorting model incorporate commuting decisions and generates equilibrium predictions of household locations under different transportation policies. We estimate the model parameters using a large household travel survey and rich housing transaction data in Beijing. The analysis illustrates the importance of incorporating travel mode choices in household location decisions and the importance of understanding sorting behavior in designing effective transportation policies.