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We quantify optimal urban transportation policies in the presence of congestion, network, and environmental externalities. We show theoretically that, beyond externality distortions, a budget constrained social planner introduces additional inefficiencies similar to those of a monopolist. We then move to an empirical analysis of the transportation system in Chicago based on an equilibrium model. To estimate supply and demand, we combine public sources and cellphone location records to construct a novel data set of the universe of public transit, ride-share, taxi, and car trips. Finally, we quantify optimal policies for a battery of scenarios. We find that congestion prices on private cars returns the largest efficiency gains relative to the status quo, but they cause a large, regressive decrease in consumer surplus.
