We investigate determinants of driving speed in large U.S. cities. We first estimate city-level supply functions for travel in an econometric framework where the supply and demand for travel are explicit. These estimations allow us to calculate an index of driving speed and to rank cities by driving speed. Our data suggest that a congestion tax of about 3.5 cents per kilometer yields welfare gains of about $30 billion per year, that centralized cities are slower, that cities with ring roads are faster, and that the provision of automobile travel in cities is subject to decreasing returns to scale.

We document how imperfect information generates heterogeneous effects in information treatments with personalized high-frequency feedback and peer comparisons. In our field experiment in retail electricity, we find that high- and low-energy users symmetrically underestimate and overestimate their relative energy use pretreatment. Responses to personalized feedback, however, are asymmetric. Households that overestimate their relative use and low users both respond by consuming more. These boomerang effects provide evidence that peer-comparison information programs, even those coupled with normative comparisons, are not guaranteed to lead to increases in prosocial behavior.