We explore the impact of rising incomes at the top of the distribution on spatial sorting patterns within large U.S. cities. We develop and quantify a spatial model of a city with heterogeneous agents and non-homothetic preferences for neighbourhoods with endogenous amenity quality. As the rich get richer, demand increases for the high-quality amenities available in downtown neighbourhoods. Rising demand drives up house prices and spurs the development of higher quality neighbourhoods downtown. This gentrification of downtowns makes poor incumbents worse off, as they are either displaced to the suburbs or pay higher rents for amenities that they do not value as much. We quantify the corresponding impact on well-being inequality. Through the lens of the quantified model, the change in the income distribution between 1990 and 2014 led to neighbourhood change and spatial resorting within urban areas that increased the welfare of richer households relative to that of poorer households, above and beyond rising nominal income inequality.

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 develop a methodology to estimate robust city-level vehicular speed indices, exactly decomposable into uncongested speed and congestion. We apply it to 180 Indian cities using 57 million simulated trips measured by a web mapping service. We verify the reliability of our simulated trips using a number of alternative data sources, including data on actual trips. We find wide variation in speed across cities that is driven more by differences in uncongested speed than congestion. Denser and more populated cities are slower, only in part because of congestion. Urban economic development is correlated with faster speed despite worse congestion. (JEL O15, O18, R23, R41)