Research

I quantify the welfare implications of competition and capacity constraints on the spatial allocation of supply in transportation markets. Using new data on shared electric scooters, I analyze the market using a dynamic spatial structural model incorporating the role of capacity constraints, economies of density, and dynamic externalities across locations on firms’ decisions. Counterfactual simulations show that by internalizing the trade-off between business stealing and spatial differentiation, a monopolist would improve welfare by 27% compared to the current duopoly. Imposed citywide capacity constraints have a regressive nature, causing distributional concerns between high and low-income areas.

We develop a novel structural model to represent individual transportation decisions and the equilibrium road traffic levels and speeds inside a city. The model has two advantages relative to the existing frameworks. First, it is micro-founded and has a high level of heterogeneity. Individuals differ in access to transportation modes, values of travel time, and schedule constraints; road congestion technologies vary within the city. Secondly, we estimate the model parameters from publicly available data. We apply our model to Paris metropolitan area to predict the road traffic equilibria under driving restrictions and road tolls and measure the policies' welfare consequences.