Essays in Transportation and Infrastructure Markets

Abstract

This dissertation studies the provision, operation, and benefits of transportation-related public goods. It focuses on how policy, regulation, and market design can improve these urban systems. The three chapters examine highway procurement, road maintenance, and public transit. Together, they use new data and quasi-experimental variation to study why infrastructure is costly to build, who bears the costs of experiencing poor infrastructure, and how public agencies should set prices and service quality. The first chapter studies whether limited competition in procurement auctions can explain the high and rising cost of U.S. road infrastructure. I assemble a new dataset covering the near-universe of state highway auctions between 2002 and 2024. I first document thin competition: one- or two-bidder auctions account for a third of awards, and this share has risen over the past decade. Using spatial variation in interstate bidder locations, I estimate that an additional bidder reduces prices by ten percent. I then develop a semi-parametric structural auction model to decompose bids into markups and production costs. The estimates imply that recent price growth is driven primarily by rising markups rather than rising production costs. Embedding the markup estimates in an entry model, I estimate large auction and market entry costs, consistent with an important role for procurement complexity and regulatory barriers. The second chapter, coauthored with Edward Glaeser and Gabriel Kreindler, studies the distributional costs of road roughness. The chapter measures road roughness throughout the United States using vertical acceleration data from Uber rides across millions of road segments. It estimates drivers’ willingness to pay to avoid roughness from speed changes around salient changes in road quality, including town borders and repaving events. One standard deviation of road roughness generates losses of $0.33 per driver-mile. Rough roads are concentrated in poorer places and neighborhoods with larger Black populations, while resurfacing is only weakly targeted to the roughest roads. The third chapter, coauthored with Lia Petrose, studies pricing and service quality in public transit. The chapter considers the problem of a welfare-maximizing transit agency subject to a budget requirement. Using rich MBTA data and quasi-experimental variation from a fare increase and salient service slowdowns, it estimates price and quality elasticities in a discrete-choice model with heterogeneity by neighborhood income. Riders are highly price-sensitive and moderately responsive to quality. Lower-income riders place greater value on lower fares and reliable service, but face fewer choice options. The estimates are used to study optimal subsidies and efficient pricing.