Specific Objectives of the Project

This project investigated the effect of transportation technology shocks on land
development within and around cities. Reductions in transportation costs over
time have resulted in land use conversion (generally agricultural to urban, as
cities expand), leading to urban sprawl and traffic congestion. Motivated by a
rapidly transforming transportation sector (e.g. high-speed rail, uber, driverless
cars), we estimated how historical changes in transportation costs have affected
urban growth in order to inform policies that promote optimal regulation of new
expansion and development.

Summary of Results

We create a novel dataset to better understand the dynamics of city growth and
transportation: national data on housing (38 million residential real estate
transactions and housing attributes from Public Records), employment (locations
and wages from the US Census County Business Patterns), and transportation
(travel times from Google, rideshare coverage from Uber). We examined how
three changes in transportation costs - (1) the National Maximum Speed Law, (2)
gasoline prices, and (3) the rollout of Uber and Lyft - have affected the structure
of cities and land price gradients within cities. I find that real estate prices
respond quickly and significantly to transportation cost changes. Housing price
changes vary with distance from the city. While changes in marginal costs (time
and fuel) have increased prices in the suburbs and encouraged suburbanization,
ridesharing services have led to larger price increases near city-centers. Future
research will explore whether the price changes from services like Uber are
attributable to substitution away from car ownership.