Commuting Infrastructure, Mode choice, and Spatial Misallocation

Closed to further applications
Faculty Member: 
This project is eligible for remote work.

Proposal Description:

Economic activity is increasingly concentrated in large metropolitan areas. Rapidly rising house prices in the most productive cities like London, San Francisco and New York suggest congestion effects which prevent wider participation in these booming urban economies. Improved commuting infrastructure could alleviate this type of misallocation by giving a much wider pool of workers access to productive cities where they can earn higher wages while living farther away. In this project we will use variation in the quality of commuting infrastructure across global cities which creates variation in the spatial extent of the surrounding labor market, to evaluate potential effects of infrastructure improvements in alleviating spatial misallocation in the United States.

First, we use google maps data on commuting times with different modes of transport to systematically compare large cities around the world in their ability to bring workers into their central business districts. Second, we measure the spatial misallocation resulting from inferior commuting infrastructure in the big metropolitan areas of the United States through the lens of a structural model of commuting. Third, we make policy recommendations on how and where US commuting infrastructure should most urgently be improved.

Requisite Skills and Qualifications:

The project is at an early stage and we are looking for 1-2 research assistants to help with the following tasks:

• Compile a review of the transportation literature on commuting infrastructure around the world.
• Collect data on the cost of commuting, parking, and general car use in cities around the world.
• Assist with data processing and analysis.


  • Nishi Felton
  • Matthew Murillo