The Design of Congestion Pricing Policies
Faculty Supervisor:
Project and Position Description:
Traffic congestion imposes high economic and environmental costs. Cities are increasingly considering different variants of congestion pricing to improve traffic flow, reduce air pollution in populated areas, and generate revenue.
This project aims to answer three questions:
1) What are the anticipated effects of different potential congestion pricing policies, including cordon-based pricing, highway tolling, and dynamic road pricing?
2) How well can simpler, more implementable policies (e.g., a flat price to enter a cordon zone) perform relative to more complex approaches (e.g., real-time road pricing) that may be challenging to implement?
3) How do the results depend on each city’s existing road network, transit options, and travel patterns?
To do so, we are building an equilibrium model of the road network and travel demand in different US cities. We will estimate the model using large-scale road segment- and trip-level traffic data, combined with data on individual travel decisions. The estimated model will allow us to simulate outcomes under counterfactual pricing policies (e.g., different cordons, highway tolls, etc).
Specific tasks will include cleaning and exploring large datasets, building simulations to better understand pieces of the model, and helping implement the estimation procedures. The hired pre-doctoral fellow will meet regularly with coauthors and me to discuss progress. Collaboration with other pre-doctoral fellows, graduate students, and faculty at Yale and other institutions will be an important component of the job.
Requisite Skills and Qualifications:
This project will use a variety of tools from industrial organization and transportation engineering. A background in economics is a plus but not required; candidates with strong technical skills who are interested in learning more about economics are encouraged to apply. Successful applicants typically have Bachelor’s or Master’s degrees with substantial coursework in math and/or computer science.
A background in CS or substantial experience with general-purpose programming languages such as Python and Julia is a big plus.