Estimating the Social Cost of Congestion Using the Bottleneck Model

Project Number


Project Summary

In this project, we measure commuters’ wasted time due to traffic congestion using a unique dataset that measures the trips and characteristics of individual commuters.  We develop a new approach to measuring congestion delays, which is simple to estimate and widely applicable.  Specifically, we first estimate how much time each commuter would have spent if she had experienced no congestion delays on her route.  We then compare this counterfactual travel time to the commuter’s actual travel time and compute the difference.  We exploit recent developments in econometrics to measure congestion costs in this manner. With those congestion-cost estimates, we can then evaluate alternative policies designed to reduce traffic congestion.  Within a traditional economic framework, the optimal policy is usually a congestion toll that depends both on time of day and location of traffic.  However, that policy is often difficult to implement for various reasons, and policymakers must consider alternatives such as land-use reforms and highway construction or expansion.  To evaluate those alternative policies, we will identify geographic determinants of traffic congestion.  Specifically, we will examine variations in congestion costs by local geographic conditions, such as population and employment density, and other characteristics measured at the Metropolitan Statistical Area (MSA) level.  This will yield an MSA-level index of traffic congestion, allowing us to identify relationships between congestion and geographical characteristics, including roadway infrastructure and the availability of public transit.  As a result, we can address questions such as: are land-use controls (such as controls on population density) an effective way to reduce congestion?  Are more sprawled cities more congested?  Will building more highway capacity reduce congestion for travelers residing in the city?  If so, how could its benefits be compared to its construction costs?  This research aims at answering these questions from our novel theoretical and empirical framework.

Project Status




Topic Area

Urban Mobility

P.I. Name & Address

Assistant Professor, Urban Economics, Transportation Economics, Economic Statistics
California State University, Long Beach
1250 Bellflower Boulevard
Long Beach, CA 90840
United States

Funding Source


Total Project Cost


Agency ID or Contract Number


Start and End Dates

9/1/2017 – 8/31/2018