Two Empirical Tests of Hypercongestion
There is a widely-held view that as demand for travel goes up, this decreases not only speed but also the capacity of the road system, a phenomenon known as hypercongestion. We revisit this idea. We propose two empirical tests motivated by previous analytical models of hypercongestion. Our first test uses instrumental variables to empirically isolate the effect of travel demand on highway capacity. Our second test uses an event study analysis to measure changes in highway capacity at the onset of queue formation. We apply these tests to three highway bottlenecks in California for which detailed data on traffic flows and vehicles speeds are available. Neither test shows evidence of a reduction in highway capacity at any site during periods of high demand. Across sites and specifications we have sufficient statistical power to rule out small reductions in highway capacity. This lack of evidence of hypercongestion has important implications for travel supply and demand models and raises questions about highway metering lights and other traffic interventions aimed at regulating demand.
Previously circulated as "Does Hypercongestion Exist? New Evidence Suggests Not." Neither of us have received any financial compensation for this project, nor do we have any financial relationships that relate to this research. We are grateful to Gilles Duranton, Jonathan Hughes, Mark Jacobsen, Ian Parry, and Kenneth Small, as well as to the editor (Hunt Allcott) and three anonymous reviewers for helpful comments. Neither of us have received any financial compensation for this project, nor do we have any financial relationships that relate to this research. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Anderson, Michael L., and Lucas W. Davis, 2020. "An Empirical Test of Hypercongestion in Highway Bottlenecks." Journal of Public Economics, vol 187