Speed: The Fastest and Slowest U.S. Cities

Which are the fastest and slowest (car-wise) U.S. metropolitan areas? The task of comparing speed across U.S. cities is daunting: First, data on car trips is sparse. Second, just ranking cities by the average speed (in km/h or miles per h) of trips is not a good way to spot the fastest and slowest U.S. cities. Indeed, in the fastest cities, households tend to use their car more! Hence just comparing the average speed of a trip in, say, Miami, FL with the average speed in Grand Rapids would likely overestimate the speed difference between those two cities.

Victor Couture, Gilles Duranton, and Matthew Turner solve these two issues. First, they use two large surveys of household trips — such data includes the trip’s purpose, its duration, and its length.  And second, they estimate the demand for car trips as well as the supply. In their paper, the authors build a metropolitan area speed index. Miami is the slowest city, while no other city than Grand Rapids (!) is the fastest city in the United States.

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Reference: Couture, Victor, Gilles Duranton, and Matthew A. Turner. “Speed.” (2013). (link here)

Data: National Household Transportation Survey.

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Readings for the week

And in the Journal of Urban Economics, the fundamental law of road congestion is worse than it seems:

Hsu, Wen-Tai, and Hongliang Zhang. “The fundamental law of highway congestion revisited: Evidence from national expressways in Japan.” Journal of Urban Economics 81 (2014): 65-76.

The fundamental law of highway congestion states that when congested, the travel speed on an expanded expressway reverts to its previous level before the capacity expansion. In this paper, we propose a theory that generalizes this statement and finds that if there exists a coverage effect, that is, the effect of longer road length on traffic conditional on capacity, then the new equilibrium travel speed could be lower than its previous level. Given the fundamental law, the theory predicts that the elasticity of traffic to road capacity is at least 1. We estimate this elasticity for national expressways in Japan and test this prediction. Using the planned national expressway extension as an exogenous source of variation for capacity expansion, we obtain elasticity estimates ranging between 1.24 and 1.34, consistent with the prediction of our theory. We further investigate the sources of the larger-than-unity elasticity and find that the coverage effect plays a critical role, compared with the effect due to lane expansion.