Does building highways reduce traffic congestion?

14:00-15:30, Monday, June 22, 2020

Tencent Meeting (Meeting ID: 718 548 277)

Dr. Debarshi INDRA is a Senior Manager at Anheuser-Busch InBev (ABInBev) in their Global Analytics Center in India. He primarily works in the area of Revenue Management, designing solutions to find the optimal price and assortment of ABInBev products. Debarshi received his Ph.D. in economics from The State University of New York at Buffalo in 2014. He has published a paper at the Journal of Regional Science.

In an influential study, Duranton and Turner (2011) confirm the existence of the fundamental law of highway congestion in the US. They build a causal model using an instrumental variable (IV) approach that yields an estimate of 1.03 for the elasticity of vehicle miles traveled (VMT) to the stock of interstate highways in US metropolitan areas. The result means that government efforts to alleviate traffic congestion by expanding capacity are likely to fail — any increase in the stock of highways is accompanied by a commensurate increase in VMT, leaving travel times unaffected. We first demonstrate using a partial equilibrium model that metropolitan statistical areas (MSAs) that are identical in all respects but have different initial congestion levels respond to added capacity differently which gives rise to heterogeneity in the elasticity of vehicle miles traveled (VMT) to capacity. We derive the conditions under which the elasticity decreases with initial congestion level. We then revisit the empirical analysis of Duranton and Turner (2011) using the instrumental variable quantile regression (IVQR) model due to Chernozhukov and Hansen (2005, 2006, 2008). The IVQR model allows for heterogeneous treatment effect in the presence of unobserved differences across cities and allows us to evaluate the impact of changes in the stock of interstate highways on the conditional distribution of VMT, not just the impact on the conditional mean as in Duranton and Turner (2011). The IVQR estimates show that the elasticity of VMT declines monotonically as one goes up the quantile ladder, being more than one at the lower quantiles and less than one at the higher quantiles. The IVQR model implies that among observationally identical cities building roads is likely to succeed in reducing travel times in the more heavily congested cities as compared to cities with lower congestion levels. We also estimate the unconditional quantile treatment effect using the generalized quantile regression (GQR) model due to Powell (2019). The GQR estimates show that building highways has no statistically significant impact on VMT at the highest quantiles, echoing the IVQR conclusion. Finally, we explore the mechanisms that drive the empirical findings by running simulations using a spatial general equilibrium model with an extensive road network calibrated to the Greater LA Region. Other than commute trips, consumers have to travel to different zones in the model to acquire consumption goods. Route choice in the network and mode choice are considered. Building roads affect driving through three channels: the total amount of consumption, mode choice, and the substitutions between goods sold at different locations. We find that the elasticity of VMT to capacity is 0.321 in LA and the elasticity decreases consistently with initial congestion level. We report the welfare effect and the changes in other travel-related variables.

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