« Back to Results

Transportation

Paper Session

Sunday, Jan. 9, 2022 3:45 PM - 5:45 PM (EST)

Hosted By: American Real Estate and Urban Economics Association
  • Chair: Nathaniel Baumsnow, University of Toronto

The City-Wide Effects of Tolling Downtown Drivers: Evidence from London's Congestion Charge.

Ian Herzog
,
Huron University College

Abstract

I study the effects of London England's Congestion Charge on regional traffic, commuting, and economic activity's spatial distribution. In 2003, London began tolling drivers to enter its central business district on workdays and this policy immediately reduced downtown traffic. I measure exposure to tolled traffic throughout London's regional road network and show that the policy also reduced rush-hour traffic on untolled roads leading downtown. I then use London's Congestion Charge as a natural experiment to identify ensuing effects of traffic on commuting by car and public transit and find that increasing a route's traffic decreases both the number of commuters and their driving rates at the margin. In a quantitative spatial model, traffic's effect on the number of commuters suggests that changing traffic patterns make certain neighbourhoods more desirable places to live and work, influencing the congestion charge's equilibrium effects, so I use a model with endogenous traffic externalities and mode choice for policy analysis. Simulations suggest that London's Congestion Charge causes untolled commuters to substitute from public transit to driving and gives the region's commuters positive net benefits that disproportionately accrue to low-skill workers.

Transport Infrastructure Improvements and Spatial Sorting: Evidence from Buenos Aires

Pablo Ernesto Warnes
,
Aalto University and Helsinki GSE

Abstract

How do improvements in the urban transport infrastructure affect the spatial sorting of residents with different levels of income and education within a city? What are the welfare effects of improving urban transit once we take into account these patterns of spatial sorting? In this paper, I study the effects of the construction of a bus rapid transit system (BRT) on the spatial reorganization of residents within the city of Buenos Aires, Argentina. To do so, I leverage an individual level panel data set of more than two million residents, which allows me to describe the intra-city migration patterns at a very fine spatial scale. I first find reduced form evidence that the construction of the BRT increased the spatial segregation between high and low-skilled residents within the city. I then develop a dynamic quantitative spatial equilibrium model of a city with heterogeneous workers that allows me to quantify the welfare effects of this BRT system while taking into account these spatial sorting patterns. With this quantitative framework, I can measure the welfare gains for residents that were living near the BRT lines before these were built.

Why Do Improvements in Transportation Infrastructure Reduce the Gender Gap in South Korea?

Eunjee Kwon
,
University of Cincinnati

Abstract

This study investigates whether the expansion of high-speed rail (HSR) helps reduce the gender gap in labor market outcomes -- a question for which there is limited prior evidence. Using an instrumental variable strategy which leverages historical railroads constructed in Korea during the Japanese colonial era, I demonstrate empirically that the gender gap in the South Korean labor market decreases with the expansion of high-speed rail (HSR). To understand the mechanisms at play, I employ a spatial general equilibrium model to structurally decompose HSR's impact into labor demand and supply channels. The quantitative decomposition shows that overall, HSR increases labor demand for female-intensive jobs and decreases women's labor participation costs. Finally, the empirical evidence of the structural estimation was provided that local service industries where women are hired more intensively, benefit most from HSR. In addition, women in non-core areas benefit from the improvement in local amenities, particularly in the areas of education and childcare, which reduces women's childcare burdens and encourages their participation in the labor force.

Congestion Costs and Scheduling Preferences of Car Commuters in California: Estimates Using Big Data

Jinwon Kim
,
Sogang University-Korea

Abstract

In this paper, we construct each commuter's travel time profile, i.e., the menu of travel times at different hypothetical trip timing choices, for a sample of California commuters using Google Maps to quantify their congestion costs. We then investigate the effect of congestion faced by the commuters on their trip scheduling choices. We find an evidence of 'adaptation', by which commuters facing a higher level of congestion on their routes at the peak hour tend to arrive at an inconvenient early or late time to avoid otherwise a long congestion delay. This paper also estimates the structural parameters of the scheduling utility. While the shape of the estimated utility is similar to that of the previous studies, we discover that it is much steeper than that of most commuters' travel time profiles, which implies that much of the variation of actual arrival times must be explained by the variation of ideal arrival times. Under this situation, a toll that is conventional in the standard bottleneck models is either ineffective or would impose a too large burden on the commuters.

Discussant(s)
Gabriel Kreindler
,
Harvard University
Alexander Rothenberg
,
Syracuse University
Sitian Liu
,
Queen's University
Jonathan D. Hall
,
University of Toronto
JEL Classifications
  • R4 - Transportation Economics