Data and Code for: Subways and Road Congestion

Principal Investigator(s): View help for Principal Investigator(s) Ben Zou, Michigan State University; Yizhen Gu, Jinan University; Chang Jiang, Baidu Inc.; Junfu Zhang, Clark University

Version: View help for Version V1

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Data and Code for: Subways and Road Congestion		0

Project Citation:

Zou, Ben, Gu, Yizhen, Jiang, Chang, and Zhang, Junfu. Data and Code for: Subways and Road Congestion. Nashville, TN: American Economic Association [publisher], 2021. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-03-16. https://doi.org/10.3886/E115681V1

Project Description

Summary:

We study whether subways alleviate road congestion by examining 45 subway line launches in China and using detailed data on road speed. Our difference-in-differences estimation finds that in the first year after a subway line is launched, rush-hour speed on nearby roads increases by about 4%. The effect is most prominent in initially-congested roads and declines over distance to the new subway line. Evidence on road speed is corroborated with substitution patterns among modes of transportation. Using auxiliary data from Beijing, we calculate that the time savings for each automobile or bus commute from faster speed is worth 0.1 USD.

Scope of Project

Subject Terms: public transportation

JEL Classification:
      L92 Railroads and Other Surface Transportation
      R41 Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
      R42 Transportation Economics: Government and Private Investment Analysis; Road Maintenance, Transportation Planning

Geographic Coverage: China

Data Type(s): observational data

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V1 [2021-03-16]

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