The Effects of Pollution on Travel Mode Choice

For my Masters thesis, I analyze how air pollution affects travel mode decisions in China using a large and detailed hourly household-level data set on hourly household-level travel mode decisions in Beijing; and hourly air pollution, weather, wind speed, and wind direction in and around Beijing. I use machine learning, LASSO regressions, and atmospheric chemistry to select and construct instruments for air pollution to address its endogeneity. My selected instruments for air pollution include wind speeds at high altitude that disperse pollution and wind blowing from upwind industrial areas towards Beijing that may increase pollution. I compare the effects of air pollution on travel mode before and after China launched a nation-wide, real-time air quality monitoring and disclosure program. According to the results of my IV regressions for 2010, prior to the reform, air pollution makes people less likely to walk; and more likely to bicycle, take bus, take car, take subway, and take other modes of transport; and air pollution decreases both the number and share of household members in each household who took at least 1 trip that hour. In contrast, in 2014, after the reform, air pollution makes people more likely to walk and take a taxi; and less likely to bicycle, take bus, take car, take subway, and take other modes of transport; and air pollution increases the number of members in household who took at least 1 trip that hour.

Name thesis:degree_name

M.S., Applied Economics and Management

Level thesis:degree_level

Master of Science

Discipline thesis:degree_discipline

Applied Economics and Management

Grantor

Cornell University

Year dc:date.issued

2019

Author dc:creator

• Li, Dingyi

Committee member dc:contributor.committeemember

• Li, Shanjun

• Environmental economics

Language dc:language.iso

en_US

DOI

https://doi.org/10.7298/hqwy-yq85

Dc Identifier Other

ProQuest Submission ID: 10636
ProQuest Publication ID: 22584803

OAI identifier oai:identifier

oai:ecommons.cornell.edu:1813/67516