Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/250561 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
IZA Discussion Papers No. 14900
Verlag: 
Institute of Labor Economics (IZA), Bonn
Zusammenfassung: 
Following market liberalisation, the vehicle population in China has increased dramatically over the past few decades. This paper examines the causal impact of the opening of a heavily used high speed rail line connecting two megacities in China in 2015, Chengdu and Chongqing, on air pollution. We use high-frequency and high spatial resolution data to track pollution along major highways linking the two cities. Our approach involves the use of an augmented regression discontinuity in time approach applied on data that have been through a meteorological normalisation process. This deweathering process involves applying machine learning techniques to account for change in meteorology in air quality time series data. Our estimates show that air pollution is reduced by 7.6% along the main affected highway. We simultaneously find increased levels of ozone pollution which is likely due to the reduction in nitrogen dioxide levels that occurred. These findings are supported using a difference-in-difference approach.
Schlagwörter: 
air pollution
China
green infrastructure
high-speed railway
regression discontinuity
machine learning
JEL: 
L92
O18
Q53
Q54
R41
Dokumentart: 
Working Paper

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