The impact of lockdown on air pollution: Evidence from an instrument

Linyuan Huang; Rui Xie; Guohao Yang

doi:10.1016/j.chieco.2021.101731

The impact of lockdown on air pollution: Evidence from an instrument

Linyuan Huang, Rui Xie, Guohao Yang

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Abstract

This paper studies the impact of lockdown measures in response to the outbreak of COVID-19 on a prefecture's air pollution in China. To avoid potential endogenous problems, we exploit the bilateral population flow from the Baidu Migration Index to predict prefectures' probability to undertake lockdown measures. Our results using difference-in-differences with the instrumental variable show that a prefecture's lockdown measures significantly reduce its air quality index (AQI) by around 35%, and yet the result for difference-in-differences with OLS is only around 11%. We also find that a prefecture under lockdown reduces its PM₁₀ and PM_2.5 by around 25% and 35% respectively, and the results of diff-in-diff with OLS are only around 11% and 12%. The sharp difference between these two approaches seems to imply that there is a strong heterogeneity in lockdown stringency across prefectures.

Original language	English
Article number	101731
Journal	China Economic Review
Volume	71
DOIs	https://doi.org/10.1016/j.chieco.2021.101731
Publication status	Published - Feb 2022

Keywords

China
COVID-19
Environment
Health
Lockdown

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10.1016/j.chieco.2021.101731

1-s2.0-S1043951X21001498-mainFinal published version, 5.58 MBLicence: CC BY

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title = "The impact of lockdown on air pollution: Evidence from an instrument",

abstract = "This paper studies the impact of lockdown measures in response to the outbreak of COVID-19 on a prefecture's air pollution in China. To avoid potential endogenous problems, we exploit the bilateral population flow from the Baidu Migration Index to predict prefectures' probability to undertake lockdown measures. Our results using difference-in-differences with the instrumental variable show that a prefecture's lockdown measures significantly reduce its air quality index (AQI) by around 35%, and yet the result for difference-in-differences with OLS is only around 11%. We also find that a prefecture under lockdown reduces its PM10 and PM2.5 by around 25% and 35% respectively, and the results of diff-in-diff with OLS are only around 11% and 12%. The sharp difference between these two approaches seems to imply that there is a strong heterogeneity in lockdown stringency across prefectures.",

keywords = "China, COVID-19, Environment, Health, Lockdown",

author = "Linyuan Huang and Rui Xie and Guohao Yang",

note = "Funding Information: This research was generously supported by the Science Fund for Distinguished Young Scholars of Hunan province (Grant No. 2021JJ10027 ). We would like to thank the participants at CRED workshops. We owe special thanks to Albrecht Glitz for his guidance. We also want to express our thanks to Lorenzo Trimarchi, Eric Melander and Zhijie Xiao for their helpful comments and discussions. Publisher Copyright: {\textcopyright} 2021",

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doi = "10.1016/j.chieco.2021.101731",

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T2 - Evidence from an instrument

AU - Huang, Linyuan

AU - Xie, Rui

AU - Yang, Guohao

N1 - Funding Information: This research was generously supported by the Science Fund for Distinguished Young Scholars of Hunan province (Grant No. 2021JJ10027 ). We would like to thank the participants at CRED workshops. We owe special thanks to Albrecht Glitz for his guidance. We also want to express our thanks to Lorenzo Trimarchi, Eric Melander and Zhijie Xiao for their helpful comments and discussions. Publisher Copyright: © 2021

PY - 2022/2

Y1 - 2022/2

N2 - This paper studies the impact of lockdown measures in response to the outbreak of COVID-19 on a prefecture's air pollution in China. To avoid potential endogenous problems, we exploit the bilateral population flow from the Baidu Migration Index to predict prefectures' probability to undertake lockdown measures. Our results using difference-in-differences with the instrumental variable show that a prefecture's lockdown measures significantly reduce its air quality index (AQI) by around 35%, and yet the result for difference-in-differences with OLS is only around 11%. We also find that a prefecture under lockdown reduces its PM10 and PM2.5 by around 25% and 35% respectively, and the results of diff-in-diff with OLS are only around 11% and 12%. The sharp difference between these two approaches seems to imply that there is a strong heterogeneity in lockdown stringency across prefectures.

AB - This paper studies the impact of lockdown measures in response to the outbreak of COVID-19 on a prefecture's air pollution in China. To avoid potential endogenous problems, we exploit the bilateral population flow from the Baidu Migration Index to predict prefectures' probability to undertake lockdown measures. Our results using difference-in-differences with the instrumental variable show that a prefecture's lockdown measures significantly reduce its air quality index (AQI) by around 35%, and yet the result for difference-in-differences with OLS is only around 11%. We also find that a prefecture under lockdown reduces its PM10 and PM2.5 by around 25% and 35% respectively, and the results of diff-in-diff with OLS are only around 11% and 12%. The sharp difference between these two approaches seems to imply that there is a strong heterogeneity in lockdown stringency across prefectures.

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KW - Environment

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VL - 71

JO - China Economic Review

JF - China Economic Review

M1 - 101731

ER -

The impact of lockdown on air pollution: Evidence from an instrument

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