Dang Hai-Anh H, Trinh Trong-Anh
Data Production and Methods Unit, Development Data Group, World Bank, United States.
GLO, IZA, Indiana University, Vietnam Academy of Social Sciences, Viet Nam.
J Environ Econ Manage. 2021 Jan;105:102401. doi: 10.1016/j.jeem.2020.102401. Epub 2020 Dec 10.
Despite a growing literature on the impacts of the COVID-19 pandemic, scant evidence currently exists on its impacts on air quality. We offer an early assessment with cross-national evidence on the causal impacts of COVID-19 on air pollution. We assemble a rich database consisting of daily, sub-national level data of air quality for 164 countries before and after the COVID-19 lockdowns and we analyze it using a Regression Discontinuity Design approach. We find the global concentration of NO and PM to decrease by 5 percent and 4 percent, respectively, using data-driven optimal bandwidth selection. These results are consistent across measures of air quality and data sources and robust to various model specifications and placebo tests. We also find that mobility restrictions following the lockdowns are a possible explanation for improved air quality.
尽管关于新冠疫情影响的文献越来越多，但目前关于其对空气质量影响的证据却很少。我们提供了一项基于跨国证据的早期评估，以研究新冠疫情对空气污染的因果影响。我们收集了一个丰富的数据库，其中包含164个国家在新冠疫情封锁前后的次国家级每日空气质量数据，并使用回归断点设计方法对其进行分析。通过数据驱动的最优带宽选择，我们发现全球一氧化氮（NO）和细颗粒物（PM）浓度分别下降了5%和4%。这些结果在空气质量测量指标和数据来源方面都是一致的，并且在各种模型设定和安慰剂检验中都很稳健。我们还发现，封锁后实施的出行限制可能是空气质量改善的一个原因。
