Discontinuities in robust nonparametric regression with α-mixing dependence

Hušková, Marie; Maciak, Matúš

doi:10.1080/10485252.2017.1303061

Cited by 5 publications

(1 citation statement)

References 24 publications

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“…Because X is continuous on both sides of the cutoff (usually regarded as two groups), an individual value for Y falling on either side of the cutoff occurs randomly. Thus, the two groups differ only in their treatment status yet are balanced for all covariates, which constitutes a quasi-experimental design near the cutoff [ 43 , 44 ].…”

Section: Methods and Datamentioning

confidence: 99%

Characterizing the interruption-recovery patterns of urban air pollution under the COVID-19 lockdown in China

Cai

Wang

et al. 2021

Building and Environment

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The COVID-19 pandemic provides an opportunity to study the effects of urban lockdown policies on the variation in pollutant concentrations and to characterize the recovery patterns of urban air pollution under the interruption of COVID-19 lockdown policies. In this paper, interruption-recovery models and regression discontinuity design were developed to characterize air pollution interruption-recovery patterns and analyze environmental impacts of the COVID-19 lockdown, using air pollution data from four Chinese metropolises (i.e., Shanghai, Wuhan, Tianjin, and Guangzhou). The results revealed the air pollutant interruption-recovery curve represented by the three lockdown response periods (Level I, Level II and Level III) during COVID-19. The curve decreased during Level I (A 25.3%–48.8% drop in the concentration of NO 2 has been observed in the four metropolises compared with the same period in 2018–2019.), then recovered around reopening, but decreased again during Level III. Moreover, the interruption-recovery curve of the year-on-year air pollution difference suggests a process of first decreasing during Level I and gradually recovering to a new equilibrium during Level III (e.g., the unit cumulative difference of NO 2 mass concentrations in Shanghai was 21.7, 22.5, 11.3 (μg/m 3 ) during Level I, II, and III and other metropolises shared similar results). Our findings reveal general trends in the air quality externality of different lockdown policies, hence could provide valuable insights into air pollutant interruption-recovery patterns and clear scientific guides for policymakers to estimate the effect of different lockdown policies on urban air quality.

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Section: Methods and Datamentioning

confidence: 99%