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The asymmetric nexus between air pollution and COVID-19: Evidence from a non-linear panel autoregressive distributed lag model.
Wen, Chen; Akram, Rabia; Irfan, Muhammad; Iqbal, Wasim; Dagar, Vishal; Acevedo-Duqued, Ángel; Saydaliev, Hayot Berk.
  • Wen C; Olin Business School, Washington University in St. Louis, St. Louis, USA.
  • Akram R; Business School, Guilin University of Electronic Technology, China. Electronic address: drrabia@guet.edu.cn.
  • Irfan M; School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, China; School of Business Administration, Ilma University, Karachi, 75190, Pakistan. Electronic address: irfansa
  • Iqbal W; Department of Management Science, College of Management, Shenzhen University, Shenzhen, China.
  • Dagar V; Department of Economics and Public Policy, Great Lakes Institute of Management, Gurgaon, 122413, Haryana, India.
  • Acevedo-Duqued Á; Public Policy Observatory Faculty of Business and Administration, Universidad Autónoma de Chile, Santiago, 7500912, Chile.
  • Saydaliev HB; Institute of Forecasting and Macroeconomic Research, Tashkent, Uzbekistan; Mathematical Methods in Economics, Tashkent State University of Economics, 100003, Tashkent, Uzbekistan.
Environ Res ; 209: 112848, 2022 06.
Article in English | MEDLINE | ID: covidwho-1654414
ABSTRACT
The emergence of a new coronavirus (COVID-19) has become a major global concern that has damaged human health and disturbing environmental quality. Some researchers have identified a positive relationship between air pollution (fine particulate matter PM2.5) and COVID-19. Nonetheless, no inclusive investigation has comprehensively examined this relationship for a tropical climate such as India. This study aims to address this knowledge gap by investigating the nexus between air pollution and COVID-19 in the ten most affected Indian states using daily observations from 9th March to September 20, 2020. The study has used the newly developed Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag (NPARDL) model for asymmetric analysis. Empirical results illustrate an asymmetric relationship between PM2.5 and COVID-19 cases. More precisely, a 1% change in the positive shocks of PM2.5 increases the COVID-19 cases by 0.439%. Besides, the estimates of individual states expose the heterogeneous effects of PM2.5 on COVID-19. The asymmetric causality test of Hatemi-J's (2011) also suggests that the positive shocks on PM2.5 Granger-cause positive shocks on COVID19 cases. Research findings indicate that air pollution is the root cause of this outbreak; thus, the government should recognize this channel and implement robust policy guidelines to control the spread of environmental pollution.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / Air Pollution / COVID-19 Type of study: Observational study / Prognostic study Topics: Long Covid Limits: Humans Country/Region as subject: Asia Language: English Journal: Environ Res Year: 2022 Document Type: Article Affiliation country: J.envres.2022.112848

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / Air Pollution / COVID-19 Type of study: Observational study / Prognostic study Topics: Long Covid Limits: Humans Country/Region as subject: Asia Language: English Journal: Environ Res Year: 2022 Document Type: Article Affiliation country: J.envres.2022.112848