PM 2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism

Jibo Chen, Keyao Chen, Guizhi Wang, Lingyan Wu, Xiaodong Liu and Guo Wei
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Jibo Chen: School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China
Keyao Chen: National Climate Center, China Meteorological Administration, Beijing 100081, China
Guizhi Wang: School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China
Lingyan Wu: School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China
Xiaodong Liu: School of Computing, Edinburgh Napier University, Edinburgh EH10 5DT, UK
Guo Wei: Department of Mathematics and Computer Science, University of North Carolina at Pembroke, Pembroke, NC 28372, USA

IJERPH, 2019, vol. 16, issue 7, 1-21

Abstract: In this paper, a vector autoregression (VAR) model has been constructed in order to analyze a two-way mechanism between PM 2.5 pollution and industry development in Beijing via the combination of an impulse response function and variance decomposition. According to the results, long-term equilibrium interconnection was found between PM 2.5 pollution and the development of primary, secondary, and tertiary industries. One-way Granger causalities were found in the three types of industries shown to contribute to PM 2.5 pollution, though the three industries showed different scales of influences on the PM 2.5 pollution that varied for about 1–2 years. The development of the primary and secondary industries increased the emission of PM 2.5 , but the tertiary industry had an inhibitory effect. In addition, PM 2.5 pollution had a certain inhibitory effect on the development of the primary and secondary industries, but the inhibition of the tertiary industry was not significant. Therefore, the development of the tertiary industry can contribute the most to the reduction of PM 2.5 pollution. Based on these findings, policy-making recommendations can be proposed regarding upcoming pollution prevention strategies.

Keywords: haze pollution; vector autoregression model; impulse response function; variance decomposition; industry development (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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