PM 2.5 Concentrations and Subjective Well-Being: Longitudinal Evidence from Aggregated Panel Data from Chinese Provinces

Pan Zhang and Zhiguo Wang
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Pan Zhang: School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200030, China
Zhiguo Wang: School of Engineering, The Hong Kong University of Science and Technology, Hong Kong 999077, China

IJERPH, 2019, vol. 16, issue 7, 1-13

Abstract: Although haze pollution with PM 2.5 as the chief pollutant has become a critical threat worldwide, little research has examined the effects of PM 2.5 concentrations on subjective well-being. Based on a longitudinal aggregated panel dataset from Chinese provinces, this study investigates the effects of PM 2.5 concentrations on levels of happiness and the inequality of happiness. The results showed that high ground-level PM 2.5 concentrations decreased the average level of happiness and high PM 2.5 concentrations had stronger negative effects on the happiness of persons with high income than those with low income. In addition, PM 2.5 concentrations were also significantly negatively related to inequality of happiness in Chinese provinces. Further empirical tests showed that the negative effects of PM 2.5 concentrations on the inequality of happiness could be explained by the stronger influence of PM 2.5 concentrations on the subjective well-being of individuals with a higher initial level of happiness than those with a lower initial level of happiness. This confirms that PM 2.5 pollution can do harm to subjective well-being and reduce variations in the subjective well-being of individuals. The policy implications of controlling haze pollution and improving well-being are discussed.

Keywords: level of happiness; PM 2.5; inequality of happiness; environmental governance (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 (3)

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