Threshold Effect in the Relationship between Environmental Regulations and Haze Pollution: Empirical Evidence from PSTR Estimation

Abstract

The impact of environmental regulations (ER) on haze pollution control has been continuously debated in the field of sustainable development. This paper explores the direct and indirect threshold effects of ER on haze pollution, and five underlying mechanisms—technological innovation (TI), industrial structure (IS), foreign direct investment (FDI), urbanization (UR), and electricity consumption (EC)—are adopted to investigate the indirect threshold effects. Panel data, over the period 2008–2018, of 284 Chinese cities were used and the threshold effects were predicted endogenously based on the panel smooth transition regression (PSTR) model. The results showed the following: (1) For the direct threshold effect, there exists a U-shaped relationship between ER and haze pollution. ER significantly reduced haze pollution when ER < 38.86 due to “cost effects”. However, ER increased haze pollution after the threshold owing to the “green paradox”, which was not significant. (2) For the indirect threshold effect, when TI = 0.37, IS = 39.61, FDI = 7.25, and UR = 42.86, the relationships between ER and haze pollution changed. The changes and corresponding reasons for the indirect threshold effects are discussed in detail. (3) After a comprehensive analysis, the threshold effects have obvious regional distribution characteristics and internal connections. Finally, based on the results, it is essential for governments to enact appropriate environmental regulatory policies and enhance inter-regional synergies in environmental governance.

The effect of haze pollution on insurance development: Evidence from 268 prefecture-level cities in China

“…This article selects PM 2.5 concentration as an indicator for haze pollution, the source of the PM 2.5 is same as study [ 3 ], which is collected from Columbia University’s Socioeconomic Data and Application Center, and the ERA-INTERIM raster meteorological data released by the European Center for Medium-Term Weather Forecast (ECMWF). ArcGIS is used to extract the data from the annual PM 2.5 density map.…”

“…This paper uses the ERA-INTERIM raster meteorological data [ 28 , 29 ]. The atmospheric quantitate model is used to obtain the air flow coefficient ( KQ ), the definition of the KQ from the study [ 3 ]. KQ is adopted as an instrumental variable of haze pollution.…”

“… Notes: the definition of the COD is same as the study [ 3 ]. COD represents the amount of oxygen required to oxidize the organic matter in water.…”

“…Accompanied with the rapid development of economies, China is suffering from several ensuing issues, which includes population explosion, resource overconsumption, and ecological destruction, especially the environment problem-haze pollution [ 1 ]. Although the Chinese government has made great efforts and promulgated a series of environmental regulations to reduce and control the environment problem since 2013 [ 2 ], the haze pollution in China is still severe [ 3 ] as shown in Fig 1 , the haze pollution eastern region is more serious comparing to the central and western regions.…”

“…Haze pollution (PM 2.5 ) can enter the human body through multiple channels and harms the physical and mental health of residents [ 3 ]. The negative effects on the human include morbidity, mortality, cognitive performance [ 4 ] and life expectancy [ 5 ].…”