Does environmental regulation affect CO2 emissions? Analysis based on threshold effect model


With the increasing pressure on China to reduce carbon dioxide (CO2) emissions, it is crucial to clarify the effect of implementing environmental regulations and their impact on the region. Many studies have focused on the linear, rather than nonlinear, relationship between environmental regulation and CO2 emissions. The exploration of nonlinear relations is conducive to the in-depth study of policy effects and regional differences of environmental regulations in China. To ensure effective CO2 emission reductions, regional differences in CO2 emissions in China should also be considered. In this study 30 provinces of China were divided into three different regions according to their level of economic development from 2004 to 2015. Taking the energy intensity and foreign direct investment (FDI) as threshold variables, a threshold model was used to examine the relationship between environmental regulation and CO2 emissions. It was found that environmental regulation has a threshold effect on CO2 emissions, with significant differences among the eastern, central, and western regions. Environmental regulations in the eastern region were ineffective for curbing CO2 emissions, while the energy intensity was in the middle and low threshold range. However, FDI had a promotional effect on CO2 emissions. In the central region, environmental regulations reduced CO2 emissions under the influence of energy intensity and FDI. In the western region, environmental regulations could not mitigate CO2 emissions when the energy intensity and FDI were used as the threshold variables. It was concluded that a diverse range of measures for CO2 reduction should be adopted according to the local economic situation.

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Fig. 1
Fig. 2
Fig. 3



Foreign direct investment

CO2 :

Carbon dioxide emissions

P :


A :

GDP per capita




Environmental regulation

X :

Explanatory variable

Y :

Dependent variable


The threshold variable

γ :

The assumed threshold value

ε :

An independent scalar

μ :

The fixed effect


An indicator function of 0 or 1

β :

The slope coefficients

ρ :

The slope coefficients

α :

The coefficient matrix

M :

The variable matrix

α T :

The transposed coefficient matrix

Y * :

The matrix form of the function

e * :

The residual for the regression function


The sum of squared errors

\(\hat{\lambda }\) :

The threshold value

\(H_{0}^{1}\) :

The null hypothesis

\(H_{1}^{1}\) :

The alternative hypothesis

F 1 :

The value of F-statistic

S 0 :

The sums of squared residuals under \(H_{0}^{1}\)

S 1 :

The sums of squared residuals (SSR) under\(H_{1}^{1}\)

\(\hat{\gamma }\) :

The OLS estimate of γ

\(\hat{\sigma }^{2}\) :

The residual variance under\(H_{1}^{1}\)

LR1 :

The value of LR statistic

i :

One of the provinces

t :

One of the years


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This study was funded by Project of Humanities and Social Sciences of the Ministry of Education of China (18XJC790014); the National Natural Science Foundation of China (71803152, 71503200); the Natural Science Basic Research Program of Shaanxi Province (No. 2018JQ7006); and the Fundamental Research Funds for the Central Universities (2017RYWB01, 2017RWYB06); the authors would like to thank the anonymous referees for their helpful suggestions and corrections on the earlier draft of our paper.

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Correspondence to Wei Chen.

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See Table 6.

Table 6 Corresponding province name of province number in Fig. 1

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Wang, Y., Zuo, Y., Li, W. et al. Does environmental regulation affect CO2 emissions? Analysis based on threshold effect model. Clean Techn Environ Policy 21, 565–577 (2019).

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  • CO2 emissions
  • Environmental regulation
  • Threshold mode
  • Regional difference