Abstract
To investigate the effects of government environmental regulation and industrial structure changes on carbon dioxide emissions, this research analyzes annual data over the period 2003–2015 covering 30 provinces in China (except for Tibet) with the panel smooth transition regression (PSTR) model. The empirical results show obvious non-linear effects of environmental regulation and industrial structure on carbon dioxide emission. Taking the effects of both linearity and non-linearity into consideration, environmental regulation will reduce carbon emissions with the change of industrial structure rationalization (SR). When the level of industrial structure optimization (SH) is low, environmental regulation promotes carbon dioxide emissions. When the level of industrial structure optimization (SH) is high, environmental regulation plays a significant inhibitive role on carbon dioxide emissions. The Kuznets relationship between GDP per capita (PGDP) and carbon dioxide emissions is influenced by local industrial structure rationalization and industrial structure optimization. Therefore, environmental regulation policies suitable for local conditions should be made based on the transition of the local industrial structure.
Notes
However, there is also a disadvantage of the PSTR model. If m = 1 and γ → ∞, then the PSTR model turns into the PTR model. If the slope parameter γ → 0, then the value of the transition function is 0.5. The PSTR models thus degenerate into linear fixed effect models (He 2008).
All calculations are done by MATLAB2011(a).
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Chen, X., Chen, Y.E. & Chang, CP. The effects of environmental regulation and industrial structure on carbon dioxide emission: a non-linear investigation. Environ Sci Pollut Res 26, 30252–30267 (2019). https://doi.org/10.1007/s11356-019-06150-6
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DOI: https://doi.org/10.1007/s11356-019-06150-6
Keywords
- Environmental regulation
- Industrial structure rationalization
- Industrial structure optimization
- Low-carbon economy
- Non-linearity