Abstract
To reduce industrial carbon emissions, various industries have been seeking ways to reduce their own emissions. Implementing carbon trading system measures is one way to effectively control industrial carbon emissions. However, in different industrial sectors, carbon trading systems have different impact. The 14-year provincial panel data (2005–2019) were analyzed by using the propensity score matching and the difference-in-difference model to evaluate the role of the emission trading system (ETS) in reducing emissions from different industries. According to the study, ETS has reduced carbon emissions from the agricultural production sector by 1.6876%. Secondly, it also had a significant inhibitory effect on the manufacturing sector, about 24.0489. Mining, electricity production, wholesale and other industrial sectors are insignificant disincentives, and construction and transportation are insignificant facilitators. China’s ETS, therefore, mainly acts as an inhibitory force for different industries, which can effectively reduce their carbon emissions.
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Funding was provided by National Natural Science Foundation of China (Grant Nos. 72171123, 72171149), Shanghai Philosophy and Social Science Foundation (Grant No. 2020BGL010), National Social Science Major Foundation of China (Grant No. 21ZDA105).
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Appendix: Parallel trend test
Appendix: Parallel trend test
First | Mining | Manufacturing | Electricity | |
|---|---|---|---|---|
Pre_4 | 1.65 (0.164) | 2.36 (0.400) | − 7.62 (0.537) | − 2.75 (0.842) |
Pre_3 | 0.62 (0.527) | − 2.36 (0.312) | 1.66 (0.871) | 1.06 (0.926) |
Pre_2 | 0.31 (0.732) | 1.16 (0.595) | − 0.48 (0.960) | 7.72 (0.469) |
Current | − 1.47 (0.111) | − 2.68 (0.219) | − 24.84 (0.010) | − 0.19 (0.986) |
Post_1 | − 2.16 (0.029) | − 2.50 (0.282) | − 22.56 (0.028) | 5.97 (0.600) |
Post_2 | − 2.78 (0.011) | − 2.02 (0.434) | − 20.18 (0.077) | 5.34 (0.672) |
Post_3 | − 3.92 (0.002) | − 0.75 (0.797) | − 24.32 (0.058) | 6.40 (0.653) |
Post_4 | − 4.26 (0.003) | − 2.77 (0.411) | − 27.30 (0.066) | 9.51 (0.563) |
Constant | − 8.03 (0.036) | 27.83 (0.000) | 72.81 (0.067) | − 41.76 (0.345) |
Control | Yes | Yes | Yes | Yes |
Province FE | Yes | Yes | Yes | Yes |
Year FE | Yes | Yes | Yes | Yes |
Province FE*year trend | Yes | Yes | Yes | Yes |
R-square | 0.8972 | 0.9707 | 0.9876 | 0.9935 |
Construction | Transport | Wholesale | Others | |
|---|---|---|---|---|
Pre_4 | − 0.36 (0.494) | − 0.13 (0.963) | 0.37 (0.861) | 0.46 (0.783) |
Pre_3 | − 0.36 (0.409) | − 0.09 (0.968) | 0.95 (0.588) | 0.20 (0.886) |
Pre_2 | − 0.05 (0.912) | 0.20 (0.926) | 0.51 (0.757) | 0.30 (0.814) |
Current | − 0.004 (0.992) | 0.70 (0.744) | 0.83 (0.616) | − 0.55 (0.669) |
Post_1 | 0.08 (0.857) | 0.53 (0.817) | − 0.27 (0.876) | − 0.20 (0.883) |
Post_2 | 0.01 (0.988) | 2.16 (0.397) | − 0.94 (0.630) | − 0.59 (0.700) |
Post_3 | − 0.87 (0.112) | 5.17 (0.072) | − 1.26 (0.568) | − 0.20 (0.909) |
Post_4 | − 0.93 (0.139) | 5.61 (0.091) | − 0.94 (0.713) | 0.38 (0.847) |
Constant | − 4.37 (0.010) | 2.45 (0.783) | − 13.67(0.046) | − 7.87 (0.141) |
Control | Yes | Yes | Yes | Yes |
Province FE | Yes | Yes | Yes | Yes |
Year FE | Yes | Yes | Yes | Yes |
Province FE*year trend | Yes | Yes | Yes | Yes |
R-square | 0.9357 | 0.9771 | 0.8710 | 0.8733 |
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Qu, S., Ma, H. The impact of carbon policy on carbon emissions in various industrial sectors based on a hybrid approach. Environ Dev Sustain 25, 14437–14451 (2023). https://doi.org/10.1007/s10668-022-02673-0
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DOI: https://doi.org/10.1007/s10668-022-02673-0