Abstract
As the most energy intensive industries, heavy industries are decisive for the realization of energy saving and emission reduction commitments. This study investigates factors behind CO2 emissions mitigation in China's heavy industries based on the system generalized method of moments (SYS-GMM) model. Results indicate that industrial structure (IS), fixed asset investment (F) and historical emissions are drivers for sectoral CO2 emission increase, while energy efficiency (EE) is a key factor for carbon emissions reduction. In order to further explore the effect of environmental regulations, we treat 2011 mandatory emission trading scheme (ETS) in high energy-consuming industries as a quasi-natural experiment, and conduct a Propensity Score Matching and Difference-in-Difference (PSM-DID) approach to analyze the policy effect. We find that the implementation of the mandatory emission reduction policy can reduce CO2 emissions of heavy industries, and the results are robust by testing the randomness of the policies. The policy implications are put forward to optimizing industrial structure and enhancing the environmental regulations in China's heavy industries.
| Original language | English |
|---|---|
| Article number | 111765 |
| Journal | Energy Policy |
| Volume | 145 |
| DOIs | |
| State | Published - Oct 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- CO emissions
- Difference-in-Difference
- Environmental regulations
- Heavy industries
- Propensity score matching
- SYS-GMM
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