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Scenario analysis of ETS revenue allocation mechanism of China: based on a dynamic CGE model

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Abstract

The successful establishment of China’s emission trading scheme (ETS) could lead the next generation of global climate carbon markets in industrializing and developing countries. The allocation of ETS revenue from auctioning carbon emission allowance is important for the achievement of China’s joint targets of economic growth, mitigation, and welfare improvement. This study develops a dynamic CGE model to evaluate the effects of different ETS revenue allocation mechanisms and identifies the proper mechanism for China’s ETS design. Ten scenarios including business as usual (BAU), no ETS revenue allocation incentive (NA) and other eight ETS revenue allocation scenarios are designed. Simulation results indicate that the tradeoff between economic cost and environmental benefit exists under different ETS revenue allocation mechanisms. ETS revenue is suggested to allocate to household sector through reducing indirect tax and, after 2020, a certain proportion of ETS revenue could be allocated to production sector for improving energy-saving technology (i.e., STP mechanism). This study provides references for policymakers in China to design effective and realistic ETS-related policies. A similar study could be conducted to explore the proper ETS and the revenue allocation policies in other countries that have similar national conditions to China, such as other BRICS countries.

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Notes

  1. Although energy is used as raw material in the chemical sector, this study does not consider it for the following aspect. First, this study mainly focuses on ETS revenue reallocation mechanisms and their different effects; Second, the data on energy input as the raw material in the chemical sector is unavailable in existing publications; Third, considering the significantly differentiated products in the chemical sector, the accounting of energy input as raw material is quite difficult; Forth, existing studies also did not consider this part of energy inputs in the chemical sector, such as Wang et al., (2015), Chen et al., (2016), Tang et al., (2016), Huang et al., (2019), and Lin and Jia (2019). The mitigation and scenario analysis of chemical sector considering energy input for both production factor and materials could be further investigated in our future study.

  2. This assumption simplifies the model used in this study. Because this study focuses on the effects of different ETS revenue allocation mechanisms and the relative changes of GDP and sectoral output, this assumption would produce small effects on simulation results. However, the Armington assumption of incomplete substitution between imported and domestic commodities will be adopted in our future study for more accurate results.

  3. Considering the current carbon mitigation situation in China, mitigation targets towards 2020 and 2030 would be achieved easily in case of large-scale renewable energy deployment. Moreover, CO2 emissions of eight emission-intensive sectors accounted for a large proportion of and their participation of ETS would play a significant role in achieving China’s mitigation targets. However, carbon leakage is not considered in this study.

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Funding

This study was financially supported by the Beijing Natural Science Foundation (No. 9172015), Beijing Social Science Foundation (No. 17JDYJB010), and Special Fund for Joint Development Program of Beijing Municipal Commission of Education.

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Authors and Affiliations

  1. School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, People’s Republic of China

    Hao Li, Yuhuan Zhao, Song Wang, Ye Cao, Qiaoling Shi & Ya Liu

  2. Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, 100081, People’s Republic of China

    Yuhuan Zhao

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA

    Jiang Lin

  4. Department of Agricultural and Resource Economics, University of California, Berkeley, CA, 94720, USA

    Jiang Lin

  5. State Grid Ningxia Electric Economic Institute of Technology, Yinchuan, 750001, People’s Republic of China

    Yanli Xiao

  6. China Southern Power Grid, Xingyi Power Supply Bureau, Xingyi, 562400, People’s Republic of China

    Junjie Li

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  1. Hao Li
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Correspondence to Yuhuan Zhao.

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Li, H., Zhao, Y., Wang, S. et al. Scenario analysis of ETS revenue allocation mechanism of China: based on a dynamic CGE model. Environ Sci Pollut Res 26, 27971–27986 (2019). https://doi.org/10.1007/s11356-019-05964-8

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