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The optimal industrial carbon tax for China under carbon intensity constraints: a dynamic input–output optimization model

Authors :
Ning Ma
GuangWei Yin
Huajiao Li
WenLi Sun
Ze Wang
Gang Liu
Dan Xie
Source :
Environmental Science and Pollution Research. 29:53191-53211
Publication Year :
2022
Publisher :
Springer Science and Business Media LLC, 2022.

Abstract

To reduce carbon emissions, the Chinese government is considering introducing a differentiated industrial carbon tax on enterprises outside the carbon trading market in the future. An efficient carbon tax must consider not only how carbon taxes impact the current economy but also how the size of the tax should be adjusted across time due to external changes. To calculate the optimal industrial carbon tax for China which is subject to certain constraints, this paper investigates the economic and environmental effects of four possible industrial carbon tax rate models under carbon intensity constraints from 2021 to 2030 by a dynamic input-output optimization model. The results show that the dynamic tax rate model leads to larger fluctuations in GDP growth than the other tax models, with a low initial tax rate in the beginning and a high tax rate exceeding ¥180/t in 2030. Second, a large quantity of capital stock is distributed across the energy-intensive industries, which leads the existing capital investment structure to be path-dependent. This offsets the performance of carbon taxes. Third, indirect energy-intensive industries such as construction and transport are insensitive to the industrial carbon tax. Finally, comparing the impacts of the four tax rate models, the optimal industrial carbon tax for China is found to be a fixed differentiated tax rate, in which energy-intensive sectors are taxed ¥75/t and low-carbon sectors are taxed ¥50/t.

Details

ISSN :
16147499 and 09441344
Volume :
29
Database :
OpenAIRE
Journal :
Environmental Science and Pollution Research
Accession number :
edsair.doi.dedup.....56764de767c1370c46fa7d4bc9a3fa42
Full Text :
https://doi.org/10.1007/s11356-022-19162-6