ORIGINAL RESEARCH
The Environment, Energy and Economic Impacts of Carbon Tax and Indirect Tax in the Coal Industry
Jingmin Wang 1, 2  
,  
Chen Zhao 1  
 
 
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1
School of Economics and Management, North China Electric Power University, Baoding, China
2
Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Changping Beijing, China
CORRESPONDING AUTHOR
Chen Zhao   

North China Elect Power Univ, Baoding Huadian Road No678, 071000 Baoding, China
Online publish date: 2019-05-31
Publish date: 2019-07-08
Submission date: 2018-06-16
Final revision date: 2018-09-12
Acceptance date: 2018-09-24
 
Pol. J. Environ. Stud. 2019;28(5):3887–3899
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ABSTRACT
The CO2 emissions from China’s coal consumption account for 14.3% of the world’s CO2 emissions. The taxation of China’s coal industry affects the progress of world emissions reduction to some extent. This paper establishes six countermeasure scenarios with different tax systems considering carbon tax and indirect tax, then constructs a dynamic recursive computable general equilibrium model to simulate the tax system changes of the coal industry. It turns out that in both rural and urban populations, coal consumption is more sensitive to the carbon tax and indirect tax compared with the consumption of other commodities. The reduction effect of increasing tax will grow and social reduction cost will be reduced over time. Increasing the coal industry tax can reduce CO2 emissions significantly and will suffer relatively less GDP loss, for example increasing 20% of indirect tax on the coal industry will lead to 3.65 billion tons of CO2 reduction during 2018-2030, accounting for 10.05% of 2015 world CO2 emissions. We found that increasing taxes can improve all industries’ energy efficiency, which reflects on the powerful role of the coal industry in guiding the market to reducing CO2 emissions. Finally, these results strongly recommend that China should increase indirect tax as quickly as possible to reach the long-term interests as soon as possible.
eISSN:2083-5906
ISSN:1230-1485