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How effective is carbon pricing?: A machine learning approach to policy evaluation

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While carbon taxes are generally seen as a rational policy response to climate change, knowledge about their performance from an ex-post perspective is still limited. This paper analyzes the emissions and cost impacts of the UK CPS, a carbon tax levied on all fossil-fired power plants. To overcome t...

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Bibliographic Details
Main Authors: Abrell, Jan (Author) , Kosch, Mirjam (Author) , Rausch, Sebastian (Author)
Format: Article (Journal)
Language:English
Published: March 2022
In: Journal of environmental economics and management
Year: 2022, Volume: 112, Pages: 1-28
ISSN:1096-0449
DOI:10.1016/j.jeem.2021.102589
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.jeem.2021.102589
Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0095069621001339
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Author Notes:Jan Abrell, Mirjam Kosch, Sebastian Rausch
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Summary:While carbon taxes are generally seen as a rational policy response to climate change, knowledge about their performance from an ex-post perspective is still limited. This paper analyzes the emissions and cost impacts of the UK CPS, a carbon tax levied on all fossil-fired power plants. To overcome the problem of a missing control group, we propose a policy evaluation approach which leverages economic theory and machine learning for counterfactual prediction. Our results indicate that in the period 2013-2016 the CPS lowered emissions by 6.2 percent at an average cost of €18 per ton. We find substantial temporal heterogeneity in tax-induced impacts which stems from variation in relative fuel prices. An important implication for climate policy is that whether a higher carbon tax leads to higher emissions reductions and higher costs depends on relative fuel prices.
Item Description:Available online 17 December 2021, versin of record 10 January 2022
Gesehen am 04.08.2022
Physical Description:Online Resource
ISSN:1096-0449
DOI:10.1016/j.jeem.2021.102589

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