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

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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Hauptverfasser: Abrell, Jan (VerfasserIn) , Kosch, Mirjam (VerfasserIn) , Rausch, Sebastian (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: March 2022
In: Journal of environmental economics and management
Year: 2022, Jahrgang: 112, Pages: 1-28
ISSN:1096-0449
DOI:10.1016/j.jeem.2021.102589
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.jeem.2021.102589
Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0095069621001339
Volltext
Verfasserangaben:Jan Abrell, Mirjam Kosch, Sebastian Rausch

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520 |a 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. 
650 4 |a Carbon pricing 
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650 4 |a Climate policy 
650 4 |a Cost and Environmental Effectiveness 
650 4 |a Electricity 
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650 4 |a Machine learning 
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