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


Abrell, Jan ; Kosch, Miriam ; Rausch, Sebastian


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URL: https://madoc.bib.uni-mannheim.de/60139
URN: urn:nbn:de:bsz:180-madoc-601395
Document Type: Working paper
Year of publication: 2021
The title of a journal, publication series: ZEW Discussion Papers
Volume: 21-039
Place of publication: Mannheim
Publication language: English
Institution: Sonstige Einrichtungen > ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung
MADOC publication series: Veröffentlichungen des ZEW (Leibniz-Zentrum für Europäische Wirtschaftsforschung) > ZEW Discussion Papers
Subject: 330 Economics
Classification: JEL: C54 , Q48 , Q52 , Q58 , L94,
Keywords (English): quantitative policy modeling , government policy , pollution control adoption and costs , distributional effects , employment effects , electric utilities
Abstract: While carbon taxes are generally seen as a rational policy response to climate change, knowledge about their performance from an expost 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 in the short run a higher carbon tax does not necessarily lead to higher emissions reductions or higher costs.

Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt.




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