Short-term impacts of carbon offsetting on emissions trading schemes: Empirical insights from the EU experience


Gavard, Claire ; Kirat, Djamel


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URL: https://madoc.bib.uni-mannheim.de/57801
URN: urn:nbn:de:bsz:180-madoc-578010
Document Type: Working paper
Year of publication: 2020
The title of a journal, publication series: ZEW Discussion Papers
Volume: 20-058
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: C32 , C58 , F18 , Q54 , Q58,
Keywords (English): emissions trading ; european allowances ; international credits ; causality analysis
Abstract: The Paris Agreement established a new mechanism by which a country can offset some of its emissions reductions in other countries. Its design is still under negotiation. While taking advantage of cheaper abatement opportunities enables efficiency gains, the impact on the price volatility in the emission trading schemes is unclear. We conduct an empirical analysis of the short-term impacts of these credits on the standard carbon markets, using the European Union experience with accepting credits for compliance in the second phase of its scheme. With vector-autoregressive models allowing regime changes at a priori unknown dates, we analyze the structural relationship between the prices of allowances and credits. Although one might expect that the allowance and credit markets influence one another, we find that, before November 2011, knowing the credit price variations helps to better predict the allowance price variations while, after November 2011, it is the opposite. We explain this by expectations and restrictions regarding credits. For the transmission of shocks and the impact on volatility, the influence is mainly from allowances to credits. The allowance price volatility explains between 56% and 72% of the credit volatility whereas the latter explains less than 2% of the former.




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