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Short-term impacts of carbon offsetting on emissions trading schemes: Empirical insights from the EU experience
Gavard, Claire
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Kirat, Djamel
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URL:
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https://madoc.bib.uni-mannheim.de/57801
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URN:
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urn:nbn:de:bsz:180-madoc-578010
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Dokumenttyp:
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Arbeitspapier
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Erscheinungsjahr:
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2020
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Titel einer Zeitschrift oder einer Reihe:
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ZEW Discussion Papers
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Band/Volume:
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20-058
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Ort der Veröffentlichung:
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Mannheim
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Sprache der Veröffentlichung:
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Englisch
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Einrichtung:
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Sonstige Einrichtungen > ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung
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MADOC-Schriftenreihe:
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Veröffentlichungen des ZEW (Leibniz-Zentrum für Europäische Wirtschaftsforschung) > ZEW Discussion Papers
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Fachgebiet:
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330 Wirtschaft
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Fachklassifikation:
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JEL:
C32 , C58 , F18 , Q54 , Q58,
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Freie Schlagwörter (Englisch):
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emissions trading ; european allowances ; international credits ; causality analysis
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Abstract:
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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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