Econometric analysis of Australian emissions markets and electricity prices
Emissions trading schemes aim to reduce the emissions in certain pollutants using a market based scheme where participants can buy and sell permits for these emissions. This paper analyses the efficiency of the two largest schemes in Australia, the NSW Greenhouse Gas Abatement Scheme and the Mandato...
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Veröffentlicht in: | Energy policy 2014-11, Vol.74, p.475-485 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | Emissions trading schemes aim to reduce the emissions in certain pollutants using a market based scheme where participants can buy and sell permits for these emissions. This paper analyses the efficiency of the two largest schemes in Australia, the NSW Greenhouse Gas Abatement Scheme and the Mandatory Renewable Energy Trading Scheme, through their effect on the electricity prices from 2004 to 2010. We use a long run structural modelling technique for the first time on this market. It provides a practical long-run approach to structural relationships which enable the determination of the effectiveness of the theoretical expectations of these schemes. The generalised forecast error variance decomposition analysis finds that both schemes׳ emissions prices have little effect on electricity prices. Generalised impulse response function analysis support this finding indicating that when shocks are applied to electricity by the two schemes it returns to equilibrium very quickly. This indicates that these schemes are not having the effect anticipated in their legislation.
•We analyse two emissions trading schemes in Australia.•We test for their effect on wholesale electricity prices.•The test uses generalised forecast error variance decomposition analysis.•The tests find long run relationship between the variables in both the samples.•The short run-dynamics indicate that they play a minimal role in electricity prices. |
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ISSN: | 0301-4215 1873-6777 |
DOI: | 10.1016/j.enpol.2014.07.024 |