| 摘要 | 1. Research Purpose
The world is trying to address climate change through The United Nations Framework Convention on Climate Change and Kyoto Protocol. Specially, the roadmap to the post 2012 was established in the 13th COP(Conference of Parties) and the 3rd CMP(Conference of Parties serving as Meeting of Parties to the Kyoto Protocol) of UNFCCC at Bali, Indonesia. Also Ad Hoc Working Group on Further Commitments for Annex I Parties under the Kyoto Protocol called for four more meetings until 2009, 5th CMP.
The Bali Action Plan was agreed upon to address global climate change including developing countries as well as developed countries. So Ad Hoc Working Group on Long-term Cooperative Action under the Convention was established and shall complete its work in 2009 and present the outcome of its work to the Conference of the Parties for adoption at its 15th session.
Until now, Korea has no quantified emissions reduction commitment on Climate Change as non-Annex I country but we may consider voluntary commitment or quantified emissions reduction commitment depending on further negotiations.
Already, the Kyoto Protocol's commitment period will start since 2008 in Annex I countries such as EU (excluding USA). To address this issue, EU Emission Trading System has been implemented from 2005. EU Emission Trading System is the largest emission trading scheme and the Carbon price of EU emission trading market(EUA) has been leading world carbon price and Index of general carbon price. ie EUA roles as an important index in determining CERs known as the carbon price of CDM(Clean Development Mechanism), and ERUs known as the carbon price of JI(Joint implementation).
It is very important to analyse determinant factors of EUA(the carbon price of EU emission trading system) and dynamic correlations between fossil fuel price(coal, oil, gas, coal-gas differentials) in order to address high oil price and climate change.
This report analyzed a dynamic correlations between fossil fuel price and EUAs by various econometrics methods. Also we analyzed DAG between several exchanges which are scattered all over EU and found out which exchanges play an important role.
2. Summary
This report analyzed dynamic correlation between fossil fuel price and EUA in the context that fossil fuel price is an important determinant factor in EUA. In addition, it analyzed simultaneous causal relationship between emissions trading all over EU.
First, the tasks was divided into two parts when we analyze dynamic correlations between fossil fuel price and EUAs, one is daily data and the other is weekly data. In daily data, EUAs were highly correlated with oil price and the coefficients of oil price to EUAs is within 99% confidence interval. As we expected, the coefficients of CGD(Coal- Gas Differentials) to EUAs are not in 95% confidence interval. It is because CGD (which indicates fuel switching in power generating sector) affects to EUAs in the long term. It tells with oil in the short term.
In weekly data, EUAs were highly correlated with oil price and the coefficients of oil price to EUAs are within 99% confidence interval. The coefficients of oil price to EUAs in weekly data are higher than in daily data. The coefficients of CGD(Coal-Gas Differentials) to EUAs in weekly data is also higher than in daily data. It is because the data term in weekly data is longer than in daily data and the power generating company could decide fuel switching in this term.
We analysed a simultaneous causal relationship among emissions trading in the EU region by two methods of PC algorithm and GES algorithm. The picture below shows simultaneous causal relationship by PC algorithm.
Graph Analysis (PC Algorithm)
As we can be seen in the figure, all 6 carbon markets (spot and forward carbon market) have been connected with any channels. As a result, 2007 forward price of Nordpool is functioning as information sink which absorbs all price information from Powernext, EEX, ECX as well as the spot price of Nordpool.
If we exclude 2007 forward price of Nordpool, EEX has 3 connections with other markets including No-Direction connections and others has one or two connections. Though any markets are not isolated, we can not judge that markets is actively connected with each other. Because the size of emerging market EEX in Austria doesn't come up to 2% of the size of all EU markets, it's connections with other markets are weak as we expected.
Graph Analysis (GES Algorithm)
Because Nordpool market plays an important role as information sink in building CO2 EU emissions trading price, we have to pay attention to trends of this market. In addition, Powernext in France plays a role of transmitting EEX price information to Nordpool forward prices based on the result of PC algorithm. It is beacause CO2 emission transaction platform of Nordpool is based on Powernext.
In the next step, we analysed a simultaneous causal relationship with emissions trading exchanges in the EU region based on GES algorithm. Though the pattern of connections among markets are similar, they move in the opposite direction in the markets. Nordpool spot price affects Nordpool forward price in PC algorithm. Nordpool forward price affects Nordpool spot price in GES algorithm. We have same results in the case of Powernext. Even though there is opposite directions in the case of Powernext and Nordpool, we have to our attention that the connections among these markets is very close.
In this research, we used Nordpool 2007 forward price and ECX 2007 forward price. But the 2008 forward permits trade in a range of price ��10~15. So We have to analyze additionally one price in one good test or bias estimation.
3. Research Results and Policy Suggestions
Oil price is a very important index when we are forecating short term price fluctuation of emissions trading price based on the results of this dynamic correlation relationship. We can forecast how much emission trading price fluctuate, if we forecast how much oil price fluctuate in the future. So financial institutions which trade emission permits in purpose of return rate can forecast short-term permits price fluctuation. Until now, the data of emission trading is limited, we could not analyze the long term price forecasting. But global emission trading system become establish and markets are mature, we can analyze the long term price forecasting in the future.
We have two important findings when we analysed a simultaneous causal relationship between emission trading exchanges of EU region. First, EU emission trading markets are connected very closely each other. We found that these markets are connected in both simultaneous causal relationship and lagged causal relationship and both directly and indirectly. In particular, Nordpool forward price play an important role as information sink and Powernext and EEX is a very important market in EU emission trading system. The power exchanges plays an important role in emission trading. If we introduce emission trading system in the future, we can consider Korean Power Exchange as carbon exchanges.
Second, The forward market price plays an important role in emission trading markets based on the fact which the spot price information converges to the forward price information of Nordpool. So Nordpool forward price plays an important role when we forecast emission permit price in the future. |
