Thursday, June 23, 2011

Forecasting the European Carbon Market
Abstract: In an effort to meet its obligations under the Kyoto Protocol, in 2005 the European Union introduced a cap-and-trade scheme where mandated installations are allocated permits to emit CO2. Financial markets have developed that allow companies to trade these carbon permits. For the EU to achieve reductions in CO2 emissions at a minimum cost, it is necessary that companies make appropriate investments and policymakers design optimal policies. In an effort to clarify the workings of the carbon market, several recent papers have attempted to statistically model it. However, the European carbon market (EU ETS) has many institutional features that potentially impact on daily carbon prices (and associated ?nancial futures). As a consequence, the carbon market has properties that are quite different from conventional financial assets traded in mature markets. In this paper, we use dynamic modelaveraging (DMA) in order to forecast in this newly-developing market. DMA is a recently-developed statistical method which has three advantages over conventional approaches. First, it allows the coefficients on the predictors in a forecasting model to change over time. Second, it allows for the entire forecasting model to change over time. Third, it surmounts statistical problems which arise from the large number of potential predictors that can explain carbon prices. Our empirical results indicate that there are both important policy and statistical benefits with our approach. Statistically, we present strong evidence that there is substantial turbulence and change in the EU ETS market, and that DMA can model these features and forecast accurately compared to conventional approaches. From a policy perspective, we discuss the relative and changing role of different price drivers in the EU ETS. Finally, we document the forecast performance of DMA and discuss how this relates to the efficiency and maturity of this market.

The full paper is available free of charge at

by Gary Koop 1 and Lise Tole 2
1. Department of Economics,University of Strathclyde Business School, Department of Economics Sir William Duncan Building, 130 Rottenrow, Glasgow G4 0GE; Phone: +44 (0)141 548 3842; Fax: +44 (0)141 548 4445,
2. Edinburgh University, Business School;
University of Strathclyde Business School, Department of Economics
Working Paper 1110; April, 20111; 40 pages
Keywords: Bayesian; carbon permit trading; financial markets; state space model; model averaging;

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