1 Intelligent Well Technology: Status and Opportunities for Developing Marginal Reserves SPE

MODELING THE PRICE SPREADBETWEEN THE EUA AND THE CER CARBON PRICES

Fatemeh Nazifi, MacquarieUniversity, Sydney, Australia,+612 98504844,

Overview

The European Union has established a direct link between the European Emission Trading Scheme (EU ETS) and the Clean Development Mechanism (CDM) in order to increase the cost-effectiveness of complying with the Kyoto Protocol. Certified Emission Reduction credits (CERs) generated from CDM projects in developing countries are fully fungible for compliance within the EU ETS and are recognised as equivalent to the European Allowances (EUAs). Secondary CERs that are underwritten by investment banks are risk-free carbon credits and are expected to be used as substitutes for EUAs and should therefore have the same price. However, EUA prices exceed CER prices. This paper is one of the first studies to highlight the difference between these two types of compliance tools in the EU ETS and investigates the strength of price convergence between these tools.I extend the existing literature by providing new insights into the issue of interdependency between the EU ETS and the CDM by investigating instances of price convergence. More specifically, it models the price differential between EUAs and CERs and investigates factors that may explain the existing differential between their current forward prices. My results indicate that a sustained convergence cannot be found between the EUA and the CER prices series over the entire period although there is a relatively brief period of price convergence between them. I identify that a cap on the amount of CERs should be considered as primary factor underlying the price spread.

Methods

My methodological approach, to formally analyse the price spread, follows a sequence of econometric tests that allows for non-stationary time series. As a first step to model the price spread, I apply unit root tests by taking into account the possibility of the existence of a shift in the level of the time series. Based on the results, in the second stage of the analysis I conduct statistical tests of co-movement between EUA and CER prices. These tests include cointegration tests, which look at the stability of the long-run relationship, as well as a convergence test that examines whether the two price series converge to the same value over time through a relative long-run equilibrium or convergence in terms of their cross sectional variance ratio rather than their difference. The reason for testing for convergence is that the price convergence can be a gradual process so applying the convergence test in this case is more useful than a cointegration test, which is good for detecting already integrated or converged prices. As the focus is on the long-run behaviour of the data, the test is applied on the long-run components by means of the Hodric-Prescott smoothing filter. Furthermore, as failure to detect cointegration does not imply that the price convergence does not exist due to its assumption of a fixed structural relationship between time series, I further investigate the issue. In brief, I use a time-varying parameter analysis which deals with the non-stationary and non-cointegrating time series, in order to explicitly detect changes in the structural relationship, model the price spread, and measure the degree of price convergence to complement the cointegration and convergence results. This statistical approach is better suited for detecting price convergence than standard techniques because it takes into consideration the possibility of a dynamic structural change in the context of investigating the price spread and allows for an assessment of the strength of the price convergence.Moreover, it allows us to compute the optimal time–varying estimates of the parameters of the model for each time period. The dataset consists of daily price observations for the EUA as well as the CER futures contracts, as listed on the European Climate Exchange.

Results

The results do not support the hypothesis that the two prices form a long-run equilibrium relationship. Furthermore, although there is a relatively brief period of price convergence at the end of 2008 and early 2009, based on the statistical evidence, a sustained convergence cannot be found between EUA and CER prices series over the entire time period considered. This is contrary to what one could expect from theory which predicts that the price differential between fungible carbon products would be eliminated through arbitrage.By plotting the results of the time-varying parameters of the model, however,I find that the degree of price convergence between them has improved in the second half of 2008. This shift in price convergence,identified using the Kalman filter, can be pinpointed by the two key events of linking the EU ETS directly to the CDM and the financial crises which have had significant impacts on carbon prices and in turn on the price spread. Moreover, it seems that the risk with respect to the delivery of CERs would not be counted as a strong explanatory variable in modeling the price spread.

Conclusions

Overall, my analysis suggests that CERs do not share a common trend with EUA prices, and empirical results reveal no convergence between them. A number of factors are hypothesised to account for this finding. Firstly, it seems that the access constraints on the use and availability of CERs, emanating from the supplementarity issue, limit the substitutability of project-based credits, so they cannot serve as equivalent substitutes for EUA and their prices consistently fall below EUA prices. In addition, EUA prices are determined in the EU ETS, which is the most established and major market for greenhouse gas emission allowances and dominates the global carbon market both in transaction and monetary value. In comparison, the CDMmarket is a relatively new market. Concerns regarding the issues such as uncertainties about the long-term future of the CDM market and its role post Kyoto, functioning of the link between the International Transaction Log (ITL) and the Community Independent Transaction Log (CITL), reputational risk (choice between internal abatement or external emission reductions), some lack of clarity regarding the use and the import of project-based credits (including swapping and banking) within the EU ETS in Phase II and III could result in less fungibility and less flexibility of CER in comparison with a more politically viable, stable and certain EUA which could impact on the speed of price convergence between them.All implies that the situation can arise in which prices behave in a fashion that is consistently at a departure with the Law of One Price and price convergence.

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