Econometric Analysis of Carbon Markets Figure 1: Carbon Prices from April 2009 to May 2010
10 11 12 13 14 15 16
9 EUA Price Dec 10 €15.94
from a broad dataset including macroeconomic, financial and commodities indicators. The results show that carbon prices tend to respond negatively to an exogenous recessionary shock on global economic indicators. While the class of factor models constitutes a promising area for future research, this issue needs further development in order to understand the core relationship between carbon prices and economic growth.
Links Between Carbon Markets CER Price Dec 10 €14.05
Finally, the links between carbon markets may be established by using other econometric tools, such as vector auto-regression and cointegration. These techniques have been applied recently to the analysis of EUAs and CERs by Mansanet-Bataller et al.14
EAU Dec 10 CER Dec 10
CER = certified emissions reduction; EAU = European Union allowance. Sources: European Climate Exchange (ECX), Reuters, Centres for Disease Control and Prevention (CDC) Climate Research.
Mansanet-Bataller et al.,9 Alberola et al.10 and Hintermann11 for the first
phase (2005–2007) of the EU ETS. These studies reveal that the main determinants of carbon price changes are linked:
• •
to energy markets – increases in oil/gas prices mechanically induce increases in the carbon price, since they are mostly used in fuel generation;
to weather events – extreme temperatures events compared with decennial averages have an impact on carbon prices;
• to regulatory choices, such as amendments to the scheme created by the European Commission; and
• to economic growth – when various industries need to create more
products, the demand for CO2 allowances is higher and hence its price increases.
These results have been derived using standard regression analysis. Link with the Macroeconomy
The first article examines the empirical relationship between the returns on carbon futures and changes in macroeconomic conditions in multivariate regression analysis with asymmetric GARCH effects.12
The link with the macroeconomy has been further studied by Chevallier.12,13
The authors
show that there is a long-term relationship between both of these emissions assets, with deviations from the equilibrium being primarily corrected by EUAs. This first result confirms that the EU ETS is the leader in the discovery of carbon prices (compared to CERs).
The authors also investigate the price fundamentals of EUAs for phase II and CERs in a vector auto-regression framework.14
This analysis reveals that the lagged values of EUAs have a statistically significant
While the class of factor models constitutes a promising area for future research, this issue needs further development in order to understand the core relationship between carbon prices and economic growth.
impact on CERs, while CERs share some of the same drivers as EUAs during the period. Most importantly, they reveal that there are significant opportunities for price arbitrage between the two markets.
Conclusion
By using variables that possess forecast power for equity and commodity returns, the author shows that carbon futures may be weakly forecast on the basis of two variables from the stock and bond markets: equity dividend yields and the junk bond premium. In the latter article,13
Chevallier carries out an assessment of the
transmission of international shocks to the carbon market in a factor-augmented vector autoregression model, with factors extracted
1. World Bank, State and Trends of the Carbon Markets, 2010, World Bank, Washington DC, US, 2010.
2. 3.
Benz E, Trueck S, Modeling the price dynamics of CO2 emission allowances, Energy Economics, 2009;31(1):4–15.
Chevallier J, Ielpo F, Mercier L, Risk aversion and institutional information disclosure on the European carbon market: a case-study of the 2006 compliance event, Energy Policy, 2009;37(1):15–28.
4. 5.
Paolella M, Taschini L, An econometric analysis of emission allowances trading prices, J Banking Finance, 2008;32(10):2022–32.
Daskalakis G, Psychoyios D, Markellos RN, Modeling CO2 emission allowance prices and derivatives: Evidence from the
6 6. 7
This article briefly reviews the time series econometric techniques that may be applied to the analysis of carbon markets. While the existing literature has already brought a wealth of insights into this quickly developing emissions asset, many areas for further developments remain. These include, for instance, the need to model the interactions between carbon markets and other energy markets in multivariate GARCH models, or to evaluate the correlations between them in such multivariate frameworks. n
European trading scheme, J Banking Finance, 2009;33(7):1230–41.
Chevallier J, Sévi B, Jump-robust estimation of realized volatility in the EU emissions trading scheme, J Energy Markets, 2010;3(2):49–67.
Christiansen A, Arvanitakis A, Tangen K, et al., Price determinants in the EU Emissions Trading Scheme, Climate Policy, 2005;5:15–30.
8. Kanen JLM, Carbon Trading and Pricing, Environmental Finance Publications, 2006.
9.
Mansanet-Bataller M, Pardo A, Valor E, CO2 prices, energy and weather, Energy J, 2007;28(3):73–92.
10. Alberola E, Chevallier J, Chèze B, Price drivers and structural
breaks in European carbon prices 2005–2007, Energy Policy, 2008;36(2):787–97.
11. Hintermann B, Allowance price drivers in the first phase of the EU ETS, J Environmental Econ Manage, 2010;59(1):43–56.
12. Chevallier J, Carbon futures and macroeconomic risk factors: A view from the EU ETS, Energy Economics, 2009;31(4):614–25.
13. Chevallier J, Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model, Economic Modelling, 2010; [Epub ahead of print].
14. Mansanet-Bataller M, Chevallier J, Mansanet-Batalla M, et al., EUA and sCER phase II price drivers: unveiling the reasons for the existence of the EUA-sCER spread, Energy Policy, 2010 [epub ahead of print].
MODERN ENERGY REVIEW – VOLLUME 3 ISSUE 1
Apr 09 May 09 Jun 09 Jul 09 Aug 09 Sep 09 Oct 09 Nov 09
Dec 09 Jan 10 Feb 10
Mar 10 Apr 10
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