Fuel Input Substitution under Tradable Carbon Permits System: Evidence from Finnish Energy Plants 2005-2008

Abstract

Following the Kyoto protocol and the European Union climate policies energy plants exceeding 20 MW capacity have been part of the EU’s emissions-trading scheme (ETS) since 2005. However, the users of renewable fuels will not pay for tradable carbon allowances. Advanced energy production technologies enable the switch from fossil fuels to renewable wood fuels, and therefore wood fuels may constitute a competitive substitute for fossil fuels, especially if the price of allowances is relatively high. In this context we analyzed plant level Finnish data from years 2005-2008 with mixed models. Econometric equations were specified and estimated for the wood-fossil fuel ratios, and for the fossil fuel cost shares. We found that the EU ETS has short term impacts on the fuel mixes of the energy plants. The elasticity ofsubstitution between fossil and non-fossil fuels is larger under the ETS. Large plants have adjusted their fuel technology choices toward more wood using and fuel price sensitive forms. The size of energy plants and heterogeneity among them across the industries determine the extent of fuel substitution. However plants’ regional locations have limited roles in the interfuel flexibility.

Keywords

EU Emission-Trading Scheme fossil energy wood energy mixed models

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References

Arimura

T.H.

(2002). “An Empirical Study of the SO2 Allowance Market: Effects of PUC Regulations.” Journal of Environmental Economics and Management 44(2): 271-289. https://dx-doi-org.web.bisu.edu.cn/10.1006/jeem.2001.1202.

Bailey

Ditty

(2009). “Energy markets, capital inertia and economic instrument impacts.” Climate Policy 9(1): 22-39. https://dx-doi-org.web.bisu.edu.cn/10.3763/cpol.2008.0454.

Baltagi

B.H.

Song

S.H.

Jung

B.C.

(2001). “The Unbalanced Nested Error Component Regression Model.” Journal of Econometrics 101: 357-381. https://dx-doi-org.web.bisu.edu.cn/10.1016/S0304-4076(00)00089-0.

Berndt

Wood

(1975). “Technology, Prices and the Derived Demand for Energy.” Review of Economics and Statistics 57: 376-384. https://dx-doi-org.web.bisu.edu.cn/10.2307/1923910.

Boucekkine

Hritonenko

Yatsenko

(2008). Optimal Firm Behaviour under Environmental Constraints. CORE DP-2008–24.

Brannlund

Kristrom

(2001). “Too hot to handle? Benefits and costs of stimulating the use of biofuels in the Swedish heating sector.” Resource and Energy Economics 23(4): 343-358.

Brannlund

Lundgren

(2004). “A dynamic analysis of interfuel substitution for Swedish heating plants.” Energy Economics 26(6): 961-976. https://dx-doi-org.web.bisu.edu.cn/10.1080/0003684042000 177170.

Brannlund

Marklund

P.-O.

Sjostrom

(2004). “Evaluating Market Efficiency without Price Data: The Swedish Market for Wood Fuel.” Applied Economics 36(1): 31-39. https://dx-doi-org.web.bisu.edu.cn/10.1016/j.eneco.2004.09.001.

Chang

K.-P.

(1994). “Capital-Energy Substitution and the Multilevel CES Production Function.” Energy Economics 16(1):22-26. https://dx-doi-org.web.bisu.edu.cn/10.1016/0140-9883(94)90014-0.

10.

EC , (2007). “EU emissions trading: an open system promoting global innovation.” Document available online at: http://ec.europa.eu/environment/climat/pdf/brochures/eu_action.pdf. Refereed 28.8.2009.

11.

EC , (2003). “Establishing a scheme for greenhouse gas emission allowance trading within the Community and amending Council Directive 96/61/EC.” Directive 2003/87/EC of the European parliament and of the council of 13 October 2003.

12.

Ericsson

Huttunen

Nilsson

L.J.

Svenningsson

(2004). “Bioenergy policy and market development in Finland and Sweden.” Energy Policy 32(15): 1707-1721. https://dx-doi-org.web.bisu.edu.cn/10.1016/S0301-4215(03)00161-7.

13.

Gelman

(2003). “Multilevel (Hierarchical) Modeling: What it Can and Cannot Do.” Technometrics 48, 432–435. https://dx-doi-org.web.bisu.edu.cn/10.1198/004017005000000661.

14.

Gelman

Hunt

(2006). Data Analysis Using Regression Analysis with Multilevel/Hierarhical Models. Cambridge: Cambridge University Press. https://dx-doi-org.web.bisu.edu.cn/10.1017/CB09780511790942.

15.

Harsstad

Eskeland

G.S.

(2007). Trading for the Future. Signaling in Permit Markets. CICERO WP 2007–1.

16.

Heathtfield

D.F.

Wibe

(1987). An Introduction to Cost and Production Functions. London: MacMillan.

17.

Jamison

D.T.

Lau

L.J.

Wang

J. J.

(2005). “Health’s Contribution to Economic Growth in an Environment of Partially Endogenous Technical Progress.” In R.B. Lopez-Casasnovas and L. Cur-rais, eds., Health and Economics. MIT Press. pp. 67-92.

18.

Kangas

H-L.

Lintunen

Uusivuori

(2009). “The Co-firing Problem of a Power Plant under Policy Regulations.” Energy Policy 37(5): 1898-1904. https://dx-doi-org.web.bisu.edu.cn/10.1016Zj.enpol.2009.01. 028.

19.

Kara

Syri

Lehtila

Helynen

Kekkonen

Ruska

Forsstrom

(2008). “The impacts of EU CO2 emission trading on electricity markets and electricity consumers in Finland.” Energy Economics 30(2): 193-211. https://dx-doi-org.web.bisu.edu.cn/10.1016/j.eneco.2006.04.001.

20.

Linden

Peltola-Ojala

(2010). “The deregulation effects of Finnish electricity markets on district heating prices.” Energy Economics 32(5): 1191-1198. https://dx-doi-org.web.bisu.edu.cn/10.1016/j.eneco.2010.03.002.

21.

Menanteu

Finon

Lamy

(2003). “Prices versus quantities: choosing policies for promoting the development of renewable energy.” Energy Policy 31(8): 799-812. https://dx-doi-org.web.bisu.edu.cn/10.1016/S0301-4215(02)00133-7.

22.

POMAR , (2007). Market analysis and risk management of EU emission trading. Project Report. University of Helsinki.

23.

Reister

D.B.

Edmonds

J.A.

(1981). “Energy Demand Models Based on the Translog and CESD Functions.” Energy 6(9): 917-926. https://dx-doi-org.web.bisu.edu.cn/10.1016/0360-5442(81)90063-3.

24.

Singer

J.D.

Willett

J.B.

(2003). Applied Longitudinal Analysis. Modelling Change and Event Occurrence. Oxford: Oxford University Press.

25.

Soderholm

(1998). “The Modelling of Fuel Use in the Power Sector: A Survey of Econometric Analyses.” Journal of Energy Literature 4(2): 3-27.

26.

Soderholm

(2000). “Fuel flexibility in the West European power sector.” Resources Policy 26: 157-170. https://dx-doi-org.web.bisu.edu.cn/10.1016/S0301-4207(00)00025-8.

27.

Soderholm

(2001). “Fossil fuel flexibility in west European power generation and the impact of system load factors.” Energy Economics 23: 77-97. https://dx-doi-org.web.bisu.edu.cn/10.1016/S0140-9883(00) 00062–1.

28.

Tauchmann

(2005). “CO2 Abatement and Fuel Mix in German Electric Power Generation: Is the “Ecological Electricity Tax” Ecologically Effective” Energy & Environment 16(2):255-271. https://dx-doi-org.web.bisu.edu.cn/10.1260/0958305053749561.

29.

Tauchmann

(2006). “Firing the furnace? An econometric analysis of utilities’ fuel choice.” Energy Policy 34(18): 3898-3909. https://dx-doi-org.web.bisu.edu.cn/10.1016Zj.enpol.2005.09.014.

30.

Tietenberg

T.H.

(2006). Emission Trading: Principles and Practice. 2nd edition. Washington: RFF.

31.

Urga

Walters

(2003). “Dynamic Translog and Linear Logit Models: A Factor Demand Analysis of Interfuel Substitution in US Industry Energy Demand.” Energy Economics 25(1): 121. https://dx-doi-org.web.bisu.edu.cn/10.1016/S0140-9883(02)00022-1.

32.

Wallis

K.F.

(1985). Topics in Applied Econometrics. 2nd edition. London: Blackwell.

33.

Zhang

(2007). Does Uncertainty Matter? A Stochastic Dynamic Analysis of Bankable Emission Permit Trading for Global Climate Policy. World Bank Policy Research WP-4215.