The Emission Trading Scheme (ETS) is a cornerstone for European efforts to reduce greenhouse gas emissions, and in its test phase will operate from 2005-2007. It is a cap-and-trade system where an aggregate cap on emissions is set by the respective government agencies to define the total number of emissions allowances. Each allowance gives the owner the right to emit one unit (usually one ton) of emissions. Covered establishments that exceeded the limits may buy emissions credits from entities with allowances they do not need to use themselves. One key feature of this system is that the amount of emissions is capped whereas the permit prices are uncertain. These permit prices are determined by economic conditions, generally, stronger economic growth means a higher permit price.
The objective of this thesis is to understand uncertainty in permit prices under the system, by determining the likelihood that permit prices will fall within a given range. This is accomplished through stochastic analysis simulation of a computable general equilibrium model of the world economy with country-level detail most of the key members of the original 15 member EU plus the 10 accession countries. Economic parameters treated as stochastic in the simulations were labor productivity growth, share of new capital vintaged, the rate of autonomous energy efficiency improvement, the elasticity of substitution between energy and non-energy composites, and oil/gas prices. Information on the likely range of future permit prices will allow operators of covered establishments to decide on the extent to which they should buy permits or invest in emissions reduction technologies possible reducing emissions below their cap, allowing them to sell allowances. While some abatement activities may involve only changes in operation and management of facilities, other may involve longer-term investment. These abatement decisions boil down to basic investment problems. How should entities affected by the ETS plan their investment policies, such that they can minimize costs? To answer this question firms need an estimate of likely future permit prices.
Results were that a zero carbon price occurred with a probability of 28-48% across variants of the Monte Carlo simulations. The mean value for the carbon prices was about $0.40 per ton of carbon, and the maximum price across the variants ranged from about $3.50 to somewhat over $6.00 per ton carbon. The implication for firms is that costly abatement investments appear difficult to justify, except to the extent that firm’s are looking beyond the ETS period when carbon permit prices would rise further.