حاشیه منحنی هزینه کاهش در تعادل عمومی: تاثیر قیمت های انرژی جهان

Marginal abatement cost curves (MACCs) are a favorite instrument to analyze international emissions trading. This paper focuses on the question of how to define MACCs in a general equilibrium context where the global abatement level influences energy prices and in turn national MACCs. We discuss the mechanisms theoretically and then use the CGE model DART for quantitative simulations. The result is, that changes in energy prices resulting from different global abatement levels do indeed affect national MACCs. Also, we compare different possibilities of defining MACCs—of which some are robust against changes in energy prices while others vary considerably.

In the last years marginal abatement cost curves (MACCs) have become a standard tool to analyze the impacts of the Kyoto Protocol and emissions trading. Once such curves are available for the different world regions it is very easy to determine permit prices, total abatement cost and regional emissions for different scenarios of international emissions trading. A detailed description of the use of the MACCs is provided in the papers of Ellerman and Decaux (1998) and Criqui et al. (1999). A number of other authors have followed the approach Blanchard et al., 2002, den Elzen and de Moor, 2002, Löschel and Zhang, 2002, Lucas et al., 2002 and van Steenberghe, 2002 analyzing scenarios such as emissions trading with and without the participation of the USA, the use of market power by Russia and the Ukraine, multiple gas abatement and banking. All these studies implicitly assume that each region/country has its unique marginal abatement cost curve independent of, e.g. the abatement levels of other regions or whether emissions trading is taking place or not. One justification for this assumption is the finding of Ellerman and Decaux (1998) that MACCs are indeed robust with respect to such policy parameters. This is somehow a surprise as Ellerman and Decaux note themselves that with international trade the abatement level in one country influences trade flows such that the MACCs may change in other countries. Their simulations with the EPPA model though, show that the variation in prices is less than 10% between different scenarios for any given level of abatement. Commonly, the marginal abatement cost for a certain abatement level is derived as the shadow price for the associated emission constraint. As we will discuss, this shadow price is influenced by world energy prices which differ across different abatement scenarios. The reason behind this is that abatement levels in one country influence its energy demand, which might in turn influence the world energy price. With, for example, higher world energy prices regions automatically demand less energy and emit less carbon so that the same emission target becomes less binding. The magnitude of the difference in shadow prices depends on a number of factors such as trade elasticities and trade structures. This suggests that MACCs depend on world energy prices and may shift across different abatement scenarios. Against this background, this paper tries to clarify what MACCs are, what factors influence the MACCs in different scenarios and how the MACCs should be used. In addition, the problem of choosing the reference point for the MACC is discussed. We will first explore the energy price effects theoretically in a stylized model and second quantify them using the computable general equilibrium model DART. The main result is that not only theoretically MACCs change with varying energy prices, but that the difference can reach a magnitude that cannot be neglected. The paper proceeds as follows. The next sections defines marginal abatement cost curves, explains how they are constructed and used in practice and presents estimates for different regions. Section 3 shows in different settings how shadow prices depend on energy prices and how this affects MACCs. Section 4 introduces the computable general equilibrium model DART, defines our scenarios and presents the results of the simulations. Section 5 concludes.

In the previous sections we have shown theoretically and empirically how marginal abatement cost curves depend on abatement levels in the rest of the world via changes in international fossil fuel prices. We also discussed three different possibilities to derive graphs for MACCs from the social cost curves of emission restrictions: in terms of emission targets, in terms of absolute abatement relative to the unconstrained emission level and finally in terms of relative (%) abatement relative to the unconstrained emission level. For each of these approaches one can define measures of robustness with respect to the reference situation of the simulation exercise. It turns out that even though in all cases MACCs react to energy prices, this reaction is rather small in the two latter cases, so that the MACCs in terms of absolute or relative abatement levels can be termed robust. The MACCs in terms of emission targets though, may change considerably. The question remains whether there is one “true” representation of a MACC. We believe this is not the case, since the three representations refer to three different ways of looking at the problem. The MACCs in terms of absolute or relative abatement levels show the marginal cost of a certain reduction level starting from a particular reference situation that is not explicitly shown in such graphs. Hence, the impact of fossil fuel prices on the overall social cost is not very transparent. Such MACCs turn out to be quite robust, mainly because absolute and relative abatement levels are taken without reference to particular emission targets. However, the costs of reaching, e.g., the Kyoto target with a fixed emission level, may be better illustrated with the MACCs shown in terms of emission levels. These graphs implicitly take into account the effect of different reference situations influencing fossil fuel prices. They are less robust, mainly because for reaching a certain emission target the abatement levels need to be varied under different reference situations thus leading to an amplification of marginal costs. Instead of using the MACCs one could directly refer to the social cost curve for achieving a certain emission target. This approach explicitly takes into account the interaction of marginal abatement costs and fossil fuel prices. In addition, it is the social cost curve that is used to determine the welfare loss in terms of GDP of a certain emission target—not any of the MACCs. As the social cost is the sum of the fossil fuel price and the marginal abatement cost, the information of MACs alone – not accompanied by the associated fossil fuel prices – is of little help. The theoretical part has shown that in the setting of open economies unique social cost curves of emissions only exist for a particular fossil fuel price – in the case of a small open economy – or for a particular emission level in the rest of the world—in the case of a large open economy. They define a set of curves as illustrated in Fig. 4. For empirical purposes, however, the simulations have shown that the differences in the shapes of these curves are very small when compared to the differences imposed by the fossil fuel prices. The discussion about the robustness of MACCs is in fact concerned with the shape of different social cost curves at different segments of these curves. In contrast, the open economy effects on the social cost curve determine the distance between the social cost curves under different reference scenarios which do hardly change the shape of a MACC. In summary, the robustness of MACCs with respect to different reference situations is something to check when transferring MACCs derived from a particular simulation exercise to other policy scenarios. The international relative price effects of the open economy framework, on the other hand, do not seem to affect MACCs in a significant way.