مشوق ها و قیمت ها در یک طرح انتشار تجاری با به روز رسانی
کد مقاله | سال انتشار | تعداد صفحات مقاله انگلیسی |
---|---|---|
19513 | 2008 | 14 صفحه PDF |
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Environmental Economics and Management, Volume 56, Issue 1, July 2008, Pages 69–82
چکیده انگلیسی
Emissions trading schemes where allocations are based on updated baseline emissions give firms less incentive to reduce emissions for a given quota (or allowance) price. Nevertheless, according to Böhringer and Lange [On the design of optimal grandfathering schemes for emission allowances, Europ. Econ. Rev. 49 (2005) 2041–2055], such allocation schemes are cost-effective if the system is closed and allocation rules are identical across firms. In this paper, we show that the cost-effective solution may be infeasible if marginal abatement costs grow too fast. Moreover, if a price cap or banking/borrowing is introduced, the abatement profile is no longer the same as in the case with an auction (or lump-sum allocation). In addition, we show that with allocation based on updated emissions, the quota price will always exceed marginal abatement costs, possibly misguiding policy makers and investors about abatement costs. Numerical simulations indicate that the quota price most likely will be several times higher than marginal abatement costs, unless a significant share of allowances is auctioned.
مقدمه انگلیسی
A competitive emissions trading market is a cost-effective way of reducing emissions, as long as emissions allowances or quotas are either auctioned or distributed in a lump-sum manner.1 This well-known result dates back to the 1970s [19]. The design of real-world emissions trading schemes shows, however, that few allowances are auctioned. Moreover, it is difficult to allocate allowances in a lump-sum manner over a longer time horizon without creating perverse distributional effects. Thus, other allocation mechanisms are introduced. Within the EU Emissions Trading Scheme (EU ETS) (cf., [10], [11] and [25]) allocation for the first two periods (2005–2007 and 2008–2012) is mostly based on recent historic emissions levels, but special rules apply for, for example, new entrants and firms’ closure. The allocation rules for future periods are not determined yet, and are open to speculation. The SO2 trading program in the US has mostly lump-sum allocation based on grandfathering, but it also includes allocation rules that have created “an additional set of incentives” [8]. The prime motive for avoiding auctioning or lump-sum allocation is to prevent a deterioration of competitiveness relative to polluters outside the trading system. In the very recent economic literature, there has been some analysis (and discussion) of different kinds of allocation rules. Following Sterner and Muller [24] it is useful to distinguish between “current allocation” and allocation based on “updating”. With current allocation, allowances are distributed based on a measure of activity in the current period, where the measure of activity may be the level of output (production), input or even emissions. With updating, allowances are distributed based on activity/emissions in a recent base year, which is continually updated. It is evident that, with either current allocation or updating, firms can influence the number of allowances they receive (either today or in the future), and so the conditions for the above-mentioned result on cost-effectiveness are no longer present.2 Nevertheless, a closed emissions trading system with updated allocation based on emissions is actually cost-effective [4]. Even though firms take into account the effect of current emissions upon future allowances, all firms face the same rule. Thus, with a fixed total emissions level and equal expectations about the future allowance or quota price, the current price is bid up and all firms adjust abatement until marginal abatement costs (MAC) equal the current quota price minus expected benefits from future allowances. In contrast, in an open system, for example, the EU ETS linked to external allowances like the Clean Development Mechanism (CDM), updating based on emissions is no longer cost-effective. Moreover, an updating system based on output levels cannot be cost-effective in either an open or closed system [4]. Åhman et al. [1] propose a 10-year updating rule, where allowances are proportional to activity levels 10 years ago. They claim that a 10-year lag would significantly weaken the unwanted effects of future allocation on current behavior, because of discounting of the value of future allowances. Keats Martinez and Neuhoff [16] argue that updating based on emissions can distort the allowance price, which would lead to inefficiencies, if different sectors or regions are faced with different allocation rules or discount rates. A simple two-period example is used to demonstrate this claim. They also derive an expression for the quota price in the case with constant emissions target and abatement costs. Burtraw et al. [6] and [7] present simulation results of different allocation rules for a regional emissions trading market for electricity producers in nine states of the US. They find the quota price to be about twice as high with updating based on production levels (two years ago) compared with auctioning or grandfathering. The social costs of this system (measured as the change in economic surplus in the electricity market) are three times higher than with the two alternative systems (see also [21]). Harstad and Eskeland [14] analyze a model where the government aims to distribute more allowances to high-cost firms, and where firms signal high costs by purchasing large amounts of allowances. They conclude that prohibiting trade in allowances may be preferable under certain conditions. Few papers have analyzed the dynamic effects on emissions trading markets of implementing allocation rules based on updating.3 This paper provides a deeper examination of the dynamic effects of an allocation scheme based on updated emissions levels, within a closed emissions trading system.4 We point to several factors that may alter the conclusion that such a system is cost-effective. First, we show that the quota price may become infinitely large, rendering the cost-effective solution infeasible, if the MAC grow too fast. Second, an overallocation of quotas will increase emissions beyond its business-as-usual level. Third, introducing a (binding) price cap is shown to give less abatement in such a system compared with a system with, for example, auctioning. Fourth, if the system allows banking and borrowing, the system is no longer dynamically cost-effective if allocation is based on updated emissions levels. Too much abatement is delayed until later periods. The analysis is based on an extension of the analytical framework in [4]. The paper examines, both theoretically and numerically, the importance of policy variables such as the allocation rate (i.e., number of allowances based on previous emissions), the time lag between emissions and allowance (cf., the 10-year rule in [1]), the emissions target over time, and the time horizon of the system. In most realistic cases, the quota price turns out to be finite but several times higher than MAC, according to the numerical simulations. This divergence may give policy makers and market players a false impression of the abatement effort (and abatement costs) taking place in the market, and potentially distort decisions on policy and investments. Moreover, the risk of inefficiencies may increase.5 The analyses suggest that increasing the amount of auctioning and/or the time lag between emissions and allowances help to reduce the gap between price and marginal costs. However, in a growing economy with a fixed or gradually tighter emissions target, it is difficult to avoid a quota price that is several times higher than MAC without auctioning a majority of the allowances. Thus, it may be argued that updating might make more sense as part of a predictable transition to another approach, such as auctioning, than as the main approach to allocation in the long run. How relevant is updating as an allocation rule in real-world emissions trading schemes? According to Neuhoff et al. [20], 10 out of 25 countries in the EU (including Germany and The Netherlands) have in their national allocation plans (NAPs) updated their base year for Phase II of EU ETS to include 2005, i.e., the first year of Phase I. What happens beyond 2012 is not clear. According to Burtraw et al. [7], the second largest US emissions trading program, regulating NOxx emissions in 19 eastern states of the US, uses updating for some portion of the allowances. Price caps and banking/borrowing are partly used in some trading schemes, at least if we consider penalties without “make good” provisions as price caps [9]. The penalties for noncompliance in the EU ETS are combined with “make good” provisions in the next period, which means that a firm that does not comply must pay the penalty and surrender allowances for the next period. Banking and borrowing are allowed within periods in the EU ETS, and banking from the second to the third period (post-2012) is permitted. The SO2 trading program in the US has allowed banking between periods [8].
نتیجه گیری انگلیسی
Allocation of free allowances within emissions trading schemes is difficult without either distorting firms’ decisions or leading to adverse distributional effects. Nevertheless, allocation of free allowances based on updated emissions could lead to a cost-effective outcome of the emissions trading market, as long as the trading scheme is closed [4] . This finding would seem intriguing to policy makers afraid of introducing auctioning because of competitiveness considerations or lobbying. However, our analysis points to a number of qualifications to such a conclusion. First, an infinite emissions trading scheme with allocation based on updating may, in fact, be infeasible, as the price of allowances may become infinitely high. Second, if the total number of quotas exceeds the unregulated level of emissions, then emissions will increase beyond its business-as-usual level. Third, if a price cap is introduced in order to avoid too high quota prices, total emissions may become higher when allowances are based on updating than in the case with an auction. Fourth, if banking and borrowing are introduced, the trading scheme will (in realistic cases) no longer be dynamically cost-effective if allocation of allowances is (partly) based on updated emissions in some year(s).Although the case for an infeasible solution does not seem very likely, there will always be a gap between the quota price and MAC whenever some allowances are distributed based on updated emissions. There are several important factors that determine the ratio between the quota price and the MAC, some of these are determined by the policy makers (in particular the allocation rate). Numerical simulations indicate that the price of allowances will be several times higher than MAC, unless a majority of the allowances are auctioned. This applies even with long time lags. Sensitivity analyses (not reported here) clearly support these numerical findings. High prices of allowances will probably give policy makers a false impression of the costs of abatement. Moreover, risk of inefficiencies increase if the system is not as pure and simple as in the model presented in Section 2.1. We have already shown some examples of this, and similar inefficiencies would occur if, e.g., allocation rules, discount rates or future expectations differ among firms, or if there is some access to external quotas. Emissions trading schemes with free allocation have so far been the most favored instrument among policy makers when it comes to reducing emissions to air. Moreover, lump-sum allocation has only partially been used. This is in contrast with most economic literature, including the current paper, which provides a variety of arguments against free allocation. Nevertheless, more research on the effects of different allocation mechanisms is needed, both as a guide to designing appropriate trading schemes and to help understand the market for emissions allowances.