Price Containment in Emissions Permit Market: Balancing Market Risk and Environmental Outcomes
Price Containment in Emissions Permit Market: Balancing Market Risk and Environmental Outcomes
复制标题
排放许可证市场的价格控制：平衡市场风险和环境成果
DOI：
10.2139/ssrn.2560980
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Yihsu Chen
中科院分区：
文献类型：
--
作者：
Andrew L. Liu;Yihsu Chen
尽管“总量管制与交易”政策一直被认为是一种有效的、基于市场的方法来调节电力行业的温室气体排放，但一个主要的批评是，由此产生的排放许可价格可能会波动，给市场参与者增加更多的不确定性，从而阻碍他们参与电力市场的兴趣。为了缓解这种担忧，已经提出了各种限制许可证价格的手段，如价格上限、最低限价或限价。虽然这些工具可能会防止许可价格变得极端，但它们可能会导致无意的结果，例如对低排放技术的投资不足或对全系统温室气体排放的减少很少，从而在一开始就违背了建立限额与交易政策的目的。为了解决这些问题，本文考察了在电力市场中实施各种价格遏制政策对投资决策和现货市场均衡的影响。我们的主要贡献在于，与该领域的其他工作不同，价格控制计划对其市场模型是外生的，我们在模型中内生地纳入了价格上限/下限，因此可以分析政策与其相应的市场结果之间的相互作用。我们进一步在我们的市场模型中引入不确定性，并使用加州的数据作为案例研究。
While cap-and-trade policies have been advocated as an efficient market-based approach in regulating greenhouse gas (GHG) emissions from the power sector, a major criticism is that the resulting prices of emissions permit may be volatile, adding more uncertainty to market participants, and hence deter their interests in participating the electricity market. To ease such a concern, various permit price-containment instruments, such as a price ceiling, floor, or collar, have been proposed. Though such instruments may prevent permit prices from being extreme, they may incur inadvertent results such as underinvestment in low-emission technologies or little reduction of system-wide GHG emissions, hence defeating the purpose of establishing a cap-and-trade policy in the first place. To address such issues, this article examines the effect of imposing various price-containment policies on investment decisions and spot market equilibria in an electricity market. Our major contribution is that, unlike other work in this area in which the price-containment schemes are exogenous to their market models we endogenously incorporate a price ceiling/floor in our models and hence can analyze the interactions between the policies and their corresponding market outcomes. We further introduce uncertainties in our market models and use California's data as a case study.
影响因子：
1.1
作者：
A. Maeda
通讯作者：
A. Maeda