欧盟碳价影响因素研究及其对中国的启示

作为一项市场创新和政策创新,即将启动的中国全国性碳市场备受国内外关注。为保证其成功建立与平稳发展,相关经验借鉴已刻不容缓,但作为投石问路的7大试点碳市场发展层次不齐,可供参考的模式有限,因此研究全球第一大碳市场——欧盟碳排放交易体系(EU ETS)及其对中国的可参照性尤为迫切;而作为市场是否成熟的风向标,碳价规律性特征的挖掘尤为重要。前期国内外学者分别发现CER价格、原油价格、煤炭价格、天然气价格、欧洲工业指数、联合国气候变化大会、政府政策、极寒天气、暖冬天气、自然灾害、重大事件等多种因素都有可能引起EUA期货价格波动。本研究通过引入MIV-BP神经网络模型,对EU ETS二期和三期的EUA期货价格进行训练和测试,模拟了上述11个因素对EUA价格的影响,弥补了传统计量模型难以同时处理较多变量及不能整合定性与定量变量等缺点。通过对EU ETS二期1 149组和三期775组数据的挖掘,得出了各变量对EUA期货价格的影响程度。其中,二期运行阶段各变量影响程度从大到小排序为:自然灾害COPCER极寒天气Coal重大事件Brent政府政策Stock600Gas暖冬天气;三期运行阶段各变量影响程度从大到小排序为:COPStock600Coal自然灾害极寒天气重大事件政府政策BrentGasCER暖冬天气。最后,本研究对二、三期各变量对碳价影响程度的变化进行了解释,并对中国未来建立全国性碳市场提出了以下四点建议:(1)稳定碳市场参与主体预期;(2)完善核证减排抵消机制,保持政策稳定;(3)配额分配考虑区域差异;(4)建立配额应急机制。

Impacts of multiple factors on EU carbon price and implications to China

As a market and policy innovation,China's national carbon market attracts great attention at home and abroad.In order to ensure its smooth establishment and sustainable development,it is rather urgent to learn from relevant best practices.However,as the only references in China,the 7 pilot carbon trading schemes could only provide very limited experiences.Therefore,studying and learning from EU-ETS-the largest carbon market in the world has become very important.As a significant indicator of whether a market matures or not,carbon price is able to present considerable signal.Various scholars have found respectively that prices of CER carbon,crude oil,coal and natural gas,along with Euro Stoxx index,UN climate change conferences,government policies,extreme weathers,warm winters,natural disasters and important events can all trigger EUA carbon prices fluctuating.This study therefore tries to introduce a MIV-BP model to train and test EUA prices during second and third phases and simulate how the above 11 factors influenced EUA prices.The model can well compensate the shortcomings of traditional models which are not able to handle multivariate or integrate quantitative and qualitative variables.Through data mining of 1 149 groups of phase 2 data and 775 groups of phase 3 data,the study finds out the degrees of how different variables can influence EUA prices,which the descending order in phase 2 is:natural disaster ＞ UN conferences ＞ CER ＞ extreme weathers ＞ coal prices ＞ important events ＞ Brent oil prices ＞ government policies ＞ Stock600 index ＞ natural gas prices ＞ warm winters;the order in phase 3 changes to:UN conferences ＞ Stock600 index ＞ coal prices ＞ natural disasters ＞ extreme weathers ＞ important events ＞ government policies ＞ Brent oil prices ＞ natural gas prices ＞ CER ＞ warm winters.Based on further analysis,the study presents explanation of why this change happened and gives suggestions to China's future national carbon market:①stabilize the expectation of market participants;②improve permits offset mechanism and maintain policy consistency;③take regional differences into account when allocate permits;④establish emergency response mechanism of carbon rights allocation.