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作 者:邹绍辉[1,2] 张甜 闫晓霞[1,2] ZOU Shao-hui;ZHANG Tian;YAN Xiao-xia(School of Management,Xi'an University of Science and Technology,Xi'an 710054,Shaanxi,China;Energy Economy and Management Research Center,Xi'an University of Science and Technology,Xi'an 710054,Shaanxi,China;University of International Business and Economics,Beijing 100029,China)
机构地区:[1]西安科技大学管理学院,陕西西安710054 [2]西安科技大学能源经济与管理研究中心,陕西西安710054 [3]对外经济贸易大学金融学院,北京100029
出 处:《山东大学学报(理学版)》2019年第5期77-87,共11页Journal of Shandong University(Natural Science)
基 金:国家自然科学基金资助项目(71273207,71704140);陕西省科学技术研究发展计划项目(2011kjxx54);陕西省留学人员科技活动择优项目
摘 要:我国碳排放权交易价格具有明显的波动性和地区差异性,科学刻画碳排放权交易价格的波动性和解析不同地区的差异性有利于规避投资风险、平稳发展碳市场和提高国内碳市场在国际市场的定价能力,对加快建立全国统一碳市场也尤为重要。H-P滤波法是经常使用的经济变量趋势分解方法,可有效地解析时间序列数据中的季节变动规律。选取2013年12月至2018年6月之间国内7大区碳市场域碳排放权交易价格月度数据,采用H-P滤波法实证研究了国内碳价波动规律和区域特征。研究结果表明,国内碳价具备“波动中下降”的显著特征,呈现3个完整周期,每个周期时间范围在10~22个月之间,峰值与谷值都呈现不同程度的下降趋势且均由正变负,周期类型都表现出陡降趋势;从区域影响看,天津和北京的碳排放权交易价格的波动一致特征更明显,而湖北和重庆的碳排放权交易价格波动对天津的影响程度较小。The price of carbon emission trading in China has obvious volatility and regional differences. Scientifically describing the volatility of carbon emission trading price and analyzing the differences of different regions are conducive to avoiding investment risks, developing carbon market smoothly and improving the pricing ability of domestic carbon market in the international market. It is also particularly important to speed up the establishment of a unified national carbon market. H-P filtering is a commonly used trend decomposition method for economic variables, which can effectively analyze the seasonal variation law in time series data. Based on monthly data of carbon emission trading prices in seven major regions of China from December 2013 to June 2018, H-P filtering method is used to empirically study the fluctuation law and regional characteristics of domestic carbon prices. The results show that the domestic carbon price has a significant characteristic of "falling in fluctuation", showing 3 complete cycles, the time range of each cycle is 10~22 months. Peak and valley values show a downward trend in varying degrees, and all of them change from positive to negative, the cycle types show a steep downward trend. From the regional perspective, the volatility of carbon emission trading price in Tianjin and Beijing is more obvious, while the fluctuation of carbon emission trading price in Hubei and Chongqing has less impact on Tianjin.
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