摘要
研究碳市场与电力市场间的风险溢出效应,对于有效防范碳金融风险以及国家节能减排战略的稳步推进具有重要意义。本文基于广义方差分解谱构建溢出指数,从频域视角考察中国碳市场与电力市场在短、中、长期的静态溢出和时变溢出,并根据溢出指数构建溢出网络,探究风险的中心与演化。结果表明:中国碳市场与电力市场之间的风险溢出短期>中期>长期,且存在一定的波动性和不确定性,受宏观经济状况影响较大。发电企业接收到的风险量与火电装机比例有关,发电企业输出风险的能力与发电量有关。在短期,碳市场属于风险净接收方,而在中长期,碳市场属于风险净溢出方。基于上述结论提出了相关政策建议。
This paper has investigated the volatility spillover and connectedness between the carbon market and power market in China by using spectral representation of generalized forecast error variance decomposition and network diagram. From a frequency domain perspective,this paper systematically investigates the spillover effect between China.s carbon market and power market in the short,medium and long-term from the two dimensions of direction and level,and then uses complex network method to discuss the spillover center and evolution. We have obtained interesting and convincing empirical results that show the spillover effects of risks mainly occurs in the short term(within 15 days). More importantly,in the“carbon-power”system,the amount of risk received by power generation enterprises is related to the proportion of thermal power installed,and the capacity of power generation enterprises to export risks is related to the power generation. Meanwhile,in the short-term,the carbon market is a net risk receiver,while in the medium and long-term,the carbon market is a net risk transmitter. Our study can help investors and managers of carbon market and power market to have more comprehensive understanding of the information and volatility transmission mechanism between carbon market and power market,thus,providing them with a basis to make investment decisions and formulate policies.
作者
王喜平
王婉晨
Wang Xiping;Wang Wanchen(Department of Economics and Management,North China Electric Power University,Baoding 071000,China)
出处
《工业技术经济》
北大核心
2022年第5期53-62,共10页
Journal of Industrial Technological Economics
基金
河北省社会科学基金项目“基于共享经济模式的雄安新区综合能源利用体系研究”(项目编号:HB19YJ011)。
关键词
碳市场
电力市场
BK溢出指数
频域
溢出网络
广义方差分解
carbon market
power market
BK spillover index
frequency domain
connectedness
generalized variance decomposition
