Climate change and carbon emissions are major problems which are attracting worldwide attention. China has had its pilot carbon emission trading markets in seven regions for more than 3 years. What affects carbon emis...Climate change and carbon emissions are major problems which are attracting worldwide attention. China has had its pilot carbon emission trading markets in seven regions for more than 3 years. What affects carbon emission trading market in China is a big question. More attention is paid to how China promotes the carbon emission trading schemes in the whole country. This paper addresses concerns about the functioning of carbon emission trading schemes in seven pilot regions and takes the weekly data from November 25, 2013, to March 19, 2017. We employ a vector autoregressive model to study how coal price, oil price and stock index have affected the carbon price in China. The results indicate that carbon price is mainly affected by its own historical price; coal price and stock index have negative effects on carbon price, while oil price has a negative effect on carbon price during the first 3 weeks and then has a positive effect on carbon price. More regulatory attention and economic measures are needed to improve market efficiency, and the mechanisms of carbon emission trading schemes should be improved.展开更多
The establishment of a global multi-regional carbon market is considered to be a cost effective approach to facilitate global emission abatement and has been widely concerned.The ongoing planned linkage between the Eu...The establishment of a global multi-regional carbon market is considered to be a cost effective approach to facilitate global emission abatement and has been widely concerned.The ongoing planned linkage between the European Union's carbon market and a new emission trading system in Australia in 2015 would be an important attempt to the practice of building up an international carbon market across different regions.To understand the abatement effect of such a global carbon market and to study its energy and economic impact on different market participants,this article adopts a global dynamic computable general equilibrium model with a detailed representation of the interactions between energy and economic systems.Our model includes 20 economic sectors and 19 regions,and describes in detail 17 energy technologies.Bundled with fossil fuel consumptions,the emission permits are considered to be essential inputs in each of the production and consumption activities in the economic system to simulate global carbon market policies.Carbon emission permits are endogenously set in the model,and can be traded between sectors and regions.Considering the current development of the global carbon market,this study takes 2020 as the study period.Four scenarios(reference scenario,independent carbon market scenario,Europe Union(EUh-Australia scenario,and China-EU-Australia scenario) are designed to evaluate the impact of the global carbon market involving China,the EU,and Australia.We find that the carbon price in the three countries varies a lot,from $32/tCO_2 in Australia,to $17.5/tCO_2 in the EU,and to $10/tCO_2 in China.Though the relative emission reduction(3%) in China is lower than that in the EU(9%) and Australia(18%),the absolute emission reduction in China is far greater than that in the EU and Australia.When China is included in the carbon market,which already includes the EU and Australia,the prevailing global carbon price falls from $22 per ton carbon dioxide(CO_2) to $12/tCO_2,due to the relatively lower abatement cost in China.Seventy-one percent of the EU's and eighty-one percent of Australia's domestic reduction burden would be transferred to China,increasing 0.03%of the EU's and 0.06%of Australia's welfare.The emission constraint improves the energy efficiency of China's industry sector by 1.4%,reduces coal consumption by3.3%,and increases clean energy by 3.5%.展开更多
为更好预测全国碳价走势,基于带有外生变量的自回归差分移动平均模型(autoregressive integrated moving average with exogenous variable model,ARIMAX),分履约期和非履约期使用不同的外生变量分别构建了全国碳价预测模型。首先,基于...为更好预测全国碳价走势,基于带有外生变量的自回归差分移动平均模型(autoregressive integrated moving average with exogenous variable model,ARIMAX),分履约期和非履约期使用不同的外生变量分别构建了全国碳价预测模型。首先,基于对全国碳市场制度规则研究和交易特征分析,识别出全国碳价在非履约期主要受参与者预期的影响,在履约期碳价主要受企业履约需求驱动;其次,在模型训练方面,采用一种自回归差分移动平均模型,在不同阶段引入不同的外生变量来提升碳价预测效果;最后,基于全国碳市场第一履约期真实价格数据验证结果表明,所提的全国碳价预测模型在准确性方面优于基准模型。展开更多
基金funded jointly by National Science and Technology Major Project under Grant No.2016ZX05016005-003the National Natural Science Foundation of China under Grant No.71173200the Development and Research Center of China Geological Survey under Grant No.12120114056601
文摘Climate change and carbon emissions are major problems which are attracting worldwide attention. China has had its pilot carbon emission trading markets in seven regions for more than 3 years. What affects carbon emission trading market in China is a big question. More attention is paid to how China promotes the carbon emission trading schemes in the whole country. This paper addresses concerns about the functioning of carbon emission trading schemes in seven pilot regions and takes the weekly data from November 25, 2013, to March 19, 2017. We employ a vector autoregressive model to study how coal price, oil price and stock index have affected the carbon price in China. The results indicate that carbon price is mainly affected by its own historical price; coal price and stock index have negative effects on carbon price, while oil price has a negative effect on carbon price during the first 3 weeks and then has a positive effect on carbon price. More regulatory attention and economic measures are needed to improve market efficiency, and the mechanisms of carbon emission trading schemes should be improved.
文摘The establishment of a global multi-regional carbon market is considered to be a cost effective approach to facilitate global emission abatement and has been widely concerned.The ongoing planned linkage between the European Union's carbon market and a new emission trading system in Australia in 2015 would be an important attempt to the practice of building up an international carbon market across different regions.To understand the abatement effect of such a global carbon market and to study its energy and economic impact on different market participants,this article adopts a global dynamic computable general equilibrium model with a detailed representation of the interactions between energy and economic systems.Our model includes 20 economic sectors and 19 regions,and describes in detail 17 energy technologies.Bundled with fossil fuel consumptions,the emission permits are considered to be essential inputs in each of the production and consumption activities in the economic system to simulate global carbon market policies.Carbon emission permits are endogenously set in the model,and can be traded between sectors and regions.Considering the current development of the global carbon market,this study takes 2020 as the study period.Four scenarios(reference scenario,independent carbon market scenario,Europe Union(EUh-Australia scenario,and China-EU-Australia scenario) are designed to evaluate the impact of the global carbon market involving China,the EU,and Australia.We find that the carbon price in the three countries varies a lot,from $32/tCO_2 in Australia,to $17.5/tCO_2 in the EU,and to $10/tCO_2 in China.Though the relative emission reduction(3%) in China is lower than that in the EU(9%) and Australia(18%),the absolute emission reduction in China is far greater than that in the EU and Australia.When China is included in the carbon market,which already includes the EU and Australia,the prevailing global carbon price falls from $22 per ton carbon dioxide(CO_2) to $12/tCO_2,due to the relatively lower abatement cost in China.Seventy-one percent of the EU's and eighty-one percent of Australia's domestic reduction burden would be transferred to China,increasing 0.03%of the EU's and 0.06%of Australia's welfare.The emission constraint improves the energy efficiency of China's industry sector by 1.4%,reduces coal consumption by3.3%,and increases clean energy by 3.5%.
文摘为更好预测全国碳价走势,基于带有外生变量的自回归差分移动平均模型(autoregressive integrated moving average with exogenous variable model,ARIMAX),分履约期和非履约期使用不同的外生变量分别构建了全国碳价预测模型。首先,基于对全国碳市场制度规则研究和交易特征分析,识别出全国碳价在非履约期主要受参与者预期的影响,在履约期碳价主要受企业履约需求驱动;其次,在模型训练方面,采用一种自回归差分移动平均模型,在不同阶段引入不同的外生变量来提升碳价预测效果;最后,基于全国碳市场第一履约期真实价格数据验证结果表明,所提的全国碳价预测模型在准确性方面优于基准模型。
