综合性能源价格指数对中国省域碳强度的调节作用及其比较——来自30个省份面板数据的实证分析
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摘要
在构建综合性能源价格指数的基础上,基于1995~2012年我国30个省份相关历史数据,通过面板数据模型和层次聚类法分析了省域能源价格对碳强度的静态和动态调节作用。结果表明:能源价格通过影响产业结构、技术水平、能源强度对碳强度分别产生了0.576%、0.048%和0.787%的作用,但经由前两个路径产生的作用大于路径变量本身的直接影响,其中结构路径的作用提高了44.4%,技术路径变动不大,而经由能源强度对碳强度产生的影响较其本身降低了7.91%。总体来看,能源价格的合理上升有利于节能减排,但价格对碳强度的杠杆作用表现出明显的区域差异性。此外,煤炭资源税的征收对降低碳强度也有明显的效果,且具有较大增长空间。按照价格杠杆作用的差异,相关省份可以被划分为调节作用弱、较弱、中、较强、强五类。东部和中东部省份能源价格变动的碳抑制作用明显高于西部和中西部省份。
Since there is no united energy price index in China, this paper constructs a comprehensive energy price index that combines industrial and nonindustrial price indices and can reflect the regional difference. Based on this, with the methods of Panel Date Model and Hierarchical Cluster analysis, this paper constructs the direct, regulatory and dynamic models respectively to test the effect of energy price lever on carbon intensity using 30 provinces' related historical data during 1995-2012 in China. The result shows that: firstly, energy price can impact on carbon intensity through industrial structure, technical level and energy intensity, the depressing effect is 0.576% 0.048%, and 0.787% respectively. Secondly,compare with the direct effect, carbon depressing effects of the former two paths are improved when considering regulatory effect of price lever, in which effect of structure path improved by 44.4%. And there are few changes of technology path.However, the depressing effect of reducing energy intensity decreases by 7.91%. Thirdly, carbon intensity has certain inertia, provincial carbon intensity of last year has a certain influence of it in current year, and the effect is about 70%.Under this condition, when regulatory effect of price lever is considered, carbon depressing effect of industrial structure optimization and energy intensity reduction is far more significant than technology improvement. It indicates that the reductions of carbon emission mainly relay on structure path in short term, but technology improvement is the key in the long run. In general, a reasonable rising energy price benefits energy saving and emission reduction, but the price leverage effect on carbon intensity shows obvious regional difference. Besides, resource tax also has significant effect on carbon intensity decreasing. According to the difference of price leverage, considering the effect of coal tax policy, provinces in China can be divided into five categories: weak, relatively weak, medium, relatively strong, and strong regulatory effect. In the sample period, depressing effect of energy price on carbon emission energy price in eastern and mid-eastern provinces is greater than that in western and mid-western provinces. Generally speaking, there is no direct relationship between the effect of price lever on carbon intensity and regional economic development, but it is influenced by economic development speed, provincial carbon intensity, technical conversion efficiency, characteristics of energy production and consumption and etc.. Besides, in the region with high market level, regulatory effect of price lever on carbon intensity is relatively high,while effect of tax policy is limited; conversely, in the region with low market level, depressing effect of tax policy on carbon intensity if significant, and regulating effect of price lever has not brought into full play.
Since there is no united energy price index in China, this paper constructs a comprehensive energy price index that combines industrial and nonindustrial price indices and can reflect the regional difference. Based on this, with the methods of Panel Date Model and Hierarchical Cluster analysis, this paper constructs the direct, regulatory and dynamic models respectively to test the effect of energy price lever on carbon intensity using 30 provinces' related historical data during 1995-2012 in China. The result shows that: firstly, energy price can impact on carbon intensity through industrial structure, technical level and energy intensity, the depressing effect is 0.576% 0.048%, and 0.787% respectively. Secondly,compare with the direct effect, carbon depressing effects of the former two paths are improved when considering regulatory effect of price lever, in which effect of structure path improved by 44.4%. And there are few changes of technology path.However, the depressing effect of reducing energy intensity decreases by 7.91%. Thirdly, carbon intensity has certain inertia, provincial carbon intensity of last year has a certain influence of it in current year, and the effect is about 70%.Under this condition, when regulatory effect of price lever is considered, carbon depressing effect of industrial structure optimization and energy intensity reduction is far more significant than technology improvement. It indicates that the reductions of carbon emission mainly relay on structure path in short term, but technology improvement is the key in the long run. In general, a reasonable rising energy price benefits energy saving and emission reduction, but the price leverage effect on carbon intensity shows obvious regional difference. Besides, resource tax also has significant effect on carbon intensity decreasing. According to the difference of price leverage, considering the effect of coal tax policy, provinces in China can be divided into five categories: weak, relatively weak, medium, relatively strong, and strong regulatory effect. In the sample period, depressing effect of energy price on carbon emission energy price in eastern and mid-eastern provinces is greater than that in western and mid-western provinces. Generally speaking, there is no direct relationship between the effect of price lever on carbon intensity and regional economic development, but it is influenced by economic development speed, provincial carbon intensity, technical conversion efficiency, characteristics of energy production and consumption and etc.. Besides, in the region with high market level, regulatory effect of price lever on carbon intensity is relatively high,while effect of tax policy is limited; conversely, in the region with low market level, depressing effect of tax policy on carbon intensity if significant, and regulating effect of price lever has not brought into full play.
引文
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①根据《中国统计年鉴》数据计算,2001–2013年,四类能源消耗占比分别为69.1%,19.65%,3.58%和7.66%.
②30个省份分别为北京、天津、河北、山西、内蒙、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、广东、广西、海南、重庆、四川、贵州、云南、陕西、甘肃、青海、宁夏、新疆。在本文的相关表格中分别用BJ、TJ、HB、SX、NMG、LN、JL、HLJ、SH、JS、ZJ、AH、FJ、JX、SD、HN、HBS、HNS、GD、GX、HNSS、CQ、SC、GZ、YN、SXS、GS、QH、NX、XJ表示.
①事实上,Pedroni检验和KAO检验的结果也支持了这一结论.Pedroni检验中panel ADF-Statistic、Group ADF-Statistic的t值为–9.844 155、–5.270352 .KAO检验中ADF检验t值为–2.108 912,均大于其临界值.
④7种聚类分析法分别为组间联接法、组内联接法、最近邻元素法、最远邻元素法、质心聚类法、中位数聚类法以及Ward法.
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①根据《中国统计年鉴》数据计算,2001–2013年,四类能源消耗占比分别为69.1%,19.65%,3.58%和7.66%.
②30个省份分别为北京、天津、河北、山西、内蒙、辽宁、吉林、黑龙江、上海、江苏、浙江、安徽、福建、江西、山东、河南、湖北、广东、广西、海南、重庆、四川、贵州、云南、陕西、甘肃、青海、宁夏、新疆。在本文的相关表格中分别用BJ、TJ、HB、SX、NMG、LN、JL、HLJ、SH、JS、ZJ、AH、FJ、JX、SD、HN、HBS、HNS、GD、GX、HNSS、CQ、SC、GZ、YN、SXS、GS、QH、NX、XJ表示.
①事实上,Pedroni检验和KAO检验的结果也支持了这一结论.Pedroni检验中panel ADF-Statistic、Group ADF-Statistic的t值为–9.844 155、–5.270352 .KAO检验中ADF检验t值为–2.108 912,均大于其临界值.
④7种聚类分析法分别为组间联接法、组内联接法、最近邻元素法、最远邻元素法、质心聚类法、中位数聚类法以及Ward法.