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能源节约型技术进步对能源消费、环境污染动态影响的实证分析 被引量:3

Empirical analysis on dynamic effect of energy-saving technology improvement to energy consumption and environmental pollution
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摘要 基于中国30个省份2005—2014年面板数据,采用面板VAR模型对能源节约型技术和能源消费、环境污染之间的动态关系进行建模,研究了能源节约型技术进步如何影响能源消费和环境污染。研究表明:中部地区能源节约型技术进步对提高能源利用效率、减少能源消费和环境污染效果显著,并存在长期的协整关系;东部地区能源节约型技术进步在前期能达到节能减排的作用,随后趋于稳定;西部地区能源节约型技术进步只在初期产生节能减排的作用。东西部能源消费对环境污染的贡献比例大于中部地区,东西部地区环境污染不仅来源于生产性能源消费,还来自其他方面。因此,根据东中西部地区不同的情况,因地制宜采取相应的措施和政策,达到节能减排的效果。 Based on the panel data of 30 provinces of China from 2005 to 2014,this paper used the panel vector autoregression model to model the dynamic relationship between energy-saving technology improvement,energy consumption and environmental pollution.The paper studied how does energy saving technology influence energy consumption and environmental pollution.The conclusion can be listed as follows:energy-saving technology improvement of middle area can engender remarkable effect to improve the efficiency of energy utilization and reduce energy consumption and environmental pollution,and there is long-term co-integration relationship;energy-saving technical improvement in eastern regions can achieve the effect of energy conservation and emissions reduction in prophase,then this effect leveled off;in the western regions,energy saving technology progress only in the early produce the effect of energy conservation and emissions reduction.The contributions of energy consumption to the environmental pollution in the eastern and western regions is greater than that in middle regions.Environment pollution in the eastern and western regions not only comes from energy consumption,but also from other aspects.Therefore,according to the different situation of eastern,middle and western regions,China should adopt corresponding measures and policies to achieve the effect of energy conservation and emissions reduction.
出处 《能源与环保》 2017年第8期24-31,共8页 CHINA ENERGY AND ENVIRONMENTAL PROTECTION
基金 高等院校研究生科研创新项目(2016XCX32)
关键词 能源节约型技术进步 能源消费 环境污染 面板VAR 面板VAR energy-saving technology improvement energy consumption environmental pollution panel VAR
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