基于SBM-GML模型的中国电力行业全要素生产率研究

发布时间：2018-10-18 12:46

【摘要】：随着改革开放后一系列改革措施的实施,我国电力行业多年来保持了高速发展势头,为国民经济持续快速增长做出了重要贡献,不过在电价制定、节能降耗、电网配置及市场化改革方面仍然存在一定的问题。本文拟从全要素生产率的角度评价我国电力行业的发展质量,并通过影响因素分析方法论证上述问题的存在性与严重性,基于实证研究结论提出提高我国电力行业全要素生产率的有效对策,这对于提高电力行业改革的质量和效率,建立持续、稳定、健康发展的电力产业体系至关重要。本文做了以下具体工作:1、介绍了电力行业全要素生产率的研究背景和意义,系统论述了国内外相关文献的研究成果,对本文的内容安排与研究方法进行了介绍;最后指出了文章的创新点。2、概述了与本文研究主题相关的理论和技术方法,具体介绍了全要素生产率和绿色全要素生产率理论,数据包络分析法和Malquist指数分析法。3、以中国30个省市为研究样本,利用基于SBM模型的GML指数,测算了2007-2013年中国电力行业环境约束下的全要素生产率指数及其分解指数,并从全国层面和区域角度做了结果分析。4、以第三部分测算的GML指数及其分解指数为被解释变量,并选取了合理的解释变量,建立了面板数据回归模型,对影响电力行业全要素生产率的影响因素进行了实证分析。5、基于实证研究结果,提出了提升我国电力行业全要素生产率的政策建议。
[Abstract]:With the implementation of a series of reform measures after the reform and opening up, the electric power industry of our country has maintained the high speed development momentum for many years, has made the important contribution to the national economy sustained fast growth, but in the electricity price formulation, the energy conservation reduces the consumption, There are still some problems in power grid allocation and market-oriented reform. This paper intends to evaluate the development quality of China's electric power industry from the perspective of total factor productivity, and prove the existence and seriousness of the above problems by means of factor analysis. Based on the conclusion of empirical research, the effective countermeasures to improve the total factor productivity of electric power industry in China are put forward, which is very important for improving the quality and efficiency of the reform of the electric power industry and establishing a sustainable, stable and healthy electric power industry system. This article has done the following concrete work: 1, introduced the electric power industry total factor productivity research background and the significance, systematically discussed the domestic and foreign related literature research results, has carried on the introduction to the content arrangement and the research method; Finally, it points out the innovation points of the article. 2, summarizes the theory and technical methods related to the subject of this paper, and introduces the theory of total factor productivity (TFP) and green total factor productivity (TFP) in detail. Data Envelopment Analysis and Malquist Index Analysis. 3. Taking 30 provinces and cities in China as the research sample, using GML index based on SBM model, the total factor productivity index (TFP) and its decomposition index under environmental constraints of China's electric power industry from 2007 to 2013 are calculated. The results are analyzed from the national and regional perspectives. 4. Taking the GML index and its decomposition index measured in the third part as explained variables, and selecting reasonable explanatory variables, a panel data regression model is established. This paper makes an empirical analysis of the factors affecting the total factor productivity of the power industry. 5. Based on the results of the empirical research, the paper puts forward some policy suggestions for improving the total factor productivity of the power industry in China.
【学位授予单位】：江苏科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F224;F426.61

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