本文選題：碳排放效率 + SBM-Super模型和視窗分析技術　； 參考：《安徽財經(jīng)大學》2016年碩士論文

【摘要】：隨著經(jīng)濟和社會的不斷發(fā)展,伴隨著經(jīng)濟增長和物質水平提高的同時,能源過度消耗和環(huán)境污染等問題隨之出現(xiàn)。尤其是二氧化碳的過量排放所引起的溫室氣體效應和氣候變暖等問題,給人們的生活與生產(chǎn)帶來負面影響。在我國大力倡導節(jié)能減排、低碳發(fā)展的背景下,相關研究成為熱點,有關碳排放效率及其影響的研究尚未形成統(tǒng)一的結論。本文基于前人的研究,對我國區(qū)域碳排放效率進行評價并對碳排放效率影響因素進行空間計量分析,主要內(nèi)容如下:首先是碳排放效率評價部分。選擇2005-2013年我國省際樣本數(shù)據(jù),運用IPCC清單法測算我國各省碳排放量,運用處理非期望產(chǎn)出的DEA模型,包括SBM-Super模型、視窗分析技術和Malmquist指數(shù)分解模型來測算和評價區(qū)域碳排放效率。結果表明:處于碳排放效率前沿面的省份占比全國23.3%,南部沿海經(jīng)濟綜合區(qū)效率均值最高,西南經(jīng)濟綜合區(qū)均值最低;部分年份中,黃河中游、南部沿海、長江中游這三個地區(qū)的碳排放效率差異呈現(xiàn)s收斂性;Malmquist指數(shù)分解結果表明技術進步是提高我國碳排放效率的主要動力。其次是碳排放效率影響因素的空間計量分析部分。根據(jù)現(xiàn)有文獻,先對碳排放效率影響因素進行理論上的分析,然后運用空間計量方法和模型進行實證分析。我國碳排放效率呈現(xiàn)出顯著的正向空間自相關性,即我國省際碳排放效率在空間的分布不是隨機的,而是碳排放效率水平相近的省份呈現(xiàn)出相互依賴和“優(yōu)勢”集聚;我國局部High-High和Low-Low集聚的省份超過了60%,碳排放效率具有空間局域的依賴性,同時也存在一定的差異性。常參數(shù)空間計量模型結果顯示,空間杜賓模型為擬合結果較優(yōu)模型;影響因素的區(qū)域內(nèi)溢出(直接效應)結果:人口結構、科技進步對于碳排放效率的直接效應顯著為正,即這些變量值的增加會促進區(qū)域內(nèi)碳排放效率的提高,消費水平、產(chǎn)業(yè)結構外貿(mào)依存度的直接效應為負,即區(qū)域內(nèi)溢出為負;影響因素的區(qū)域間溢出(間接效應)結果:人口結構的間接效應顯著為負,外貿(mào)依存度則顯著為正,說明人口結構指標變量的增加、外貿(mào)依存度指標變量的減少對其他區(qū)域的碳排放效率產(chǎn)生抑制作用�？臻g變參數(shù)計量模型結果顯示,指數(shù)距離權重的地理加權回歸模型為擬合最優(yōu)模型,在不同地位置上的省份,碳排放效率影響因素的影響力度和影響方向存在一定的差異性,其中外貿(mào)依存度對于碳排放效率影響程度在全國各省份中具有很大的差異性,除了中西部等地區(qū)外,外貿(mào)依存度對于其他各省碳排放效率的影響系數(shù)均為正。其次是人口結構、消費水平和產(chǎn)業(yè)結構。人口結構對各省碳排放效率的影響系數(shù)基本均為正,且對部分沿海經(jīng)濟發(fā)達地區(qū)的影響力度較大;消費水平和產(chǎn)業(yè)結構對各省碳排放效率的影響系數(shù)有正有負,波動變化;技術進步對碳排放效率的影響程度在全國各省份相近。最后,根據(jù)本文在實證過程中得到的結論,分別從合理規(guī)劃城市規(guī)模;理性消費,低碳消費;加快轉變經(jīng)濟發(fā)展方式,打造升級版產(chǎn)業(yè)結構;科學地引進外資,實現(xiàn)技術有效溢出;提高自主創(chuàng)新能力,加強產(chǎn)學研相結合這五個方面給出如何提高我國碳排放效率的相關政策建議。
[Abstract]:With the continuous development of economy and society, along with the economic growth and the improvement of the material level, the problems of excessive energy consumption and environmental pollution, especially the greenhouse gas effect and climate warming caused by excessive carbon dioxide emissions, have brought negative effects on people's life and production. In the background of energy saving and emission reduction and low carbon development, related research has become a hot spot. The research on carbon emission efficiency and its impact has not yet formed a unified conclusion. Based on previous studies, this paper evaluates the efficiency of China's regional carbon emission and carries out spatial econometric analysis on the influencing factors of carbon emission efficiency. The main contents are as follows: the first is the carbon emission. In the evaluation part of efficiency, we choose the interprovincial sample data in China for 2005-2013 years, calculate the carbon emissions of China's provinces by IPCC list method, use the DEA model to deal with undesired output, including the SBM-Super model, the window analysis technology and the Malmquist index decomposition model to estimate and evaluate the efficiency of the regional carbon emission. The frontier provinces accounted for 23.3% of the whole country, the average efficiency of the southern coastal economic zone was the highest and the southwest economic zone was the lowest. In some years, the carbon emission efficiency of the three regions in the middle reaches of the Yellow River, the southern coast and the middle reaches of the Yangtze River showed s convergence, and the Malmquist index decomposition results showed that technological progress was the improvement of carbon emissions in China. The second is the spatial econometric analysis of the factors affecting the efficiency of carbon emissions. Based on the existing literature, the theoretical analysis of the factors affecting the efficiency of carbon emissions is first analyzed, and then the spatial measurement method and model are used to carry out an empirical analysis. The distribution of carbon emission efficiency in space is not random, but the provinces with similar carbon emission efficiency have interdependence and "advantage" agglomeration. The local High-High and Low-Low provinces in our country have more than 60%, the carbon emission efficiency has spatial local dependence, and there are some differences. The results show that the spatial doberen model is a better model for the fitting results, and the result of the regional spillover (direct effect) of the influencing factors: the direct effect of the population structure and the progress of science and technology on the carbon emission efficiency is positive, that is, the increase of these variables will promote the increase of carbon emission efficiency in the region, the consumption level and the dependence on the foreign trade structure of the industrial structure. The direct effect is negative, that is, the intra regional spillover is negative, and the result of the interregional spillover (indirect effect) of the influencing factors: the indirect effect of the population structure is significantly negative, the dependence of foreign trade is significantly positive, the increase of the index variable of the population structure and the reduction of the index variable of the degree of dependence on the foreign trade dependence on the carbon emission efficiency of other regions. The result of the spatial variable parameter measurement model shows that the geo weighted regression model of the index distance weight is the optimal model. There is a certain difference between the influence force and the influence direction of the influence factors of the carbon emission efficiency in the provinces with different locations. The influence degree of the dependence on the carbon emission efficiency is in the provinces of the country. There are great differences. In addition to the central and western regions, the influence coefficient of the degree of dependence on the carbon emission efficiency of other provinces is positive. Secondly, the population structure, consumption level and industrial structure. The influence coefficient of population structure on the carbon emission efficiency of the provinces is basically positive, and the impact on some coastal economic developed areas is greater. The influence coefficient of consumption level and industrial structure on the carbon emission efficiency of all provinces is positive and fluctuant; the impact of technological progress on carbon emission efficiency is similar in all provinces in China. Finally, according to the conclusions obtained in the empirical process, the rational consumption and low carbon consumption are planned, and the economic development is accelerated. Ways to build up the industrial structure of the upgraded version; introduce foreign investment scientifically, realize the effective spillover of technology, improve the ability of independent innovation, and strengthen the combination of production, school and research in the five aspects to give relevant policy suggestions on how to improve China's carbon emission efficiency.
【學位授予單位】：安徽財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：X321

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