| At the Copenhagen Climate Summit in 2009,the Chinese government made a promise that“in 2020,my country's unit GDP2 emissions will be reduced by40%-45%compared to 2005”;at the Paris Climate Summit in 2015,Commit to achieving peak emissions by 2030.However,it is not easy to fulfill this commitment.The pressure on my country to reduce carbon emissions,energy conservation and emissions reduction is increasing.The government has also gradually increased its emphasis on environmental issues.my country's energy policy has gradually shifted from ensuring energy supply to energy conservation,reducing unit energy consumption,and so on,taking into account economic and environmental benefits.Due to the differences and imbalances in regional economic development and resource endowments,there are significant differences in regional energy efficiency in my country.In order to improve energy efficiency and achieve emission reduction targets,China must fully consider the spatial distribution characteristics of energy efficiency,and combine regional development strategies to introduce corresponding industrial and energy policies to provide reference and reference for the formulation and implementation of regional carbon emission reduction policies.In order to effectively achieve the emission reduction target at a lower economic cost.In the aforementioned context,this article measures China's regional energy efficiency and analyzes the factors affecting energy efficiency,with a view to providing theoretical support and policy recommendations for the government to formulate and implement reasonable energy-saving and emission-reduction policies.The main contents of this paper are as follows:Measured regional energy efficiency from the single-factor and full-factor perspectives,revealing the changing laws of regional energy efficiency;tested the spatial correlation of regional energy efficiency,explored the evolution path of regional energy efficiency;established a spatial measurement model,from the perspective of industrial structure,technological progress,energy consumption structure,foreign direct investment and the level of opening up to the outside world expounds its impact on regional energy efficiency,clarifies the mechanism and path of technological progress,industrial structure and other factors on regional energy efficiency,and proposes promotion Effective strategies for improving regional energy efficiency;a variable weight combined forecasting model(VWCFM)based on gray forecasting method and exponential smoothing method is constructed,which predicts total energy consumption and energy efficiency,and provides services for optimizing energy structure,saving energy,and improving energy efficiency.Basis for decision-making.The research theme of this article is conducive to achieving the goal of coordinated development of economy and environment.It is necessary to deeply analyze the spatial difference of regional energy efficiency and the change trend of the difference,and it is very necessary to seek regional energy efficiency improvement strategies.The contents and conclusions of the study are as follows:(1)Explains the research background of the thesis,analyzes the research significance of the thesis,summarizes and sorts out the research status and literature review on related issues such as regional energy efficiency influencing factors at home and abroad,and clarifies the research content of the thesis on this basis.Research methods and technical routes;introduced the relevant theories used in this article,including environmental technology theory,sustainable development theory,low-carbon economic theory,environmental economics theory and spatial econometrics theory.Under the guidance of these five theories,gradually Started research.(2)Analysis of the status quo of China's energy consumption and energy efficiency.The status quo of energy consumption,energy efficiency and regional energy efficiency in China is summarized,the evolution trend is analyzed,and the differences between regions and the causes are analyzed.(3)Measurement and evaluation of regional energy efficiency.On the basis of estimating the absolute amount of regional carbon emissions,based on the single-factor perspective and the full-factor perspective,different methods are used to measure regional energy efficiency,and comparative analysis is performed to screen out the optimal energy efficiency required by this article.First,the measurement results of single-element energy efficiency characterized by unit energy consumption output value show that there are significant differences in regional energy efficiency.Beijing,Guangdong,Zhejiang,Jiangsu and Fujian are the five provinces and cities with the highest energy consumption per unit output value in my country,while Xinjiang,The five provinces of Guizhou,Shanxi,Qinghai and Ningxia are the five provinces and cities with the lowest output value per unit of energy consumption.In addition,from the perspective of energy efficiency in various regions,the energy efficiency of most provinces is showing an increasing trend,while the trend of changes in a small number of provinces is not obvious,and the overall fluctuation is stable.Secondly,the total factor results calculated by the non-parametric DEA-SBM model show that the provincial differences are also significant.Beijing and Guangdong have the highest relative total factor energy utilization efficiency,with an annual efficiency value of 1,indicating that even if carbon dioxide emissions pollution is considered,They are still at the forefront of production,showing that their all-factor energy efficiency is effective.The average efficiencies of Tianjin and Shanghai are 0.920 and 0.906,indicating that they have energy-saving potentials of8.00%and 9.44%,respectively;the averages of provinces such as Gansu,Guizhou,and Qinghai are all lower than 0.40,indicating that these provinces and cities have improved input and output.Space gradually withdraws from the frontier.Based on the perspectives of the three major regions,single-factor energy efficiency has shown a steady increase over time,while the dynamic evolution trajectory of total-factor energy efficiency has not changed much.The results of the DEA window analysis show that Beijing's energy efficiency is increasing year by year,and its energy efficiency presents the characteristics of phased changes.From 2006 to 2009,energy efficiency showed a trend of first increasing and then decreasing.From 2010 to 2011,energy efficiency showed first increase.After a downward trend,after a brief decline in 2012,it rose again after 2013.In a word,the energy efficiency of the whole country and each region shows the characteristics of stage changes and the fluctuation range is not large.Among them,some eastern provinces such as Beijing show an overall upward trend,and the three northeast provinces of Heilongjiang and western Qinghai show a trend of first increasing and then decreasing.(4)Analysis of the spatial distribution characteristics of regional energy efficiency.On the basis of determining the optimal regional energy efficiency,using global spatial autocorrelation Moran's I,local spatial autocorrelation Moran's I and Moran scatter plots and other indicators to analyze the spatial correlation or heterogeneity of regional energy efficiency,for the following energy The use of spatial measurement methods for efficiency influencing factors provides a corresponding basis.Based on the global and local spatial autocorrelation Moran's I test of regional energy efficiency,it is found that over time,the phenomenon of spatial agglomeration and distribution becomes more and more obvious.Provinces with lower energy efficiency tend to be similar to those with lower energy efficiency.Adjacent,and provinces with higher energy efficiency tend to be adjacent to the same higher energy efficiency,forming a hierarchical spatial structure pattern.Based on the Moran scatter diagram,the regional energy efficiency is tested,and it is obtained that my country's regional energy efficiency is spatially dependent and spatially heterogeneous.(5)Research on influencing factors of regional energy efficiency based on spatial measurement model.Based on the spatial measurement model,based on a comprehensive analysis of my country's regional energy efficiency related factors,the Spatial Dubin Model(SDM)was established to investigate the underlying causes of regional energy efficiency differences,and to decompose the spatial effects of each factor.Further study the influence and impact of different variables on energy efficiency from the direct effects,indirect effects and overall effects to test whether different variables have significant spatial spillovers in the spatial interaction process of energy efficiency.In order to further analyze the influencing factors and spatial interaction effects of China's regional energy efficiency in different periods,the influence effects of each influencing factor are further divided into different time periods for empirical analysis.Based on this,this paper takes 2010 as the node and divides it into two time intervals,2006-2010 and 2011-2015,to examine the spatial evolution trends of China's regional energy efficiency influencing factors in different periods.The research results show that the increase in foreign direct investment,the level of opening to the outside world and the improvement of technological progress can improve regional energy efficiency;the improvement of industrial structure and energy consumption structure will reduce regional energy efficiency,and the industrial structure,technological progress,energy consumption structure,foreign direct investment and The level of opening to the outside world has a significant spatial spillover effect.(6)Research on energy consumption and energy efficiency forecasting.Based on the GM(1,1)model,the exponential smoothing model,and the variable-weight combination forecasting model that combines the two,long-term forecasts are made on the total energy consumption,energy consumption by variety,and energy efficiency.Obtained the variable weight combination forecasting model,which can achieve the total energy consumption of 4.907 billion tons in 2020,exceeding the binding requirement of"controlling the total energy consumption to 5 billion tons in2020"in the"Thirteenth Five-Year Plan".A systematic and comprehensive scientific forecast of China's energy consumption and energy efficiency not only provides a reasonable basis and decision-making reference for the optimization of energy consumption structure and improvement of energy efficiency,but also provides a substantial basis for formulating energy development plans and policies.(7)Conclusions and prospects.Summarizes the main research conclusions of this article,summarizes the innovation points,and proposes future work prospects.The main innovations of this paper are:(1)Analyze and test the global and local spatial correlation of regional energy efficiency.First,through exploratory spatial data analysis,a spatial connection matrix is established,and the global Moran index is used to test the spatial correlation of regional energy efficiency;second,the local spatial autocorrelation test is combined to further analyze the atypical characteristics of local regions and explore regional energy efficiency The evolution path of China's regional energy efficiency has been found to have agglomeration and radiation effects in the spatial distribution of regional energy efficiency,which provides a basis for the application of spatial econometric models.(2)Constructed a spatial measurement model of influencing factors of regional energy efficiency.First,a spatial measurement model was established,which measured the direct,indirect,and total effects of regional energy efficiency influencing factors in China,and clarified technological progress,industrial structure,energy consumption structure,foreign direct investment,and the level of opening to the outside world.The impact mechanism and path of regional energy efficiency reveals the spatial path law of regional energy efficiency influencing factors,further expands the research ideas of regional energy efficiency,and proposes policy recommendations to promote regional energy efficiency,which makes up for previous related research influencing factors discuss the current situation that is not systematic and comprehensive,and provide theoretical and empirical evidence for improving China's regional energy efficiency,formulating industrial policies,and improving regional environmental conditions.(3)Constructed a variable weight combined forecasting model(VWCFM)based on grey forecasting model and exponential smoothing model.First,the gray forecast model and exponential smoothing model are used to predict the total energy consumption,energy consumption by variety,and energy efficiency.Secondly,based on the variable-weight combined forecasting model(VWCFM)that has been built,the weight coefficients of the gray forecasting model and exponential smoothing model at different times are predicted,and on this basis,the total energy consumption and the energy consumption of different categories are calculated according to the weighting coefficients,and energy efficiency variable-weight combination model prediction value,solved the problem of low prediction accuracy and poor stability of gray theory and exponential smoothing method,systematically and comprehensively predict energy consumption and energy efficiency scientifically,in order to optimize energy Structure,energy saving,and improvement of energy efficiency provide decision-making reference. |
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