| Our country is in the critical period of economic transformation.With the increasing attention of people to the ecology,resources and environment,the constraint cost is becoming stronger and stronger.Therefore,under this background,the study of China's regional energy saving and environmental protection R&D investment performance of the spatial differences,and on this basis,it is of great practical significance to explore the effective mode and policy recommendations of China's energy saving and environmental protection R&D investment.Firstly,this paper discusses the present situation of energy saving and environmental protection in various regions of our country and the reasons for the differences.Then,the spatial correlation test and spatial panel model are applied to the empirical analysis.Using the annual data,the paper will select the sample interval: 2007-2015 years,samples from 30 provinces and cities in China(except Tibet);From the input and output of the selected indicators,combined with relevant literature at home and abroad,the unit GDP energy consumption will be selected as the final outcome indicators;Energy saving and environmental protection R&D expenditure and total investment in environmental pollution control will be selected as input level indicators;Annual amount of solid waste treatment and the proportion of tertiary industries will be selected as output level indicator.In order to eliminate the multicollinearity,the data will be processed by logarithm,and then the data will be analyzed by panel data.The spatial weight matrix will be determined by the method of determining the spatial weight matrix,and the spatial auto-correlation index(Moran)and the scatter plot will be used to analyze the spatial auto-correlation.Which kind of spatial panel model should be selected by using LM-Error test and LM-Lag test panel data.The results show that combined with the fixed effect value of each region,we find that the performance of energy saving and environmental protection R&D input in different regions of China is different,showing the gradual decline from east to west,that is,the eastern region's energy saving and environmental protection R&D investment performance is higher than the central,central energy conservation and environmental protection R&D input performance is higher than the west.The eastern region energy saving and environmental protection R&D investment performance is better,which is closely related to its unique geographical environment;Regional energy conservation and environmental protection R&D activity needs to be further strengthened.On this basis,putting forward our country's energy saving and environmental protection R&D investment mode is to continue to increase the eastern region of energy saving and environmental protection R&D investment and pay more attention to the Midwest energy saving and environmental protection R&D investment,to the east to promote the development of the mid-west.It is suggested that China should adjust the regional resource differences according to different provinces to form an effective resource allocation structure.Because of the difference of history,culture and geographical location,each region has its own environmental resources.Therefore,each government should be based on the actual situation of each region,to develop their own advantages,and actively play the government's "leverage effect";At the same time,the government should control the balance between energy efficiency and environmental protection R&D investment in universities,research institutions and enterprises to carry out the balance between the three main R&D activities and the government energy conservation and environmental protection R&D direct investment and indirect investment.The main innovations of this paper are shown as follows: to analyze the performance differences of China's regional energy conservation and environmental protection R&D input,and to analyze the spatial correlation and spatial difference of China's regional energy saving and environmental protection R&D investment performance by using the spatial panel models. |
PDF Full Text Request