| Land resources are the material basis for human survival and development,and also the key element of ecological civilization construction.With the rapid development of industrialization and urbanization in China,the ecological environment risk of land development and utilization is becoming increasingly prominent.The high extensive,high pollution and low efficiency land development mode seriously limits the sustainable development of China's industry.As an important carrier of urban development,how to change the extensive use of industrial land and realize the sustainable utilization and efficiency maximization of industrial land resources has become a hot and difficult problem to be solved by the government and academia.The Fifth Plenary Session of the 19 th CPC Central Committee put forward that promoting green development and realizing new progress in ecological civilization construction have become one of the main goals of economic and social development during the "14th five year plan" period.The development concept of "high quality development" proposed in the 14 th five year plan provides a new idea for the sustainable and efficient use of industrial land.Therefore,improving the economic and environmental carrying capacity of industrial land and deeply studying the efficiency of industrial land and its influencing factors have important theoretical and practical significance for building a resource-saving society and promoting high-quality industrial development.On the basis of systematically combing the evolution of green development,this paper deeply expounds the connotation of green development,and establishes a more scientific and comprehensive evaluation index system reflecting the green development level of China's industrial land.This paper uses super efficiency EBM model and GML index to measure the industrial land use efficiency and green total factor productivity of China's 288 prefecture-level cities(states)from 2003 to 2018,and explores the temporal and spatial evolution characteristics of industrial land use efficiency and green total factor productivity from static and dynamic aspects.This paper studies the convergence and dynamic evolution trend of efficiency differences,and identifies the key factors affecting the efficiency of industrial land use in China based on the exploration of spatial correlation,so as to provide theoretical basis for government departments to formulate industrial land use policies,and promote the green,high-quality and sustainable use of industrial land in China.The main contents and conclusions of this paper are as follows.The measurement of industrial land use efficiency and the analysis of temporal and spatial evolution characteristics in China.This paper uses the super efficiency EBM model based on unexpected output and GML index to measure the industrial land use efficiency of China's 288 prefecture-level cities(states)from 2003 to 2018,and explores the temporal and spatial evolution characteristics of industrial land use efficiency from static and dynamic aspects.The results show that: 1)from the perspective of overall characteristics,the industrial land use efficiency shows a fluctuating upward trend from2003 to 2018,and the green total factor productivity has a spiral upward trend,but the overall level is low,and the green development still has a long way to go.2)From the perspective of spatial distribution pattern,the utilization efficiency of industrial land in East China and South China is higher than that in other regions,which indicates that the two regions take the lead in promoting the construction of ecological civilization,and the further promotion of pollution control can effectively improve the efficiency of industrial land.The spatial imbalance development has obvious differences,and has a significant agglomeration characteristics,showing a "high in the East and low in the west" layer by layer decreasing distribution characteristics.In addition,the number of cities whose comprehensive technical efficiency and scale efficiency reached the reasonable level of "1" increased from 9 in 2003 to 34 in 2018,accounting for 11.8% of the total number of cities,while the value of pure technical efficiency increased from 23 in 2003 to 67 in 2018,accounting for 23.3% of the total number of cities.3)From the perspective of efficiency decomposition,Total factor productivity growth of industrial land mainly comes from technological progress,and provinces(cities)present different "single track" or "double track" driving modes of technological efficiency and technological progress.(2)Spatial convergence analysis of industrial land use efficiency in China.Based on the theories and methods of convergence hypothesis,this paper tests the convergence and dynamic evolution trend of regional disparity of industrial land use efficiency in China from four aspects: absolute convergence,conditional convergence,PS convergence and club convergence.The results show that: there is no ? convergence in the efficiency of industrial land use in China,but there are absolute ? convergence,conditional ? convergence and club convergence at the same time.A "catch-up effect" is exist in the efficiency of regions with the same initial conditions,which converges towards their own stable level.However,the gap between high efficiency and low efficiency regions will exist objectively for a long time and will not disappear spontaneously in a short time.(3)The spatial correlation analysis of the industrial land use efficiency in China.Using the Exploratory Spatial Data Analysis Method(ESDA),through Moran's I index and LISA cluster map,the global and local spatial correlation characteristics of industrial land use efficiency in China are explored.The results show that: 1)Overall,the spatial correlation of industrial land use efficiency in China is weak.2)Locally,the industrial land use efficiency in China has the characteristics of high-high-type(HH)aggregation and low-low-type(LL)aggregation.There is obvious path dependence in spatial geographic distribution,and it is difficult to get rid of the current agglomeration category.3)There is a spatial correlation effect between industrial land utilization efficiency and total factor productivity of industrial land,but it does not show good spatial coordination.(4)Spatial econometric analysis of the factors which affect the industrial land use efficiency in China.Based on the analysis of efficiency influencing mechanism,the spatial geographic factors(spatial interaction effects)are included in the regression analysis framework,and the Spatial Dubin Measurement(SDM)model is used to conduct empirical analysis on the influencing factors of industrial land use efficiency in China.The research found that: 1)Spatial and geographic factors have a significant positive impact on the efficiency of industrial land utilization.With the deepening of China's industrial marketization and the continuous improvement of the social service system,the exchanges of various elements and information between regions are getting closer and closer.2)From a national perspective,the local economy level,the optimization of industrial structure and the investment in the treatment of industrial environmental pollution sources have a significant positive impact on the utilization efficiency of industrial land,while the degree of population aggregation,land revenue,industrial development level and industrial energy consumption have an inhibitory effect on the utilization efficiency of industrial land.The spatial spillover effect of this region on neighboring regions has significant negative correlation with land revenue,foreign investment level and industrial development level.3)From the perspective of regional scale,the impact of each region is different.Under the current national strategic background of green industry development,underdeveloped regions should scientifically and reasonably plan industrial layout and industrial structure based on their own advantages,improve the quality of labor force,rely on technological progress,increase investment in industrial environmental governance,improve industrial production mode and other policies,to transform the industrial production environment effectively,improve the industrial production efficiency,and promote the improvement of industrial land use efficiency.Based on the above situation,this paper discusses the industrial land assessment index system from the following aspects: the concept of green development,optimizing the industrial land development pattern;giving play to the spatial spillover effect,promoting cross regional linkage and cooperation;following the inter city differences,promoting the implementation of policies according to the city;building a regulatory mechanism,reasonably controlling the scale of land use;optimizing the allocation of key factors,speeding up technological innovation;revitalizing the secondary land market,promoting the saving and intensive use of industrial land and other aspects,put forward relevant countermeasures and suggestions to promote China's industrial land use efficiency.In summary,compared with the existing research results,the innovations of this article can be summarized in the following three aspects.From a research perspective,this article comprehensively considers the resource consumption and ecological environment pollution problems faced in industrial land use process,and provides a reference analysis framework for the study of industrial land use efficiency based on green development,and improves the theoretical system and application of efficiency study.Second,in terms of research content,multi-spatial scale and multi-level in-depth research on 288 prefecture-level cities(states)have enriched the multi-spatial research on industrial land in China.Third,in terms of research methods,the use of cutting-edge econometric methods for research,such as the use of Super-efficiency EBM and GML indexes based on undesired output to measure the efficiency of industrial land utilization,and the use of exploratory spatial data analysis(ESDA)from global and local to explore its spatial relevance,and using the Spatial Dubin Econometric Model(SDM)to incorporate spatial geographic factors into the influencing factor regression analysis framework,making the research process more standardized and closer to reality,and the research conclusions more scientific. |
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