| The mineral resources industry provides strong support and resource guarantee for the world’s economic and social development,and China,as a major country in the global mineral resources industry,has an important influence on the world’s mineral resources production and supply.However,the rapid development of the mineral resources industry has led to excessive resource consumption,serious carbon emissions,and low resource utilization efficiency,which has threatened the ecological environment.To bring China’s mineral resources industry out of the dilemma of resource depletion and environmental degradation,improving green total factor productivity(GTFP)is the key,which is important for achieving high-quality development of the mineral resources industry.Using data on mineral resource industries in 30 provinces in China from 2004 to 2019,we measure GTFP and analyze the space-time evolution characteristics to explore the spatial effects of variables such as import trade and resource endowment on GTFP,with a view to providing more precise policy recommendations for improving GTFP in mineral resource industries.The main research conclusions are as follows:The Super-SBM model with undesirable output is used to measure the GTFP of mineral resources industry,and resource inputs are separately considered in the framework,which can reflect the actual GTFP level more realistically,accurately and comprehensively.The GIS spatial analysis method and standard deviation ellipse method are used to explore the space-time evolution characteristics of GTFP of mineral resources industry and lay the foundation for the analysis of space-time effects.The space-time distribution characteristics show that the high value areas of GTFP in mineral resources industry and smelting and processing industry are mainly distributed in coastal provinces,and the high value areas of GTFP in mining industry are mainly distributed in northern and some coastal provinces,both showing polarization trends.In addition,the center of gravity of GTFP in mineral resources industry and smelting and processing industry is mainly distributed in central China,with the former showing a changing pattern from north to south and then to east,and the latter moving from the central China to the southeast,with the distance and speed of movement gradually decreasing.The short axis and long axis of the standard deviation ellipse of GTFP of mineral resources industry and smelting and processing industry keep shrinking,and the area of the ellipse decreases,showing agglomeration development.The change trend of GTFP in mining industry is not obvious.The spatial association distances of GTFP of mineral resources industry,mining industry and smelting and processing industry calculated by using the space-time semivariogram are 635.28 km,536.13 km and 722.31 km,respectively,which are used as the threshold of spatial weight matrix in the spatial effect model to improve the accuracy of spatial analysis.The spatial panel model is used to estimate the spatial spillover effects of import openness,import structure,resource endowment and other variables on the GTFP of mineral resources industry,and the results found that: 1)There is a significant positive effect of import openness on the GTFP of mineral resources industry and smelting and processing industry.The imported mineral products have high grade and good quality,and the technology inflow accompanying the import has improved the production efficiency.The positive impact of import openness on GTFP in mining industry is not significant.The mining industry mainly imports concentrates,which can improve resource utilization efficiency and reduce carbon emissions,but the decrease in international prices of minerals will lead to a portion of imported ore tunnels and increase input costs.There is a significant positive spatial spillover effect of import openness on GTFP of mineral resources industry and smelting and processing industry.The increase of import openness of neighboring provinces can expand the source channels of local resources and reduce local inventory,saving time and economic costs.The spatial spillover effect of mining industry is not significant.2)There is a significant negative impact and negative spatial spillover effect of import structure on GTFP of mineral resources industry.The increase in the share of mining industry imports in the total imports of mineral resources industry causes an increase in environmental pollution,a decrease in the inflow of advanced technology,and a weakening of interprovincial flow of mineral products.3)The resource endowment has a negative impact on the mineral resource industry GTFP,and the spatial distribution of resource rich areas and key mining areas is inconsistent.4)There are positive effects of R&D investment,environmental regulation intensity,transportation infrastructure and economic development level on GTFP of mineral resources industry.Environmental regulation intensity and transportation infrastructure have positive spatial spillover effects on GTFP.There is a negative spatial spillover effect of economic development level on GTFP.The spatial spillover effect of R&D investment is not significant.The direct effects and spatial spillover effects of variables in the smelting and processing industry on GTFP are consistent with those in the mineral resources industry.Mining industry is slightly different,the direct effect of environmental regulation intensity on GTFP is not significant,and the spatial spillover effect of economic development level on GTFP is not significant.The SPVAR model is used to analyze the space-time impulse effects of import openness/import structure,R&D investment and GTFP in the mineral resources industry,and the results show that: 1)The direction of the effects of import openness,import structure and R&D investment on GTFP is consistent with the spatial spillover effects.2)Under the impact of the same variable in the same province,the change trend of the same response variable of mineral resources industry,mining industry and smelting and processing industry in the local and neighboring provinces is consistent,and the response value is different.3)Under the impact of the same variable,the eastern region has the largest response value,the central region has the middle response value,and the western region has the smallest response value.4)After the impact in the local,there is regional difference in the response range of neighboring provinces.The response value of coastal provinces is larger than that of inland provinces,and the closer the province is to the impact,the greater the response value. |
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