Research On The Impact Of The Scale And Structure Of Factor Agglomeration On Innovation Efficiency

China's economic development is still in and will remain in an important period of strategic opportunities for a long time,according to the central economic work conference held in December 2018.In the past,there were many reasons for China's sustained and rapid economic growth,among which positive innovation was one of them.However,based on the present situation of uneven common resources distribution,under the dual function of factor endowment and industrial policy,there are differences in factor agglomeration among regions,which are reflected in the scale and structure.As a result,the innovation efficiency among regions will be enlarged,causing the imbalance of regional development and hindering further coordinated economic development.Therefore,it is necessary to optimize and adjust the scale and structure of factor agglomeration to promote the improvement of innovation efficiency,promote the construction of China's sustainable economic development strategy and achieve a virtuous economic cycle.After reviewing relevant literatures,this paper first discusses the theoretical basis,focusing on Marshall industrial zone theory and krugman's core-edge model,and studies the typical characteristics of factor agglomeration and the resulting forces,so as to explain the causes of scale and structural changes in factor agglomeration.Then,based on the characteristics of material capital elements and human capital elements,the synergistic effect and interaction between elements are discussed qualitatively,so as to analyze the different action paths of the influence of factor agglomeration on innovation efficiency from the scale and structure,and make a comparison.Then,based on the actual situation,empirical research was conducted on the provincial data of China from 2000 to 2016 to analyze the impact of the scale and structure of interregional factor agglomeration on innovation efficiency.Through the pre-test,it is concluded that the spatial panel data model can better fit the real situation,the specific model is the spatial lag model and the spatial error model.At the present stage,blindly increasing the absolute scale of factor agglomeration cannot effectively improve the innovation efficiency.It needs to be matched with the local economic output,paid attention to the agglomeration structure of material capital elements and human capital elements,and given full play to their interaction,so as to have a positive impact on innovation efficiency.In order to achieve this goal,the relative scale of material capital elements should be focused on,rather than the absolute scale,and the degree of material capital input should be controlled to match the economic output.In terms of human capital elements,it is necessary to pay attention to the economic conversion rate of human capital,pay attention to the economic transformation of innovation achievements,carry out commercialization and industrialization,and appropriately adjust the weight of relevant performance assessment.According to the local economic development and industrial development,the introduction of talents of different levels shall be arranged according to the local conditions,and the local human capital structure shall be optimized.It is not recommended to blindly introduce high-level,refined and top-notch talents,resulting in the phenomenon of "unsatisfactory use and untenable retention" which forming a waste of resources.