| Improving Total Factor Productivity(TFP)is the core meaning of the economy from high-speed growth to high-quality development,while matching the factor endowment structure is the proper meaning of improving Total Factor Productivity.In the process of system transition and economic transformation,the structure of factor endowment in China is changing with each passing day.Theoretically,there is evidence for the influence of factor endowment structure on TFP.However,in practice,the traditional neoclassical economic growth model is limited by the assumption of steady economic growth,and tends to weaken or even ignore the influence of the change of factor endowment structure on total factor productivity.In order to explore the effect of factor endowment structure change on total factor productivity,theoretically,based on the three dimensions of micro enterprise,medium industry and macro economy,through theoretical analysis and mathematical derivation,this paper analyzes the influence mechanism of factor endowment structure change on China’s total factor productivity from two paths of technology choice and factor flow.Empirically,based on the fact that China’s factor income share is time-varying,this paper introduces a time-varying elasticity production function model(TVE),and uses the shift-share method to decomposed the economic growth force,constructing the technology choice effect measurement model and the factor flow effect measurement model of the factor endowment structure.The empirical research on the technology selection effect and factor flow effect of the factor endowment structure is carried out at different levels,stages and industries.The main research conclusions are as follows: First,the factor endowment structure change has a significant impact on the improvement of total factor productivity in China,with an average contribution rate of 32.61%.From 1988 to 2019,the contribution rates of internal productivity growth effect,biased technological progress effect,capital transfer effect and labor transfer effect to total factor productivity improvement were 67.39%,-2.15%,35.57% and-0.81%,respectively.Second,the suitability of technological progress and factor endowment structure in China needs to be improved.At the macro level,the biased technological progress effect inhibits the improvement of total factor productivity.At the industrial level,only the technological choice of the primary industry is appropriate to the factor endowment and positively affects its economic growth,while the technological choice of the secondary industry and the tertiary industry has a negative effect.Third,although labor transfer between industries releases "demographic dividend",it has the possibility of restricting the improvement of total factor productivity.From 1978 to 2019,the average contribution of labor factors to economic growth was 10.05%,but the contribution of labor transfer effect to total factor productivity was-0.81%.The possible marginal contribution of this paper is as follows: First,the measurement model of structural change effect of factor endowment is constructed.Based on unsteady China’s economic growth of the facts,this paper introduces a time-varying elasticity production function model(TVE),and uses the Shift-Share Method to decompose total factor productivity into productivity internal growth effect,bias technology progress effect,the structure of the output change effect,capital transfer effect and labor transfer effect,which provides a possible model reference for quantifying the effect of structural change of factor endowment.Second,it confirms the influence of factor endowment structure on total factor productivity.Based on the technology selection and flow elements of two paths,through theory expatiates and empirical study,illustrates the structure of factor endowments change influence on total factor productivity.This justifies the effect of structural change of factor endowment,which is weakened or even ignored by neoclassical economic growth theory,and provides a possible new perspective for developing countries to improve total factor productivity. |