Analysis On The Impact Of Social Population Age Distribution's Discrete Degree On Product Innovation

This paper explores the influence of the discrete degree of population age distribution on product innovation by studying the internal relation between population age distribution and enterprise product innovation behavior.The discrete degree of population age distribution and the investment on product innovation of enterprise are the two core variables of this paper.To find the relationship of two core variables,this paper constructs the model in stages.At first,discrete degree is internalized in the function of population age distribution,and the relationship between the discrete degree of population age distribution and the intermediate variable is obtained.Then,expected demand for new products can be acquired by the population distribution function and the utility function.Ignoring the marginal cost of new products,we can obtain the intermediate variables and profitability when the enterprise is expected to maximize profitability.Then we can use the probability distribution function of innovative to associate innovative inputs with innovation probability distribution.Moreover,we use the continuous discount model and Cournot model to derive the present value,which contains the intermediate variable,of the expected profit coming from enterprise production innovation.In combination with the equation of the discrete degree of population age distribution and the intermediate variable,we can finally acquire two functions of the two core variables and the intermediate variables.And then we use the MATLAB7.0 software to eliminate the intermediate variables,direct relationship between the two core variables can be got.Then,we plot the relationship and get the conclusion of the model analysis;Finally,we extend the model part which shows enterprise product innovation behavior to the field of industry product innovation behavior.The results of the theoretical model are verified by the ADF test,the Hausman test and the fixed effect model,and the final conclusion is obtained:when the discrete degree of population age distribution is not high,the increase of the data will stimulate product innovation;when the discrete degree of population age distribution is very high and more than the critical value,product innovation will fall into the trough.At present,the discrete degree of population age distribution in our country is low,and the data will be still in the level stimulating product innovation.In addition,we research the competition degree,research efficiency,and real interest rate and discuss their impact on product innovation.The conclusion of this paper can provide some suggestion for China's population policy,industrial innovation policy and intellectual property protection policy,which is beneficial to our country to implement the innovation-driven development strategy and to jump over the "middle income trap" as soon as possible to realize the great Chinese dream!The innovation of this paper has three:First,the research perspective is fresh,and embarks from the discrete degree of population age distribution to study product innovation creatively,which is different from the former articles.They embark mostly from the vendor behavior of supply side or income level,income gap and other demand side to study the product innovation,and the paper analyzes the influence of the discrete degree of population age distribution on the product innovation.The conclusion of the article also has the innovative value and provides a way to consider the product innovation from population age distribution.Second,the author constructs the power function model of population age distribution creatively,and then uses the mathematical expectation method and the density function corresponding to the distribution function to connect the population distribution discrepancy with the population age distribution function,and then builds the whole theoretical model frame.Thirdly,in the data,after smoothing the data of the population age,we simulate the approximate age distribution of population.Based on the calculation of population age distribution from 2003 to 2013,the database is provided for the empirical analysis.