Improved Adaptive Lasso Algorithm And Its Application In Birth Rate

Since the reform and opening up,with the rapid development of China’s economy,the population structure of our country presents low birth rate,low death rate and low growth rate.In recent years,as the number of labor force began to decrease,the aging trend of China’s population has become increasingly obvious,which has seriously affected the economic development of China.The study of the factors affecting the birth rate is one of the core questions in a demographic study.Based on the panel data from 2007 to 2017 in China,this paper proposes an improved adaptive Lasso algorithm and uses it to make sparse selection of variables affecting the birth rate.First of all,this paper introduces the method of Lasso,adaptive Lasso method and basic idea and algorithm step of OMP algorithm,based on the above three algorithms proposed adaptive orthogonal matching pursuit(AOMP)algorithm,by using the real data on artificial AOMP algorithm numerical experiment,the numerical experiment results show that the proposed AOMP fast algorithm of dimension reduction and has stronger robustness,can be completed quickly sparse variable selection.Secondly,Lasso method,OMP algorithm and AOMP algorithm were used to model and solve the factors affecting the birth rate,and a comparative experiment was conducted on the three algorithms.It was found that AOMP algorithm has low sparsity and small error.Birth rate variable selection based on AOMP algorithm results show that children’s dependency ratio,infant mortality rates,gross domestic product(GDP)and the consumer price index for most affect fertility,including children’s dependency ratio,gross domestic product(GDP)and the consumer price index for the influence of the birth rate is positive,and infant mortality is a negative impact on fertility;Finally,based on the selected variables affecting the birth rate,some Suggestions are put forward: mainly including improving residents’ housing security,strictly controlling inflation and price increase,improving medical conditions,reducing the occurrence of caesarean section,and other measures to stimulate the population’s desire to have children.