Birth Rate Study of Henan Province Based on Ridge Regression Model
Автор: Mengke Ye.
Журнал: International Journal of Mathematical Sciences and Computing @ijmsc
Статья в выпуске: 4 vol.9, 2023 года.
Бесплатный доступ
In order to explore the underlying reasons for the decline in birth rate, this article selects 12 explanatory variables and uses ridge regression method to study the birth rate in Henan Province from 2015 to 2021. Research has shown that four factors, namely the average salary of urban unit employees, the urbanization degree, the ratio of female employees with a university degree or above, and the population mortality rate, can not explain the birth rate. However, the proportion of gross domestic product of the second and third industries, as well as the proportion of female population over 15 years of age who are illiterate, has a positive impact on the car success rate. The gross domestic product per capita, the number of beds per 10000 people in medical institutions, the per capita disposable income of urban residents, the per capita disposable income of rural residents, the adolescent dependency ratio, and the elderly dependency ratio have a negative impact on the birth rate. Through the research in this article, the main factors affecting the birth rate in Henan Province have been identified, and policy recommendations for improving the birth rate have been proposed. The positive impact represents increasing investment in these factors, which can effectively improve the birth rate in Henan Province and solve the serious problems we are currently facing. The negative factor is the opposite.
Birth rate, Influencing factors, Multicollinearity, Ridge regression, Ridge trace map
Короткий адрес: https://sciup.org/15019064
IDR: 15019064 | DOI: 10.5815/ijmsc.2023.04.02
Список литературы Birth Rate Study of Henan Province Based on Ridge Regression Model
- Yiqun Zhou, Guojun Wang. (2016) Empirical analysis on Chinas birth rate and saving rate based on provincial panel data. CHINA POPULATIONESOUCES AND ENVIONMENT, 26 (11), 266-269.
- Zhigang Guo,Xiwei Wu. (2006) Applicati on of Poisson Regressi on i n Fertility Study. POPULATION JOURNAL, (4), 2-95.
- Xizhe Peng. (1990) Application of generalized linear model in differential fertility analysis. China Academic Journal Electronic Publishing House, (02), 49-52.
- Mian Tan. (2011) Analysis of the influencing factors of population fertility rate in Hunan Province. China Academic Journal Electronic Publishing House, 211-212.
- Zhenwu Zhai, Shujing Li. (2023) The influencing factors of low fertility rate in China in the new era. JOURNAL OF UNIVERSITY OF JINAN(Social Science Edition), 33 (1),13-24.
- Shuangyue Lan. (2022) The effect of retirement on fertility in offspring families: an empirical test based on CFPS data. Southwestern University of Finance and Economics.
- Wei Chen. (2009) Methods of Fertility Rate Studies in China: An Overview of the Past Thirty Years. POPULATION JOURNAL, (3), 3-8.
- Liangzhen Guo. (2022) Study on the influencing factors and trend forecast of birth rate in Hubei Province. Central China Normal University.
- Robert I.Kabacoff. (2016) R in Action. POSTS & TELECOM PRESS.
- Bradley Efron, Trevor Hastie. (2017) Computer Age Statistical Inference Algorithms, Evidence, and Data Science. Cambridge University Press.
- Xiaoqun He. (2017) Applied Regression Analysis(R Language Edition). PUBLISHING HOUSE OF ELECTRONICS INDUSTRY.
- Shisong Mao,Yiming Cheng,Xiaolong Pu. (2011) Probability theory and mathematical statistics (Second Edition). PHigher Education Press.
- Shunan Zhang. (2022) The National Bureau of Statistics responded to the “birth rate decline”: there are three reasons. https://www.163.com/dy/article/GTTU1HOA0519C6T9.html.
- Liying Wan. (2016) Analysis and Application of Ridge Regression. JOURNAL OF XUCHANG UNIVERSITY, 35(2), 19-23.
- Xiaogang Dong, Yajing Diao, Hunling Li, Chunjie Wang, Linan Wen. (2018) The analysis of the fiscal revenue factors under the ridge regression,LASSO regression and the Adaptive-LASSO regression. Journal of Jilin Normal University(Natural Science Edition), 39(2), 45-53.
- Hailong Zhu, Pingping Li. (2022) Analysis of influencing factors of fiscal revenue in Anhui province based on ridge regression and lasso regression. Journal of Jiangxi University of Science and Technology, 43(1), 59-65.