AR  >> Vol. 3 No. 2 (June 2016)

    我国老龄化人口的影响因素分析
    Analysis on the Influencing Factors of Aging Population in China

  • 全文下载: PDF(844KB) HTML   XML   PP.11-18   DOI: 10.12677/AR.2016.32002  
  • 下载量: 1,950  浏览量: 5,712  

作者:  

李恩来:云南财经大学,统计与数学学院,云南 昆明

关键词:
人口老龄化定量分析多元回归分析建议Aging Population Quantitative Analysis Multiple Regression Analysis Suggestion

摘要:

随着人类文明不断地进步,人类的医疗水平和生活质量也不断地提高,导致人类的平均寿命不断增长以及其他各方面原因,使得人类老龄化问题越来越严重,尤其是我国老龄化问题。有不少学者提出人口出生率、死亡率、自然增长率这三个因素是影响人口老龄化的主要因素,本文基于这三个主要因素基础,添加一些其他因素来构建一个多元回归分析来定量分析我国老龄化人口数与哪些因素有关。本文一方面定量分析我国老龄化人口的变化趋势与我国人口出生率和我国人均GDP之间的关系,另一方面也论证了我国今年年初实行的放开“二胎”政策的必要性和合理性。本文最后给出一些合理的建议来应对我国老龄化问题。

With the continuous progress of human civilization, human health and quality of life continue to improve, so that the average human life expectancy is growing, which makes the human aging problem is becoming more and more serious, especially the aging problem in China. Many scho-lars put forward that the birth rate, death rate and natural growth rate are the main factors in-fluencing aging. Based on the three main factors, this paper adds some other factors to build a multiple regression analysis to make a quantitative analysis of the reasons of aging population. In this paper, on the one hand the quantitative analysis of the relationship between the aging population trend, birth rates and per capita GDP is conducted. On the other hand, it also demonstrates the necessity and rationality of the “two-child” policy released earlier this year. Finally, we give some reasonable suggestions to deal with the problem of aging.

文章引用:
李恩来. 我国老龄化人口的影响因素分析[J]. 老龄化研究, 2016, 3(2): 11-18. http://dx.doi.org/10.12677/AR.2016.32002

参考文献

[1] Hansen, P.E. (1989) Leslie Matrix Models. Mathematical Population Studies, 2, 209-222.
[2] Bijak, J. (1985) Population and Labor Force Projections for 27 European Countries, 2002-252: Impact of International Migration On population Aging. Europe Journal of Population, 23, 1-31.
[3] Wildasin, D.E. (1991) The Marginal Cost of Public Funds With an Aging Population. Journal of Population Economics, 4, 111-135.
http://dx.doi.org/10.1007/BF00176002
[4] 尹春华, 陈雷. 基于BP神经网络人口预测模型的研究与应用[J]. 人口学刊, 2005, 27(2): 45-49.
[5] 安和平. 中国人口预测的自回归分布滞后模型研究[J]. 统计与决策, 2005, 21(16): 4-7.
[6] 朱兴造, 庞飞宇. 自回归及logistic 离散模型在中国人口预测中的应用[J]. 统计与决策, 2009, 25(13): 157-159.
[7] 甘蓉蓉, 陈娜姿. 人口预测的方法比较——以生态足迹法、灰色模型法及回归分析法为例[J]. 西北人口, 2010, 31(1): 57-60.
[8] 蒋远营, 王想. 人口发展方程模型在我国人口预测中的应用[J]. 统计与决策, 2011, 27(15): 52-54.
[9] 任强, 侯大道. 人口预测的随机方法: 基于Leslie矩阵和ARMA模型[J]. 人口研究, 2011, 35(2): 28-42.
[10] 杜鹏. 中国人口老龄化主要影响因素的量化分析[J]. 中国人口科学, 1992, 6(6): 18-24.
[11] 高采文, 张静静. 中国人口老龄化序列分析预测研究[J]. 山西大同大学学报, 2014, 30(4): 9-10, 21.