山西省人口构成现状及预测研究

发布时间：2018-06-08 00:22

本文选题：山西省 + 人口预测　；参考：《山西医科大学》2011年硕士论文

【摘要】：研究目的通过建立山西省人口预测模型，预测未来人口构成状况，为山西省未来人口政策的制定，人口、社会和环境的可持续发展提供参考依据。研究方法研究资料来源于山西省1953年、1964年、1982年、1990年、2000年5次人口普查资料和2000～2010年的《山西省统计年鉴》。主要研究方法有： 1.文献研究法：对已有的文献资料，进行整理、综合和分析； 2.计算分析法：根据历次人口普查和历年来人口抽样调查数据模拟了山西省人口发展的一元线性回归模型、二次多项式回归模型、三次多项式回归模型和灰色GM（1，1）模型，运用SPSS13.0、Matlab和灰色系统理论软件，对山西省人口发展过程及其现状进行描述； 3.比较分析法：运用模型对山西省2005～2009年的总人口数、男性人口数和女性人口数，2007～2009年的总抚养比、老年抚养比和少儿抚养比进行分析并比较。研究结果 1.截止2009年山西省总人口数为3427.36万人，年增长率为0.61%。其中，男性人口数为1758.13万人，占总人口数的51.30%，女性人口数为1669.23万人，占总人口数的48.70%，男女性别比为1.05:1； 2.未来10年山西省总人口数由2010年的3465.82万人增加到2019年的3581.81万人，呈逐年递增的趋势，但年增长率逐年下降； 3.未来10年山西省男性人口数与女性人口数趋于平衡，两者比例为1：1； 4.2010～2015年山西省总抚养比分别为32.91、31.57、30.15、28.63、26.97、25.17，呈逐年下降趋势； 5.2010～2015年山西省老年抚养比分别为11.84、13.08、14.74、16.91、19.64、23.00，老年人口比例逐年增加； 6.2010～2015年山西省少儿抚养比分别为21.07、18.49、15.38、11.67、7.26、2.05，呈逐年下降趋势，出生人口数减少。研究结论 1.三次多项式回归模型的误差最小、精度最高，，适合对山西省的未来人口状况进行预测； 2.未来10年山西省的总人口数增加，但年增长率逐年下降；未来5年山西省总抚养比下降；老年人口数增多，人口老龄化进程加快。
[Abstract]:The purpose of this study is to establish a population prediction model of Shanxi Province, to predict the future population composition, and to make the population for the future population policy of Shanxi Province. The data of the research methods are obtained from the five census data of Shanxi Province in 1953, 1964, 1982, 1990, 2000 and the Statistical Yearbook of Shanxi Province from 2000 to 2010. The main research methods are as follows: 1. Literature research method: collate, synthesize and analyze the existing documents. 2. Calculation and analysis method: based on the data of population census and sampling survey over the years, this paper simulates the univariate linear regression model, quadratic polynomial regression model, cubic polynomial regression model and grey GM-1) model of population development in Shanxi Province. SPSS 13.0 Matlab and grey system theory software are used to describe the population development process and present situation of Shanxi Province. Comparative analysis method: the total population, male population and female population of Shanxi Province from 2005 to 2009 were analyzed and compared with the total dependency ratio of 2007 ~ 2009, the old age dependency ratio and the child dependency ratio of Shanxi Province from 2007 to 2009. The results are as follows: 1. As of 2009, the total population of Shanxi Province is 34.2736 million people, the annual growth rate is 0.61%. Among them, the male population is 17.5813 million, accounting for 51.30% of the total population, and the female population is 16.6923 million, accounting for 48.70% of the total population. The ratio of male to female is 1.05: 1; 2. In the next 10 years, the total population of Shanxi Province will increase from 34.6582 million in 2010 to 35.8181 million in 2019, which will increase year by year, but the annual growth rate will decrease year by year. In the next 10 years, the male population and the female population of Shanxi Province tend to balance. The ratio of the two is 1: 1; the total dependency ratio of Shanxi Province from 2010 to 2015 is 32.91 / 31.5730.15 / 28.63326.9 / 25.17, respectively, showing a decreasing trend, and the old dependency ratio of Shanxi Province from 5.2010 to 2015 is 11.844 (13.08) 14.714 (16.91b) (19.623.00), the proportion of the elderly population increases year by year, and the dependency ratio of children in Shanxi Province from 6.2010 to 2015 is 21.0718.49 / 15.811.677.262.05, respectively, showing a decreasing trend year by year. Reduction in the number of births. Conclusion 1. The cubic polynomial regression model has the smallest error and the highest precision, which is suitable for predicting the future population situation of Shanxi Province. 2. In the next 10 years, the total population of Shanxi Province will increase, but the annual growth rate will decrease year by year, the total dependency ratio of Shanxi Province will decrease in the next five years, and the elderly population will increase and the aging process of the population will accelerate.
【学位授予单位】：山西医科大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：C924.2

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