安徽省人口老龄化的影响因素及地区差异性分析

发布时间：2018-09-08 17:18

【摘要】：根据1956年联合国报告《人口老龄化及其社会经济后果》声明的划分标准,自20世纪末期中国就已进入人口老龄化阶段。虽然我国进入老龄化的时间较西方发达国家稍晚,但速率很快,大约用20年时间达到了西方发达国家50-80年的老龄化进程,老龄化的步伐已经无法阻挡。位于我国华东区域的人口大省安徽省,是长三角经济区的重要组成部分,其人口结构无疑对我国的人口结构有较大的影响。目前安徽省正处于转型发展的关键时期,因此,我们有理由相信,有针对性的研究和分析安徽省人口老龄化的影响因素及地区差异性问题显得尤为重要。本文首先对安徽省人口老龄化现状及原因简单分析,用2000-2015年安徽省抚养比数据作出了变化趋势图,结果表明老年抚养比直线上升,基于2015年老龄系数数据,初步显示本省16个市老龄化程度存在区域差异性,基于五普、六普数据描述了高龄人口占比情况,环形图结果显示80岁及以上人口占比10年翻一番,与此同时把安徽省老龄化系数和全国及周边六省老龄化情况作对比,结果显示,安徽省老龄化程度较严重,位居周边第二。其次,从人口结构因素、经济发展因素、社会发展因素、教育发展因素角度分析,选取六个解释变量,用老龄化系数衡量老龄化程度。采用2006-2015年安徽省16个市的面板数据,对老龄化的影响因素进行实证分析。首先通过计量经济学中豪斯曼(Hausman)检验,得出符合固定效应模型。借助Eviews软件对模型进行两种不同方法的操作,第一:16个地市的面板数据截面系数相同时;第二:16个地市的面板数据的截面系数不相同时。结果发现第一种情况下,死亡率、每万人拥有的卫生技术人员数两个变量不显著;第二种情况下,各个市的情况存在差异,详情请见下文第三章。最后,本文的第二个重点为安徽省人口老龄化地区差异性实证分析。首先选用2015年16个地市4个相关指标的数据,采用K-均值法对样品进行Q型聚类分析,借助SPSS软件得出最初分类重心表、最终分类重心表、方差分析表等,静态比较分析分类的结果。其次再选取2010年安徽省16个地级市的相关指标数据,用SPSS软件聚类分析,纵向分析十二五到十三五期间安徽省人口老龄化内在的一些变化,从而定量把握安徽省各个地级市人口老龄化的变化。结果表明2015年重度、中度、中轻度、轻度四种类型城市数分别为3个,5个,6个,2个;2010年重度、中度、中轻度、轻度四种类型城市数分别为2个,10个,3个,1个,总体的划分标准全部是提高的,并纵向分析了 5年内各个城市的老龄化变化,有利于因地制宜采取科学措施,应对人口老龄化问题。由此可见,安徽省的人口老龄化问题已经日益凸显,并且成为本省亟待解决的问题,科学合理的做好老龄化问题的应对措施,对安徽省的可持续发展意义非凡,本文结合实证分析,给出了对策建议。
[Abstract]:According to the classification criteria of the 1956 UN report "population ageing and its Social and Economic consequences", China has entered the stage of population aging since the end of the 20th century. Although the aging time of our country is a little later than that of the western developed countries, but the rate is very fast, it takes about 20 years to reach the aging process of 50-80 years in the western developed countries, and the pace of the aging has been irresistible. Anhui Province, a large population province in East China, is an important part of the Yangtze River Delta Economic Zone. Its population structure undoubtedly has a great influence on the population structure of our country. At present, Anhui Province is in the critical period of transformation and development. Therefore, we have reason to believe that it is particularly important to study and analyze the influencing factors and regional differences of population aging in Anhui Province. This paper first analyzes the current situation and causes of population aging in Anhui Province, and makes a change trend map using the data of dependency ratio in Anhui Province from 2000 to 2015. The results show that the dependency ratio of the elderly increases in a straight line, based on the data of the aging coefficient in 2015. The preliminary results show that there are regional differences in the degree of aging in 16 cities in this province. Based on the data of five people and six people, the proportion of the elderly population is described. The results of the circular chart show that the proportion of the population aged 80 and over has doubled in 10 years. At the same time, the aging coefficient of Anhui Province is compared with the aging situation of the whole country and the six surrounding provinces. The result shows that the aging degree of Anhui Province is more serious, ranking second in the periphery. Secondly, from the point of view of population structure, economic development, social development and educational development, six explanatory variables are selected to measure the degree of aging. Using the panel data of 16 cities in Anhui Province from 2006 to 2015, this paper makes an empirical analysis on the influencing factors of aging. First of all, through the Hausmann (Hausman) test in econometrics, the consistent fixed effect model is obtained. Eviews software is used to operate the model in two different ways: the first is when the cross-section coefficient of the panel data is the same in 16 prefectures and the second is when the cross-section coefficient of the panel data of 16 prefectures and cities is different. The results showed that in the first case, the mortality rate, the number of health technicians per 10,000 population, was not significant; in the second case, there were differences among the cities. For more details, see Chapter III below. Finally, the second focus of this paper is the empirical analysis of the regional difference of population aging in Anhui Province. Firstly, using the data of 4 related indexes of 16 cities in 2015, using the method of K-means to carry on the Q cluster analysis to the sample, using the SPSS software to obtain the initial classification barycenter table, the final classification barycenter table, the variance analysis table and so on. Static comparative analysis of classification results. Secondly, selecting the relevant index data of 16 prefecture-level cities in Anhui Province in 2010, using the cluster analysis of SPSS software to analyze the internal changes of population aging in Anhui Province during the period from the 12th to the 13th Five-Year Plan. Thus quantitatively grasp the changes of population aging in each prefectural city of Anhui Province. The results showed that in 2015, the number of four types of cities was 3, 5, 6 and 2, respectively, and in 2010, the number of severe, medium, mild and mild four types of cities was 2, 10, 3, 1, respectively. The overall standard of classification is improved, and the aging changes of each city in five years are analyzed vertically, which is helpful to take scientific measures according to local conditions and to deal with the problem of population aging. It can be seen from this that the problem of population aging in Anhui Province has become increasingly prominent and has become an urgent problem to be solved in this province. It is of great significance for the sustainable development of Anhui Province to do a good job of scientific and reasonable measures to deal with the problem of aging. Combined with empirical analysis, this paper gives some countermeasures and suggestions.
【学位授予单位】：安徽大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：C924.2

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