中国人口分布及影响因素分析

发布时间：2018-04-23 12:37

本文选题：人口分布 + 人口密度　；参考：《吉林大学》2012年硕士论文

【摘要】：我国有13多亿人口，主要分布在东南沿海省份，这种情况是自然、社会和经济等因素长期作用的结果。随着各地区经济的发展和大规模人口的流动，截止到2010年，我国的人口分布状态仍然是东部地区人口占全国总人口比重最大，其次是中部和西部地区。我国人口分布还是呈现着稳定性和不平衡性的特点，目前来说人口分布的格局还是比较合理的。影响我国人口分布的因素是哪些，影响有多大，研究我国的人口分布及其影响因素，对于掌握我国人口分布格局、人口走势，从而制定影响人口分布的有关政策，都具有重要的现实意义。本文以我国31个省市区为研究单元，结合1982年中国统计年鉴、1991年中国统计年鉴、2000年第五次全国人口普查资料和2011年中国统计年鉴资料，总结了从民国初期到2010年我国的人口分布状况。并运用SPSS统计软件中的单因素相关分析、主成分分析、多元线性回归分析方法，以人口密度为反映人口分布的因变量，以自然、社会和经济因素中共31个指标为自变量，对影响人口分布的因素进行定量分析，其中单因素相关分析主要观察各因素与人口密度的相关系数的大小，从而判断哪类因素与人口分布的关系最大。主成分分析主要是通过降维的方式，将原本31个指标降为5个因子，既方便计算又避免了由于指标之间存在高度的共线性而给结果带来的影响。采用多元线性回归主要是通过计算得到相关指标与人口密度的回归方程，分析主要指标对人口密度影响的大小。分析结果表明，在自然因素、社会因素和经济因素中，，经济规模和分配、人均占有量和产业结构、文化生活质量、劳动参与情况、农业发展水平对人口密度有较大的影响，特别是人均地区生产总值和城镇单位就业人员平均工资对人口密度的正向影响最大。最后，总结以上分析结果，预测未来随着各地区经济的不断发展，特别是东北地区老工业基地的崛起和西部地区大开发战略各项目的投产，会使当地经济实力一跃而起，吸纳人口的数量也会大幅度的增加，届时我国的人口分布格局会有比较大的改观。
[Abstract]:There are more than 1.3 billion people in China, mainly distributed in the southeast coastal provinces. This situation is the result of the long-term action of natural, social and economic factors. With the development of regional economy and large-scale population flow, by 2010, the distribution of population in China is still the largest proportion of the population in the eastern region, followed by the central and western regions. China's population distribution still presents the characteristics of stability and imbalance, the pattern of population distribution is reasonable. What are the factors that affect the population distribution in our country and how big the impact is? to study the population distribution in China and its influencing factors, to grasp the pattern and trend of population distribution in our country, and to formulate relevant policies that affect the population distribution, Are of great practical significance. In this paper, 31 provinces and municipalities in China are taken as the research units, combining the data of the 1982 China Statistical Yearbook, the 1991 China Statistical Yearbook, the 2000 Fifth National population Census and the 2011 China Statistical Yearbook. This paper summarizes the population distribution from the beginning of the Republic of China to 2010. Using the single factor correlation analysis, principal component analysis and multivariate linear regression analysis method of SPSS statistical software, taking population density as dependent variable to reflect population distribution, taking 31 indexes of natural, social and economic factors as independent variables. The factors influencing the population distribution were analyzed quantitatively. The single factor correlation analysis mainly observed the correlation coefficient between each factor and the population density, so as to determine which factors had the greatest relationship with the population distribution. Principal component analysis (PCA) reduces the original 31 indexes to 5 factors by dimensionality reduction, which is not only easy to calculate but also avoids the influence on the results due to the existence of a high degree of collinearity among the indicators. The regression equation of correlation index and population density is obtained by multivariate linear regression, and the influence of main index on population density is analyzed. The results show that, among the natural, social and economic factors, economic scale and distribution, per capita possession and industrial structure, quality of cultural life, labor participation, and the level of agricultural development have great influence on population density. In particular, the per capita regional GDP and the average wage per person employed in urban areas have the greatest positive impact on population density. Finally, by summing up the above analysis results, it is predicted that with the continuous development of the regional economy in the future, especially the rise of the old industrial base in the Northeast region and the production of various projects in the strategy of the great development of the western region, the local economic strength will spring up in a leap forward. The number of absorbed population will also increase by a large margin, and the pattern of population distribution in China will be greatly improved.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：C922

【引证文献】