基于主成分分析和灰色聚类对我国居民收入差距分析  

Income Gap of Chinese Residents Based on Principal Component Analysis and Grey Cluster

作　　者：陈宝平 CHEN Bao-ping(Department of Computer Information and Management,NeiMongol Finance and Economics College,Hohhot 010051,China)

机构地区：[1]内蒙古财经大学计算机信息管理学院

出　　处：《数学的实践与认识》2018年第24期134-143,共10页Mathematics in Practice and Theory

基　　金：内蒙古高等学校科学研究项目(NJZZ18117)

摘　　要：针对我国各个地区工资收入不平衡的问题,选取30个地区2007-2016年19个行业的平均工资,测算各地区泰尔指数.此基础上,采用主成分分析对每个地区10年的泰尔指数降维,转化成三个主成分因子,代表原来信息量的96%.通过灰色聚类分析主成分得分矩阵,将30个地区划分为三类.结果显示基于居民收入泰尔指数对各地区的划分,基本与按地理位置划分的东部、中部、西部地区的划分一致,居民收入从东部到西部递减,具有明显的区域性、集聚性特点.结合分析结果提出相应的对策建议.On the imbalance of wage income in different regions of China,this paper industries the average wage of 30 regions from 2007 to 2016 and calculates the Thiel index in each region. Principal component analysis was conducted with the Thiel index in each region.The three principal components that reflected 96% of the original information quantity were extracted from the initial ten indices.The 30 regions are divided into three categories by grey principal which analyzed the component score matrix cluster.The results shows that the division of each region based on the Thiel index is basically consistent with the division between east and west,and the income of residents decreases from east to west with obvious regional and agglomeration characteristics.Combined with the results of the analysis,the corresponding countermeasures and suggestions are put forward.

关 键 词：泰尔指数 主成分分析法 灰色聚类分析 收入差距 

分 类 号：F126.2[经济管理—世界经济] TP311.13[自动化与计算机技术—计算机软件与理论]