北京邮电大学学报(社会科学版) ›› 2014, Vol. 16 ›› Issue (6): 71-80.

• • 上一篇    下一篇

“以房养老”模式的影响因素研究——基于我国20个城市经济指标分析

  

  1. 1安徽财经大学 金融学院, 安徽 蚌埠233030;2上海财经大学 国际工商管理学院,上海200433
  • 收稿日期:2014-07-25 出版日期:2014-12-30 发布日期:2023-03-27
  • 基金资助:
    安徽财经大学科学研究基金项目(ACKY1444);安徽省省级大学生创新创业计划项目(AH201310378470);安徽财经大学资产价格与稳定特区基金项目(ACZCJGYJRWD20142D11)

Influencing Factors of“Reverse Mortgage”Mode ——Based on Economic Indicators of 20 Cities in China

  1. 1School of Finance, Anhui University of Finance and Economics, Bengbu 233030, China; 2 School of International Business Administration, Shanghai University of Finance and Economics, Shanghai 200433, China
  • Received:2014-07-25 Online:2014-12-30 Published:2023-03-27

摘要: 利用SPSS对我国20个城市的经济发展和人口组成两大指标,即“以房养老”影响的四个因素(经济状况、养老设施总量、受教育程度和老龄化水平)进行主成分分析,提出了“以房养老”模式的试点应该在北京和上海两个城市率先开展。并且使用聚类分析法将20个城市划分为5类,并给出“以房养老”模式的试点城市的顺序,分析结果得出,“以房养老”在需求上存在明显的地域差异,传统观念和养老基础设施对“以房养老”的开展有重要影响。

关键词: 老龄化, 以房养老, 主成分分析, 聚类分析

Abstract: By using SPSS to make principal component analysis of two indicators of economic development and demographic composition, that is, four influencing factors of “reverse mortgage” (economic conditions, the total pension facilities, education and aging level) of 20 cities in our country, it is proposed that “reverse mortgage” pilot mode should be implemented first in Beijing and Shanghai Also, cluster analysis is used to divide the 20 cities into five categories, and “reverse mortgage” pilot cities sequential mode is given The results show that “reverse mortgage” has obvious geographical differences in demand, and traditional ideas and pension infrastructure have significant influence on “reverse mortgage”

Key words: aging, reverse mortgage, principal component analysis, cluster analysis

中图分类号: