人口研究 ›› 2020, Vol. 44 ›› Issue (5): 60-79.

• 老龄问题研究 • 上一篇    下一篇

中国老年人消费结构及消费升级的影响因素

杨凡1,潘越2,黄映娇3   

  1. 杨凡1,中国人民大学人口与发展研究中心;潘越2、黄映娇3,中国人民大学社会与人口学院。
  • 出版日期:2020-09-29 发布日期:2020-10-15
  • 作者简介:杨凡,中国人民大学人口与发展研究中心副教授;潘越、黄映娇,中国人民大学社会与人口学院硕士研究生。
  • 基金资助:
    本研究得到国家自然科学基金重大项目“特征、规律与前景——老龄社会的人口学基础研究”(71490731) 、国家社会科学基金重点项目“中国妇女生育模式变动及其影响因素研究”(18ARK003)以及国家社会科学基金青年项目“新健康老龄化视角下的老年体育服务利用研究”(16CTY015)的资助。

Chinese Older Adults' Consumption Expenditure Structure and Its Determinants

Yang Fan1,Pan Yue2,Huang Yingjiao3   

  1. Yang Fan1,Center for Population and Development Studies,Renmin University of China; Pan Yue2 and Huang Yingjiao3,School of Sociology and Population Studies,Renmin University of China.
  • Online:2020-09-29 Published:2020-10-15
  • About author:Yang Fan is Associate Professor,Center for Population and Development Studies,Renmin University of China; Pan Yue and Huang Yingjiao are Master Students,School of Sociology and Population Studies,Renmin University of China.

摘要: 随着中国进入人口老龄化加速发展的新阶段,老年人在消费群体中的比重快速增加,成为日益重要的消费人群。利用中国老年社会追踪调查(CLASS)数据,以科特勒消费行为模型为分析框架,运用Kmeans聚类分析方法对中国老年人消费结构的类型进行划分和描述,采用Logistic回归模型对影响老年人消费结构升级的因素进行研究,并考虑不同群体的异质性。结果表明,老年人的消费类型趋向多样化,并没有表现出阻碍消费升级的情况;老年人要实现从基本型向发展型消费结构的升级,受到需求要素的驱动和资源要素的影响,还需要社会网络、技术等信息渠道要素的支持;影响老年人消费结构升级的因素存在城乡、年龄和收入水平的异质性,促进老年人消费升级需要分类精准施策。

关键词: 老年人, 消费结构, 聚类分析, Logistic回归

Abstract: In the era of accelerated population aging, the proportion of older adults in the consumer group also increases tremendously. Based on data from China Longitudinal Aging Social Survey, this article employs the analytical framework of Kotler's consumption behavior model and K-means clustering analysis method to categorize different types of consumption structure for Chinese older adults. Logistic regression method is conducted to analyze the factors affecting the consumption structure upgrading. The results show that the consumption patterns of the older adults are diverse, and their upgrades have not been hindered. The transformation from the basic to the developmental consumption structure is driven by demand factors and restricted by resource factors, and also supported by social networks, technology, and other external factors. These factors have heterogeneous impacts on older adults from urban/rural areas at different ages and income levels. These differences call for differentiated policies targeting on different subgroups.

Keywords: Older Adults, Types of Consumption Structure, Cluster Analysis, Logistic Regression