人口研究 ›› 2015, Vol. 39 ›› Issue (3): 3-17.

• 论文 •    下一篇

中国城乡居民年龄别消费模式量化与分析

朱勤1魏涛远2   

  1. 1 复旦大学社会发展与公共政策学院、人口与发展政策研究中心,上海 200433;2 挪威奥斯陆国际气候与环境研究中心(CICERO)
  • 出版日期:2015-05-29 发布日期:2015-08-27
  • 作者简介:1 复旦大学社会发展与公共政策学院、人口与发展政策研究中心副教授;2 挪威奥斯陆国际气候与环境研究中心(CICERO)高级研究员

Quantitative Analysis of Age Pattern of Household Consumption in Urban and Rural China

Zhu Qin1,Wei Taoyuan2   

  1. 1 School of Social Development and Public Policy, Fudan University, Shanghai 200433; 2  Center for International Climate and Environmental Research – Oslo (CICERO), Norway
  • Online:2015-05-29 Published:2015-08-27
  • About author:1 Associate Professor, School of Social Development and Public Policy, Fudan University; 2 Senior Researcher, Center for International Climate and Environmental Research – Oslo (CICERO), Norway
  • Supported by:

    国家自然科学基金重大课题(编号71490734),教育部人文社科基金一般项目(编号11YJCZH260)、中央高校基本科研业务费专项资金

摘要: 本文采用2010年中国家庭追踪调查(CFPS)数据量化分析年龄别居民消费模式。针对同类研究只采用年龄变量作为自变量的不足,在经典的需求和消费函数基础上扩展年龄变量构建计量模型,获得了更好的解释力和准确性。基于计量分析结果刻画了分年龄、性别的中国城乡居民消费模式,并进行城乡比较。研究发现,居民家庭消费生命周期中存在30~34岁及45~49岁两个消费高峰;城乡居民消费差距最大的是高龄老人;农村老人在高龄阶段的医疗保健消费明显下降;农村中年妇女的医疗保健支出低于男性。文章认为,应从政策层面有针对性地加大对特定年龄性别人群的扶助力度;同时,未来产业规划应充分考虑人口结构变动因素的影响。

关键词: 家庭消费, 年龄别消费模式, 消费函数, 家庭调查

Abstract: Based on household survey data from China Family Panel Study (CFPS) in 2010, this paper econometrically quantifies and estimates household consumption pattern by age and gender in both urban and rural China. Unlike previous studies in which only age factors are considered to be independent variables, we expand classical demand and consumption functions by including age variables in our econometric model to obtain stronger explanatory power and higher accuracy. Our results show that people aged 30-34 and 45-49 have the highest household consumption in their lifecycle; people aged 80 and above are the group with the largest urban-rural consumption disparity; rural residents reduce their expenditure on health care considerably at their very advanced age; rural middle-age women expend less than men on health care. Thus it is necessary to strengthen policy support to a certain groups of residents. Policy makers should pay more attention to population dynamics when they make decisions on adjusting industrial structure and planning public resources allocation.

Keywords: Household Consumption, Age-specific Consumption Pattern, Consumption Function, Household Survey