摘要
基于中国家庭追踪调查数据,本文考察了互联网使用对城乡家庭消费差距的影响及其作用机理。研究发现,工具变量分位数回归结果显示,互联网使用能够显著缩小城乡家庭消费差距,且这一作用在高消费群体中更为明显;MM分解的结果显示,城乡家庭消费差距主要源于家庭互联网使用等变量本身的特征差异,城乡家庭间的回报差异存在,但主要影响低分位点处的消费差距;RIF单变量分解的结果显示,随着分位数水平的提高,总特征差异效应和总回报差异效应对城乡消费差距的解释力都逐渐增强,尤以特征差异效应对城乡消费差距的贡献度最大。进一步的机制检验显示,收入效应、信息渠道效应、社会资本效应和非正规金融效应是互联网使用影响城乡消费差距的主要渠道。
Based on the CFPS2014 data,this paper examines the impact of Internet use on the consumption gap between urban and rural households and its mechanism.Instrumental variable quantile regression shows that the Internet can significantly reduce the consumption gap between urban and rural households,and this effect is more pronounced in high-consumption groups;the results of MM decomposition show that the consumption gap between urban and rural households is mainly due to the differences in the characteristics of household Internet use and other variables,and the return difference between households exists,but it mainly affects the consumption gap at the low quantile point.The results of RIF univariate decomposition show that as the quantile level increases,the total characteristic difference effect and the total return difference effect have an impact on the urban-rural consumption gap.The explanatory power is gradually increasing,especially the characteristic difference effect has the greatest contribution to the urban-rural consumption gap.Further inspection of mechanism testing shows that income effects,information channel effects,social capital effects,and informal financial effects are the main channels through which Internet use affects the urban-rural consumption gap.
作者
冯大威
高梦桃
周利
FENG Dawei;GAO Mengtao;ZHOU Li(Jiangxi University of Finance and Economics,Nanchang,330013;Shandong University,Jinan,250100;Guangdong University of Foreign Studies,Guangzhou,510006)
出处
《中国经济问题》
CSSCI
北大核心
2022年第3期98-114,共17页
China Economic Studies
基金
国家自然科学基金面上项目(72073081)
国家社会科学基金重大项目(20&ZD169)
国家社会科学基金重大项目(20ZDA047)的资助
国家社会科学基金重大项目(21&ZD113)的资助。
关键词
互联网
城乡消费差距
分位数估计
MM分解
RIF分解
internet
urban-rural consumption gap
quantile estimate
MM decomposition
RIF decomposition