数字经济对居民收入的影响效应研究——基于多层线性模型的实证分析
Research on the Impact of Digital Economy on Residents'Income——Empirical Analysis Based on Hierarchical Linear Model
宋宝琳 1王丽 2宋卓展2
作者信息
- 1. 河北大学管理学院,河北保定 071000;沧州交通学院,河北沧州 061199
- 2. 河北大学管理学院,河北保定 071000;河北大学共同富裕研究中心,河北保定 071000
- 折叠
摘要
本文基于中国家庭追踪调查微观数据和中国城市统计宏观数据,探讨数字经济与居民收入之间存在的逻辑关系,并运用多层线性模型分析数字经济对居民收入的影响.研究表明:地区数字经济水平对居民收入具有显著正向提升作用,在解决内生性问题以及一系列稳健性检验后结论依然成立;数字经济对不同特征居民的收入影响具有显著异质性,即数字经济会因居民自身特征的不同而对其收入产生不同程度的影响.机制检验结果表明,在数字经济影响居民收入中,居民受教育程度发挥了重要调节作用.结合研究结果,本文提出相关对策建议,以期将数字经济促进居民增收的作用发挥到最大,实现数字经济快速发展和居民收入水平提高的双重目标.
Abstract
Based on the micro-data of China Family Panel Studies and macro-data of China's urban statistics,this paper explores the logical relationship between the digital economy and residents'income,and analyzes the impact of the digital economy on residents'in-come by using a hierarchical linear model.The study shows the followings.The level of regional digital economy has a significant positive enhancement effect on residents'income,and the conclusion still holds after solving the endogeneity problem as well as a series of ro-bustness tests.The impact of the digital economy on the income of residents with different characteristics is significantly heterogeneous,that is,the digital economy will affect the income of residents to different degrees due to the differences in their own characteristics.The mechanism test shows that in the digital economy affecting residents'income,the education level of residents plays an important modera-ting role.Combined with the results of the study,this paper puts forward relevant countermeasure suggestions,with a view to maximi-zing the role of the digital economy in promoting residents'income,and realizing the dual goals of rapid development of the digital econ-omy and improvement of residents'income level.
关键词
数字经济/居民收入/教育水平/多层线性模型Key words
Digital economy/Resident income/Education level/Hierarchical linear model引用本文复制引用
基金项目
河北省"三三三人才工程"资助项目(2023)(C20231132)
河北省教育厅基础研究重点培育项目(JCZX2023022)
河北大学雄安新区专项研究项目(2023HXA013)
出版年
2024
NETL
NSTL
万方数据