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上海大学学报(社会科学版) ›› 2023, Vol. 40 ›› Issue (6): 91-106.

• • 上一篇    

数字经济发展对收入差距的影响 ——基于技能偏向型技术进步视角

  

  1. 上海大学 经济学院
  • 收稿日期:2023-01-02 出版日期:2023-11-15 发布日期:2023-11-09
  • 作者简介:何树全（1972- ），男，湖南江永县人。上海大学经济学院教授，博士生导师。研究方向：技 术发展与全球价值链产业链、数字经济与贸易、世界经济和国际贸易理论、区域国别经济。 陈京（1998- ），女，湖北孝感人。上海大学经济学院硕士研究生。研究方向：世界经济。
  • 基金资助:
    国家社会科学基金重大项目（20&ZD140）（23ZDA032）

The Influence of the Development of Digital Economy on Income Gap —From the Perspective of Skill-biased Technological Advancement

  1. School of Economics, Shanghai University
  • Received:2023-01-02 Online:2023-11-15 Published:2023-11-09

摘要： 数字经济成为中国经济发展的加速器，它能否缩小收入差距是中国发展中需要关 注的问题。如果数字技术进步具有技能偏向性，数字经济的发展也会存在技能偏向性特征， 从而影响收入差距。基于《企研数据：数字经济产业专题数据库》构建的城市数字经济综合指 标和中国劳动力动态调查（CLDS）个体微观数据，采用再中心化影响函数（RIF）分位回归模型 研究数字经济对收入差距的影响，可以发现：（1）中国数字经济发展总体上扩大了收入差距； （2）数字经济通过技能偏向型技术进步提高中高技能工人技能溢价而扩大收入差距；（3）数字 经济在低收入人群中的技能偏向型特征不明显，甚至存在偏向低技能劳动力的倾向；（4）数字 经济对女性、农村和资本密集型行业收入差距影响较大，技能偏向性特征更加明显。

关键词: 数字经济, 技能偏向型技术进步, 收入差距, RIF回归

Abstract: Digital economy has become the“accelerator”of China’s economic development. Whether or not it can narrow income gap is an issue that calls for attention in China’s development. If the advance of digital technology is skill-biased, then the development of digital economy will have the same characteristic, thus affecting income gap. The quantile regression model of Recentered Influence Functions (RIF) is employed here to study the influence of digital economy on income gap. The research data comes from the comprehensive indicators of urban digital economy based on Enterprise Research Data: Special Database of Digital Economy Sector and the individual microscopic data of China Labor-force Dynamic Survey (CLDS). The findings are as follows: (1) The development of digital economy in China has widened income gap on the whole. (2) The digital economy increases the skill premium of middle and high skilled workers and widens the income gap through skill-biased technological progress. (3) The skill-biased feature of digital economy does not have a significant influence on the low-income group, if not in favor of the low-skilled labor force. (4) The digital economy has a greater influence on women, rural residents and people engaged in capital-intensive sectors with a more obvious skill-biased tendency.

Key words: digital economy, skill-biased technological progress, income gap, RIF regression

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