管理评论 ›› 2023, Vol. 35 ›› Issue (10): 10-21.

• 经济与金融管理 • 上一篇    下一篇

数据要素利用、智能技术进步与内生增长

刘征驰, 陈文武, 魏思超   

  1. 湖南大学经济与贸易学院, 长沙 410079
  • 收稿日期:2022-08-23 出版日期:2023-10-28 发布日期:2023-11-27
  • 作者简介:刘征驰,湖南大学经济与贸易学院教授,博士生导师,博士;陈文武(通讯作者),湖南大学经济与贸易学院博士研究生;魏思超,湖南大学经济与贸易学院副教授,硕士生导师,博士。
  • 基金资助:
    国家自然科学基金面上项目(72071073);教育部人文社会科学基金青年项目(21YJC790123);湖南省自然科学基金面上项目(2020JJ4226);湖南省研究生科研创新项目(CX20210394)。

Data Factor Utilization, Intelligence Technology Progress and Endogenous Growth

Liu Zhengchi, Chen Wenwu, Wei Sichao   

  1. School of Economics & Trade, Hunan University, Changsha 410079
  • Received:2022-08-23 Online:2023-10-28 Published:2023-11-27

摘要: 数智化转型是驱动新时代经济持续增长的核心动力。已有文献讨论了数据要素或智能技术影响经济增长的作用机制,但忽略了数据要素利用推动智能技术进步的关键作用。基于此,本文将数据要素利用与智能技术进步同时纳入内生增长模型框架,以探究其对经济增长的联合影响。研究发现,数据要素利用通过促进智能技术进步能够推动经济持续增长。进一步分析发现,模型存在两种“制约效应”和一个“增长陷阱”。数据要素利用对长期经济增长的促进作用受到消费者隐私侵犯厌恶的制约;智能技术进步对长期经济增长的促进作用受到人口增长的制约。数智化转型时期先后的差异可能导致长期经济增长率的差异,后转型经济体陷入增长率持续低于先转型经济体的增长陷阱。本研究不仅为理解数字经济时代的宏观增长机制提供了理论参考,也为当前全球主要经济体在大数据和人工智能等技术与产业领域的激烈竞争提供了理论阐释。

关键词: 数据要素, 人工智能, 内生增长, 增长陷阱, 数智化转型

Abstract: Data-intelligence transformation is a core driving force for the sustained economic growth in the new era. The existing literature has discussed the mechanisms of how data factor or intelligent technology affect economic growth respectively, but ignored the key role of data factor in promoting the progress of intelligent technology. Based on this, this paper integrates the utilization of data factors and the progress of intelligent technology into the endogenous growth model framework to explore their joint impact on economic growth. It is found that data factor utilization can promote sustained economic growth by promoting the progress of intelligent technology. Further analysis shows that the model economy has two “restricting effects” and a “growth trap”. The promoting effect of data factor utilization on long-term economic growth is restricted by consumers’ aversion to privacy infringement. The contribution of intelligent technology progress to long-term economic growth is restricted by population growth. The difference in the sequence of digitalized transition may lead to diverged long-term economic growth rate, and the economy with a late transition may fall into a growth trap where the growth rate is continuously lower than that of the economy with an early transition. This study not only provides a theoretical reference for understanding the macro growth mechanism in the era of digital economy, but also provides a theoretical explanation for the fierce competition among major economies in the technological and industrial fields such as big data and artificial intelligence.

Key words: data factor, artificial intelligence, endogenous growth, growth trap, data-intelligence transformation