人工智能、劳动力任务类型与城市规模工资溢价

人工智能、劳动力任务类型与城市规模工资溢价

AI, Labor Type and Urban Wage Premium

《财经研究》2023年49卷第12期 页码：62-76 online：2023年12月3日

作者

中：李静1,2 , 闫曰奇2 , 潘丽群3

英：Li Jing1,2, Yan Yueqi2, Pan Liqun3

作者单位：1. 厦门大学 宏观经济研究中心，福建 厦门 361005; 2. 新疆财经大学 经济学院，新疆 乌鲁木齐 841100; 3. 广州大学 经济与统计学院，广东 广州 510006

摘要及关键词

摘要：人工智能是任务偏向型技术，其广泛应用可能会扩大工资差距，但对城市规模工资溢价影响需深入研究。文章利用中国劳动力动态调查微观数据和人工智能应用数据，实证探讨在人工智能冲击下非常规和常规劳动力所获得的城市规模工资溢价及其机制。研究发现：相比于常规劳动力，人工智能使得非常规劳动力得到了更高的城市规模工资溢价，该结论在工具变量法、重新划分劳动力类型和扩展样本的检验下依然稳健。机制分析表明：相对于常规劳动力，具有任务偏向型属性的人工智能应用能够强化非常规劳动力在城市集聚经济下的学习、匹配效应，从而提高其城市规模工资溢价。进一步研究表明，不同任务类型劳动力获得城市规模工资溢价会因所处的区位、个体特征而呈现一定的差异性。文章为区域协调发展政策和共同富裕政策的制定提供了理论依据与经验支撑。

关键词：人工智能；非常规和常规工作；城市规模工资溢价

Summary: With the vigorous development of a new round of global technological revolutions, artificial intelligence (AI) will profoundly change the income distribution structure and regional economic development pattern. How to actively respond to the adverse impact of AI technology on income inequality and deeply explore its impact mechanism is a major theoretical research challenge to achieve the goal of common prosperity. This paper first reviews the literature on routine-biased technological change of AI, the differences in urban wage premium, and their impact mechanisms. Then, it proposes two hypotheses and empirically tests them using CLDS, IFR, and prefecture-level city statistical data. The conclusions are that: First, there are differences in urban wage premium caused by AI for non-routine and routine labor. Second, for non-routine labor, AI can strengthen learning and matching mechanisms to promote the increase of urban wage premium. Third, the urban wage premium for non-routine labor will exhibit certain differences depending on their location: The central region is susceptible to the positive impact from AI, while the eastern and western regions are negatively affected. Moreover, there are gender and skill differences in the impact of AI on urban wage premium, with female routine labor and high-skilled routine labor susceptible to the negative impact of AI.The marginal contributions of this paper are that: First, it analyzes the heterogeneity of urban wage premium from the perspective of non-routine and routine labor, expanding the traditional perspective of gender and skill heterogeneity, and indirectly explaining the reasons for the increasing income inequality within Chinese cities to some extent. Second, taking AI as a typical technological representative, it examines the impact of AI as an exogenous technology shock on urban wage premium, expanding the scope of research on the impact of AI on income inequality. Third, it analyzes how AI interacts with the learning and matching micro mechanisms of agglomeration economies, enabling workers of different task types to obtain different urban wage premium.

Key words:AI; Non-Routine and Routine Work; Urban Wage Premium

其他信息

DOI：10.16538/j.cnki.jfe.20230917.401

收稿日期：2023-02-10

基金项目：国家社会科学基金一般项目（22JLB00346）

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