Digitalization of industries and labor mobility in China

IF 5.2 1区经济学 Q1 ECONOMICS

中国经济评论 Pub Date : 2024-08-02 DOI:10.1016/j.chieco.2024.102248

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引用次数: 0

Abstract

The paper utilizes data from the China Family Panel Studies (2014–2018) and China's Input-Output Table to investigate how digital development affects labor mobility decisions at industry level. Our findings demonstrate that the increased levels of digitalization, both in manufacturing and services dimensions, significantly boost the likelihood of labor mobility across industries. This relationship remains valid even after considering endogeneity issues. Mechanism analysis shows that digitalization affects the cross-industry mobility decision of workers by affecting the quality of skill matching, income level, and occupational prestige. The heterogeneous results show that the impact of digital development on industry mobility decisions in the overall and manufacturing dimensions exists in the labor force in economically underdeveloped regions, the labor force engaged in consumer services, and entrepreneurs. The development of digitalization in the services dimension mainly has a strong industry crowding-out effect on the workers from economically developed regions, the workers engaged in non-productive service industries, and the workers with employment security.

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中国的产业数字化与劳动力流动

本文利用《中国家庭面板研究》（2014-2018 年）和《中国投入产出表》的数据，研究了数字化发展如何影响行业层面的劳动力流动决策。我们的研究结果表明，无论是在制造业还是服务业层面，数字化水平的提高都会显著提高劳动力跨行业流动的可能性。即使考虑到内生性问题，这种关系依然有效。机制分析表明，数字化通过影响技能匹配的质量、收入水平和职业声望来影响工人的跨行业流动决策。异质性结果显示，数字化发展在整体和制造业维度上对行业流动决策的影响存在于经济欠发达地区的劳动力、从事消费服务的劳动力和企业家。服务业维度的数字化发展主要对经济发达地区的劳动力、从事非生产性服务业的劳动力以及有就业保障的劳动力产生了强烈的行业挤出效应。

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来源期刊

中国经济评论 ECONOMICS-

CiteScore

10.60

自引率

4.40%

发文量

380

期刊介绍： The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.