"Does artificial intelligence affect the pattern of skill demand? Evidence from Chinese manufacturing firms"

by Xie, Mengmeng; Ding, Lin; Xia, Yan; Guo, Jianfeng; Pan, Jiaofeng; Wang, Huijuan (2021)

Abstract

In view of the recent penetration of artificial intelligence (AI) into production activities, we undertake a quasi-natural experiment to identify its impact on employment at different skill levels using micro-enterprise data from Chinese manufacturing during 2011–2017. Employing a robust difference-in-differences method with propensity score matching, we investigate the heterogeneous impact of AI adoption upon different skills across three dimensions — geographical regions, enterprise types, and the length of time since the adoption of AI. We find that AI reduces the relative demand for low-skilled labor across all regions in China, while increasing the relative demand for high-skilled labor only in the eastern region. These differential impacts of AI upon relative demand for different skills reflect firm-level technological intensity. Results also show that the longer the duration of AI use, the greater is the impact upon the relative demand for high-skilled labor.

Key Passage

In the long run, the application of AI is an inevitable trend which willimprove the firm-level labor skills. Comparing with some developed countries where AI has no significant impact on high-skilled employment, the developing countries represented by China should pay more attention to the adverse effects brought by the polarization of employment. Since the damaging effects of AI on the employment of low-skilled workers first occur in high-tech enterprises, which are mostly concentrated in the eastern region of China, policy-makers should focusmore on the employment of low-skilled labor of high-tech enterprises inthe eastern region. Policies aimed at improving the employment of largenumbers of low-skilled workers in the central and western regions byshifting manufacturing from the east to the two regions have failedbecause of the adoption of AI. Training low-skilled manufacturingworkers nationwide may be one of the most effective measures to improve the employment of low-skilled workers.  (p.304)

Keywords

Artificial Intelligence, Skill Demand, Heterogeneity Analysis, Robust Did, China Manufacturing

Themes

Skills, Automation

Links to Reference

• https://www.sciencedirect.com/science/article/pii/S0264999321000171
• http://dx.doi.org/10.1016/j.econmod.2021.01.009
• https://www.sciencedirect.com/science/article/pii/S0264999321000171?casa_token=MKeibz3PiV0AAAAA:Y8VM7xnBhp69tG_L5kjgSp_w7Veoq860LQ8I_5tlaxTNK-Bkx9dxTZT_sjmJ13m2ZSLaYxX2

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