This paper empirically investigates the impact of industrial robot use on China’s labor market using data from 13 segments of manufacturing industry between 2006 and 2016. According to the findings, the use of industrial robots has a displacement effect on labor demand in manufacturing industry. The specific performance is that for every 1% increase in industrial robot stock, labor demand falls by 1.8%. After endogenous processing and a robustness test, this conclusion remains valid. This paper also discusses the effects of industrial robots across industries and genders. According to the results, industrial robot applications have a more pronounced displacement effect in low-skilled manufacturing than in high-skilled manufacturing. In comparison to female workers, industrial robot applications are more likely to decrease the demand for male workers. Moreover, this paper indicates that the displacement effect is significantly influenced by labor costs. Finally, we make appropriate policy recommendations for the labor market’s employment stability based on the findings.
C. Luo and L. Xu, Online-to-offline on the railway: Optimization of on-demand meal ordering on high-speed railway, Transp. Res. C, vol. 152, p. 104143, 2023.
C. Luo, L. Shen, and A. Xu, Modelling and estimation of system reliability under dynamic operating environments and lifetime ordering constraints, Reliab. Eng. Syst. Saf., vol. 218, p. 108136, 2022.
X. Zhou, X. Yang, J. Ma, and K. I. K. Wang, Energy-efficient smart routing based on link correlation mining for wireless edge computing in IoT, IEEE Internet Things J., vol. 9, no. 16, pp. 14988–14997, 2022.
X. Zhou, W. Liang, K. Yan, W. Li, K. I. K. Wang, J. Ma, and Q. Jin, Edge-enabled two-stage scheduling based on deep reinforcement learning for Internet of everything, IEEE Internet Things J., vol. 10, no. 4, pp. 3295–3304, 2022.
X. Xu, J. Gu, H. Yan, W. Liu, L. Qi, and X. Zhou, Reputation-aware supplier assessment for blockchain-enabled supply chain in industry 4.0, IEEE Trans. Ind. Inform., vol. 19, no. 4, pp. 5485–5494, 2023.
M. Han, Q. Han, and L. Xia, The impact of industrial robot application on manufacturing employment: An empirical study sased on the data of prefecture level cities in China, (in Chinese), Reform, no. 3, pp. 22–39, 2020.
X. Yan, B. Zhu, and C. Ma, Employment under robot impact: Evidence from China manufacturing, (in Chinese), Stat. Res., vol. 37, no. 1, pp. 74–87, 2020.
L. Li, X. Wang, and Q. Bao, The employment effect of robots: Mechanism and evidence from China, (in Chinese), Manag. World, vol. 37, no. 9, pp. 124–139, 2021.
D. H. Autor, F. Levy, and R. J. Murnane, The skill content of recent technological change: An empirical exploration, Q. J. Econ., vol. 118, no. 4, pp. 1279–1333, 2003.
G. Michaels, A. Natraj, and J. Van Reenen, Has ICT polarized skill demand? Evidence from eleven countries over twenty-five years, Rev. Econ. Stat., vol. 96, no. 1, pp. 60–77, 2014.
M. Han, and G. Qiao, The impact of industrial robot usage on employment in China’s manufacturing industry: empirical evidence from the industry level, (in Chinese), Mod. Manag., vol. 40, no. 2, pp. 88–92, 2020.
Y. Wang, and W. Dong, How the rise of robots has affected China’s labor market: Evidence from China’s listed manufacturing firms, (in Chinese), Econ. Res. J., vol. 55, no. 10, pp. 159–175, 2020.
S. Zhou and B. Chen, Employment in industry and robots: A view from the sub-task model, (in Chinese), Stat. Decis., vol. 38, no. 23, pp. 85–89, 2022.
This work was supported by the National Social Science Fund of China (No. 21CGL038), the Ministry of Education Humanities and Social Science Project (No. 22JJD790073), and the Scientific Research Foundation for Scholars of Hangzhou Normal University (No. RWSK 20201028).
This work is available under the CC BY-NC-ND 3.0 IGO license:https://creativecommons.org/licenses/by-nc-nd/3.0/igo/