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Automation impacts on China’s polarized job market

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Abstract

When facing automation threats, a large Chinese city worker might not be as lucky as a worker in a large US city. Empirical studies found that large US cities exhibit resilience to automation impacts because of the increased occupational and skill specialization. However, in this study, we observe polarized responses in large Chinese cities to automation impacts. The polarization might be attributed to the elaborate master planning of the central government. Cities are assigned with different industrial goals to achieve globally optimal economic success and a fast-growing economy. By dividing Chinese cities into two groups based on their administrative levels and premium resources allocated by the central government, we find that Chinese cities follow two distinct industrial development trajectories: one trajectory involves government support leading to a diversified industrial structure and, thus, a diversified job market, and in the other trajectory an absence of government support leads to specialty cities and, therefore, a specialized job market. By estimating the impact of automation on a polarized job market, we observe a Simpson's paradox: overall, there is not a statistically significant relationship between city size and resilience to automation, but when we disaggregate by the level of job diversity, we find larger cities with a diversified job market exhibit greater resilience, while larger cities with specialized job markets are more susceptible. These findings inform policymakers to deploy appropriate policies to mitigate polarized automation impacts.

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Acknowledgements

We thank Esteban Moro (Universidad Carlos III de Madrid) and Lijun Sun (McGill University) for helpful suggestions and comments on this study. We also thank the anonymous reviewers for their valuable suggestions.

Funding

This research was funded by National Natural Science Foundation of China, Grant no [197010884].

Author information

Author notes

  1. HaohuiCaron Chen and Xun Li contributed equally to this work.

Authors and Affiliations

  1. Data61, Commonwealth Scientific and Industrial Research Organization (CSIRO), Canberra, Australia

    Haohui Caron Chen

  2. Faculty of Information Technology, Monash University, Clayton, Australia

    Haohui Caron Chen

  3. Sun Yat-Sen University, Guangzhou, China

    Xun Li, Xiaozhen Qin & Weipan Xu

  4. China Regional Coordinated Development and Rural Construction Institute, Sun Yat-Sen University, Guangzhou, China

    Xun Li, Xiaozhen Qin & Weipan Xu

  5. Department of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, USA

    Morgan Frank

  6. Media Laboratory, Massachusetts Institute of Technology, Cambridge, USA

    Morgan Frank

  7. Digital Economy Lab, Stanford Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA, USA

    Morgan Frank

  8. Center for Humans and Machines, Max-Planck Institute for Human Development, Berlin, Germany

    Manuel Cebrian & Iyad Rahwan

Authors
  1. Haohui Caron Chen
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  2. Xun Li
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  4. Xiaozhen Qin
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Contributions

X.L., H.C., M.C. and I.R. conceived of the research question. X.L., P.X. and X.Q. processed the Census data. X.L., H.C., M.F. and M.C. interpreted the result. X.L., H.C., M.F., X.Q., M.C. and I.R drafted the manuscript and compiled supplementary information. All authors edited the manuscript and supplementary information and aided in concept development.

Corresponding authors

Correspondence to Haohui Caron Chen, Xun Li or Iyad Rahwan.

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Chen, H.C., Li, X., Frank, M. et al. Automation impacts on China’s polarized job market. J Comput Soc Sc 5, 517–535 (2022). https://doi.org/10.1007/s42001-021-00134-8

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  • DOI: https://doi.org/10.1007/s42001-021-00134-8

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