Internal migrants, skill complementarity and wage premium for local workers: a micro econometric analysis of Chinese households

Abstract

China’s rapid urbanization has been driven by large-scale internal migrants, and it is worth exploring the impact of internal migrants on local labor markets. Based on data from China’s population census, population sample survey and urban household survey, this study empirically tests the wage premium effect of internal migrants on local labor, and further investigates the mechanisms of wage premium from skill complementarity, as well as the policy adjustment effect of labor market reforms. The results show that: (1) The wage premium effect originating from migrants is significant, and gradually decreases over time and with the increase of local worker wages. (2) The wage premium effect is more prominent in large cities, mega and super-sized cities, which can be explained by economic agglomeration and division of labor induced by skill complementarities. (3) Labor market-oriented reforms contribute to enhancing the wage premium effect, with marginal effects of 3.71% and 3.64%.

Keywords:

• Internal migrants
• wage premium
• labor heterogeneity
• skill stratification

Authors contributions

All authors contributed to the study conception and design. Conceptualization, methodology, data curation, and original draft writing are performed by Weiping Wu and Yuxuan Yang. Software, visualization, supervision and writing-review & editing are completed by Leyan Su, Yuwei Sun and Tuozhi Liu.

Consent to publish

The authors agree to publication in the Journal.

Data availability statement

The datasets used in the current study are available from the corresponding author on reasonable request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The data is sourced from the World Bank’s WDI database, which provides urbanization rates for 1950 and beyond.

Additional information

Funding

This research is supported by the National Natural Science Foundation of China (Grant No. 71903056), National Science Foundation for Post-doctoral Scientists of China (Grant No. 2020M672464), Scientific Research Project of Hunan Education Department in China (Grant No. 23A0487; No. 23A0483), Research and Innovation Project for Graduate Students in Hunan Province (Grant No. CX20231122), Natural Science Foundation of Hunan Province in China (Project No. 2024JJ5117), National Social Science Foundation Major Project (No. 2023 & ZD067) and Shanghai Education Commission Research and Innovation Major Project (No. 2023SKZD12).