Labor migration, economic growth, and welfare inequality: A quantitative analysis of China

Cao-Yuan Ma, Xiu-Feng Ni and Ting-Rui Li

Economic Systems, 2025, vol. 49, issue 3

Abstract: This study examines how differing migration restrictions for labor with heterogeneous skills affect economic development and welfare inequality in China. Combining micro individual data with a general equilibrium model that includes skilled and unskilled workers, endogenous productivity, and housing supply, we quantify the differing migration costs for skilled and unskilled workers and its consequences. The findings reveal that unskilled workers’ interprovincial migration cost is much higher than that of skilled workers, resulting in a 1.286 % output loss and widening economic disparity by 3.996 %, causing the interprovincial income gap to expand by 5.929 % and expanding the income gap between skilled and unskilled workers by 0.059 %. Regarding skill heterogeneity, facilitating the smooth interprovincial migration of unskilled workers can produce more significant and positive output and welfare effects compared with skilled workers. Across China’s regions, rationalizing the proportion of skilled and unskilled workers and improving the complementarity between skilled and unskilled workers would help optimize the spatial allocation of workers and enhance the output and welfare effects of labor migration. Therefore, eliminating the exclusion of unskilled workers and guiding the rational and orderly migration of skilled and unskilled workers will promote output growth, narrow the economic gap, and improve workers’ welfare, narrowing the welfare gap and establishing a mutually beneficial outcome of efficiency and fairness.

Keywords: Economic growth; Heterogeneous skills; Labor migration; Quantitative spatial general equilibrium model; Welfare inequality (search for similar items in EconPapers)
JEL-codes: I38 J24 J31 J61 J71 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosys:v:49:y:2025:i:3:s0939362525000032

DOI: 10.1016/j.ecosys.2025.101291

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