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Influence of skill relatedness on the location choice of heterogeneous labor force in Chinese prefecture-level cities

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  • Xiaoqi Zhou
  • Rongjun Ao
  • Yierfanjiang Aihemaitijiang
  • Jing Chen
  • Hui Tang

Abstract

High-quality regional development should be promoted by facilitating inter-regional mobility of heterogeneous labor force to optimize its spatial allocation. This study incorporates skill relatedness into spatial categorization and selection effects, and explores how skill-relatedness affects the location choice of heterogeneous labor force. To do so, we use labor force migration data and employee data by occupation subcategory from the 2000 National Population Census and 2015 National Population Sample Survey. The empirical evidence provides three major findings. First, there are significant regional differences in labor migration rates by the occupational group between cities in China, and the trend is increasing. Regional concentration of location choice is increasing and six significant agglomerations are formed. Second, skill relatedness positively affects the location choice of the heterogeneous labor force in Chinese cities. When cities’ skill-relatedness is more robust, influence on labor location choice is more remarkable. In cities with high-size classes, the effect of high-skill relatedness on labor location choice is higher. Third, labor force with solid skill relatedness with regional employment moves to the location owing to the spatial sorting effect. Labor force without skill relatedness or weak relatedness moves out or does not move to the location owing to the spatial selection effect.

Suggested Citation

  • Xiaoqi Zhou & Rongjun Ao & Yierfanjiang Aihemaitijiang & Jing Chen & Hui Tang, 2023. "Influence of skill relatedness on the location choice of heterogeneous labor force in Chinese prefecture-level cities," PLOS ONE, Public Library of Science, vol. 18(8), pages 1-21, August.
  • Handle: RePEc:plo:pone00:0289803
    DOI: 10.1371/journal.pone.0289803
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    References listed on IDEAS

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