Spatial heterogeneity of internal migration in China: The role of economic, social and environmental characteristics

PLoS One. 2022 Nov 17;17(11):e0276992. doi: 10.1371/journal.pone.0276992. eCollection 2022.

Abstract

The purpose of this paper is to explore the spatial heterogeneity of internal migration in China and to discuss the influence of economic, social and environmental characteristics on this demographic process. The overall results suggest that migration in China occurred from inland to coastal areas and from rural areas to urban areas. By stepwise regression, we identified that 9 out of 15 factors with potential influence on internal migration were retained, and the multicollinearity among them was reduced. In addition, we used the OLS and GWR regression analysis to discuss the global and local effects of relevant factors on internal migration. Economic scale (GDP), population concentration (population density) and demographic dividend (labour force proportion) were the three main driving forces of internal migration. In turn, internal migration further widened the gap of economic scale, population agglomeration and demographic dividend between counties and cities. Internal migration in southern coastal areas of China was most affected by economic aspects and demographic dividend. In the central China, the population was more concentrated in high-density cities, while in the eastern regions, areas with high level of education were conducive to immigration, thus forming talent reserve highlands. In the west, areas with highly educated level faced out-migration, which might cause brain drain and widen further the gap in talent reserves between the east and the west in China. From the perspective of location, the net immigration of the provincial capital was accompanied by the net immigration of the surrounding area, which was conducive to the formation of city clusters or urban sprawl. On the other side, the net immigration in prefecture-level cities often meant the net out-migration in surrounding areas. The correlation is particularly strong in eastern coastal provinces.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China / epidemiology
  • Cities
  • Emigration and Immigration*
  • Population Density
  • Population Dynamics

Grants and funding

Specify the role(s) played the National Social Science Fund of China(20BRK022) Sponsored by Natural Science Foundation of Shanghai (19ZR1415200).