Spatial Differentiation and Driving Forces of Migrants’ Socio-Economic Integration in Urban China: Evidence from CMDS

• Published in: Social indicators research 2022-02, Vol.159 (3), p.1035-1056
• Main Authors: Zou, Jing, Deng, Xiaojun
• Format: Article
• Language: English
• Subjects: Adaptation; Automobiles; Differentiation; Distribution patterns; Driving; Economic factors; Economic integration; Economic research; Economic stabilization; Economics; Education; GDP; Gross Domestic Product; Growth rate; Heterogeneity; Housing conditions; Human Geography; Identity; Individualized Instruction; Length of stay; Microeconomics; Middle schools; Migrants; Migration; Mobility; Original Research; Policy making; Population growth; Public Health; Quality of Life Research; Social capital; Social integration; Social networks; Social Sciences; Social security; Social stability; Sociodemographics; Socioeconomic factors; Socioeconomics; Sociology; Teachers; Urban areas; Urban policy; Urbanization
• ISSN: 0303-8300; 1573-0921
• DOI: 10.1007/s11205-021-02785-6

Migrants’ socio-economic integration is a major theme in migration research, which can provide economic and cultural benefits. And it will contribute to social stability. The investigation from the spatial perspective should also be considered. This paper aims to examine the spatial differentiation of the socio-economic integration of migrants and identify its driving forces to provide crucial evidence and policy recommendations to urban policymakers and further improve migrants’ socio-economic integration. Based on the latest China Migrants Dynamic Survey, this paper uses global Moran’s I index, hot spot analysis and GWR model to explore spatial differentiation and driving forces of the socio-economic integration of 155,789 migrants in 291 cities at prefecture level and above in China. The results show that: (1) The socio-economic integration of migrants consists of five dimensions, which are economic integration, cultural integration, social security, social relation and psychological integration. Among them, psychological integration is the highest (73.16) and economic integration is the lowest (13.38). (2) The socio-economic integration of migrants is mainly influenced by their own characteristics instead of the destination characteristics. Four factors (age, education, length of stay and population growth rate) positively affect migrants’ socio-economic integration, while three factors (inter-provincial mobility, proportion of tertiary industry in GDP, and ratio of teacher to student in middle school) negatively impact the socio-economic integration of migrants. (3) The socio-economic integration of migrants shows the distribution pattern of agglomeration. And the integration also presents a significant spatial heterogeneity. The driving forces of the socio-economic integration exhibit various zonal spatial differentiation patterns, including “E–W”, “SE–NW”, “NE–SW”, and “S–N”. Finally, some useful recommendations are given for improving migrants’ socio-economic integration.