Background
Previous studies indicate that migrant integration is associated with migrants’ characteristics as well as restrictions and opportunities in receiving cities. However, the effect of receiving cities and the relationship between migrants and receiving cities have not been fully explored due to the lack of large samples from cities. The objective of this study is to examine the effects of receiving cities alone and their regulating role in the interaction with individual characteristics.
Methods
Cross-city data on 154,044 Chinese domestic migrants above 15 years old in 289 cities from the 2017 China Migrants Dynamic Survey are used. Migrant integration is assessed by a four-dimensional model proposed by Esser, which is slightly adjusted according to the characteristics of Chinese migrants. A hierarchical linear model is used to measure the proportion of effects of city factors in migrant integration as well as the effects when city factors are considered alone and in interaction with individual factors.
Results
The individual-level and city-level factors are responsible for 69.81% and 30.19% of the effect on migrant integration, respectively. City political factors do not affect migrant integration directly, and cities with larger sizes and higher wages can directly and significantly improve integration, while higher housing prices will directly inhibit integration. From the cross-level interaction of city and individual, different social, economic and political factors at the city level have an indirect impact on migrant integration by inhibiting or strengthening the effect of individual-level factors on migrant integration.
Conclusion
This study is one of the first to show the effect of cities and the relationship between receiving cities and migrants on migrant integration by keeping the national context constant. It is necessary to weaken the social and economic privileges associated with a city’s administrative level and reduce the negative impact of cities’ social and economic conditions by implementing city agglomeration, developing advantageous industries and optimizing the industrial structure. It is also essential to improve migrants’ socioeconomic capital through social support, occupation training and contiguous education.
Since the reform and opening up, the socioeconomic status of women in rural China has risen rapidly. However, unlike men, women have not been able to earn higher wages by “working in all directions”. Based on the interview data of 2064 migrant workers, this paper explores the nonlinear interaction of individual characteristics and urban geographic factors with gender differences in migrant workers’ wages with the help of random forest regression models. The results show the following: (1) migrant workers’ wages show obvious gender differences in different dimensions, but in general, men’s wages are higher than women’s wages; (2) there are also gender differences in the influencing factors of migrant workers’ wages. Work experience is more important for male migrant workers’ wages, age is more important for female migrant workers’ wages, and there is a variable effect of each factor on migrant workers’ wages. This paper is of great help in understanding the travel trajectories of migrant workers and gender differences in wages and holds reference value for guiding migrant workers in choosing jobs and places and increasing their income.
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