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What Drives Migrants to Settle in Chinese Cities: a Panel Data Analysis

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Abstract

Understanding the drivers of the floating population’s settlement intentions in Chinese cities is vital to guide evidence-based urban economic development policies. Prior studies have been inclined to use static cross-sectional analysis providing insights into the relative importance of the factors that drive the distribution of urban settlement intentions. Yet, little has adopted longitudinal data approaches to delve into their spatial-temporal patterns and changes in determinants. This study applies China Migrants Dynamic Survey data of 2014–2017 to examine the spatial distribution of urban settlement intentions of floating migrants and their determinants over time. It reveals a persistent and spatially differentiated pattern of urban settlement intentions, where floating migrants relocating to some small and medium-sized cities in several northern parts of China are more willing to settle down. Results from a two-way fixed-effects panel model indicate that both internal motivations and external constraints are closely related to the settlement decision process of floating migrants. The number of family members living together, marriage rate, duration of stay, insurance coverage, the average wage of employees, the proportion of employees in the education industry, and per capita fiscal expenditure positively correlate with settlement intentions, while the proportion of interprovincial floating migrants and urban employment rate have a negative relationship with settlement intentions. Our results further suggest that internal drivers are a prerequisite for external drivers to play a role in driving the urban settlement of migrants.

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Notes

  1. Since prices level have changed over years, we divide the average annual wage of urban employees by the CPI of the corresponding year.

  2. We apply the Gini index (GI) and Coefficient of variation (CV) to measure the spatial inequality of settlement intentions at the city level. The GI is computed as: \( GI=\frac{1}{2{n}^2\overline{x}}\sum \limits_{i=1}^n\sum \limits_{j=1}^n\left|{x}_i-{x}_j\right| \), where n refers to the number of cities, \( \overline{x} \) is the average of settlement intentions, xi, xj represent the values of settlement intentions in any two cities. The CV is expressed as: \( CV=\frac{1}{\overline{x}}\sqrt{\frac{\sum \limits_{i=1}^n{\left({x}_i-\overline{x}\right)}^2}{n-1}} \), where xi is the value of settlement intention in a city i.

  3. The Moran’s I (MI) is widely used in detecting spatial autocorrelation in the data. It be expressed as: \( MI=\frac{X^{\prime}\boldsymbol{W}X}{X^{\prime }X} \), where X denotes the vector settlement intentions of cities, W represents the distance-based spatial weight matrix.

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Acknowledgments

The work described in this study was funded by the National Natural Science Foundation of China (No.71733001), the National Social Science Foundation of China (No. 17ZDA055), and China Scholarship Council (201906010255).

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Authors and Affiliations

  1. School of Government, Peking University, Beijing, 100871, China

    Hengyu Gu

  2. Center for Spatial Data Science, University of Chicago, Chicago, IL, 60637, USA

    Hengyu Gu

  3. Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, 361005, China

    Yangyang Jie

  4. College of Humanities and Development Studies, China Agricultural University, Beijing, 100083, China

    Zhitao Li

  5. School of Government, Peking University, Beijing, 100871, China

    Tiyan Shen

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Correspondence to Tiyan Shen.

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Gu, H., Jie, Y., Li, Z. et al. What Drives Migrants to Settle in Chinese Cities: a Panel Data Analysis. Appl. Spatial Analysis 14, 297–314 (2021). https://doi.org/10.1007/s12061-020-09358-z

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