首页|Push-pull mechanisms in China's intercity population migration: Nonlinearity and asymmetry

Push-pull mechanisms in China's intercity population migration: Nonlinearity and asymmetry

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  • NETL
  • NSTL
  • Elsevier
© 2024 Elsevier LtdPrevious research has often assumed a predefined, typically linear, relationship between migration and city characteristics. However, few studies have explored how these factors asymmetrically influence migration as push factors at the origin and pull factors at the destination. This study utilizes mobility data from the return-to-home phase of Chunyun in 2020 and employs the Random Forest (RF) model to construct a nonlinear explanatory framework for the push-pull effects and their asymmetry in intercity population migration. The findings reveal three key insights: Firstly, there is a notable asymmetry between push and pull effects in the predictive importance of feature variables. Pull effects at the destination are more prominent for economic and employment factors, whereas push effects at the origin are more influential for factors related to the living environment and gender differences. Secondly, we identify the phase transition points and threshold intervals of coupling effects based on the variations in the shapes, gradients, and thresholds of the nonlinear push-pull effects. In addition, we examine the disparities in the context of push and pull dynamics for the interaction effects of multiple variables. Thirdly, heterogeneity in demographic subsamples and different urban scenarios is observed, with within-group differences exhibiting various patterns of change. These findings provide valuable insights for policymakers to develop targeted population policies that account for the complex interplay of push and pull factors.

City characteristicsHeterogeneity analysisIntercity population migrationNonlinear and asymmetric analysisPush-pull mechanismsRandom forest

Shi F.、Geng W.、Huang R.、Jia J.、Mao Y.

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School of Economics and Management Southwest Jiaotong University||Service Science and Innovation Key Laboratory of Sichuan Province||Hangzhou International Urbanology Research Center and Zhejiang Urban Governance Studies Center

School of Economics and Management Southwest Jiaotong UniversitySchool of Economics and Management Southwest Jiaotong University||Service Science and Innovation Key Laboratory of Sichuan Province||

School of Management and Economics The Chinese University of Hong Kong (Shenzhen)||Hangzhou International Urbanology Research Center and Zhejiang Urban Governance Studies Center||Zhejiang Business College

School of Management and Economics The Chinese University of Hong Kong (Shenzhen)||Shenzhen Institute of Artificial Intelligence and Robotics for Society

Hangzhou International Urbanology Research Center and Zhejiang Urban Governance Studies Center

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2025

10.1016/j.cities.2024.105624

Cities

Cities

ISSN：0264-2751
年,卷(期)：2025.157(Feb.)
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