National School of Development, Southeast University, Nanjing, 210000, China.
School of Finance, Zhejiang University of Finance and Economics, Hangzhou, 310018, China.
Sci Rep. 2020 Jul 31;10(1):12917. doi: 10.1038/s41598-020-68913-3.
Despite persistent efforts in understanding the motives and patterns of human migration behaviors, little is known about the microscopic mechanism that drives migration and its association with migrant types. To fill the gap, we develop a population game model in which migrants are allowed to be heterogeneous and decide interactively on their destination, the resulting migration network emerges naturally as an Nash equilibrium and depends continuously on migrant features. We apply the model to Chinese labor migration data at the current and expected stages, aiming to quantify migration behavior and decision mode for different migrant groups and at different stages. We find the type-specific migration network differs significantly for migrants with different age, income and education level, and also differs from the aggregated network at both stages. However, a deep analysis on model performance suggests a different picture, stability exists for the decision mechanism behind the "as-if" unstable migration behavior, which also explains the relative invariance of low migration efficiency in different settings. Finally, by a classification of cities from the estimated game, we find the richness of education resources is the most critical determinant of city attractiveness for migrants, which gives hint to city managers in migration policy design.
尽管人们一直在努力理解人类迁移行为的动机和模式，但对于驱动迁移的微观机制及其与移民类型的关系，我们知之甚少。为了填补这一空白，我们开发了一个人口博弈模型，在该模型中，允许移民具有异质性，并在互动中决定他们的目的地，由此产生的迁移网络自然成为纳什均衡，并持续依赖移民特征。我们将该模型应用于当前和预期阶段的中国劳动力迁移数据，旨在量化不同移民群体和不同阶段的迁移行为和决策模式。我们发现，具有不同年龄、收入和教育水平的移民的特定类型的迁移网络有显著差异，而且在两个阶段都与综合网络不同。然而，对模型性能的深入分析表明了一个不同的情况，即“貌似”不稳定的迁移行为背后的决策机制是稳定的，这也解释了不同环境下低迁移效率的相对不变性。最后，通过对估计博弈的城市分类，我们发现教育资源的丰富程度是移民对城市吸引力的最关键决定因素，这为城市管理者在移民政策设计中提供了启示。
