Modelling interprovincial migration in China from 1995 to 2015 based on an eigenvector spatial filtering negative binomial model
Modelling interprovincial migration in China from 1995 to 2015 based on an eigenvector spatial filtering negative binomial model
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DOI：
10.1002/psp.2253
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发表时间：
2019-09-11
影响因子：
2.4
通讯作者：
Meng, Xin
中科院分区：
文献类型：
--
作者：
Gu, Hengyu;Liu, Ziliang;Meng, Xin
区际人口流动是影响中国未来城市化和区域发展格局的关键问题。针对人口迁移网络中普遍存在的网络自相关现象，基于人口普查和人口抽样调查的四阶段面板数据，将特征向量空间滤波（ESF）与负二项引力模型相结合，分析了1995 - 2015年中国省际人口迁移的影响因素。结果表明：（1）省际人口迁移网络存在显著的空间溢出效应。ESF可以有效地捕捉数据中的NA，以减少模型的估计偏差。前1.4%的特征向量可以提取高NA。(b)各省间的移民流动过于分散。负二项回归重力模型比其他模型更适合于估计移民的驱动机制。(c)与引力模型的初始变量一样，人口规模仍然对流出和流入产生重大影响。考虑NA的影响后，空间距离的影响减弱。此外，经济、就业、社会保障和教育等因素是影响省际移民格局的主要力量。如果地区失业率和平均工资每增加1%，流出和流入分别增加0.351%和0.502%;地区原籍性别比系数也较高，这与迁移动机和就业市场性别差异有密切关系。
Interregional migration is a key issue affecting China's future pattern of urbanisation and regional development. In response to the phenomenon of network autocorrelation (NA) commonly found in migration networks, this paper combines eigenvector spatial filtering (ESF) with a negative binomial gravity model based on four-stage panel data derived from censuses and population sampling surveys, and it analyses the factors that influenced China's interprovincial migration from 1995 to 2015. The results showed that (a) there is a significant spatial spillover effect in the interprovincial migration network. ESF can effectively capture NA in the data to reduce the model's estimation bias. The top 1.4% eigenvectors can extract high NA. (b) There is overdispersion in the interprovincial migration flows. A negative binomial regression gravity model is more appropriate for estimating the driving mechanism for migration than other models. (c) As with the initial variables of the gravity model, population size still exerts a great impact on both outflows and inflows. After considering the influence of NA, the effect of spatial distance is weakening. Additionally, economic, employment, social security, and educational factors are the main forces that are shaping the pattern of interprovincial migration. If the regional unemployment rate and average wages increase by 1%, the outflows and inflows increase by 0.351% and 0.502%, respectively; the coefficient of regional sex ratio at origin is also high, which has a close relationship with the migration motivations and gender differences in the employment market.