应用时空滤波模型的亚洲内部国际人口迁移流影响因素分析及短期预测  

Analysis of Influential Factors and Short-term Forecast of International Migration Flows in Asia Using Eigenvector Space-Time Filtering Models

作　　者：叶绮霖 蒲英霞[1,2,3] 叶翠 YE Qilin;PU Yingxia;YE Cui(School of Geography and Ocean Science,Nanjing University,Nanjing 210023,China;Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology,Nanjing 210023,China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China)

机构地区：[1]南京大学地理与海洋科学学院,南京210023 [2]江苏省地理信息技术重点实验室,南京210023 [3]江苏省地理信息资源开发与利用协同创新中心,南京210023

出　　处：《地球信息科学学报》2024年第6期1374-1389,共16页Journal of Geo-information Science

基　　金：国家自然科学基金项目(42371435、41771417)。

摘　　要：亚洲是国际人口迁移的活跃区域。除区域社会经济因素外,迁移流之间的时空依赖也不可忽视。本文基于1990—2020年6个时期亚洲国家双边移民流量数据,采用零膨胀负二项回归以及与之相结合的特征向量空间滤波和时空滤波模型(时空同期和时空滞后),分析亚洲内部国际人口迁移的影响因素,并对2020—2025年人口迁移流进行预测。结果初步表明:①亚洲国际人口迁移流存在显著的时空自相关,且同期邻近迁移流比过去邻近迁移流影响更大,加入表征时空依赖的特征向量能够有效提高模型拟合能力;②人口规模、经济水平、战乱情况以及邻近性是影响亚洲国际人口迁移流的主要因素,在1990—2020年,人口规模效应先减后增,经济差异驱动力则先强后弱,因战乱死亡人数仍具有较强的推力,地理距离的阻碍作用在减小,语言邻近和经济合作依然对人口迁移具有显著的促进作用;③综合时空同期和时空滞后2种模型的预测结果,2020—2025年巴基斯坦和印度之间、印度→沙特、巴基斯坦→阿富汗和叙利亚→约旦的迁移趋势明显;④根据2种时空滤波模型的结果,2020—2025年亚洲国际人口迁移流总量约为1.8×10^(7)人。揭示亚洲内部国际人口迁移的时空依赖特性和其他规律有助于准确预测未来人口迁移趋势,同时为国家经济社会发展的宏观政策制定等提供科学决策参考。With the continuous advancement of the globalization process,communication and cooperation among countries and regions around the world are becoming increasingly closer,and the scale of international migration flows is also expanding.Asia stands out as an active region for international migration,with a large portion of migratory movements occurring within its borders.In addition to the social and economic factors of the origin and destination regions,spatial and temporal dependence among migration flows is crucial in understanding international migration dynamics,indicating that migration is influenced by neighboring and past migration flows.Different from other kinds of data(e.g.,regional GDP),migration flows between different regions often contain many zero values,necessitating specific methods for handling them.Additionally,spatial and temporal dependence among migration flows can be categorized into space-time contemporaneous and lagged structures,with the former reflecting the links to the preceding location and the instantaneous neighboring locations,and the latter pertaining to the preceding location and the preceding neighboring locations.Based on the bilateral migration data of Asian countries in six periods from 1990 to 2020,this study utilizes eigenvector space-time filtering models,along with contemporaneous and lagged dependent structures,as well as eigenvector spatial filtering models and zero-inflated negative binomial regression models,to explore the influential factors of the international migration flows within Asia and their changes during 1990-2020.Finally,this study aims to forecast international flows within Asia between 2020 and 2025 based on two types of space-time filtering models.Preliminary results indicate significant space-time autocorrelation of international migration flows within Asia,with neighboring migration flows exerting a greater influence over the same time period compared to the past.Incorporating eigenvectors to represent spatial and temporal dependence effectively improv

关 键 词：国际人口迁移流 零膨胀负二项回归模型 时空依赖 特征向量时空滤波模型 时空同期结构 时空滞后结构 人口迁移预测模型 亚洲 

分 类 号：K901[历史地理—人文地理学] C922[社会学—人口学]