| 中国省际人口迁移的多边效应机制分析 |
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| 引用本文： | 蒲英霞,韩洪凌,葛莹,孔繁花.中国省际人口迁移的多边效应机制分析[J].地理学报,2016,71(2):205-176. |
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| 作者姓名： | 蒲英霞 韩洪凌 葛莹 孔繁花 |
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| 作者单位： | 1. 南京大学地理与海洋科学学院,南京 2100232. 江苏省地理信息技术重点实验室,南京 2100233. 江苏省地理信息资源开发与利用协同创新中心,南京 2100234. 临沂大学商学院,临沂 2760005. 河海大学地球科学与工程学院,南京 2100986. 南京大学国际地球系统科学研究所,南京 210023 |
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| 基金项目： | 国家自然科学基金项目(41271388);江苏高校优势学科建设工程资助项目;江苏省地理信息资源开发与利用协同创新中心资助项目 |
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| 摘 要： | 区际人口迁移不仅与迁出地和目的地的要素特征以及距离有关,而且还受到周边迁移流的影响.基于网络自相关理论,利用"六普"省际人口迁移数据和相关统计资料,在重力模型的基础上考虑迁移流之间可能存在的几种空间依赖形式,构建中国省际迁移流的空间OD模型,初步揭示区域经济社会等因素及其空间溢出效应对省际人口迁移的影响,并就区域要素变化对整个省际人口迁移系统产生的"连锁反应"进行了模拟.结果表明:① 中国省际迁移流之间存在显著的网络自相关效应.目的地和迁出地的自相关效应皆为正,导致迁入和迁出流的空间效仿行为;迁出地和目的地周边则出现负的自相关效应,导致迁移流的空间竞争行为;② 区域经济社会等因素通过网络空间关系对周边地区产生的多边溢出效应导致迁移流在空间上集聚.其中,距离衰减效应位居各要素之首,其溢出效应进一步加剧距离的摩擦作用;对目的地而言,区域工资水平和迁移存量超过GDP的影响并产生正的溢出效应,促进周边地区吸引更多的外来人口;对迁出地而言,人口规模和迁移存量产生正的溢出效应,推动周边地区人口外迁;③ 区域要素变化潜在地对整个省际人口迁移系统产生一系列"连锁反应",震荡中心及其周边区域的迁移流波动较大.江苏省GDP增长5%的模拟结果表明,江苏迁往全国其他省份的人口数量都有不同程度地减少,而其他省份入迁人口均有所增加.相对而言,江苏周边省份的迁入或迁出流受到的波动较大,偏远省份波及较小,这是传统的重力模型所无法解释的.
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| 关 键 词： | 人口迁移流 网络自相关 多边效应 空间OD模型 空间机制 中国 |
| 收稿时间： | 2015-05-14 |
| 修稿时间： | 2015-08-01 |
Multilateral mechanism analysis of interprovincial migration flows in China |
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| Yingxia PU,Hongling HAN,Ying GE,Fanhua KONG.Multilateral mechanism analysis of interprovincial migration flows in China[J].Acta Geographica Sinica,2016,71(2):205-176. |
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| Authors: | Yingxia PU Hongling HAN Ying GE Fanhua KONG |
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| Abstract: | Population migration flows between different regions are related to not only the origin- and destination-specific characteristics, but also to the migration flows to and from neighborhoods. Intuitively, changes in the characteristics of a single region will impact both inflows and outflows to and from other regions. In order to explore the spatial interaction mechanism driving the increasing population migration in China, this paper builds the spatial OD model of interprovincial migration flows based on the sixth national population census data and related social-economic data. The findings are as follows: (1) Migration flows show significant autocorrelation effects among origin and destination regions, which means that the migration behavior of migrants in some region is influenced by that of migrants in other places. The positive effects indicate the outflows from an origin or the inflows to a destination tend to cluster in a similar way. Simultaneously, the negative effects suggest the flows from the neighborhood of an origin to the neighborhood of a destination tend to disperse in a dissimilar way. (2) Multilateral effects of the regional economic and social factors through the spatial network system lead to the clustering migration flows across interrelated regions. Distance decay effect plays the most influential force in shaping the patterns of migration flows among all the factors and the negative spillover effect further aggravates the friction of distance. As for destinations, the influence of wage level and migration stocks is beyond that of GDP and the positive spillover effects of these factors enhance the attraction of neighborhood regions. The spillover effects of unemployment rate and college enrollment of higher education are significantly negative while the effect of population in a destination is not significant. As for origins, population and migration stocks lead to positive spillover effects on the neighborhoods while the effects of other factors are negative. (3) Changes in the regional characteristics will potentially lead to a series of events to the whole migration system, and the flows to and from the center of oscillation and its neighborhoods vibrate greatly compared with other regions. The simulation results of 5% GDP increase in Jiangsu province indicate that the outflows to other regions decrease while the inflows from all others increase to some different extent. Comparatively, the influence on the flows to and from the regions neighboring Jiangsu is significant while that of remote regions is much less, which cannot be explained by the traditional gravity model. |
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| Keywords: | population migration flows network autocorrelation multilateral effects spatial OD model spatial mechanism analysis China |
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