| 中国高学历流动人口流动的空间特征及形成机制 |
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| 引用本文： | 林赛南,王雨,马海涛. 中国高学历流动人口流动的空间特征及形成机制[J]. 地理研究, 2022, 41(12): 3229-3244. DOI: 10.11821/dlyj020220122 |
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| 作者姓名： | 林赛南 王雨 马海涛 |
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| 作者单位： | 武汉大学城市设计学院 湖北省人居环境工程技术研究中心,武汉430072;(美国)康奈尔大学建筑、艺术与规划学院,伊萨卡14853;中国科学院地理科学与资源研究所 中国科学院区域可持续发展分析与模拟重点实验室,北京100101 |
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| 基金项目： | 国家自然科学基金项目(42171205);国家自然科学基金项目(41971209) |
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| 摘 要： | 进入创新驱动发展的新时代，未取得流入地户籍的高学历流动人口成为各地竞相引进的重要资源。本文基于2017年中国流动人口动态监测数据，结合探索性空间数据分析等方法精细刻画高学历流动人口流动的空间格局，并借助嵌套Logit模型揭示其空间选择机制。结果发现：(1)中国高学历流动人口不断集聚，形成以京、沪为核心的流动网络；各城市流出的人口中高学历人才占比在空间上具有明显的“东高西低、北高南低、中部塌陷”特征，但各城市吸引的流动人口受教育水平在南北方向上的空间分异较小；高学历流动人口流动的空间依赖性显著，呈现出城市群的雏形。(2)在机制方面，个体因素对高学历流动人口的空间选择影响更大；其普遍表现出近距离、跨级别向上流动的倾向；学历越高、户籍所在地行政等级越高、50岁以下年龄越大的人才越倾向于流入一线城市。(3)城市特征变量中，经济因素变量如工资水平、第三产业占比等和地方品质变量如公共服务、高等教育、空气质量等均对高学历流动人口的空间选择具有显著的正向作用。本研究为不同城市制定人才引进政策、促进城市高质量发展提供了实证依据和科学参考。
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| 关 键 词： | 人才流动 高学历流动人口 空间格局 形成机制 嵌套Logit模型 |
| 收稿时间： | 2022-02-11 |
Spatial mobility pattern of highly educated migrants and its mechanisms in China |
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| LIN Sainan,WANG Yu,MA Haitao. Spatial mobility pattern of highly educated migrants and its mechanisms in China[J]. Geographical Research, 2022, 41(12): 3229-3244. DOI: 10.11821/dlyj020220122 |
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| Authors: | LIN Sainan WANG Yu MA Haitao |
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| Affiliation: | 1. School of Urban Design, Wuhan University, Hubei Habitat Environment Research Centre of Engineering and Technology, Wuhan 430072, China2. College of Architecture, Art, and Planning, Cornell University, Ithaca 14853, United States3. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China |
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| Abstract: | Entering a new era of innovation-driven development, fierce competition among Chinese cities for highly educated migrants who have not yet obtained a local hukou has intensified in recent years. Despite the increasing literature exploring the spatial distribution of highly educated talents and its underlying determinants, little attention has been paid to highly educated migrants, who may have different spatial choices and be influenced by different factors due to absence of a local hukou. Based on the 2017 China Migration Dynamics Survey, this paper utilizes social network analysis and spatial statistics to finely depict the spatial pattern of highly educated migrants and reveals underlying mechanism with Nested Logit Model. The results are as follows: (1) The highly educated migrants continue to agglomerate, shaping a migration network with Beijing and Shanghai as the cores. The ability of each city to contribute highly educated migrants displays an obvious trend of "high in the east and low in the west, high in the north and low in the south, and collapse in the middle" while the spatial differentiation of the attractiveness to highly educated migrants between the north and the south is not marked. The spatial autocorrelation of the flow of highly educated migrants between cities is significant, demonstrating the prototype of the urban agglomerations. (2) In terms of underlying mechanism, individual factors have a stronger influence on the spatial choice compared with city attributes. Highly educated migrants tend to choose neighboring cities with higher hierarchy. Those who are equipped with higher educational attainment level, hold local hukou in bigger cities, and are older (under the age of 50) tend to choose the first-tiered cities. (3) As for the city attributes, economic opportunities including annual wage, the proportion of tertiary industry, as well as amenities including public services, higher education scale, air quality, are all significantly positively correlated with the migrants' spatial choice. This study provides an empirical evidence and references for different cities to formulate talent policies and promote high-quality development. |
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| Keywords: | talent flow highly educated migrants spatial pattern mechanism Nested Logit Model |
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