| 2000—2015年中国高学历人才省际迁移的演化格局及影响机理 |
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| 引用本文： | 齐宏纲,赵美风,刘盛和,高苹,刘振.2000—2015年中国高学历人才省际迁移的演化格局及影响机理[J].地理研究,2022,41(2):456-479. |
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| 作者姓名： | 齐宏纲 赵美风 刘盛和 高苹 刘振 |
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| 作者单位： | 1.天津师范大学地理与环境科学学院,天津 3003872.中国科学院地理科学与资源研究所,区域可持续发展分析与模拟重点实验室,北京 1001013.中国科学院大学,北京 100049 |
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| 基金项目： | 国家自然科学基金项目（42101237、41661144023）； |
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| 摘 要： | 经济快速增长和社会转型促使中国人才迁移的地理景观正涌现出一些新特征和新趋势。利用中国2005年、2010年和2015年千分之一人口抽样调查微观数据,揭示2000—2005年、2005—2010年和2010—2015年全国高学历人才省际迁移格局的演化趋势,选用零膨胀负二项回归模型解释高学历人才省际迁移格局的演化机理。结果发现：① 中国高学历人才跨省流动性呈先增后减的演化趋势,人才省际迁移规模的空间分布开始趋于均衡化。② 东部发达省市人才净流入活跃,中部、东北和河北等地区人才净迁出活跃,2010年后发达地区的人才高强度净流入及欠发达地区的人才高强度净流失问题均开始缓解。③ 高学历人才由中西部流动至东部地区的主要迁移模式比较稳定,但东部向中西部地区的高学历人才迁移规模持续上升。④ 从影响因素的演化趋势上看,全国人才省际迁移主要为经济驱动型,但收入在人才迁移决策中的重要性开始减弱,产业转型、购房成本、教育服务舒适性及气候舒适性对人才跨省流动性的影响开始增强。⑤ 全国人才跨省流动性的演化机制具有一定的阶段分异性,前期,城镇居民收入差距的扩大是人才跨省流动性升高的主要动因;之后人才跨省流动性的减弱主要受城镇居民收入差距的缩小、发达地区过高的购房成本及小学教育服务设施短缺等因素影响。
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| 关 键 词： | 高学历人才 省际迁移 演化格局 演化机理 中国 |
| 收稿时间： | 2020-12-07 |
Evolution pattern and its driving forces of China's interprovincial migration of highly-educated talents from 2000 to 2015 |
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| QI Honggang,ZHAO Meifeng,LIU Shenghe,GAO Ping,LIU Zhen.Evolution pattern and its driving forces of China's interprovincial migration of highly-educated talents from 2000 to 2015[J].Geographical Research,2022,41(2):456-479. |
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| Authors: | QI Honggang ZHAO Meifeng LIU Shenghe GAO Ping LIU Zhen |
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| Institution: | 1. School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China2. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China3. University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | The rapid economic growth and social transition in China brings about some new trends of skilled migration.Based on microdata of China's 2005,2010 and 2015 onethousandth population sample survey,this paper analyzes the evolution pattern of China's interprovincial migration of highly-educated labors in the periods of 2000-2005,2005-2010 and 2010-2015,and employs zero inflation negative binomial regression models to explain the evolution mechanism of the interprovincial migration of highly-educated talents.Results show that:(1)the interprovincial mobility of China's highly-educated workers rose first and then declined from 2000 to 2015,and the spatial distribution of migration volume of highlyeducated talents tended to be balanced.(2)The net inflow rate of highly-educated talents was high in the eastern developed provinces,while the net out-flow rates were high in the central region,northeastern region and Hebei Province;the high-intensity net inflow of highlyeducated talents in developed areas as well as high-intensity net outflow in less-developed areas began to ease after 2010.(3)Highly-educated individuals mainly migrated from central and western regions to eastern coastal areas,while the sizes of highly-educated labors migrating from eastern regions to central and western regions continuously increased.(4)From the perspective of the evolution trend of influencing factors,China's interprovincial migration of highly-educated talents was mainly driven by economic factors,but the importance of income in the decision-making of skilled migration tended to weaken,and the impact of industrial transformation,housing price income ratio,education service facility,and climate on the interprovincial mobility of talents began to increase.(5)The evolution mechanism of the interprovincial mobility of highly-educated talents in China varied in development stages.In the early stage,the widening urban residents'income gap was the main driver for the increase of the interprovincial mobility of highly-educated talents.After that,the decrease of the interprovincial mobility of highly-educated talents was mainly affected by the narrowing urban residents'income gap,the high housing price income ratio and the shortage of primary education service facilities in developed areas. |
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| Keywords: | highly-educated labors interprovincial migration evolution pattern evolution mechanism China |
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