Talents are the core driving force for regional innovation and development, and they are also the key to urban competition in the future. Based on the data of the sixth population census and the national 1% population sampling survey in 2015, this paper uses the concentration index (CI), Gini index (GI) and several related spatial analysis methods to examine the spatial patterns of highly educated talents across China and the drivers behind these patterns from 2010 to 2015. The results are as follows: (1) Talents show highly concentrated and unbalanced spatial distribution patterns at the city level over the five years, but the trend of concentration and imbalance has gradually eased. Results from standard deviation ellipse (SDE) indicate that the distribution direction of highly educated people is "NE-SW". Furthermore, there is a significant spatial spillover effect in the distribution of talents, with three major urban agglomerations of China as the highlands. (2) Economic opportunities are the dominant drivers for the distribution of highly educated talents in China. Among them, wages are the core driver, and gross GDP and industrial structure of each city also exert a significant impact. (3) After controlling the impacts of economic opportunities, local quality variables represented by basic public services (e.g., education and medical care), transportation accessibility and urban consumption facilities play an important role in the distribution of highly educated talents. (4) There are significant differences between the driving factors for talents in urban agglomerations and non-urban agglomerations: economic opportunities are the main driving force for the distribution of talents in both urban agglomerations and non-urban agglomerations, while local qualities including education, consumption, transportation and natural environment have a more significant impact on the distribution of talents in urban agglomerations. This study provides references for the formulation of urban and regional talent policies and regional development policies.

人才是推动地区创新发展的核心动力,也是未来城市竞争的关键。基于第六次全国人口普查和2015年全国1%人口抽样调查数据,运用集聚度、基尼系数等空间统计分析以及负二项回归模型方法,对2010—2015年中国城市高学历人才的空间演化特征及驱动因素展开研究。结果发现：① 人才呈现出高度集中且不平衡的空间分布格局,但不平衡的趋势有所缓解,分布方向为“东北—西南”走向。人才分布的空间溢出效应显著,城市群是人才集聚的高地。② 经济机会是影响中国高学历人才集聚的主导力量,其中工资是核心驱动因素,地区的发展水平、产业结构同样产生显著影响。③ 控制经济机会的影响后,以教育和医疗等基础公共服务、交通可达性和城市消费设施为核心的地方品质变量在高学历人才的空间集聚过程中发挥重要作用。④ 城市群与非城市群人才驱动因素存在显著差异：经济机会是城市群和非城市群人才集聚的主要驱动力;教育、消费、交通以及自然环境等地方品质变量对城市群人才集聚的影响更为显著。本研究为城市和区域人才政策和区域发展政策的制定提供借鉴与参考。

In this paper, we estimate wage gains due to geographic mobility of Italian university graduates three years after graduation. By means of a matching procedure we quantify wage premia associated with the choice of studying far from home, moving after graduation and moving back home after graduation. We find evidence of large heterogeneity in the returns to different migration patterns. The results show large gains for those who move after graduation and smaller gains for those who migrate to study. Conversely, those who choose to go back home after having studied in regions different from that of origin suffer small losses. Our findings are robust to a finer definition of mobility and to the subsample of individuals originating from the South.

Cities make it easier for humans to interact, and one of the main advantages of dense, urban areas is that they facilitate social interactions. This paper provides evidence for the US suggesting that the resurgence of big cities in the 1990s is due, in part, to the increased demand for these interactions and due to the reduction in big city crime, which had made it difficult for urban residents to enjoy these social amenities. However, while density is correlated with consumer amenities, we show that it is not correlated with social capital and that there is no evidence that sprawl has hurt civic engagement.

This paper examines how culture and gender shape entrepreneurial perceptions and intentions within Hofstede's cultural dimensions framework and gender role theory. We test whether gender differences exist in the way university students in three nations perceive barriers to entrepreneurship and whether gender has a moderating effect on the relationship between perceived barriers and entrepreneurial intentions across nations. Findings indicate significant gender differences in barrier perceptions. However, this gap is not consistent across cultures. Also, a moderating effect of gender on the relationship between barriers and entrepreneurial intentions is identified. Implications for research and practice are discussed.

Human capital is the key driver of urban innovation and development. In 2017, the "vying for talent" competition was initiated by some second-tier cities, since then cities have been competing each other fiercely for recruiting and retaining talent. This paper focuses on China′s "first-class" university graduates, who are regarded as the main target of the "vying for talent" competition and an important carrier of human capital. Based on 2018 Graduate Employment Reports, this paper demonstrates the spatial mobility of graduates using Cartogram. In addition, an evaluation system for assessing talent policy is constructed through analyses of the talent policies issued by different cities. With a directional migration model, the determinants of graduate mobility are explored. The results reveal that there are significant regional disparities in retention rates, with the geographical patterns of the Y-shaped low-value areas in the northeastern, northwestern, and central regions, and the U-shaped high-value areas covering east coast to southwest. Graduates have been accumulating spatially, and the T-shaped cluster along east coast and the Yangtze River Economic Belt has formed. The spatial patterns of "neighborhood interaction" and "long-distance unidirectional flow" are presented between the city of university and the city of employment. Moreover, the differences in city attractiveness are remarkable. First-tier cities are preferred by graduates, even though limited talent policies have been implemented there. Some second-tier cities have issued talent policies to make up for the lack of attractiveness in economy and amenities. The findings suggest that economic factors, such as income level and technological innovation, as well as amenities including natural and cultural environment, educational resources, and public transportation are positively associated with the volume of graduates inflow. It has been found that a higher ratio of house price to income has squeezed out university graduates. With regard to talent policies, only relaxed hukou policy has a strong effect on attracting graduates, whereas the effects of housing and employment policies are relatively limited. However, it needs to be noted that talent policies may take a longer time to show effects, which requires follow-up investigation. In addition, heterogeneity at the individual level in terms of place of origin, major, etc. should be explored in the future studies.

自2017年以来,“人才争夺战”如火如荼,城市步入以人才为核心要素的高维竞争阶段。作为人才争夺战的主要目标和人力资本的重要承载者,本文聚焦中国“一流大学”毕业生,基于2018年《毕业生就业质量报告》,运用Cartogram地图呈现了毕业生的空间流动特征,并梳理政府人才政策文件构建了人才政策评价指标体系,运用有向迁移模型剖析毕业生流动的影响因素。结果表明：① 就学地存在粘滞性,但区域差异显著,毕业生向一线城市集聚。② 城市吸引力水平分异明显,部分城市通过发布人才政策以补充地方经济、舒适性吸引力的不足。③ 经济维度要素与城市舒适性均能有效吸引毕业生流入,较高房价收入比会引发“挤出效应”。人才政策中,落户政策对毕业生流入起激励作用。

Human capital has been acknowledged as a key driver for innovation, thereby promoting regional economic development in the knowledge era. University graduates from China’s “first-class” universities—the top 42 universities, included in the “double first-class” initiative, are considered highly educated human capital. Their migration patterns will exert profound impacts on regional development in China, however, little is known about the migration of these elite university graduates and its underlying driving forces. Using data from the 2018 Graduate Employment Reports, this study reveals that the uneven distribution of “first-class” universities and regional differentials largely shaped the migration of graduates from the university to work. Graduates were found aggregating in eastern first-tier cities, even though appealing talent-orientated policies aimed at attracting human capital had been launched in recent years by second-tier cities. Employing negative binomial models, this study investigates how the characteristics of the city of university and destinations affect the intensity of flows of graduates between them. The results showed that both jobs and urban amenities in the university city and destination city exert impacts on the inflow volume of graduates; whereas talent attraction policies introduced by many second-tier cities are found not to exert positive effects on attracting “first-class” university graduates presently. The trend of human capital migration worth a follow-up investigation, particularly given ongoing policy dynamics, and would shed light on the regional development disparities in China.

By looking into the enrollment and employment data of graduates from universities directly administered by China Ministry of Education and with the method of index evaluation and hot-cold spot analysis, this article analyzed the graduates’ regional flowing patterns of two flowing stages of enrolled in the university and employed after graduation, and the resulting spatial distribution at the provincial level. The study found that the flow of talent from the university to study in different stages, can more clearly reveal the characteristics of the geographical space for talents. The local spatial viscosity in different regions dominates the flow of talent, and geopolitical and income factors in subsequent plays a role of regional adjustment. In the two stages, the flow of talent has significant spatial viscous characteristics. The geographical pattern of the flow includes “local-leapfrog” mode, “local-semi adherent” mode and “local-adherent” mode. Under the influence of different factors, the enrollment stage is dominated by “local-(semi) adherent” mode due to the adherence to the geo-social relations, while the employment stage is dominated by “local-leapfrog” type, which is adhered to the multiple possibilities of regional employment opportunities and benefits. From the perspective of the provincial pattern formed by talent flow, however, the spatial distribution of talents at the level of provincial level is more flat, while the phase of employment flow is more polarized in the longitudinal distribution. The “arch” pattern along the southeastern coast and the Yangtze River is characterized in both two stages, and the Yangtze River Delta region belongs to the hot spot of talent. However, because of the lack of provincial integration and linkage, the centralization of talent is not significant enough in the central and western regions, which highlight the important effect of the dominant area’s viscosity in the formation of the high ground of talent. It is suggested that different cities should bring into full play the role of local glutinosity to enhance the work of introducing university intelligence, from the two stages of talent generation and with the help of the strength of the urban agglomeration.

依据教育部直属高校2015届本科毕业生生源与就业数据,采用指标评价与冷热点分析方法,分析升读大学与本科就业两个流动阶段的人才流动地域模式及省域空间分布格局。研究表明：① 人才流动具有明显的本地空间粘滞性特征,地域模式包括“本地-跃迁”型、“本地-半依附”型和“本地-依附”型。② 省际层面形成沿东南沿海与长江沿岸分布的“弓形”格局,显示了优势区域的整体粘滞性对人才高地形成的意义。研究指出,把握关键节点、依托城市群来发挥粘滞作用有助于城市推进引智工作。

In the era of knowledge economy, talent are acknowledged as a key driver for innovation, and thereby determine the vitality and competitiveness of regional economy. The competition of attracting talent initiated by some second-tier cities is increasingly heating up. The central government has repeatedly stressed the importance of reasonable, fair, smooth and orderly mobility of talent to facilitate economic transformation. Against this background, based on the “Graduate Employment Quality Report” and first-hand questionnaire survey data of university graduates from Nanjing, this study adopted chord diagram and map visualization to depict the previous and subsequent migration patterns of university graduates. Furthermore, multinominal logistic regressions were employed to explore the factors underlying graduates’ migration choice. The results show that the the number of people flowing into Nanjing for higher education decreases with the increase in distance. Nearly 84% of the graduates originally come from the eastern and central regions. After graduation, their subsequent migration shows further concentration to the east. Using a measurement of regional circulation, the overall migration path of graduates presents an “east-west asymmetric U-shaped” pattern, with the Yangtze River Delta region constituting the core area for graduates to flow to. The economic development level of the destination of graduates’ subsequent migration is obviously higher than that of their domicile, and the destination is often in close proximity to their domicile. At the individual level, the rank of the university, discipline, social netweok, and graduates’ evaluation on job opportunities all have significant influence on graduates’ migration decisions.

知识经济时代人才是决定区域经济竞争力的重要资源，各地政府发起的人才争夺战日益白热化，中央政府也一再强调应当引导合理、公正、畅通、有序的人才社会性流动。基于南京市高校《毕业生就业质量报告》和一手问卷调查数据，进行毕业生择校迁移与择业迁移模式并采用多项逻辑斯蒂回归模型探究其影响因素研究。研究表明：① 南京市高校毕业生中近84%来自东部和中部地区，而择业迁移进一步向东集聚。② 毕业生整体迁移路径呈“东西非对称U型”格局，长三角城市群构成毕业生流动的核心区域；就业地经济发展水平明显高于生源地且往往与生源地邻近。③ 个体的教育背景、家庭和社会网络和对就业机会的评估都会显著影响毕业生的流动类型选择。

Maintaining a young, well-educated labor force is an important strategy for regional economic development and social vitality. Based on a comparative study of China and Japan, this article aims to elicit 1) the factors that affect college students’ employment migration preference; and 2) the differences between migration preferences of students from the two countries and the possible explanations for such differences. With the use of survey data from approximately 2,000 college students in the two countries, this study identifies region of origin as a key determinant of employment migration choice in both countries. The region of origin functions as a critical point differentiating primary and secondary labor markets for individuals, whereas the first-tier region in each country is a popular work destination. A one-way bottom-up migration from lower-ranking to higher-ranking regions is revealed in our regional hierarchy model. Findings suggest that Chinese students were oriented to employment opportunities and economic well-being while Japanese students were more inclined to consider personal lifestyle and local amenities. The findings imply that reducing regional disparities in economic development and income levels in China and enhancing urban service facilities in Japan may encourage college graduates to remain in their home regions.

Members of the family of spatial-interaction models commonly referred to as gravity models are shown to be misspecified. One result of this misspecification is the occurrence of an undesirable ‘spatial-structure effect’ in estimated distance-decay parameters and this effect is examined in detail. An alternative set of spatial-interaction models is formulated from which more accurate predictions of interactions and more accurate parameter estimates can be obtained. These new interaction models are termed competing destinations models, and estimated distance-decay parameters obtained in their calibration are shown to have a purely behavioural interpretation. The implications of gravity-model misspecification are discussed.

The migration of skilled individuals has become an important issue in promoting new-type urbanization in China and a key factor affecting China's regional innovation output and high-quality development. Considering the issues of zero inflation and network autocorrelation in skilled migration data, this paper combines the eigenvector space filtering (ESF) technique and the "two-stage" hurdle model into a comprehensive united framework to construct a longitudinal spatial hurdle gravity model. It then has been employed in the case study exploring the spatiotemporal patterns and influencing factors of interprovincial skilled migration in China during 2000-2015. The results are listed as follows: First, from 2000 to 2015, the mobility proportion of the skilled migration increased first and then decreased. The agglomeration pattern of skilled migration maintains the imbalance of its spatial distribution. With the elapse of time, the migration of skilled presents a dispersing trend and drives the decline of its spatial distribution and agglomeration. Talent migration presents a persistent and significant network autocorrelation, and its distribution presents a persistent and significant spatial autocorrelation. Second, China's interprovincial skilled migration during 2000-2015 was driven by gravity factors (population scales at origin and destination, distance), regional economic and scientific and technological development (average wage, spending on science & technology and education), natural amenities (average temperature difference, air quality), urban amenities (public health and education services, urban greening), and other factors (social networks, the cost of living, and population density). Third, the migration of skilled people can be regarded as a "two-stage" process, where factors affecting its migration probability and migration scale are different. Such differences are mostly reflected in factors of amenities versus economy. Fourth, the impact of economic growth, investment in science and education, natural amenities, and basic public services on skilled migration has increased over time, while the impact of wages and urban greening has weakened over time. The conclusion of this paper provides policy references for regional talent management and the balance of regional development.

高技能人才迁移是推进新型城镇化建设的重要议题,也是影响地区创新产出和高质量发展的关键要素。针对人才迁移数据中蕴含的零膨胀和网络自相关特性,本文将特征向量空间滤波（ESF）技术和“两阶段”Hurdle模型结合,构建空间Hurdle引力模型,结合2000—2015年中国省际高技能人才迁移面板数据,研究人才迁移的时空演化格局和驱动机制。研究结论显示：① 2000—2015年人才迁移的跨省迁移比例先升后降;人才迁移表征出集聚格局,维系了其空间分布的不均衡性;随时间推移,人才迁移格局呈现分散趋势,人才空间分布集聚性下降;人才迁移和空间分布均呈现出持续显著的网络与空间自相关性特征。② 引力因素（人口规模、空间距离）、地区经济和科技发展水平（工资、科教投入）、自然舒适度（平均温差、空气质量）、城市舒适度（医疗及教育公共服务、城市绿化）以及其他因素（社会网络、生活成本、人口密度）共同驱动了跨世纪以来中国省际人才迁移过程。③ 人才迁移可被看作一个“两阶段”过程,影响其迁移概率和迁移规模的因素呈现一定差异。④ 经济增速、科教投入、自然舒适度和基础公共服务对人才迁移的影响随时间增强,而工资和城市绿化的影响随时间减弱。本文的研究结论为地区人才治理及实现地区均衡发展提供政策参考。

This paper explores the relationship between spatial structure and spatial interaction at the intraurban level. To examine this relationship an experimental framework is designed based on the application of a doubly constrained entropy-type gravity model to journey-to-work data for twenty-four Canadian urban areas. The study demonstrates that distance-decay exponents are strongly influenced by geographic structure and the geometry of origins and destinations. As such, both the influence of map pattern and the friction of distance should be explicitly incorporated into spatial interaction models. The paper also explores the impact of city size and the nature of the economic base of the urban area upon distance-decay exponents.

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.

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.

Using the spatial OD model<span>，<span>this study analyzes the migration flows among <span>31 <span>provinces <span>in China by exploring geographical effects<span>，<span>driving mechanism<span>，<span>and gender differences based on the inter-provincial migration data of the <span>6<span>th <span>Population Census<span>． <span>Inter-provincial migration exhibit significant <span>spatial dependence<span>，<span>in which the origin and destination separate spatial autocorrelation promotes migration<span>， <span>whereas the origin-destination joint spatial autocorrelation hinders migration<span>． <span>In general<span>， <span>the <span>&ldquo;<span>push<span>&rdquo;<span>from origin is weaker than the <span>&ldquo;<span>pull<span>&rdquo;<span>from destination in Chinese inter-provincial migration<span>．<br><span>There are significant gender differences in the driving mechanism<span>． <span>Impact of driving factors on female <span>migration is stronger than that for male migration<span>． <span>Unemployment risk and employment discrimination <span>are more evident in female migration<span>． <span>Males are more strongly influenced by spatial dependence than<br><span>females in the choice of migration destination<span>， <span>which could be explained by the gender differences of <span>endowment and social environment<span>．</span></span></span></span></span></span></span><br></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span>

文章基于空间OD模型和&ldquo;六普&rdquo; 人口省际迁移流数据， 研究中国人口省际迁移流的地缘效应、 驱动机制与男女差异。文章得出的主要结论: ( 1) 中国人口迁移流内含显著的空间依赖，其中迁出、 迁入地独立的空间自相关效应促进人口迁移， 而迁出地-迁入地交互的空间自相关效应阻碍人口迁移。( 2) 总体上，中国人口省际迁移流受迁出地推力作用弱于迁入地的拉力作用， 表明人口迁移更多是出于对迁入地的&ldquo;美好预期&rdquo; ，而非对迁出地的&ldquo;过度抱怨&rdquo;。( 3) 人口迁移流的驱动机制有显著的性别差异: 女性迁移流受驱动因子的影响强于男性，女性的失业风险、 就业歧视更为明显; 男性在人口迁移的空间选择上受空间依赖的影响强于女性，这与性别禀赋和社会环境有关。

The relationship between population distribution and resources, environment, social and economic development has attracted much attention for a long time. This paper set up an index system and some models for the assessment of the coordination between population and resources, environment, social and economic development. Then it used the index system and models to evaluate this coordination quantitatively at the county level. Based on this, the suitability and restriction of population distribution at the county level was graded and classified respectively, and its spatial and temporal patterns as well as regional characteristics were also revealed quantitatively. The results showed that: (1) population distribution was generally coordinated with human settlements environment in more than 3/5 of counties in China in 2010, which meant that population distribution was highly consistent with the natural suitability of human settlements environment at the county level; (2) population growth was merely not restricted by water and land resources in about half of counties in China in 2010, indicating that population distribution had medium coordination with the suitability of water and land resources; (3) population distribution was generally coordinated with social and economic development in more than 3/5 of counties in China in 2010, suggesting that population distribution was highly consistent with social and economic development; (4) the suitability degree of population distribution was larger than 60 in about 3/5 of counties in China in 2010, which showed that the relationship between population, resources, environment and development was coordinated or relatively coordinated; (5) as for the coordination between population, resources, environment and development at the county level, the eastern region was the best, the central region ranked second and the western region was the worst; (6) the suitability degree of population distribution at the county level could be identified into four grades, including basic coordination, relative coordination, under coordination and urgent need for coordination and 10 restricted classes.

以人口空间分布及其与资源环境和社会经济协调性评价为核心，提出了一整套人口与资源环境和经济社会发展协调水平评价的指标体系与模型方法；以分县为基本单元，定量评价了2010 年中国人口与资源环境和社会经济发展的协调性和协调程度；根据人口分布适宜度高低和限制性差别，划分了中国分县人口分布适宜等级和限制类型，定量揭示了中国不同地区人口与资源环境和社会经济协调发展的时空格局和地域特征。研究表明：① 2010 年中国有3/5 以上的县（市、区） 人口分布与人居环境基本适宜，中国分县人口分布与人居环境自然适宜性保持了高度一致性；② 2010 年中国有1/2 以上的县（市、区） 人口发展基本不受水土资源约束，分县人口分布与水土资源适宜性处于中等水平；③ 2010 年中国有超3/5 的县（市、区） 人口与社会经济发展基本协调，人口分布的社会经济协调性良好；④ 2010 年中国近3/5 的县（市、区） 人口分布适宜度在60 以上，人口资源环境与发展处于基本协调或相对协调状态；⑤2010 年中国分县人口资源环境与发展的协调程度东部优于中部、中部优于西部；⑥ 2010 年中国分县人口分布适宜度可划分为人口资源环境与发展基本协调、相对协调、有待协调和亟待协调4个适宜等级与10 个限制类型。

基于2000和2010年全国人口普查分县数据和地级行政单元数据,采用不均衡指数和空间自相关分析等方法,刻画中国高技能劳动力和一般劳动力的空间分布格局及其变化,并采用空间滞后模型,识别高技能劳动力与一般劳动力空间分布的决定因素及其变化。结果表明：① 两类劳动力总体的空间特征均为东南密集,西北稀疏;② 2000—2010年,高技能劳动力在空间分布上呈集中化的趋势,而一般劳动力呈分散化的趋势;③ 十年间高技能劳动力集聚区虹吸作用加强,其分布越发集中于沿海特大城市群,而一般劳动力集聚区回波作用加强,其分布越发均衡;④ 空间回归分析结果表明,职工平均工资、是否直辖市或省会、每万人在校高校学生、是否沿海城市、常住人口数和空间溢出效应在十年中一直都是决定高技能劳动力和一般劳动力空间分布的主要因素,而失业率、中学生师比、二氧化硫排放量和绿地率在2010年也成为影响两类劳动力空间分布的主要因素。对比两类劳动力的模型结果可得,高技能劳动力的空间分布受行政因素、高校因素和地区生活舒适度的影响更大,而一般劳动力的空间分布受劳动力市场因素的影响更大。

China has witnessed unprecedented urbanization over the past decades. The rapid expansion of urban population has been dominated by the floating population from rural areas, of which the spatiotemporal patterns, driving forces, and multidimensional effects have been scrutinized and evaluated by voluminous empirical studies. However, the urban and economic development mode has been reshaped by the globalization and marketization processes and the socioeconomic space has been restructured as a consequence. How has the spatial pattern of floating population evolved against these backdrops? How has the evolution been driven by the interaction of state and market forces? What have been the contribution of population mobility to the urbanization of origin and destination regions and the evolution of China's urban system? The latest national censuses conducted in 2000 and 2010 offer the opportunity to systematically answer these questions. Analysis based on the county-level data comes to conclusions as follows. (1) The spatial pattern of floating population remained stable over the first decade of the 21st century. Three coastal mega-city regions, namely the Yangtze River Delta, the Pearl River Delta, and the Beijing-Tianjin-Hebei Region, were major concentration areas. As the emergence and rapid development of other coastal mega-city regions, the coastal concentration area of floating population tended to geographically united as a whole, whereas the spatial distribution within each region variegated significantly. (2) Floating population gradually moved into provincial capitals and other big cities in interior regions and its distribution center of gravity moved northward around 110 km during the study period. (3) Compared with extensively investigated inter-provincial migrants, intra-provincial migrants had higher intention and ability to permanently live in cities they worked in and thus might become the main force of China's urbanization in the coming decades. (4) The spatial pattern of floating population was shaped jointly by the state and market forces in transitional China. While the impacts of state forces have been surpassed by market forces in the country as a whole, they are still important in shaping the development space of central and western China. (5) The massive mobility of population contributed a large proportion to the increase of urbanization levels of both origin and destination regions and reshaped China's urban system in terms of its hierarchical organization and spatial structure.

基于2000和2010年全国人口普查分县数据,对中国流动人口空间格局的演变特征、形成机制及其城镇化效应进行了系统分析。研究发现,流动人口分布的空间格局具有较强的稳定性,长三角、珠三角和京津冀等沿海城市群仍然是其主要集中地,且沿海集中区有连绵化的趋势,但在城市群内部的空间分布模式差异显著。流动人口向内陆地区的省会等特大城市集中趋势明显,其分布重心出现了明显的北移。省内县际的流动人口规模已接近于省际流动,且有更高的意愿和更强的能力永久居留城镇,省内县际的永久性迁移将成为未来中国人口城镇化的主导模式。中国流动人口迁入地的选择受到政府和市场双重力量的影响,后者的影响力更强。远距离流入东部地区的人口在务工之外,对享受城市生活也开始有所考虑;而中西部地区政府力量在引导人口流动中仍起到重要作用。大规模的人口流动对流出地和流入地的城镇化水平提高均有显著贡献,同时在很大程度上重构了中国城镇体系的等级规模结构和空间布局模式。

With the loosing of the household registration (hukou) system, China has witnessed massive volumes of interregional migration. Among all kinds of migration, skilled migration and less-skilled migration present differential spatial patterns and network characteristics over time and may exert distinguished impacts on regional development and innovation. However, due to limited data availability, prior studies only adopted cross-sectional data analysis and examined the patterns of skilled and less-skilled migrations before 2005, whereas few have been done on related topics after 2005. Drawing on previous studies, the present paper uses micro-level datasets from population censuses and sample surveys to assess the spatial evolution patterns of China's skilled and less-skilled internal migrations between 1995 and 2015. Besides, several complex network analysis methods have been employed, together with the network visualization technique. The results of the paper are listed as follows. First, there were spatial clustering and uneven patterns in both skilled and less-skilled internal migrations over the 20 years of 1995-2015, where migration flows containing a large percentage of skilled and less-skilled migrants originated from inland western and central regions to the eastern coastal areas of China. However, the degree of spatial unevenness in the migration patterns has been slightly weakened. In addition, the average migration distance of skilled migration was farther than that of less-skilled migration in the same period. Second, both of the two migration networks have presented a “small-world” property over the 20 years. In comparison, the intensity and connection degree of less-skilled migration networks have prevailed over that of the skilled migration networks. Third, results from the community detection have revealed that both skilled and less-skilled migrations exhibited a network structure where Beijing, Shanghai, and Guangdong served as the core nodes. Skilled migration presented a more stable network structure during the 20 years, while less-skilled migrations showed a persistently changing pattern. Fourth, the paper suggested that regional economic disparity, path dependence effect, the heterogeneity of different labour forces in the job market, and the differences in labour market demand for different labour forces were underpinning factors shaping the spatial evolution pattern and network structure of the two types of migration from 1995 to 2015.

自户籍制度放宽以来,中国经历了大规模的人口迁移。其中,异质性劳动力（高技能劳动力、普通劳动力）在迁移过程中表征出不同的空间格局和网络组织特征,对地区经济发展产生各异的影响。本研究基于人口普查和抽样调查微观抽样数据,使用复杂网络理论对1995—2015年中国异质性劳动力迁移的时空格局和网络演化展开分析,并分析了格局背后的可能成因。研究发现：① 省际高技能和普通劳动力迁移均呈现出持续高度不平衡的空间集聚特征,承载大量人口的迁移流主要由中国中西部地区指向东部沿海地区,但这种空间不平衡特征呈现出一定的减弱趋势。高技能劳动力的平均迁移距离比普通劳动力更长;② 两类劳动力迁移网络中均呈现明显的“小世界”特性,但普通劳动力迁移网络的迁移强度和关联程度均高于高技能劳动力迁移网络;③ 两类劳动力迁移网络均呈现出以北京、上海、广东为主要核心节点的网络结构。高技能劳动力网络结构呈现相对稳定的特征,而普通劳动力网络结构则呈现出变化的趋势;④ 地区经济差异、路径依赖效应、异质性劳动力在就业市场上的差异性以及劳动力市场对异质性劳动力需求的差异是导致两类劳动力迁移格局差异性的重要成因。