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Geography of talent in China During 2000-2015:An Eigenvector Spatial Filtering Negative Binomial Approach

Chinese Geographical Science 2021年第2期31卷 297-312页

作者： GU Hengyu Francisco ROWE LIU Ye SHEN Tiyan School of Government Peking UniversityBeijing 100871China Geographic Data Science Lab Department of Geography and PlanningUniversity of LiverpoolLiverpool L69United Kingdom School of Geography and Planning Sun Yat-sen UniversityGuangzhou 510275China Guangdong Key Laboratory for Urbanization and Geo-Simulation Sun Yat-sen UniversityGuangzhou 510275China

The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and *** how educated talent locates and re-locates across the country can guide future policy discussions of equality,firm localization and service *** studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in ***,few adopt longitudinal analysis to examine the temporal dynamics in the stregnth of existing *** released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in *** four-year city-level data from national population censuses and 1%population sample surveys conducted every five years between 2000 and 2015,we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over *** reveal that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and *** also shows gradually strengthened and significantly positive spatial autocorrelation in the distribution of *** eigenvector spatial filtering negative binomial panel is employed to model the spatial determinants of talent *** indicate the influences of both economic opportunities and urban amenities,particularly urban public services and greening rate,on the distribution of *** results highlight that urban economic-and amenity-related factors have simultaneously driven China’s talent’s settlement patterns over the first fifteen years of the 21st century.

关键词： talent distribution determinants eigenvector spatial filtering panel data analysis China

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