地理学报 ›› 2021, Vol. 76 ›› Issue (2): 326-340.doi: 10.11821/dlxb202102006

• 人口与城市研究 • 上一篇    下一篇

中国高学历人才的空间演化特征及驱动因素

古恒宇(), 沈体雁()   

  1. 北京大学政府管理学院,北京 100871
  • 收稿日期:2019-03-27 修回日期:2020-08-01 出版日期:2021-02-25 发布日期:2021-04-25
  • 作者简介:古恒宇(1994-), 男, 广东广州人, 博士生, 研究方向为空间人口学、区域分析与规划。E-mail: henry.gu@pku.edu.cn
  • 基金资助:
    国家社会科学基金项目(17ZDA055);国家自然科学基金项目(71733001)

Spatial evolution characteristics and driving forces of Chinese highly educated talents

GU Hengyu(), SHEN Tiyan()   

  1. School of Government, Peking University, Beijing 100871, China
  • Received:2019-03-27 Revised:2020-08-01 Published:2021-02-25 Online:2021-04-25
  • Supported by:
    National Social Science Foundation of China(17ZDA055);National Natural Science Foundation of China(71733001)

摘要:

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。

关键词: 高学历人才, 空间演化, 驱动因素, 地级以上城市, 中国

Abstract:

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.

Key words: highly educated talents, spatial patterns, driving forces, prefecture-level cities, China