Geographical Research, Volume. 39, Issue 9, 2000(2020)

Talents concentration in the Guangdong-Hong Kong-Macao Greater Bay Area, China: Evolution pattern and driving factors

Honggang QI1, Wei QI2,3、*, and Shenghe LIU2,3
Author Affiliations
  • 1School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
  • 2Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    Figures & Tables(12)
    Definitions of talents in China
    Spatial distribution of the share of talents in the Guangdong-Hong Kong-Macao Greater Bay Area from 2005 to 2015
    Service and manufacturing employment share of different counties in the Guangdong-Hong Kong-Macao Greater Bay Area in 2015
    The correlations between shares of highly-educated and highly-skilled talents
    Relationships among highly-educated, less-educated, highly-skilled and lowed-skilled workers in 2015
    Talents share comparisons among Hong Kong, Macao and prefecture-level cities in the Pearl River Delta in 2015
    The gap between the level of concentration of highly-educated and highly-skilled talents
    • Table 1. Talents distribution of top three urban agglomerations in China

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      Table 1. Talents distribution of top three urban agglomerations in China

      城市群高学历人才占比与规模高技能人才占比与规模
      2005年2010年2015年2005年2010年2015年
      粤港澳大湾区12.4716.3522.1312.8114.0715.17
      (402.26)(649.59)(858.78)(413.04)(558.99)(588.47)
      其中:珠三角9.5913.5619.2810.2011.9612.52
      (274.96)(487.01)(667.59)(292.58)(429.63)(433.35)
      京津冀10.2114.8321.2812.5811.4114.08
      (527.04)(853.95)(1193.72)(649.03)(657.03)(789.77)
      长江三角洲9.3014.8120.0310.2612.7014.00
      (720.74)(1332.83)(1769.11)(794.98)(1143.50)(1236.60)
    • Table 2. Statistics of employment, economy and education of top three urban agglomerations in China

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      Table 2. Statistics of employment, economy and education of top three urban agglomerations in China

      城市群2015人均GDP(万元)2015年第三产业就业人口占比(%)211高校数量
      粤港澳大湾区12.6646.5511
      其中:珠三角10.6042.064
      京津冀7.0545.5131
      长江三角洲10.2642.3022
    • Table 3. The coefficient of variance of the share of highly-educated and highly-skilled workers

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      Table 3. The coefficient of variance of the share of highly-educated and highly-skilled workers

      2005年2010年2015年
      高学历人才1.000.880.83
      高技能人才0.770.670.70
    • Table 4. Description and statistics of explanatory variables

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      Table 4. Description and statistics of explanatory variables

      符号变量说明Obs2005年2010年2015年
      MeanStdMeanStdMeanStd
      MAU制造业劳动力占就业人口的比例(%)2428.1320.9031.5621.0530.0217.63
      TER服务业劳动力占就业人口的比例(%)2430.8718.9033.2220.1440.1519.05
      WAG职工平均工资(元)2424643.2025964.9037212.6020993.3062719.1027184.00
      MED每万人医疗卫生机构床位数(张/万人)2423.0611.4325.3411.2338.3619.36
      EDU每千人高学历在校生(人/千人)248.9015.7813.6225.3518.1632.30
      MST中学在校生与教师的比值2418.471.8116.121.6312.971.49
    • Table 5. Regression results of drivers of talent concentration

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      Table 5. Regression results of drivers of talent concentration

      高学历人才占比高技能人才占比
      MAU-0.1870.0190.0520.026
      (-1.602)(0.293)(0.643)(0.664)
      TER0.961***0.750***0.850***0.840***
      (3.742)(4.562)(4.801)(8.039)
      WAG0.533***0.305***0.1100.105
      (3.951)(2.834)(1.177)(1.492)
      MST0.385-0.0890.0670.147
      (1.108)(-0.313)(0.279)(0.772)
      MED-0.478**-0.205-0.389***-0.285***
      (-2.589)(-1.427)(-3.056)(-3.034)
      EDU0.357***0.236***0.0840.097***
      (2.833)(4.298)(0.971)(2.811)
      _cons-6.189***-3.155*-1.104-1.520
      (-2.848)(-1.868)(-0.737)(-1.360)
      N72727272
      R20.7380.8520.5570.856
      Hausman′s p0.1280.118
      ModelFEREFERE
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    Honggang QI, Wei QI, Shenghe LIU. Talents concentration in the Guangdong-Hong Kong-Macao Greater Bay Area, China: Evolution pattern and driving factors[J]. Geographical Research, 2020, 39(9): 2000

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    Paper Information

    Received: Jun. 22, 2020

    Accepted: --

    Published Online: Apr. 23, 2021

    The Author Email: QI Wei (qiwei@igsnrr.ac.cn)

    DOI:10.11821/dlyj020200575

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