Geographical Research, Volume. 39, Issue 9, 2130(2020)

The spatio-temporal characteristics of the Guangdong-Hong Kong-Macao Greater Bay Area's population aging and its economic effects

Qiong LI1,2, Songlin LI1, Lanlan ZHANG3, Hao LI4, and Yi LIU5、*
Author Affiliations
  • 1Business School of Jishou University, Jishou 416000, Hunan China
  • 2Jishou University Academician Workstation, Institute of Geographic Sciences and Natural Resources Research, CAS, Jishou 416000, Hunan China
  • 3School of Economics and Management, Changsha University of Science and Technology, Changsha 410000, China
  • 4School of Accounting, Hunan University of Technology and Business, Changsha 410205, China
  • 5Academy of Great Bay Area Studies, Guangzhou 510070, China
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    Figures & Tables(15)
    Population aging trends in the Guangdong-Hong Kong-Macao Greater Bay Area, Guangdong Province, and China from 1990 to 2015
    Per capita GDP trend of the Guangdong-Hong Kong-Macao Greater Bay Area from 1990 to 2015
    Evolution of the spatial pattern of aging coefficients in the Guangdong-Hong Kong-Macao Greater Bay Area in 1990, 2000, 2010 and 2015
    Evolution of the spatial pattern of per capita GDP in the Guangdong-Hong Kong-Macao Greater Bay Area in 1990, 2000, 2010 and 2015
    LISA clustering chart of per capita GDP of the Guangdong-Hong Kong-Macao Greater Bay Area in 2015
    • Table 1. Aging coefficient and population age structure (%)

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      Table 1. Aging coefficient and population age structure (%)

      老龄化系数(P)人口结构类型老龄化系数(P)人口结构类型
      P < 4.0年轻型7~10老年型I期
      4.0~5.5成年型I期10~14老年型II期
      5.5~7.0成年型II期P≥14.0老年型III期
    • Table 2. Evolution of population age structure in the Guangdong-Hong Kong-Macao Greater Bay Area from 1990 to 2015

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      Table 2. Evolution of population age structure in the Guangdong-Hong Kong-Macao Greater Bay Area from 1990 to 2015

      1990年2000年2010年2015年
      深圳年轻型年轻型年轻型年轻型
      东莞成年型I期年轻型年轻型年轻型
      惠州成年型II期成年型II期成年型II期成年型II期
      中山成年型II期成年型I期成年型I期成年型II期
      佛山成年型II期成年型I期成年型I期成年型II期
      珠海成年型I期成年型I期成年型I期成年型II期
      广州成年型II期成年型II期成年型II期老年型I期
      肇庆成年型II期老年型I期老年型I期老年型II期
      澳门成年型II期老年型I期老年型I期老年型I期
      江门老年型I期老年型I期老年型I期老年型II期
      香港老年型I期老年型II期老年型II期老年型III期
      区域平均成年型II期成年型II期成年型II期老年型I期
      全国成年型II期老年型I期老年型I期老年型II期
    • Table 3. [in Chinese]

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      Table 3. [in Chinese]

      地区1990年2000年2010年2015年
      人均GDP老龄化系数人均GDP老龄化系数人均GDP老龄化系数人均GDP老龄化系数
      广州10386.3030956.10129186.67218607.92
      佛山8696.7724435.25118635.25173836.79
      肇庆3256.238967.8641349.08781210.2
      深圳13212.2239611.23139291.79253592.90
      东莞9504.9916522.0977992.29121373.74
      惠州4185.9416766.2357095.91106316.55
      珠海10574.6233544.03115055.01200266.64
      中山7336.2818214.6289804.43150935.73
      江门5097.9415528.6652629.08796311.39
      香港131108.462531910.943255013.084243015.29
      澳门100416.59148797.08526507.38707958.98
      区域平均30706.5656095.64129805.96205097.37
    • Table 4. Moran ’s I test results of the global per capita GDP of the Guangdong-Hong Kong-Macao Greater Bay Area

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      Table 4. Moran ’s I test results of the global per capita GDP of the Guangdong-Hong Kong-Macao Greater Bay Area

      Moran’s IE(I)SDZP
      0.2681-0.02330.10452.78320.0170
    • Table 5. Regression results of the impact of population aging on economic growth in the Guangdong-Hong Kong-Macao Greater Bay Area

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      Table 5. Regression results of the impact of population aging on economic growth in the Guangdong-Hong Kong-Macao Greater Bay Area

      被解释变量:ln Y
      VariableOLSSEMSAR
      Constant-11.4904***(1.93)-13.4848***(1.45)-11.1651***(1.81)
      p-0.0343**(0.02)-0.0291**(0.01)-0.0284*(0.02)
      ln K0.5694***(0.10)0.5799***(0.08)0.5519***(0.10)
      ln L1.5501***(0.18)1.7165***(0.13)1.3829***(0.20)
      Rho0.1468(1.17)
      Lambda-0.5047**(0.20)
      Adj-R-squared0.7955
      AIC23.704319.944724.6494
      SC30.841127.081533.5703
      Log likelihood-7.8522-5.9723-7.3247
    • Table 6. Model regression results under economic distance weight matrix and geographical distance weight matrix

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      Table 6. Model regression results under economic distance weight matrix and geographical distance weight matrix

      被解释变量:ln Y
      Variable经济距离权重地理距离权重
      SEMSARSEMSAR
      Constant-15.7945***(2.46)-10.7587***(1.66)-11.4904***(1.90)-22.2587***(2.03)
      p-0.0449***(0.01)-0.0459***(0.01)-0.0343**(0.02)-0.0350**(0.02)
      lnK0.5545***(0.08)0.548***(0.08)0.5694***(0.10)0.5815***(0.09)
      lnL1.5381***(0.15)1.5185***(0.15)1.5501***(0.17)1.5828***(0.17)
      Rho-0.3146***(0.10)0.9091***(0.06)
      Lambda-0.3006***(0.10)1.1000***(0.07)
      Adj-R-squared
      AIC18.755518.802922.271024.2710
      SC29.460729.508029.407733.1919
      Log likelihood-3.3778-3.4015-7.1355-7.1355
    • Table 7. Evolution of the age structure of Hong Kong's population from 1990 to 2018

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      Table 7. Evolution of the age structure of Hong Kong's population from 1990 to 2018

      年份老龄化系数(%)类型人均GDP(美元)年份老龄化系数(%)类型人均GDP(美元)
      19908.46老年型I期13110200512.25老年型II期26093
      19918.73老年型I期14955200612.43老年型II期27697
      19929.00老年型I期17356200712.61老年型II期29902
      19939.25老年型I期19659200812.69老年型II期30871
      19949.51老年型I期21673200912.89老年型II期30696
      19959.78老年型I期22765201013.08老年型II期32550
      199610.12老年型II期24702201113.31老年型II期35142
      199710.42老年型II期27169201213.70老年型II期36732
      199810.66老年型II期25507201314.27老年型III期38403
      199910.93老年型II期24713201414.71老年型III期40315
      200010.94老年型II期25319201515.29老年型III期42430
      200111.22老年型II期24771201615.85老年型III期43735
      200211.52老年型II期24120201716.43老年型III期46221
      200311.82老年型II期23293201816.99老年型III期48672
      200412.07老年型II期24454
    • Table 8. ADF unit root test

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      Table 8. ADF unit root test

      变量ADF检验各显著性水平的临界值
      0.010.050.10
      lnY-2.4939-4.6679-3.7332-3.3103
      D(lnY)-3.4700-3.9591-3.0810-2.6813
      lnK-2.6971-4.8000-3.7912-3.3423
      D(lnK)-7.6940-4.8000-3.7912-3.3423
      lnL-1.9862-4.6679-3.7332-3.3103
      D(lnL)-4.0244-3.9591-3.0810-2.6813
      O-2.1373-4.6679-3.7332-3.3103
      D(O)-2.8201-4.7283-3.7597-3.3249
      D(D(O))-5.3735-4.0044-3.0989-2.6904
    • Table 9. Johansen cointegration test results

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      Table 9. Johansen cointegration test results

      假设条件EigenvalueTrace Statistic5% Crititical ValueProb.
      None0.982799.274447.85610.0000
      At most 10.909442.479429.79710.0011
      At most 20.39078.855015.49470.3790
    • Table 10. regression results of the impact of population aging on economy

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      Table 10. regression results of the impact of population aging on economy

      VariableCoefficientStd.Errort-statisticProb.
      Constant-27.33224.7933-5.70220.0001
      lnL2.44370.40386.05210.0001
      D(p)-0.40530.1842-2.20040.0481
      lnK1.01600.13157.72710.0000
      R-squared0.9010Mean dependent var12.3441
      Adjusted R-squared0.8763S.D. dependent var0.1869
      S.E. of regression0.0657Akaike info criterion-2.3937
      Sum squared resid0.0519Schwarz criterion-2.2005
      Log likelihood23.1496Hannan-Quinn criter.-2.3838
      F-statistic36.4117Durbin-Watson stat2.0637
      Prob(F-statistic)0.0000
      Sample(adjusted):1997:2012
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    Qiong LI, Songlin LI, Lanlan ZHANG, Hao LI, Yi LIU. The spatio-temporal characteristics of the Guangdong-Hong Kong-Macao Greater Bay Area's population aging and its economic effects[J]. Geographical Research, 2020, 39(9): 2130

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    Paper Information

    Received: May. 6, 2020

    Accepted: --

    Published Online: Apr. 23, 2021

    The Author Email: LIU Yi (liuy@igsnrr.ac.cn)

    DOI:10.11821/dlyj020200360

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