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Analysis of the agglomeration of Chinese manufacturing industries and its effect on economic growth in different regions after entering the new normal

Fangxu Ren
Fangxu Ren
   | 08. Apr. 2021
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Online veröffentlicht: 08. Apr. 2021
Seitenbereich: 89 - 98
Eingereicht: 25. Nov. 2020
Akzeptiert: 31. Jan. 2021
DOI: https://doi.org/10.2478/amns.2021.1.00025
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© 2021 Fangxu Ren, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Scatter point relationship between main variables.A. Industrial agglomeration and industrial added value B. Investment in fixed assets, government expenditure and industrial added value
Scatter point relationship between main variables.A. Industrial agglomeration and industrial added value B. Investment in fixed assets, government expenditure and industrial added value

Estimated results of EG indices and economic growth

Explained variable lngdp
Explanatory variables Fe model Re model Be model A model B model
L1.lngdp 0.83*** 0.85***
14.8 14.02
EG −0.10 −0.04 0.97 1.07 2.86***
−0.38 (−0.13) −1.04 0.84 3.05
EG2 −5.2**
−2.18
lnge 0.61*** 1.01*** 0.94*** 0.16*** 0.15***
5.01 9.45 5.17 2.96 2.13
lnassets 0.21*** 0.30*** 0.54*** 0.14*** 0.13***
6.00 8.53 8.03 3.25 3.26
Constant 106.66*** 196.12*** −3.49*** 47.44*** 48.40***
4.40 9.08 (−3.06) 6.17 5.27
Time control −0.05*** −0.10*** (omitted) −0.02*** −0.02***
−4.17 (−8.90) (−6.13) (−5.20)
Area control Yes Yes
Wald – chi2 1326.05 1269.25
Wald – Prob. 0 0
Sargan – chi2 7.7003 9.0495
Sargan – Prob. 0.3598 0.2491
Abond AR(1) 0.0483 0.0494
Abond AR(2 0.9076 0.8012

Industrial agglomeration status of 31 provinces and cities in China's manufacturing industry from 2012 to 2016

Area Gini index EG index
2012 2016 Increase or decrease Increase 2012 2016 Increase or decrease Increase Rank Rank increase or decrease
Beijing 0.013 0.016 0.002 18.92 0.013 0.016 0.002 19.08 13 0
Tianjing 0.011 0.005 −0.006 −58.1 0.011 0.005 −0.006 −58.1 24 −8
Hebei 0.014 0.018 0.004 26.74 0.014 0.018 0.004 27.09 11 1
Shanxi 0.017 0.008 −0.01 −56 0.017 0.008 −0.01 −56.1 16 −7
Neimenggu 0.004 0.006 0.002 59.59 0.004 0.006 0.002 59.77 20 5
North mean 0.012 0.01 −0.001 −12.6 0.012 0.01 −0.001 −12.6
Liaoning 0.044 0.026 −0.018 −41.5 0.044 0.026 −0.018 −41.6 9 −2
Jilin 0.011 0.018 0.007 66.7 0.011 0.018 0.007 66.76 10 7
Heilongjiang 0.015 0.005 −0.01 −64.1 0.015 0.005 −0.01 −64.1 23 −12
Northeast mean 0.023 0.016 −0.007 −29.6 0.023 0.016 −0.007 −29.6
Shanghai 0.026 0.028 0.002 9.247 0.026 0.028 0.002 9.628 7 1
Jiangsu 0.057 0.11 0.053 92.14 0.057 0.11 0.053 93.23 2 3
Zhejiang 0.140 0.081 −0.06 −42.5 0.141 0.081 −0.06 −42.6 3 0
Anhui 0.005 0.004 −0.002 −29.2 0.005 0.004 −0.002 −29.5 26 −3
Fujian 0.158 0.075 −0.082 −52.1 0.158 0.075 −0.083 −52.2 4 −2
Jiangxi 0.004 0.007 0.003 82.91 0.004 0.007 0.003 83.03 17 9
Shandu 0.066 0.054 −0.012 −17.9 0.066 0.054 −0.012 −18 5 −1
Eastern mean 0.065 0.051 −0.014 −21.2 0.065 0.051 −0.014 −21.3
Henan 0.011 0.027 0.015 132.8 0.011 0.026 0.015 134.2 8 10
Hubei 0.013 0.012 −0.001 −9.58 0.013 0.012 −0.001 −9.67 15 −1
Hunan 0.012 0.007 −0.005 −39.5 0.012 0.007 −0.005 −39.5 18 −3
Guangdong 0.168 0.429 0.262 156.2 0.169 0.44 0.272 161.2 1 0
Guangxi 0.009 0.006 −0.002 −25.5 0.008 0.006 −0.002 −25.5 19 1
Hainan 0.000 0.000 0.000 −22.6 0.000 0.000 0.000 −22.6 30 −1
South Central mean 0.035 0.08 0.045 126.2 0.036 0.082 0.046 130.4
Chongqing 0.008 0.006 −0.003 −31.9 0.008 0.005 −0.003 −32.1 22 −1
Sichuan 0.017 0.016 −0.001 −5.47 0.017 0.016 −0.001 −5.4 12 −2
Guizhou 0.007 0.004 −0.003 −47.8 0.007 0.004 −0.003 −47.8 27 −5
Yunnan 0.047 0.044 −0.002 −5.2 0.047 0.044 −0.002 −5.19 6 0
Xizang 0.000 0.000 0.000 2.598 0.000 0.000 0.000 2.594 31 −1
Southwest mean 0.016 0.014 −0.002 −11.9 0.016 0.014 −0.002 −11.9 0
Shanxi 0.009 0.012 0.003 33.94 0.009 0.012 0.003 34.07 14 5
Gansu 0.005 0.006 0.001 15.31 0.005 0.006 0.001 15.39 21 3
Qinghai 0.001 0.001 0.000 −31.4 0.001 0.001 0.000 −31.4 29 −1
Ningxia 0.000 0.001 0.000 42.15 0.000 0.001 0.000 42.2 28 3
Xinjiang 0.004 0.004 0.000 12.51 0.004 0.004 0.000 12.51 25 2
Northwest mean 0.004 0.005 0.001 22.15 0.004 0.005 0.001 22.23
National average 0.029 0.033 0.004 15.45 0.029 0.034 0.005 16.49

Descriptive statistics of variables

Variable Observations Meaning Unit Mean Standard deviation Minimum value Max LLC inspection
lngdp 155 Industrial added value 100 million yuan 8.592 1.241 4.014 10.394 −12.186
eg 155 Index - 0.033 0.075 0.000 0.474 −71.246
eg2 155 Exponent square - 0.007 0.033 0.000 0.225 −53.053
lnassets 155 Manufacturing fixed asset investment (excluding farmers) 100 million yuan 7.947 1.364 3.362 10.060 −4.206
lnge 155 Fiscal General Budget Expenditure 100 million yuan 8.226 0.568 6.762 9.506 −19.127
time 155 Time-controlled variable year 2014 1.419 2012 2016 -
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