Journal of Natural Resources, Volume. 35, Issue 4, 767(2020)

Impact of China's "four modernizations" on water footprint intensity

Cai-zhi SUN1...2,*, Can-can ZHANG1 and Xiao-wen GAO1 |Show fewer author(s)
Author Affiliations
  • 1School of Geography, Liaoning Normal University, Dalian 116029, Liaoning, China
  • 2Marine Economics and Sustainable Development Research Center, Liaoning Normal University, Dalian 116029, Liaoning, China
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    Figures & Tables(8)
    • Table 1. The selection of "four modernizations" index

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      Table 1. The selection of "four modernizations" index

      一级指标二级指标计算方法权重
      工业化水平工业劳动生产率工业增加值/第二产业就业人数/(元/人)0.0041
      工业就业比例第二产业就业人数/就业总人数/%1.0316
      工业产出比例第二产业增加值/地区生产总值/%0.0226
      工业固体废物综合利用率0.0153
      科技投入比例R&D经费支出占地区生产总值的比例/%0.0056
      信息化水平固定电话普及率固定电话/总人口数/(户/万人)0.0090
      移动电话普及率移动电话/总人口数/(户/万人)0.0108
      互联网普及率宽带互联网接入数/总人数/(户/万人)0.0163
      年末邮电局总数0.9386
      邮电业务指数邮电业务总量/总人口数/(元/人)0.4998
      城镇化水平人口城镇化率城镇人口/总人口/%0.9356
      城镇居民恩格尔系数城镇居民食品支出/消费支出/%0.1622
      就业城镇化率城镇就业人数/就业总人数/%0.3335
      建成区绿化覆盖率绿化覆盖率/城区面积/%0.1946
      每万人拥有公共交通车辆公共交通运营车标台数/(城区人口+城区暂住人口)/标台0.1453
      农业现代化水平农业劳均经济产出农林牧渔业总产值/第一产业从业人数/(元/人)0.0671
      农业机械化水平农业机械总动力/耕地面积/(kW/hm2)0.1900
      有效灌溉率实际灌溉面积/灌溉总面积/%1.0734
      农村居民恩格尔系数农村居民食品支出/消费支出/%0.0002
      城乡居民收入比城镇居民家庭人均可支配收入/农村居民家庭人均纯收入/%0.0013
    • Table 2. Water footprint intensity level in 30 provincial-level regions in China in some years (104 m3/104 yuan)

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      Table 2. Water footprint intensity level in 30 provincial-level regions in China in some years (104 m3/104 yuan)

      地区2000年2004年2008年2012年2016年
      北京0.06750.04170.03120.02440.0204
      天津0.08040.05090.03230.02110.0160
      河北0.25730.18170.13730.10210.0815
      山西0.28660.19170.11570.09710.0742
      内蒙古0.38670.30720.22000.14050.0926
      辽宁0.15630.12390.08550.05830.0511
      吉林0.29250.25230.15910.10880.0900
      黑龙江0.42510.32440.25880.18940.1171
      上海0.08160.05290.03740.02810.0207
      江苏0.18900.11940.08000.05370.0537
      浙江0.14760.08600.05650.04070.0277
      安徽0.43830.32450.22610.15340.1077
      福建0.18400.12890.08340.05890.0446
      江西0.47870.32660.23260.15770.1290
      山东0.23040.13770.09270.06610.0638
      河南0.35220.24820.18120.13010.0867
      湖北0.35690.23430.16580.11210.0690
      湖南0.42390.30390.19440.12990.0876
      广东0.16060.10220.06170.04940.0421
      广西0.51750.34100.21630.14820.1457
      海南0.33140.23810.18110.13430.1108
      重庆0.32870.23440.15350.08850.0601
      四川0.49190.32900.20510.13050.0747
      贵州0.64390.46570.29140.16380.1087
      云南0.35300.26140.20300.14440.0896
      陕西0.36750.26650.18390.13020.1140
      甘肃0.37070.26580.20380.15480.0915
      青海0.32670.23810.17000.09150.0459
      宁夏0.40990.28750.26130.19560.2080
      新疆0.32540.24980.20660.17830.1607
    • Table 3. The level of "four modernizations" in 30 provincial-level regions in China in 2016

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      Table 3. The level of "four modernizations" in 30 provincial-level regions in China in 2016

      地区工业化信息化城镇化农业现代化
      北京0.175128.19710.99230.4273
      天津0.311616.08861.09520.4115
      河北0.211415.13910.97690.4401
      山西0.207613.80210.96280.2400
      内蒙古0.340214.55870.96000.2145
      辽宁0.263315.07341.02020.1575
      吉林0.246411.27020.94490.1322
      黑龙江0.014614.94120.96300.2262
      上海0.240924.83831.13380.6130
      江苏0.282221.50431.06590.5023
      浙江0.292321.80651.06820.4285
      安徽0.186113.79270.95830.4348
      福建0.258519.86781.04030.4934
      江西0.200513.48630.99460.3777
      山东0.240719.94551.01250.4143
      河南0.208521.16130.92700.3899
      湖北0.198813.32220.97270.3511
      湖南0.190012.11480.95820.4426
      广东0.268335.85551.08300.4575
      广西0.176612.94480.93060.2334
      海南0.312810.16360.99740.2599
      重庆0.209715.19171.01460.1865
      四川0.186227.78830.95910.2660
      贵州0.138111.39670.87220.1751
      云南0.136912.20150.91330.1794
      陕西0.238716.00770.99540.2188
      甘肃0.160812.48250.87930.1753
      青海0.20728.42180.95560.2309
      宁夏0.145412.38380.97190.2518
      新疆0.194310.18510.91630.5063
      最大值0.340235.85551.13380.6130
      最小值0.01468.42180.87220.1322
      平均值0.214816.53110.98450.3279
      方差0.004037.82110.00370.0166
      标准差0.06366.14990.06060.1288
      变异系数0.29620.37200.06160.3928
    • Table 4. Variance expansion factor VIF value of each explanatory variable

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      Table 4. Variance expansion factor VIF value of each explanatory variable

      变量INDINFURBAGRrjGDPPATPCPIIUAMean VIF
      VIF3.921.712.522.376.734.391.306.513.68
    • Table 5. Statistical description of the main variables

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      Table 5. Statistical description of the main variables

      变量均值标准差变异系数最小值最大值样本数/个
      Y0.17320.11160.64430.01600.6439510
      IND0.15990.05910.36980.01460.3402510
      INF14.81868.28150.55891.264772.3543510
      URB0.77810.22390.28780.26121.1588510
      AGR0.28070.11710.41700.08700.6130510
      rjGDP2.14931.57000.73050.27428.9392510
      PAT4.25517.18971.68970.129946.2853510
      PCP7.61673.74830.49211.299423.5310510
      IIUA0.71080.80071.12650.00444.7668510
    • Table 6. OLS regression results of water footprint intensity of four modernizations in each provincial-level region

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      Table 6. OLS regression results of water footprint intensity of four modernizations in each provincial-level region

      解释变量123456
      rjGDP-0.0751***
      (0.0121)
      -0.0362*
      (0.0186)
      -0.0361*
      (0.0188)
      -0.0161
      (0.0123)
      -0.0140
      (0.0113)
      -0.0195**
      (0.0091)
      PAT0.0063***
      (0.0014)
      0.0036**
      (0.0015)
      0.0036**
      (0.0015)
      0.0018
      (0.0011)
      0.0021*
      (0.0012)
      0.0006
      (0.0008)
      PCP-0.0014
      (0.0024)
      -0.0013
      (0.0018)
      -0.0013
      (0.0018)
      -0.0037***
      (0.0014)
      -0.0032**
      (0.0013)
      -0.0014
      (0.0011)
      IND-0.9845***
      (0.3813)
      -0.9854***
      (0.3837)
      -0.4852*
      (0.2721)
      -0.4531*
      (0.2692)
      -0.4316**
      (0.2028)
      INF-0.0002
      (0.0012)
      -0.0001
      (0.0007)
      -0.0001
      (0.0007)
      -0.0015
      (0.0011)
      URB-0.2289***
      (0.0338)
      -0.2199***
      (0.0302)
      -0.2476***
      (0.0246)
      AGR-0.1988*
      (0.1061)
      -0.6409***
      (0.1847)
      IIUA0.0776***
      (0.0161)
      hausman11.54
      (0.0092)
      7.16
      (0.1276)
      7.31
      (0.1983)
      10.36
      (0.1103)
      12.24
      (0.0930)
      31.83
      (0.0001)
      模型FEREREREREFE
      常数项0.3182***
      (0.0270)
      0.4030***
      (0.0359)
      0.4055***
      (0.0390)
      0.4852***
      (0.0339)
      0.5185***
      (0.0405)
      0.6318***
      (0.0594)
      R20.51050.60880.60900.75330.76220.8200
      F
      (wald值)
      13.33
      (0.0000)
      85.24
      (0.0000)
      85.59
      (0.0000)
      184.21
      (0.0000)
      196.33
      (0.0000)
      37.01
      (0.0000)
      观测值510510510510510510
    • Table 7. GMM regression results of water footprint intensity of four modernizations in each provincial-level region

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      Table 7. GMM regression results of water footprint intensity of four modernizations in each provincial-level region

      解释变量123456
      rjGDP-0.0571***
      (0.0040)
      -0.0273***
      (0.0048)
      -0.0274***
      (0.0047)
      -0.0113***
      (0.0031)
      -0.0110***
      (0.0032)
      -0.0145***
      (0.0032)
      PAT0.0023***
      (0.0006)
      0.0014**
      (0.0006)
      0.0017***
      (0.0006)
      0.0003
      (0.0005)
      0.0004
      (0.0005)
      -0.0004
      (0.0005)
      PCP-0.0033***
      (0.0008)
      -0.0008
      (0.0007)
      -0.0007
      (0.0007)
      -0.0029***
      (0.0007)
      -0.0027***
      (0.0008)
      -0.0020***
      (0.0007)
      IND-0.9281***
      (0.1076)
      -0.9104***
      (0.1056)
      -0.5724***
      (0.0868)
      -0.5545***
      (0.0861)
      -0.6439***
      (0.0781)
      INF-0.0010**
      (0.0004)
      -0.0012***
      (0.0003)
      -0.0011***
      (0.0003)
      -0.0022***
      (0.0005)
      URB-0.2259***
      (0.0256)
      -0.2256***
      (0.0256)
      -0.2304***
      (0.0249)
      AGR-0.0336
      (0.0269)
      -0.1135***
      (0.0365)
      IIUA0.0358***
      (0.0090)
      常数项0.3065***
      (0.0100)
      0.3762***
      (0.0132)
      0.3868***
      (0.0136)
      0.5018***
      (0.0179)
      0.5046***
      (0.0182)
      0.5412***
      (0.0224)
      R20.60300.67750.68320.74950.75060.7608
      wald395.54
      (0.0000)
      718.29
      (0.0000)
      770.64
      (0.0000)
      1257.68
      (0.0000)
      1268.66
      (0.0000)
      1520.87
      (0.0000)
      Root MSE0.06520.05880.05830.05180.05170.0506
      观测值480480480480480480
    • Table 8. Elastic coefficients of four modernizations to water footprint intensity on various percentiles in China

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      Table 8. Elastic coefficients of four modernizations to water footprint intensity on various percentiles in China

      弹性系数1%5%10%25%50%75%90%95%99%
      ξINDINF-0.6284-0.6044-0.5930-0.5642-0.5398-0.5056-0.4496-0.4239-0.2817
      URB-0.6031-0.5979-0.5895-0.5361-0.5172-0.5072-0.4957-0.4874-0.4767
      AGR-0.6030-0.5888-0.5836-0.5715-0.5445-0.4845-0.4665-0.4503-0.4297
      ξINFIND-0.0017-0.0016-0.0015-0.0013-0.0010-0.0007-0.0003-0.00010.0001
      URB-0.0018-0.0017-0.0016-0.0010-0.0008-0.0007-0.0006-0.0005-0.0004
      AGR-0.0018-0.0016-0.0015-0.0014-0.0011-0.0005-0.0003-0.00010.0001
      ξURBIND-0.2212-0.2194-0.2177-0.2135-0.2071-0.2009-0.1937-0.1911-0.1869
      INF-0.2272-0.2223-0.2199-0.2140-0.2090-0.2020-0.1905-0.1852-0.1560
      AGR-0.2220-0.2191-0.2180-0.2155-0.2100-0.1976-0.1939-0.1906-0.1864
      ξAGRIND-0.0879-0.0830-0.0784-0.0667-0.0490-0.0318-0.0118-0.00450.0071
      INF-0.1047-0.0910-0.0845-0.0681-0.0542-0.0347-0.0028-0.01180.0928
      URB-0.0903-0.0873-0.0825-0.0521-0.0413-0.0356-0.0291-0.0243-0.0182
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    Cai-zhi SUN, Can-can ZHANG, Xiao-wen GAO. Impact of China's "four modernizations" on water footprint intensity[J]. Journal of Natural Resources, 2020, 35(4): 767

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    Paper Information

    Category:

    Received: Dec. 14, 2018

    Accepted: --

    Published Online: Oct. 17, 2020

    The Author Email: SUN Cai-zhi (suncaizhi@lnnu.edu.cn)

    DOI:10.31497/zrzyxb.20200402

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