• Resources Science
  • Vol. 42, Issue 9, 1715 (2020)
Jing HAN1, Zexiu CHEN1, and Xinhai LU1、2、*
Author Affiliations
  • 1College of Public Administration, Central China Normal University, Wuhan 430079, China
  • 2College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China
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    DOI: 10.18402/resci.2020.09.07 Cite this Article
    Jing HAN, Zexiu CHEN, Xinhai LU. Spatiotemporal change of China’s overseas investment in farmlands and influencing factors[J]. Resources Science, 2020, 42(9): 1715 Copy Citation Text show less
    Spatial variogram
    Fig. 1. Spatial variogram
    Trend of the spatial difference of China’s overseas farmland investment activities
    Fig. 2. Trend of the spatial difference of China’s overseas farmland investment activities
    序号被投资国地区意向项目数量/个营运项目数量/个意向项目面积/万hm2营运项目面积/万hm2最早投资年份
    1尼加拉瓜北美洲1130.0030.002013
    2牙买加北美洲111.801.802011
    3澳大利亚大洋洲423.950.452011
    4巴布亚新几内亚大洋洲4451.6951.692009
    5埃塞俄比亚非洲3110.502.502008
    6安哥拉非洲3252.152.152010
    7贝宁非洲432.961.962001
    8刚果(金)非洲4339.5428.632007
    9加纳非洲213.650.052013
    10津巴布韦非洲4315.571.392003
    11喀麦隆非洲222.012.012006
    12利比里亚非洲111.001.002010
    13马达加斯加非洲553.953.452005
    14马里非洲112.002.002009
    15莫桑比克非洲986.386.262000
    16尼日利亚非洲644.233.232006
    17塞拉利昂非洲6517.824.152009
    18苏丹非洲221.671.172009
    19坦桑尼亚非洲310.130.062007
    20乌干达非洲445.240.582009
    21赞比亚非洲430.440.502003
    22阿根廷南美洲6634.3434.342010
    23巴西南美洲7544.404.402007
    24玻利维亚南美洲111.251.252005
    25哥伦比亚南美洲1140.0040.002010
    26圭亚那南美洲1162.7127.412011
    27乌拉圭南美洲440.400.402008
    28白俄罗斯欧洲1110.0010.002017
    29保加利亚欧洲557.426.622008
    30俄罗斯欧洲55101.3384.332004
    31乌克兰欧洲321.441.142013
    32菲律宾亚洲84254.445.642006
    33柬埔寨亚洲282725.7824.982000
    34老挝亚洲292875.2529.672002
    35缅甸亚洲232194.8285.312006
    36塔吉克斯坦亚洲4311.8911.092012
    37印度尼西亚亚洲151494.0262.652004
    38越南亚洲141336.5526.552005
    Table 1. An overview of China’s overseas farmland investment, 2000-2017
    子目标指标单位数据来源
    资源基础耕地总面积(C1hm2FAO数据库
    人均耕地面积(C2hm2FAO数据库
    农用地比例(C3%FAO数据库
    谷物单产(C4kg/hm2FAO数据库
    人均淡水资源量(C5m3FAO数据库
    地缘政治建交时长(C6《中国外交》
    高层交往总数(C7《中国外交》
    领事磋商总数(C8《中国外交》
    声明、宣言和公报总数(C9《中国外交》
    对华免签证件数量(C10《中国外交》
    地缘经济年均出口总额(C11万美元《中国贸易外经统计年鉴》
    年均出口额增长率(C12%《中国贸易外经统计年鉴》
    年均进口总额(C13万美元《中国贸易外经统计年鉴》
    年均进口额增长率(C14%《中国贸易外经统计年鉴》
    年均对外承包工程完成营业额(C15万美元《中国贸易外经统计年鉴》
    对中投资合作政策数量(C16《中国外交》
    地缘文化年均在华留学生人数(C17《中国贸易外经统计年鉴》
    年均赴华旅游人数(C18人/次《中国贸易外经统计年鉴》
    人文合作交流总数(C19《中国外交》
    驻华领事机构数量(C20《中国外交》
    Table 2. Factors affecting the change of spatial pattern of China’s overseas farmland investment development, 2000-2017
    年份Moran’s IZP年份Moran’s IZP
    2000-0.01701.24520.113220090.54737.17150.0010
    2001-0.0411-0.28550.441020100.40335.00610.0022
    2002-0.0713-0.68350.258320110.30603.90240.0063
    2003-0.0369-0.11060.479020120.33214.21500.0051
    20040.24613.55860.012020130.32324.14610.0041
    20050.37125.11800.001220140.31043.99760.0053
    20060.41145.70020.004320150.37274.82100.0014
    20070.46846.87450.002220160.37924.89810.0010
    20080.53817.16040.001120170.42110.00130.0021
    Table 3. Overall Moran’s I index of China’s overseas farmland investment development, 2000-2017
    年份模型变程块金值残差平方和基台值块金系数判定系数偏基台值
    2000高斯1333.680.00003.91E-030.03020.0000.1660.0302
    2004高斯22014.370.01401.25E-030.06340.2210.5560.0494
    2009高斯14306.740.00541.59E-030.05380.1000.6830.0484
    2017高斯14358.700.00631.73E-030.07170.0880.7810.0654
    Table 4. Fitting results of China’s overseas farmland investment pattern variogram model
    年份全方向南—北东北—西南东—西西北—东南
    DR2DR2DR2DR2DR2
    20001.8530.2581.9450.2541.9790.0251.9290.1161.8930.188
    20041.8570.1961.9470.0051.7100.1191.9830.0011.5610.416
    20091.6710.5211.8310.1011.5600.2721.6330.1341.2260.653
    20171.6090.7341.8710.0501.6410.1881.5020.3531.2440.728
    Table 5. China’s overseas farmland investment variability function fractal dimension
    TestMI/DFValueProb
    LM(lag)14.04540.04429
    R-LM(lag)15.76110.01638
    LM(error)10.15590.69296
    R-LM(error)11.87160.17129
    Table 6. Spatial dependence test results of spatial regression models
    模型OLSSLMSEM
    CONSTANT-0.19740.4194-0.3593
    lnC10.01450.00610.0266
    lnC2-0.03150.0003-0.0479
    C3-0.0025-0.0032**-0.0043***
    lnC40.09990.0833**0.1745***
    lnC5-0.0203-0.0338-0.0448*
    C60.00300.00160.0025
    C7-0.0006-0.00090.0008
    C8-0.0240-0.0077-0.0135
    C90.00980.0123**0.0077*
    C10-0.0182-0.0368**-0.0136
    lnC11-0.00300.02050.0214
    C120.00410.0053*0.0057*
    lnC130.01820.02160.0191
    C140.00060.00080.0008
    lnC15-0.0319-0.0460*-0.0615**
    C160.00160.00120.0008
    lnC170.00810.00960.0107
    lnC18-0.0514-0.0637*-0.0883***
    C19-0.0010-0.0008-0.0028
    C200.04520.0451**0.0417**
    ρ-0.8654**
    λ7.8271***
    R-squared0.69380.72900.5487
    LogL29.083331.04953.3681
    AIC-16.1666-18.0990-18.7363
    SC18.222717.927915.6530
    Table 7. Regression results of influencing factors of China’s overseas farmland investment development
    Jing HAN, Zexiu CHEN, Xinhai LU. Spatiotemporal change of China’s overseas investment in farmlands and influencing factors[J]. Resources Science, 2020, 42(9): 1715
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