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    Journals >Journal of Geographical Sciences >Volume 30 >Issue 3 >Page 378 > Article
    • Journal of Geographical Sciences
    • Vol. 30, Issue 3, 378 (2020)
    How farmers’ non-agricultural employment affects rural land circulation in China?
    Jiayue WANG1、2, Liangjie XIN1、*, and Yahui WANG3
    Author Affiliations
  • 1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China
  • 3. School of Geographical Science, Southwest University, Chongqing 400715, China
    • show less
    DOI: 10.1007/s11442-020-1733-8 Cite this Article
    Jiayue WANG, Liangjie XIN, Yahui WANG. How farmers’ non-agricultural employment affects rural land circulation in China?[J]. Journal of Geographical Sciences, 2020, 30(3): 378 Copy Citation Text show less
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    TypeVariableDefinitionMeanStandard deviationMinMaxSample size
    Rural land circulationtransfer_outLand transfer-out (Yes=1; No=0)0.210.41015450
    transfer_inLand transfer-in (Yes=1; No=0)0.310.46012536
    Non-agricultural employmentnaincome_ratioProportion of non-agricultural income0.570.37015450
    nalabor_ratioProportion of non-agricultural laborers0.200.26015450
    naasset_ratioProportion of non-agricultural fixed operating assets0.450.110.280.755450
    Householders’ characteristicseducationEducation level (lowest level=1→highest level=8)2.730.91185416
    marriageMarital status (unmarried=1; married or has been married=0)0.010.11015450
    Households’ characteristicsaver_ageAverage age of household labor46.0011.8721.5935450
    cadreVillage cadres in households (Yes=1; No=0)0.060.23015434
    forestGrain for Green Project (Yes=1; No=0)0.120.33015450
    organizationAgricultural cooperative economic organization (Yes=1; No=0)0.030.18015450
    Households’ characteristicsrequisitionLand requisition (Yes=1; No=0)0.100.30015450
    Land managementpclandPer capita area of farmland (mu/person) (1 mu=1/15 ha)1.892.160.0812.55450
    Economic levelpcgdpThe logarithm values of per capita GDP of provinces (yuan/person)10.650.3410.1011.445450
    Landform conditionlandformsLandforms (plain=1; mountainous area=0)0.560.50015450
    Regional dummy variableseastEastern China =1; other areas=00.360.48015450
    centralCentral China =1; other areas=00.430.50015450
    westWestern China =1; other areas=00.210.41015450
    Table 1.

    Variable definition and statistical description

    View in the Article
    ProvinceBeijingLiaoningJiangsuShandongGuangdong
    Eastern ChinaLand transfer-out rate27.883.1921.245.4314.51
    Land transfer-in rate9.8520.7414.9329.2355.21
    Proportion of non-agricultural income66.2547.8273.2358.9977.41
    Proportion of non-agricultural laborers22.7414.5817.0716.9222.49
    Proportion of non-agricultural fixed operating assets47.3242.0147.5743.7748.94
    Central ChinaProvinceShanxiAnhuiHenanHubeiHunan
    Land transfer-out rate7.5517.176.146.799.11
    Land transfer-in rate10.5829.869.2125.0731.28
    Proportion of non-agricultural income52.0759.2065.7956.6370.54
    Proportion of non-agricultural laborers19.9332.4322.0828.3428.47
    Proportion of non-agricultural fixed operating assets48.2444.3244.3844.3345.61
    Western ChinaProvinceSichuanChongqingYunnanGansu-
    Land transfer-out rate13.417.345.671.65-
    Land transfer-in rate10.9713.8110.0210.06-
    Proportion of non-agricultural income67.8172.9158.4959.18-
    Proportion of non-agricultural laborers22.1225.0016.9323.09-
    Proportion of non-agricultural fixed operating assets43.3444.3344.6739.11-
    Table 2.

    Land transfer rate and farmers’ non-agricultural employment in different provinces in 2013 (%)

    View in the Article
    VariableModel 1Model 2Model eastModel centralModel west
    CoefficientMarginaleffectsCoefficientMarginaleffectsCoefficientMarginaleffectsCoefficientMarginaleffectsCoefficientMarginaleffects
    naincome_ratio0.617***0.090***0.598***0.088***0.2930.0450.934***0.134***0.872**0.106**
    (0.122)(0.018)(0.122)(0.018)(0.196)(0.030)(0.184)(0.026)(0.346)(0.042)
    nalaborratio0.2220.0320.2170.032-0.519**-0.080**0.589**0.085**0.673*0.082*
    (0.154)(0.022)(0.153)(0.022)(0.265)(0.041)(0.231)(0.033)(0.361)(0.044)
    naassetratio4.721***0.689***4.761***0.697***4.728***0.729***4.999***0.720***3.871***0.472***
    (0.358)(0.050)(0.356)(0.049)(0.582)(0.085)(0.575)(0.079)(0.791)(0.092)
    education0.164***0.024***0.154***0.023***0.254***0.039***0.0850.0120.216**0.026**
    (0.040)(0.006)(0.039)(0.006)(0.064)(0.010)(0.065)(0.009)(0.092)(0.011)
    marriage-0.145-0.021-1.343*-0.207*-0.118-0.0171.214*0.148*
    (0.312)(0.045)(0.764)(0.118)(0.427)(0.061)(0.698)(0.085)
    average0.037***0.005***0.037***0.005***0.035***0.005***0.041***0.006***0.027***0.003***
    (0.004)(0.001)(0.004)(0.001)(0.006)(0.001)(0.005)(0.001)(0.010)(0.001)
    cadre-0.149-0.022-0.104-0.0160.0180.003-0.481-0.059
    (0.167)(0.024)(0.266)(0.041)(0.258)(0.037)(0.414)(0.050)
    forest-0.229*-0.033*-0.215*-0.031*-0.180-0.028-0.196-0.028-0.407**-0.050**
    (0.119)(0.017)(0.118)(0.017)(0.319)(0.049)(0.175)(0.025)(0.202)(0.024)
    organization0.437**0.064**0.431**0.063**-0.110-0.0170.851**0.123**0.746**0.091**
    (0.194)(0.028)(0.194)(0.028)(0.338)(0.052)(0.337)(0.048)(0.363)(0.044)
    requisition0.0740.011-0.204-0.0320.0340.0050.3570.044
    (0.111)(0.016)(0.181)(0.028)(0.188)(0.027)(0.236)(0.029)
    Model 1Model 2Model eastModel centralModel west
    VariableCoefficientMarginaleffectsCoefficientMarginaleffectsMarginalCoefficienteffectsCoefficientMarginal effectsCoefficientMarginaleffects
    pcland-0.346***-0.050***-0.352***-0.052***-0.357*** -0.055***-0.238***-0.034***-0.945*** --0.115***
    (0.034)(0.005)(0.034)(0.005)(0.054) (0.008)(0.044)(0.006)(0.132)(0.015)
    pcgdp0.3630.0530.3620.0531.359*** 0.210***-1.420*-0.204*-0.235-0.029
    (0.257)(0.037)(0.256)(0.038)(0.407) (0.062)(0.860)(0.124)(0.417)(0.051)
    landforms-0.264**-0.039**-0.260**-0.038**omitted-0.497***-0.072***omitted
    (0.116)(0.017)(0.115)(0.017)(0.161)(0.023)
    east-0.059-0.009-0.065-0.010
    (0.269)(0.039)(0.268)(0.039)
    central-0.026-0.004-0.033-0.005
    (0.125)(0.018)(0.124)(0.018)
    Constant-9.328***-9.265***-20.452***8.908-2.173
    (2.650)(2.643)(4.484)(9.078)(4.290)
    McFadden’s R20.1180.1180.1270.10580.2053
    AUC0.7390.7390.7420.7280.811
    N54005416194023301130
    Table 3.

    The impact of non-agricultural employment on farmers5 land transfer-out behavior in China, Eastern China, Central China and Western China in 2013

    View in the Article
    Model 1Model 2Model eastModel centralModel west
    VariableCoefficientMarginaleffectsCoefficientMarginaleffectsCoefficientMarginaleffectsCoefficientMarginaleffectsCoefficientMarginaleffects
    naincome ratio—0.414***-0.071***-0.411**-0.071**-0.346-0.047-0.222-0.041-0.939**-0.197**
    (0.161)(0.028)(0.161)(0.028)(0.275)(0.037)(0.242)(0.0440(0.431)(0.088)
    nalabor ratio-0.231-0.040-0.234-0.0400.4340.059-0.413-0.076-1.133**-0.238**
    (0.223)(0.038)(0.222)(0.038)(0.376)(0.051)(0.343)(0.063)(0.521)(0.107)
    naasset_ratio-1.057**-0.182**-1.090**-0.188**-1.492*-0.202*0.0090.002-2.944**-0.618**
    (0.469)(0.081)(0.469)(0.081)(0.765)(0.103)(0.754)(0.138)(1.175)(0.239)
    education-0.143**-0.025**-0.142**-0.024**-0.156-0.021-0.240**-0.044**-0.009-0.002
    marriage(0.060)-0.720(0.529)(0.010)-0.124(0.091)(0.060)(0.010)(0.100)0.410(0.723)(0.014)0.056(0.098)(0.097)-2.975**(1.224)(0.018)-0.546**(0.223)(0.136)0.495(1.431)(0.029)0.104(0.300)
    aver_age-0.030***-0.005***-0.030***-0.005***-0.031***-0.004***-0.026***-0.005***-0.037**-0.008**
    (0.005)(0.001)(0.005)(0.001)(0.008)(0.001)(0.007)(0.001)(0.015)(0.003)
    cadre0.467**0.081**0.477**0.082**0.807**0.109**0.0310.0060.906*0.190*
    forest(0.202)0.098(0.162)(0.035)0.017(0.028)(0.202)(0.035)(0.323)1.047**(0.422)(0.043)0.142**(0.057)(0.318)-0.383(0.248)(0.058)-0.070(0.045)(0.503)0.268(0.277)(0.104)0.056(0.058)
    organization1.035***0.178***1.028***0.177***1.701***0.231***0.3260.0601.407**0.295**
    requisition(0.238)-0.128(0.175)(0.040)-0.022(0.030)(0.237)(0.040)(0.347)-0.081(0.275)(0.046)-0.011(0.037)(0.446)-0.147(0.292)(0.082)-0.027(0.054)(0.563)-0.186(0.426)(0.115)-0.039(0.089)
    Model1Model 2Model eastModel centralModel west
    VariableCoefficientMarginalMarginalCoefficientMarginalCoefficientCoefficientMarginalCoefficientMarginal
    effectseffectseffectseffectseffects
    0.310***0.053***0.310*** 0.054***0.430*** 0.058***0.293***0.054***0.0930.019
    pcland(0.026)(0.004)(0.026) (0.004)(0.044) (0.005)(0.045)(0.008)(0.064)(0.013)
    0.713*0.123*0.743** 0.128**-2.365*** -0.321***1.7170.3151.901***0.399***
    pcgdp(0.376)(0.065)(0.370) (0.064)(0.724) (0.097)(1.163)(0.212)(0.624)(0.125)
    -1.113*** -0.192***-1.119*** -0.193***-1.099***-0.201***
    landforms(0.160)(0.027)(0.159) (0.027)omitted(0.213)(0.037)omitted
    -0.047-0.008-0.087 -0.015
    east(0.396)(0.068)(0.389) (0.067)
    0.397**0.068**0.380** 0.066**
    central(0.183)(0.031)(0.180) (0.031)
    -6.154-6.430*26.356***-16.609-16.691***
    Constant(3.860)(3.798)(7.949)(12.277)(6.421)
    McFadden’s R20.1590.1580.2300.1580.100
    AUC0.7640.7630.7890.7620.723
    N250725071154987366
    Table 4.

    The impact of non-agricultural employment on farmers5 land transfer-in behavior in China, Eastern China, Central China and Western China in 2013

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    Jiayue WANG, Liangjie XIN, Yahui WANG. How farmers’ non-agricultural employment affects rural land circulation in China?[J]. Journal of Geographical Sciences, 2020, 30(3): 378
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