• Resources Science
  • Vol. 42, Issue 2, 217 (2020)
Hao WEI, Ying XIA*, Yun LI, Kaiyu LV, and Haiying WANG
Author Affiliations
  • Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Science, Beijing 100081, China
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    DOI: 10.18402/resci.2020.02.02 Cite this Article
    Hao WEI, Ying XIA, Yun LI, Kaiyu LV, Haiying WANG. Effects of farmers’ credit demand rationing on the adoption of agricultural technologies that improve cultivated land quality:An analysis based on the moderating effect of farmer differentiation[J]. Resources Science, 2020, 42(2): 217 Copy Citation Text show less
    信贷需求抑制度量方法Figure 1
    Fig. 1. 信贷需求抑制度量方法Figure 1
    变量类型变量名称赋值说明均值标准差最小值最大值
    因变量是否采用少耕或免耕技术是=1;否=00.350.4801
    是否采用深耕或深松技术是=1;否=00.540.5001
    是否采用平整土地或改良土壤技术是=1;否=00.150.3601
    核心自变量是否受到信贷需求抑制是=1;否=00.500.5001
    农户分化变量农户分化纯农业型:是=1;否=00.330.4701
    兼业型:是=1;否=00.470.5001
    纯非农业型:是=1;否=00.200.4001
    工具变量金融项目参与数/个存款、自动取款机、刷卡机、网银、理财、外汇项目用过几项1.661.2706
    控制变量年龄/岁户主实际年龄55.9610.822785
    身体健康程度是否常年生病,不能干活:是=1;否=00.060.2401
    受教育程度/年受教育年限6.823.19016
    耕地规模/亩2017年实际耕地面积81.40153.480.51000
    家庭年均纯收入/万元2017年年均纯收入9.1113.660.1105.9
    家庭人口数/口2017年家庭人口数量4.201.79113
    农业劳动力占比农业劳动力与家庭人口数比值0.540.260.11
    土地确权土地是否确权:是=1;否=00.870.3301
    土地细碎化程度/块家庭耕地地块数10.3812.25085
    家庭社会资本家人是否当过村干部:是=1;否=00.290.4501
    技术培训次数/次2014-2017年农户参加技术培训/讲座次数2.083.52030
    是否有技术示范户本村是否有技术示范户:是=1;否=00.250.4301
    能否灌溉是=1;否=00.800.3901
    土壤质量1=好;2=中;3=差1.550.6113
    地块面积/亩最大地块面积17.7847.290.5827
    是否转入地块是=1;否=00.500.5001
    村农业技术推广活动/次2017年你们村农业技术推广活动或观摩会次数0.971.63018
    地区虚拟变量1=黑龙江;0=其他0.240.4301
    1=四川;0=其他0.270.4401
    1=浙江;0=其他0.250.4301
    Table 1.

    耕地质量提升型农业技术回归分析的变量定义及统计描述

    平整土地/%改良土壤/%少耕/%免耕/%深松/%深耕/%
    全样本(957户)10.557.4231.563.667.9448.80
    黑龙江(231户)13.856.063.465.636.4943.72
    浙江(240户)11.256.6713.335.831.2571.25
    四川(258户)10.0813.1818.223.103.8817.83
    河南(228户)7.023.0794.300.0021.0565.35
    Table 2.

    不同类型耕地质量提升型农业技术采用基本情况

    全样本黑龙江浙江河南四川
    纯农户户数/户15463154036
    比重/%48.8958.3323.0876.9240.00
    兼业户户数/户22556229750
    比重/%49.5651.8522.0076.3842.02
    纯非农户户数/户9811243825
    比重/%52.1373.3332.0077.5551.02
    Table 3.

    样本户信贷需求抑制基本情况

    样本户数采用不同类型耕地质量提升型农业技术比例
    受到信贷需求抑制/%无信贷需求抑制/%
    采用平整土地、改良土壤技术14714.8815.83
    采用少耕、免耕技术33734.8335.87
    采用深耕、深松技术49751.5356.01
    Table 4.

    耕地质量提升型农业技术信贷需求抑制比例

    变量名称平整土地、改良土壤少耕、免耕深耕、深松
    回归1(probit)回归2(CMP)回归3(probit)回归4(CMP)回归5(probit)回归6(CMP)
    信贷需求抑制0.0445-1.195***0.0258-0.7930.103-1.030***
    (0.41)(-4.72)(0.23)(-1.59)(1.02)(-3.47)
    年龄-0.0108*-0.00813*-0.0139**-0.0123**0.002840.00104
    (-1.83)(-1.67)(-2.14)(-2.11)(0.53)(0.39)
    身体健康程度-0.0396-0.01010.08410.09160.05790.0415
    (-0.18)(-0.05)(0.38)(0.43)(0.30)(0.23)
    教育水平0.00191*0.0014*0.0471**0.0428**0.005370.00325
    (1.65)(1.68)(2.48)(2.45)(0.33)(0.21)
    耕地规模0.000603*0.00030*0.0000441-0.0000110.000572*0.000547*
    (1.61)(1.71)(0.1)(-0.03)(1.65)(1.68)
    年均纯收入0.002620.00300**-0.00496-0.0065-0.0008460.00679*
    (0.68)(2.19)(-0.93)(-1.27)(-0.24)(1.94)
    家庭人口数0.0330.0281-0.0388-0.0343-0.0179-0.0156
    (0.88)(0.84)(-0.93)(-0.87)(-0.56)(-0.54)
    农业劳动力占比0.120-0.0209-0.362-0.300-0.1320.00645
    (0.47)(-0.12)(-1.39)(-1.28)(-0.61)(0.03)
    土地是否确权-0.02350.0343-0.0903-0.027-0.210-0.225
    (-0.14)(0.24)(-0.56)(-0.19)(-1.41)(-1.60)
    耕地细碎化程度-0.003310.001330.002840.00523-0.00163-0.00267
    (-0.70)(0.25)(0.61)(1.17)(-0.39)(-0.64)
    社会资本0.1050.1540.00717-0.0357-0.107-0.0247
    (0.88)(1.44)(0.06)(-0.30)(-1.04)(-0.25)
    技术培训次数0.0202*0.0106*-0.00642-0.0102-0.0131-0.00397
    (1.74)(1.91)(-0.39)(-0.63)(-0.96)(-0.30)
    村技术推广次数0.01640.02680.02170.03040.04110.0162
    (0.49)(0.96)(0.52)(0.83)(1.38)(0.55)
    技术示范户0.1820.17-0.136-0.1120.1040.0567
    (1.51)(1.47)(-1.04)(-0.89)(0.96)(0.56)
    能否灌溉---0.473***-0.355***0.233*0.104*
    --(-3.35)(-2.74)(1.88)(1.89)
    土壤质量--0.1060.095*-0.0914-0.0679
    --(1.57)(1.72)(-1.23)(-0.97)
    地块面积---0.00186-0.00140.00346*0.00233
    --(-0.94)(-0.73)(1.85)(1.36)
    是否转入地块---0.174-0.176*-0.121-0.0464
    --(-1.42)(-1.61)(-1.14)(-0.50)
    黑龙江虚拟变量0.2790.0355-3.031***-2.801***-0.531***-0.251
    (1.63)(0.23)(-14.77)(-9.89)(-3.65)(-1.36)
    四川虚拟变量0.680***0.136-2.619***-2.629***-1.229***-0.589*
    (3.83)(0.64)(-13.45)(-12.04)(-7.88)(-1.88)
    浙江虚拟变量-0.407**-0.255*-2.504***-2.688***0.09420.729***
    (-2.20)(-1.57)(-12.54)(-14.24)(0.60)(3.36)
    常数项-1.138**-0.004161.521**2.057***0.436-0.687
    (-2.25)(-0.01)(2.53)(3.86)(0.88)(-1.48)
    atanhrh-12-1.005***-0.811**--1.203**
    (3.02)(2.55)(-2.60)
    一阶段估计信贷需求抑制信贷需求抑制信贷需求抑制
    金融项目参与数--0.180***--0.181***--0.161***
    (-5.08)(-4.70)(-3.90)
    观察值个数957957924
    对数似然值-392.08308-968.13921-354.47194-929.99739-532.25895-1106.5542
    LR卡方值36.77-532.79-211.11-
    wald卡方值-320.22-566.61-533.18
    hausman检验-29.77-54.78-42.79
    Table 5.

    信贷需求抑制对耕地质量提升型农业技术回归结果

    变量名称回归7回归8回归9回归10回归11回归12回归13
    纯农户兼业+纯非农纯农户兼业户纯非农纯农户兼业+纯非农
    第一阶段估计是否受到信贷需求抑制是否受到信贷需求抑制是否受到信贷需求抑制
    金融参与项目数-0.066**-0.052***-0.192**-0.161***-0.154*-0.0611**-0.051***
    (-2.48)(-3.14)(-2.49)(-2.59)(-1.86)(-2.24)(-3.00)
    其他控制变量引入引入引入引入引入引入引入
    第二阶段估计平整土地,改良土壤技术少耕,免耕技术深耕,深松技术
    信贷需求抑制-1.851***-1.029***-0.589-0.899-0.634-1.09***-1.594*
    (-7.83)(-3.40)(-1.09)(-0.27)(-0.66)(-3.5)(-1.65)
    其他控制变量引入引入引入引入引入引入引入
    atanhrh-121.683***1.020*0.248*0.700*0.63-0.948*-1.710***
    (3.76)(1.88)(1.77)(1.68)(0.77)(-1.89)(-4.75)
    观测值315642315454188302622
    wald卡方值243.46239.91152.42290.15132.08195.82486.73
    Fisher 经验P0.130纯农户与兼业户:0.430;兼业户与纯非农户:0.280;纯农户与纯非农:0.2500.060
    Table 6.

    农户分化调节效应分组回归结果

    Hao WEI, Ying XIA, Yun LI, Kaiyu LV, Haiying WANG. Effects of farmers’ credit demand rationing on the adoption of agricultural technologies that improve cultivated land quality:An analysis based on the moderating effect of farmer differentiation[J]. Resources Science, 2020, 42(2): 217
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