• Journal of Natural Resources
  • Vol. 35, Issue 3, 728 (2020)
Xin YANG and Yue-ying MU*
Author Affiliations
  • College of Economics and Management, China Agricultural University, Beijing 100083, China
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    DOI: 10.31497/zrzyxb.20200317 Cite this Article
    Xin YANG, Yue-ying MU. Irrigation water pressure, supply elasticity and grain production structure based on heterogeneous coefficient Nerlove model[J]. Journal of Natural Resources, 2020, 35(3): 728 Copy Citation Text show less
    Theoretical framework
    Fig. 1. Theoretical framework
    Average comparison of irrigation water pressure index and simplified irrigation water pressure index of each province in China from 2002 to 2017
    Fig. 2. Average comparison of irrigation water pressure index and simplified irrigation water pressure index of each province in China from 2002 to 2017
    变量符号平均值标准差最小值最大值样本量/个
    灌溉水压力指数/%δ33.9235.333.08158.59432
    年降水量/mmrain957.74557.97142.712555.80432
    每年≥10 ℃日数/天tep231.1964.11119.00363.00432
    有效灌溉面积比例/%irr45.8020.5613.7098.64432
    农业劳动力价格/元lab2364.442010.21132.0114886.07432
    第一产业就业人数比例/%fir0.430.120.190.81432
    小麦价格/(元/kg)P11.130.510.103.51432
    水稻价格/(元/kg)P21.170.360.102.26432
    玉米价格/(元/kg)P31.030.480.102.42432
    豆类价格/(元/kg)P42.671.450.717.78432
    薯类价格/(元/kg)P52.771.050.659.67432
    油料价格/(元/kg)P62.230.710.825.48432
    蔬菜价格/(元/kg)P71.401.190.307.77432
    小麦产量/万tY1414.00714.6321.783705.20240
    水稻产量/万tY21042.85665.83110.602819.30304
    玉米产量/万tY3835.69752.43100.203703.10336
    豆类产量/万tY478.09112.789.70719.00384
    薯类产量/万tY5131.31101.418.18531.10432
    Table 1. Descriptive statistics
    小麦水稻玉米豆类薯类
    Sargan检验0.2510.3020.3630.2730.292
    Arellano-Bond检验AR(1)0.0230.0030.0120.0480.036
    AR(2)0.8450.2530.6710.9960.432
    Table 2. Sargan test and Arellano-Bond test for Nerlove model
    变量小麦水稻玉米豆类薯类
    lnδt-1-0.140***-0.316***0.221***-0.145**-0.216***
    (0.029)(0.060)(0.036)(0.066)(0.059)
    lnYt-10.555***0.603***0.608***0.604***0.718***
    (0.050)(0.039)(0.042)(0.060)(0.046)
    lnP1,t-10.899***-0.030-0.1530.0660.465***
    (0.188)(0.080)(0.110)(0.208)(0.152)
    lnP2,t-1-0.907***0.782**0.469***-0.2020.076
    (0.200)(0.098)(0.123)(0.221)(0.103)
    lnP3,t-1-0.1160.213***0.661***-0.301**0.268**
    (0.163)(0.077)(0.104)(0.148)(0.114)
    lnP4,t-10.362***0.147***0.179***0.283***-0.097
    (0.129)(0.055)(0.052)(0.101)(0.106)
    lnP5,t-10.037-0.0770.062-0.0430.181***
    (0.092)(0.074)(0.054)(0.103)(0.009)
    lnP6,t-1-0.0110.188***0.083-0.102-0.308***
    (0.117)(0.059)(0.061)(0.115)(0.106)
    lnP7,t-10.1380.0610.0400.067-0.432***
    (0.123)(0.070)(0.061)(0.124)(0.089)
    lnraint-0.341***0.074*-0.029-0.0290.162***
    (0.077)(0.045)(0.054)(0.086)(0.069)
    lntept1.448***-0.366*-0.1070.0450.631*
    (0.274)(0.137)(0.190)(0.250)(0.332)
    lnirrt0.459***0.060***-0.0340.092-0.443***
    (0.116)(0.015)(0.077)(0.136)(0.122)
    lnlabt-0.075***-0.0200.094***-0.0180.188***
    (0.052)(0.030)(0.028)(0.046)(0.044)
    lnfirt-0.049-0.201*-0.0850.166**0.589***
    (0.255)(0.104)(0.131)(0.207)(0.204)
    CPt-0.224***-0.0540.098***0.1050.242***
    (0.066)(0.037)(0.037)(0.098)(0.062)
    WPt0.297***0.054-0.0740.074-0.312***
    (0.082)(0.049)(0.055)(0.081)(0.092)
    RPt-0.223***0.103***0.002-0.117*-0.174***
    (0.083)(0.034)(0.043)(0.062)(0.060)
    常数项-5.266***5.073***2.173**1.9820.608
    (1.531)(0.854)(1.008)(1.420)(1.568)
    观测值225285315360405
    Table 3. Regression results of Nerlove model
    变量(自然对数形式)小麦水稻玉米豆类薯类
    以灌溉水压力指数回归的结果
    lnPk,t-1×lnδt-1-0.254*0.199**0.169***-0.308***-0.157*
    (0.145)(0.089)(0.071)(0.118)(0.091)
    lnPk,t-11.665***0.557*0.6451.678***1.159*
    (0.476)(0.283)(0.611)(0.253)(0.326)
    lnδt-10.268***-0.0890.248***0.161-0.009
    (0.010)(0.057)(0.039(0.135)(0.110)
    lnYt-10.541***0.417***0.495***0.618***0.509***
    (0.051)(0.043)(0.043)(0.061)(0.060)
    以简化灌溉水压力指数回归的结果
    lnPk,t-1×lnδt-1'-0.337**0.508***0.305*-0.213*0.367***
    (0.154)(0.122)(0.091)(0.113)(0.158)
    lnPk,t-11.944***-0.640***0.2281.263***-0.380
    (0.449)(0.180)(0.057)(0.265)(0.410)
    lnδt-1'0.079-0.078-0.066-0.323**-0.507***
    (0.087)(0.063)(0.058)(0.133)(0.179)
    lnYt-10.591***0.750***0.700***0.533***0.367**
    (0.043)(0.039)(0.040)(0.050)(0.157)
    Table 4. Regression results of heterogeneous coefficient Nerlove model
    灌溉水压力指数平均值/%长期供给弹性
    小麦水稻玉米豆类薯类
    不同年份2003年28.7731.7682.1022.8891.6841.286
    2008年33.2881.6882.1522.9591.5661.240
    2013年36.3141.6402.1823.0001.4961.212
    2017年36.0261.6442.1792.9961.5031.214
    南方粮食主产区江苏13.4912.1881.8442.5292.2951.528
    安徽6.0942.6271.5722.1512.9351.783
    湖北8.9932.4121.7052.3362.6221.658
    湖南25.5982.0621.7781.324
    江西24.8962.0531.333
    四川13.5422.1851.8452.5312.2921.527
    平均值15.4362.3531.8472.3872.3841.526
    北方粮食主产区河北147.8660.8633.6690.3640.763
    山东61.7551.3462.3633.2531.0681.042
    河南70.3601.2742.4073.3150.9631.000
    内蒙古28.5551.7732.8861.6901.289
    黑龙江9.7582.3671.7332.3742.5561.632
    辽宁75.4531.2352.4313.3480.9070.978
    吉林46.4421.5032.2663.1171.2981.133
    平均值62.8841.4802.2403.1371.2641.120
    Table 5. Spatio-temporal changes of irrigation water pressure index and long-term supply elasticity of grain in main grain-producing areas of China
    Xin YANG, Yue-ying MU. Irrigation water pressure, supply elasticity and grain production structure based on heterogeneous coefficient Nerlove model[J]. Journal of Natural Resources, 2020, 35(3): 728
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