基于农户受偿意愿的休耕补偿标准探讨——以河北样本户为例

曾黎, 杨庆媛, 廖俊儒, 陈展图, 陈伊多, 杨人豪

Fallow compensation based on farmer willingness to accept in Hebei

Li ZENG, Qingyuan YANG, Junru LIAO, Zhantu CHEN, Yiduo CHEN, Renhao YANG

表3 模型回归结果

Table 3 Results of Binary Logistic models

变量代码 模型1(B) Exp (B) 模型2(B) Exp (B) 模型3(B) Exp (B) 模型4(B) Exp (B) Igender -0.099 (0.885) 0.906 -0.618 (0.400) 0.539 -0.654 (0.384) 0.520 -0.702 (0.406) 0.495 Iage 0.048*** (0.002) 1.049 0.054*** (0.001) 1.056 0.061*** (0.001) 1.063 0.072*** (0.001) 1.075 Ihealth -0.022 (0.923) 0.978 -0.029 (0.908) 0.971 -0.101 (0.705) 0.904 -0.229 (0.450) 0.795 Iedu 0.092 (0.655) 1.097 0.133 (0.527) 1.142 0.145 (0.513) 1.156 0.107 (0.667) 1.113 Icadre 1.645 (0.116) 5.183 1.492 (0.159) 4.445 1.328 (0.216) 3.775 0.602 (0.601) 1.826 Ffamily -0.261** (0.031) 0.770 -0.246* (0.081) 0.782 -0.338** (0.049) 0.713 Flabour 0.838 (0.163) 2.312 0.945 (0.145) 2.572 1.479** (0.044) 4.389 Fprof 1.482** (0.013) 4.401 -1.420 (0.468) 0.242 -1.960 (0.380) 0.141 Finc 0.000 (0.295) 1.000 0.000 (0.843) 1.000 0.000 (0.591) 1.000 Pfarm -3.810 (0.102) 0.022 -5.341** (0.050) 0.005 Proi 0.795*** (0.005) 2.214 0.739** (0.016) 2.093 Ppcland -3.473 (0.189) 0.031 -4.228 (0.154) 0.015 Pfrag 0.031 (0.269) 1.031 0.022 (0.465) 1.022 Csubj -0.104 (0.421) 0.901 Cpurp -1.043 (0.168) 0.352 Ccogn 1.661*** (0.006) 5.265 Csati 1.500*** (0.000) 4.480 Cexpect 0.075* (0.071) 1.078 D -1.135 0.321 -1.684 0.186 0.215 1.240 -6.570 0.001 -2LL 234.307 194.254 102.561 87.379 Nagelkerke R2 0.079 0.219 51.312 66.544 预测准确率(%) 88.640 89.213 90.019 91.901 卡方值 13.574 39.183 53.635 90.502 sig. 0.019 0.000 0.000 0.000