Acta Agriculturae Zhejiangensis ›› 2020, Vol. 32 ›› Issue (12): 2261-2270.DOI: 10.3969/j.issn.1004-1524.2020.12.18
• Agricultural Economy and Development • Previous Articles Next Articles
Received:
2020-07-03
Online:
2020-12-25
Published:
2020-12-25
CLC Number:
CHEN Yinrong, WANG Xiaomei. Impact of rural-household differentiation on cultivated land protection behavior based on intermediary effect[J]. Acta Agriculturae Zhejiangensis, 2020, 32(12): 2261-2270.
变量 Variable | 变量说明及其赋值 Variable description and assignment | 均值 Mean | 标准差 Standard deviation | |
---|---|---|---|---|
Y1 | 耕地保护行为 Cultivated land protection behavior | 是否采取耕地保护行为(是=1;否=0) Do you take cultivated land protection behavior (Yes=1; No=0) | 0.26 | 0.44 |
Y2 | 劳动偏向型耕地保护行为 Labor-biased behavior | 是否采取劳动偏向型耕地保护行为(是=1;否=0) Do you take labor-biased behavior (Yes=1; No=0) | 0.13 | 0.34 |
Y3 | 资金偏向型耕地保护行为 Capital-biased behavior | 是否采取资金偏向型耕地保护行为(是=1;否=0) Do you take capital-biased behavior (Yes=1; No=0) | 0.18 | 0.39 |
F | 农户分化 Rural-household differentiation | 纯农户=0;Ⅰ兼农户=1;Ⅱ兼农户=2 Full-time farmers=0; Type Ⅰ farmers=1; Type Ⅱfarmers=2 | 1.04 | 0.65 |
V0 | 耕地价值认知 Cultivated land value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.72 | 0.08 |
V1 | 经济产出价值认知 Economic output value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.81 | 0.14 |
V2 | 社会保障价值认知 Social security value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.84 | 0.09 |
V3 | 生态保育价值认知 Ecological conservation value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.82 | 0.10 |
V4 | 景观文化价值认知 Landscape cultural value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.79 | 0.12 |
X1 | 性别 Gender | 男=1;女=0 Male=1; Female=0 | 0.59 | 0.49 |
X2 | 年龄 Age | <35=1;35~45=2;46~55=3;56~65=4;>65=5 | 3.57 | 1.10 |
X3 | 家庭劳动力人数 Family labor number | 实测数值 Measured value | 3.36 | 1.58 |
X4 | 家庭劳动力平均文化程度 Average education level of family labor | 未上过学=1;小学=2;初中=3;高中(中专)=4;大专及以上=5 Have not attended school=1; Elementary school=2; Junior high school=3; High school (secondary school)=4; Junior college and above=5 | 3.10 | 0.71 |
X5 | 耕地规模 Cultivated land scale | 耕地总面积Cultivated land area(<1 000 m2=1;1 000~<3000 m2=2; 3 000~<5 000 m2=3;5 000~<8 000 m2=4;8 000~<12 000 m2= 5;12 000~<15 000 m2=6;≥15 000m2=7) | 2.45 | 1.56 |
X6 | 耕地破碎度 Cultivated land fragmentation | 耕地总块数Cultivated land number(<3=1;3~5=2;6~8=3; 9~12=4;13~18=5;>18=6) | 1.68 | 1.06 |
X7 | 耕地水肥条件 Water and fertilizer conditions of cultivated land | 很差~非常好=1~5 Very bad-Very good=1-5 | 2.19 | 0.88 |
X8 | 务工环境满意度 Satisfaction toward working environment | 村民对当地务工环境的满意度(极不满意~极其满意=1~5) Villagers’ satisfaction toward the local working environment (Extremely dissatisfied-Extremely satisfied=1-5) | 2.65 | 0.97 |
X9 | 耕地保护补贴政策满意度 Satisfaction toward cultivated land protection subsidy policy | 极不满意~非常满意=1~5 Extremely dissatisfied-Extremely satisfied=1-5 | 2.94 | 1.09 |
X10 | 周围农户是否参与耕地保护 Whether neighbors participate in cultivated land protection | 是=1;否=0 Yes=1; No=0 | 0.25 | 0.43 |
Table 1 Variable description and descriptive statistics
变量 Variable | 变量说明及其赋值 Variable description and assignment | 均值 Mean | 标准差 Standard deviation | |
---|---|---|---|---|
Y1 | 耕地保护行为 Cultivated land protection behavior | 是否采取耕地保护行为(是=1;否=0) Do you take cultivated land protection behavior (Yes=1; No=0) | 0.26 | 0.44 |
Y2 | 劳动偏向型耕地保护行为 Labor-biased behavior | 是否采取劳动偏向型耕地保护行为(是=1;否=0) Do you take labor-biased behavior (Yes=1; No=0) | 0.13 | 0.34 |
Y3 | 资金偏向型耕地保护行为 Capital-biased behavior | 是否采取资金偏向型耕地保护行为(是=1;否=0) Do you take capital-biased behavior (Yes=1; No=0) | 0.18 | 0.39 |
F | 农户分化 Rural-household differentiation | 纯农户=0;Ⅰ兼农户=1;Ⅱ兼农户=2 Full-time farmers=0; Type Ⅰ farmers=1; Type Ⅱfarmers=2 | 1.04 | 0.65 |
V0 | 耕地价值认知 Cultivated land value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.72 | 0.08 |
V1 | 经济产出价值认知 Economic output value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.81 | 0.14 |
V2 | 社会保障价值认知 Social security value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.84 | 0.09 |
V3 | 生态保育价值认知 Ecological conservation value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.82 | 0.10 |
V4 | 景观文化价值认知 Landscape cultural value cognition | 采用熵值法进行测算 Calculated by Entropy method | 0.79 | 0.12 |
X1 | 性别 Gender | 男=1;女=0 Male=1; Female=0 | 0.59 | 0.49 |
X2 | 年龄 Age | <35=1;35~45=2;46~55=3;56~65=4;>65=5 | 3.57 | 1.10 |
X3 | 家庭劳动力人数 Family labor number | 实测数值 Measured value | 3.36 | 1.58 |
X4 | 家庭劳动力平均文化程度 Average education level of family labor | 未上过学=1;小学=2;初中=3;高中(中专)=4;大专及以上=5 Have not attended school=1; Elementary school=2; Junior high school=3; High school (secondary school)=4; Junior college and above=5 | 3.10 | 0.71 |
X5 | 耕地规模 Cultivated land scale | 耕地总面积Cultivated land area(<1 000 m2=1;1 000~<3000 m2=2; 3 000~<5 000 m2=3;5 000~<8 000 m2=4;8 000~<12 000 m2= 5;12 000~<15 000 m2=6;≥15 000m2=7) | 2.45 | 1.56 |
X6 | 耕地破碎度 Cultivated land fragmentation | 耕地总块数Cultivated land number(<3=1;3~5=2;6~8=3; 9~12=4;13~18=5;>18=6) | 1.68 | 1.06 |
X7 | 耕地水肥条件 Water and fertilizer conditions of cultivated land | 很差~非常好=1~5 Very bad-Very good=1-5 | 2.19 | 0.88 |
X8 | 务工环境满意度 Satisfaction toward working environment | 村民对当地务工环境的满意度(极不满意~极其满意=1~5) Villagers’ satisfaction toward the local working environment (Extremely dissatisfied-Extremely satisfied=1-5) | 2.65 | 0.97 |
X9 | 耕地保护补贴政策满意度 Satisfaction toward cultivated land protection subsidy policy | 极不满意~非常满意=1~5 Extremely dissatisfied-Extremely satisfied=1-5 | 2.94 | 1.09 |
X10 | 周围农户是否参与耕地保护 Whether neighbors participate in cultivated land protection | 是=1;否=0 Yes=1; No=0 | 0.25 | 0.43 |
变量 Variable | Y1 | Y1 | Y2 | Y2 | Y3 | Y3 |
---|---|---|---|---|---|---|
模型9 Model 9 | 模型10 Model 10 | 模型11 Model 11 | 模型12 Model 12 | 模型13 Model 13 | 模型14 Model 14 | |
F | -0.918*** (0.277) | -0.742*** (0.265) | -0.716** (0.262) | -0.533** (0.257) | -0.560* (0.279) | -0.410* (0.271) |
V0 | 5.581*** (1.004) | — | 3.138*** (0.997) | — | 2.775*** (1.011) | — |
V1 | — | 4.869*** (0.822) | — | 3.026*** (0.797) | — | 1.733** (0.806) |
V2 | — | 3.857*** (0.794) | — | 1.845** (0.762) | — | 1.672** (0.766) |
V3 | — | 2.164** (1.035) | — | 1.496* (0.991) | — | 1.953** (1.027) |
V4 | — | 4.343*** (0.946) | — | 2.871*** (0.881) | — | 3.764*** (0.895) |
Table 3 Model estimation result after excluding extreme values
变量 Variable | Y1 | Y1 | Y2 | Y2 | Y3 | Y3 |
---|---|---|---|---|---|---|
模型9 Model 9 | 模型10 Model 10 | 模型11 Model 11 | 模型12 Model 12 | 模型13 Model 13 | 模型14 Model 14 | |
F | -0.918*** (0.277) | -0.742*** (0.265) | -0.716** (0.262) | -0.533** (0.257) | -0.560* (0.279) | -0.410* (0.271) |
V0 | 5.581*** (1.004) | — | 3.138*** (0.997) | — | 2.775*** (1.011) | — |
V1 | — | 4.869*** (0.822) | — | 3.026*** (0.797) | — | 1.733** (0.806) |
V2 | — | 3.857*** (0.794) | — | 1.845** (0.762) | — | 1.672** (0.766) |
V3 | — | 2.164** (1.035) | — | 1.496* (0.991) | — | 1.953** (1.027) |
V4 | — | 4.343*** (0.946) | — | 2.871*** (0.881) | — | 3.764*** (0.895) |
变量 Variable | Y1 | Y1 | Y2 | Y2 | Y3 | Y3 |
---|---|---|---|---|---|---|
模型9 Model 9 | 模型10 Model 10 | 模型11 Model 11 | 模型12 Model 12 | 模型13 Model 13 | 模型14 Model 14 | |
F | -0.554*** (0.218) | -0.569*** (0.217) | -0.475** (0.220) | -0.427** (0.218) | -0.320* (0.223) | -0.323* (0.222) |
V0 | 7.243*** (0.659) | — | 4.592*** (0.647) | — | 2.866*** (0.655) | — |
V1 | — | 6.721*** (0.886) | — | 5.184*** (0.872) | — | 3.226*** (0.874) |
V2 | — | 4.967*** (1.217) | — | 3.225** (1.214) | — | 2.940** (1.198) |
V3 | — | 2.983** (1.105) | — | 2.009* (1.110) | — | 2.255* (1.106) |
V4 | — | 5.799*** (0.943) | — | 2.145** (0.945) | — | 5.113*** (0.951) |
Table 4 Outer suburbs model estimation result
变量 Variable | Y1 | Y1 | Y2 | Y2 | Y3 | Y3 |
---|---|---|---|---|---|---|
模型9 Model 9 | 模型10 Model 10 | 模型11 Model 11 | 模型12 Model 12 | 模型13 Model 13 | 模型14 Model 14 | |
F | -0.554*** (0.218) | -0.569*** (0.217) | -0.475** (0.220) | -0.427** (0.218) | -0.320* (0.223) | -0.323* (0.222) |
V0 | 7.243*** (0.659) | — | 4.592*** (0.647) | — | 2.866*** (0.655) | — |
V1 | — | 6.721*** (0.886) | — | 5.184*** (0.872) | — | 3.226*** (0.874) |
V2 | — | 4.967*** (1.217) | — | 3.225** (1.214) | — | 2.940** (1.198) |
V3 | — | 2.983** (1.105) | — | 2.009* (1.110) | — | 2.255* (1.106) |
V4 | — | 5.799*** (0.943) | — | 2.145** (0.945) | — | 5.113*** (0.951) |
变量 Variable | Y1 | Y1 | Y2 | Y2 | Y3 | Y3 |
---|---|---|---|---|---|---|
模型9 Model 9 | 模型10 Model 10 | 模型11 Model 11 | 模型12 Model 12 | 模型13 Model 13 | 模型14 Model 14 | |
F | -0.719*** (0.306) | -0.641*** (0.303) | -0.520** (0.294) | -0.497* (0.310) | -0.433* (0.302) | -0.415* (0.298) |
V0 | 5.963*** (0.783) | — | 3.211*** (0.775) | — | 2.343*** (0.782) | — |
V1 | — | 4.785*** (0.111) | — | 4.146*** (0.109) | — | 2.560** (1.108) |
V2 | — | 2.884*** (0.859) | — | 2.015** (0.913) | — | 1.747** (0.884) |
V3 | — | 3.006** (1.002) | — | 2.182** (0.997) | — | 2.559** (1.001) |
V4 | — | 3.791*** (1.032) | — | 2.193** (1.044) | — | 3.577*** (1.041) |
Table 5 Suburban villages model estimation result
变量 Variable | Y1 | Y1 | Y2 | Y2 | Y3 | Y3 |
---|---|---|---|---|---|---|
模型9 Model 9 | 模型10 Model 10 | 模型11 Model 11 | 模型12 Model 12 | 模型13 Model 13 | 模型14 Model 14 | |
F | -0.719*** (0.306) | -0.641*** (0.303) | -0.520** (0.294) | -0.497* (0.310) | -0.433* (0.302) | -0.415* (0.298) |
V0 | 5.963*** (0.783) | — | 3.211*** (0.775) | — | 2.343*** (0.782) | — |
V1 | — | 4.785*** (0.111) | — | 4.146*** (0.109) | — | 2.560** (1.108) |
V2 | — | 2.884*** (0.859) | — | 2.015** (0.913) | — | 1.747** (0.884) |
V3 | — | 3.006** (1.002) | — | 2.182** (0.997) | — | 2.559** (1.001) |
V4 | — | 3.791*** (1.032) | — | 2.193** (1.044) | — | 3.577*** (1.041) |
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