草业学报 ›› 2021, Vol. 30 ›› Issue (6): 1-15.DOI: 10.11686/cyxb2020228
• 研究论文 • 下一篇
收稿日期:
2020-05-21
修回日期:
2020-07-29
出版日期:
2021-05-21
发布日期:
2021-05-21
通讯作者:
唐增
作者简介:
Corresponding author. E-mail: tangz@lzu.edu.cn基金资助:
Shi-qi GUAN1(), Hong-wei LI2, Zeng TANG1()
Received:
2020-05-21
Revised:
2020-07-29
Online:
2021-05-21
Published:
2021-05-21
Contact:
Zeng TANG
摘要:
草原牧区的发展对于我国畜牧业而言具有非常重要的战略意义,为了促进牧区的可持续发展和牧民增收,我国政府于2011年开始实施草原生态补偿政策,在此政策背景下,基于16篇实证研究的3099个样本,运用Meta分析和累积Meta分析方法,探讨了政策实施以来影响牧民收入的重要因素,并分析了这些因素的影响作用随时间的变化趋势。研究结果表明,显著促进牧民收入的因素有牧民受教育程度、家庭劳动力数量、牲畜养殖规模、草场承包面积;其中牧户最为关注的因素有草场承包面积和牲畜养殖规模;而随着政策实施,牲畜数量的影响作用明显增加,其他因素都在减弱;很多变量都存在异质性,其中家庭劳动力数量和草场面积的异质性来源主要是地区因素,除此之外还有政策实施时间和抽样方式的影响。
关士琪, 李泓薇, 唐增. 影响牧民收入的关键因素研究—基于Meta分析与累积Meta分析[J]. 草业学报, 2021, 30(6): 1-15.
Shi-qi GUAN, Hong-wei LI, Zeng TANG. Key factors affecting herder’s income: A Meta-analysis and cumulative Meta-analysis[J]. Acta Prataculturae Sinica, 2021, 30(6): 1-15.
检索项目Search items | 详细条件Detailed conditions |
---|---|
中英文数据库Chinese and English database | 中国知网,万方数据库,维普中文科技期刊数据库,施普林格,科学网,科学直接,威利在线图书馆。China national knowledge infrastructure, Wanfang data knowledge service platform, China science and technology journal database, Springerlink, web of science, science direct, wiley online library. |
中英文关键词Chinese and English keywords | 牧民收入,影响因素,生计资本,草原生态补奖政策,草地补偿政策。Income of herders, influence factors, livelihood capital, grassland ecological protection subsidy incentive mechanic, grassland ecological compensation, eco-compensation policy. |
表1 检索项目
Table 1 Search items
检索项目Search items | 详细条件Detailed conditions |
---|---|
中英文数据库Chinese and English database | 中国知网,万方数据库,维普中文科技期刊数据库,施普林格,科学网,科学直接,威利在线图书馆。China national knowledge infrastructure, Wanfang data knowledge service platform, China science and technology journal database, Springerlink, web of science, science direct, wiley online library. |
中英文关键词Chinese and English keywords | 牧民收入,影响因素,生计资本,草原生态补奖政策,草地补偿政策。Income of herders, influence factors, livelihood capital, grassland ecological protection subsidy incentive mechanic, grassland ecological compensation, eco-compensation policy. |
文献序号 Document number | 第一作者 First author | 样本量 Sample size | 发表年限 Year | 研究地区 Study area | 模型方法 Model |
---|---|---|---|---|---|
韩枫[ | 236 | 2017 | 甘肃甘南Gannan, Gansu | OLS | |
刘宇晨[ | 511 | 2019 | 内蒙古Inner Mongolia | Logit | |
雷文玉[ | 123 | 2016 | 内蒙古Inner Mongolia | Logit | |
杜三强[ | 142 | 2019 | 甘南,肃南Gannan, Sunan | Logit | |
杨伊侬[ | 98 | 2009 | 内蒙古Inner Mongolia | 多元线性回归 | |
欧孝双[ | 179 | 2017 | 内蒙古Inner Mongolia | OLS | |
王冬雪[ | 108 | 2016 | 内蒙古Inner Mongolia | 多元线性回归 | |
达布希拉图[ | 120 | 2014 | 内蒙古Inner Mongolia | Logit | |
刘玉春[ | 27 | 2013 | 内蒙古Inner Mongolia | 多元线性回归 | |
宁银仓[ | 100 | 2011 | 甘肃天祝Tianzhu, Gansu | 多元线性回归 | |
方芳[ | 193 | 2014 | 新疆乌鲁木齐Urumqi, Xinjiang | Logit | |
张瑞霞[ | 81 | 2016 | 内蒙古Inner Mongolia | Logit | |
马晓萍[ | 112 | 2017 | 内蒙古Inner Mongolia | 多元线性回归 | |
游力[ | 455 | 2016 | 新疆阿勒泰Altay, Xinjiang | Logit | |
殷芳[ | 212 | 2013 | 青海省三江源Three-river-source, Qinghai | 多元线性回归 | |
王小鹏[ | 402 | 2011 | 甘肃肃南肃北Sunan, Subei, Gansu | OLS |
表2 文献编码
Table 2 Literature coding
文献序号 Document number | 第一作者 First author | 样本量 Sample size | 发表年限 Year | 研究地区 Study area | 模型方法 Model |
---|---|---|---|---|---|
韩枫[ | 236 | 2017 | 甘肃甘南Gannan, Gansu | OLS | |
刘宇晨[ | 511 | 2019 | 内蒙古Inner Mongolia | Logit | |
雷文玉[ | 123 | 2016 | 内蒙古Inner Mongolia | Logit | |
杜三强[ | 142 | 2019 | 甘南,肃南Gannan, Sunan | Logit | |
杨伊侬[ | 98 | 2009 | 内蒙古Inner Mongolia | 多元线性回归 | |
欧孝双[ | 179 | 2017 | 内蒙古Inner Mongolia | OLS | |
王冬雪[ | 108 | 2016 | 内蒙古Inner Mongolia | 多元线性回归 | |
达布希拉图[ | 120 | 2014 | 内蒙古Inner Mongolia | Logit | |
刘玉春[ | 27 | 2013 | 内蒙古Inner Mongolia | 多元线性回归 | |
宁银仓[ | 100 | 2011 | 甘肃天祝Tianzhu, Gansu | 多元线性回归 | |
方芳[ | 193 | 2014 | 新疆乌鲁木齐Urumqi, Xinjiang | Logit | |
张瑞霞[ | 81 | 2016 | 内蒙古Inner Mongolia | Logit | |
马晓萍[ | 112 | 2017 | 内蒙古Inner Mongolia | 多元线性回归 | |
游力[ | 455 | 2016 | 新疆阿勒泰Altay, Xinjiang | Logit | |
殷芳[ | 212 | 2013 | 青海省三江源Three-river-source, Qinghai | 多元线性回归 | |
王小鹏[ | 402 | 2011 | 甘肃肃南肃北Sunan, Subei, Gansu | OLS |
维度Dimension | 变量Variable | 变量说明及测量方式Variable description and measurement method |
---|---|---|
牧民个体特征变量Individual characteristic variables of herdsmen | 年龄Age | 牧民的年龄∶连续变量或者分段变量。Herdsman’s age: Continuous or segmented variable. |
受教育程度Education | 牧民的文化水平∶分段变量。Literacy level of herdsmen: Piecewise variable. | |
牧户家庭特征变量Characteristic variables of pastoral households | 家庭人口数量 Family households | 牧户家庭实际人口数∶连续变量或者分段变量。Actual household size: Continuous or segmented variable. |
家庭劳动力数量 No. of labor | 牧户家庭的劳动力人数∶连续变量或者分段变量。The size of the pastoral workforce: A continuous or segmented variable. | |
牲畜存栏数 No. of livestock | 牧户家庭的牲畜数量∶连续变量或者分段变量。Number of livestock in a household: Continuous or segmented variable. | |
草场面积 Grassland area | 牧户家庭的承包面积∶连续变量或者分段变量。The contracted area of a pastoral household: Continuous variable or subsection variable. | |
贷款情况Debt | 牧户家庭每年的贷款情况∶连续变量或者分段变量Annual loans to pastoral households: Continuous variable or subsection variable |
表3 变量描述
Table 3 Description of variables
维度Dimension | 变量Variable | 变量说明及测量方式Variable description and measurement method |
---|---|---|
牧民个体特征变量Individual characteristic variables of herdsmen | 年龄Age | 牧民的年龄∶连续变量或者分段变量。Herdsman’s age: Continuous or segmented variable. |
受教育程度Education | 牧民的文化水平∶分段变量。Literacy level of herdsmen: Piecewise variable. | |
牧户家庭特征变量Characteristic variables of pastoral households | 家庭人口数量 Family households | 牧户家庭实际人口数∶连续变量或者分段变量。Actual household size: Continuous or segmented variable. |
家庭劳动力数量 No. of labor | 牧户家庭的劳动力人数∶连续变量或者分段变量。The size of the pastoral workforce: A continuous or segmented variable. | |
牲畜存栏数 No. of livestock | 牧户家庭的牲畜数量∶连续变量或者分段变量。Number of livestock in a household: Continuous or segmented variable. | |
草场面积 Grassland area | 牧户家庭的承包面积∶连续变量或者分段变量。The contracted area of a pastoral household: Continuous variable or subsection variable. | |
贷款情况Debt | 牧户家庭每年的贷款情况∶连续变量或者分段变量Annual loans to pastoral households: Continuous variable or subsection variable |
变量Variable | E | SE | 置信区间Confidence interval | Z | P | Q | PQ | I2 | Tau2 | TB | PB | n | N | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
下限Lower | 上限Upper | |||||||||||||
年龄Age | 0.034 | 0.084 | -0.132 | 0.199 | 0.399 | 0.690 | 15.888 | 0.026 | 55.941 | 0.030 | 0.93004 | 0.38824 | 8 | 1489 |
受教育程度Education | 0.248 | 0.062 | 0.126 | 0.370 | 3.988 | 0.000 | 25.908 | 0.011 | 53.681 | 0.025 | 1.29948 | 0.22035 | 13 | 2557 |
家庭人口数量Family households | 0.133 | 0.197 | -0.253 | 0.518 | 0.674 | 0.500 | 39.196 | 0.000 | 89.795 | 0.171 | 0.58917 | 0.59717 | 5 | 1157 |
家庭劳动力数量No. of labor | 0.250 | 0.106 | 0.043 | 0.457 | 2.372 | 0.018 | 45.782 | 0.000 | 80.342 | 0.086 | 1.64151 | 0.13932 | 10 | 2098 |
牲畜存栏数No. of livestock | 0.258 | 0.086 | 0.090 | 0.426 | 3.009 | 0.003 | 36.897 | 0.000 | 72.897 | 0.055 | 1.89334 | 0.09085 | 11 | 2312 |
草场面积 Grassland area | 0.373 | 0.115 | 0.147 | 0.599 | 3.239 | 0.001 | 41.561 | 0.000 | 80.751 | 0.091 | 3.43743 | 0.01088 | 9 | 1881 |
贷款情况Debt | 0.101 | 0.256 | -0.400 | 0.602 | 0.396 | 0.692 | 28.912 | 0.000 | 86.165 | 0.241 | 1.82205 | 0.16598 | 5 | 605 |
表4 Meta分析结果
Table 4 Meta-analysis results
变量Variable | E | SE | 置信区间Confidence interval | Z | P | Q | PQ | I2 | Tau2 | TB | PB | n | N | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
下限Lower | 上限Upper | |||||||||||||
年龄Age | 0.034 | 0.084 | -0.132 | 0.199 | 0.399 | 0.690 | 15.888 | 0.026 | 55.941 | 0.030 | 0.93004 | 0.38824 | 8 | 1489 |
受教育程度Education | 0.248 | 0.062 | 0.126 | 0.370 | 3.988 | 0.000 | 25.908 | 0.011 | 53.681 | 0.025 | 1.29948 | 0.22035 | 13 | 2557 |
家庭人口数量Family households | 0.133 | 0.197 | -0.253 | 0.518 | 0.674 | 0.500 | 39.196 | 0.000 | 89.795 | 0.171 | 0.58917 | 0.59717 | 5 | 1157 |
家庭劳动力数量No. of labor | 0.250 | 0.106 | 0.043 | 0.457 | 2.372 | 0.018 | 45.782 | 0.000 | 80.342 | 0.086 | 1.64151 | 0.13932 | 10 | 2098 |
牲畜存栏数No. of livestock | 0.258 | 0.086 | 0.090 | 0.426 | 3.009 | 0.003 | 36.897 | 0.000 | 72.897 | 0.055 | 1.89334 | 0.09085 | 11 | 2312 |
草场面积 Grassland area | 0.373 | 0.115 | 0.147 | 0.599 | 3.239 | 0.001 | 41.561 | 0.000 | 80.751 | 0.091 | 3.43743 | 0.01088 | 9 | 1881 |
贷款情况Debt | 0.101 | 0.256 | -0.400 | 0.602 | 0.396 | 0.692 | 28.912 | 0.000 | 86.165 | 0.241 | 1.82205 | 0.16598 | 5 | 605 |
变量Variable | E | SE | 置信区间Confidence interval | Z | P | Q | PQ | I2 | Tau2 | n | N | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
下限Lower | 上限Upper | |||||||||||
年龄Age | 0.047 | 0.108 | -0.164 | 0.258 | 0.436 | 0.663 | 15.888 | 0.014 | 62.235 | 0.050 | 7 | 1253 |
年龄Age | -0.001 | 0.088 | -0.173 | 0.172 | -0.009 | 0.993 | 13.161 | 0.041 | 54.410 | 0.028 | 7 | 978 |
年龄Age | 0.080 | 0.082 | -0.080 | 0.240 | 0.982 | 0.326 | 10.970 | 0.089 | 45.305 | 0.020 | 7 | 1347 |
年龄Age | 0.048 | 0.095 | -0.138 | 0.233 | 0.506 | 0.613 | 15.754 | 0.015 | 61.914 | 0.037 | 7 | 1310 |
年龄Age | 0.057 | 0.094 | -0.126 | 0.241 | 0.611 | 0.541 | 15.233 | 0.019 | 60.611 | 0.035 | 7 | 1381 |
年龄Age | -0.014 | 0.077 | -0.164 | 0.137 | -0.179 | 0.858 | 10.833 | 0.094 | 44.615 | 0.018 | 7 | 1369 |
年龄Age | -0.002 | 0.086 | -0.171 | 0.167 | -0.024 | 0.981 | 13.014 | 0.043 | 53.896 | 0.026 | 7 | 1408 |
年龄Age | 0.063 | 0.097 | -0.128 | 0.254 | 0.646 | 0.518 | 14.819 | 0.022 | 59.511 | 0.037 | 7 | 1377 |
牲畜存栏数No. of livestock | 0.292 | 0.093 | 0.111 | 0.473 | 3.155 | 0.002 | 30.664 | 0.000 | 70.650 | 0.058 | 10 | 2076 |
牲畜存栏数No. of livestock | 0.254 | 0.092 | 0.073 | 0.436 | 2.755 | 0.006 | 36.485 | 0.000 | 75.333 | 0.061 | 10 | 1801 |
牲畜存栏数No. of livestock | 0.259 | 0.093 | 0.076 | 0.442 | 2.778 | 0.005 | 36.735 | 0.000 | 75.500 | 0.062 | 10 | 2189 |
牲畜存栏数No. of livestock | 0.214 | 0.082 | 0.054 | 0.374 | 2.624 | 0.009 | 28.791 | 0.001 | 68.740 | 0.043 | 10 | 2171 |
牲畜存栏数No. of livestock | 0.252 | 0.092 | 0.072 | 0.433 | 2.741 | 0.006 | 36.328 | 0.000 | 75.226 | 0.060 | 10 | 2204 |
牲畜存栏数No. of livestock | 0.301 | 0.084 | 0.137 | 0.465 | 3.596 | 0.000 | 30.279 | 0.000 | 70.276 | 0.046 | 10 | 2192 |
牲畜存栏数No. of livestock | 0.285 | 0.093 | 0.102 | 0.467 | 3.063 | 0.002 | 35.258 | 0.000 | 74.474 | 0.060 | 10 | 2212 |
牲畜存栏数No. of livestock | 0.214 | 0.082 | 0.054 | 0.374 | 2.622 | 0.009 | 28.781 | 0.001 | 68.729 | 0.032 | 10 | 2119 |
牲畜存栏数No. of livestock | 0.285 | 0.097 | 0.095 | 0.475 | 2.945 | 0.003 | 34.272 | 0.000 | 73.739 | 0.066 | 10 | 2200 |
牲畜存栏数No. of livestock | 0.242 | 0.092 | 0.062 | 0.423 | 2.625 | 0.008 | 34.347 | 0.000 | 73.796 | 0.059 | 10 | 1857 |
牲畜存栏数No. of livestock | 0.239 | 0.091 | 0.060 | 0.417 | 2.617 | 0.009 | 33.316 | 0.000 | 72.986 | 0.057 | 10 | 2100 |
表5 变量的敏感性分析
Table 5 Variable sensitivity analysis
变量Variable | E | SE | 置信区间Confidence interval | Z | P | Q | PQ | I2 | Tau2 | n | N | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
下限Lower | 上限Upper | |||||||||||
年龄Age | 0.047 | 0.108 | -0.164 | 0.258 | 0.436 | 0.663 | 15.888 | 0.014 | 62.235 | 0.050 | 7 | 1253 |
年龄Age | -0.001 | 0.088 | -0.173 | 0.172 | -0.009 | 0.993 | 13.161 | 0.041 | 54.410 | 0.028 | 7 | 978 |
年龄Age | 0.080 | 0.082 | -0.080 | 0.240 | 0.982 | 0.326 | 10.970 | 0.089 | 45.305 | 0.020 | 7 | 1347 |
年龄Age | 0.048 | 0.095 | -0.138 | 0.233 | 0.506 | 0.613 | 15.754 | 0.015 | 61.914 | 0.037 | 7 | 1310 |
年龄Age | 0.057 | 0.094 | -0.126 | 0.241 | 0.611 | 0.541 | 15.233 | 0.019 | 60.611 | 0.035 | 7 | 1381 |
年龄Age | -0.014 | 0.077 | -0.164 | 0.137 | -0.179 | 0.858 | 10.833 | 0.094 | 44.615 | 0.018 | 7 | 1369 |
年龄Age | -0.002 | 0.086 | -0.171 | 0.167 | -0.024 | 0.981 | 13.014 | 0.043 | 53.896 | 0.026 | 7 | 1408 |
年龄Age | 0.063 | 0.097 | -0.128 | 0.254 | 0.646 | 0.518 | 14.819 | 0.022 | 59.511 | 0.037 | 7 | 1377 |
牲畜存栏数No. of livestock | 0.292 | 0.093 | 0.111 | 0.473 | 3.155 | 0.002 | 30.664 | 0.000 | 70.650 | 0.058 | 10 | 2076 |
牲畜存栏数No. of livestock | 0.254 | 0.092 | 0.073 | 0.436 | 2.755 | 0.006 | 36.485 | 0.000 | 75.333 | 0.061 | 10 | 1801 |
牲畜存栏数No. of livestock | 0.259 | 0.093 | 0.076 | 0.442 | 2.778 | 0.005 | 36.735 | 0.000 | 75.500 | 0.062 | 10 | 2189 |
牲畜存栏数No. of livestock | 0.214 | 0.082 | 0.054 | 0.374 | 2.624 | 0.009 | 28.791 | 0.001 | 68.740 | 0.043 | 10 | 2171 |
牲畜存栏数No. of livestock | 0.252 | 0.092 | 0.072 | 0.433 | 2.741 | 0.006 | 36.328 | 0.000 | 75.226 | 0.060 | 10 | 2204 |
牲畜存栏数No. of livestock | 0.301 | 0.084 | 0.137 | 0.465 | 3.596 | 0.000 | 30.279 | 0.000 | 70.276 | 0.046 | 10 | 2192 |
牲畜存栏数No. of livestock | 0.285 | 0.093 | 0.102 | 0.467 | 3.063 | 0.002 | 35.258 | 0.000 | 74.474 | 0.060 | 10 | 2212 |
牲畜存栏数No. of livestock | 0.214 | 0.082 | 0.054 | 0.374 | 2.622 | 0.009 | 28.781 | 0.001 | 68.729 | 0.032 | 10 | 2119 |
牲畜存栏数No. of livestock | 0.285 | 0.097 | 0.095 | 0.475 | 2.945 | 0.003 | 34.272 | 0.000 | 73.739 | 0.066 | 10 | 2200 |
牲畜存栏数No. of livestock | 0.242 | 0.092 | 0.062 | 0.423 | 2.625 | 0.008 | 34.347 | 0.000 | 73.796 | 0.059 | 10 | 1857 |
牲畜存栏数No. of livestock | 0.239 | 0.091 | 0.060 | 0.417 | 2.617 | 0.009 | 33.316 | 0.000 | 72.986 | 0.057 | 10 | 2100 |
调节变量 Moderator variable | 家庭人口数量People | 家庭劳动力数量Labor | 草场面积Area | 贷款情况Debt | ||||
---|---|---|---|---|---|---|---|---|
系数 Coefficient | 校正拟合优度 Adjusted R2 (%) | 系数 Coefficient | 校正拟合优度 Adjusted R2 (%) | 系数 Coefficient | 校正拟合优度 Adjusted R2 (%) | 系数 Coefficient | 校正拟合优度Adjusted R2 (%) | |
时间因素Time factor | -0.149 | 43.74 | -0.078 | 42.78 | -0.070 | 15.01 | -0.138 | -47.70 |
地区因素Regional factor | 0.083 | -107.98 | -0.436 | 28.66 | -0.450 | -18.20 | -0.987 | -48.42 |
变量类型Variable types | -0.378 | -0.71 | 0.124 | -13.37 | 0.469 | 13.87 | -2.532 | 11.52 |
抽样方式Sampling method | 0.361 | 18.29 | -0.063 | -17.50 | -1.733 | -32.31 | ||
回归模型Regression model | -0.657 | 84.17 | 0.224 | -18.84 | 0.160 | -19.24 | 1.445 | -128.49 |
表6 各变量的Meta回归分析
Table 6 Meta regression of variables
调节变量 Moderator variable | 家庭人口数量People | 家庭劳动力数量Labor | 草场面积Area | 贷款情况Debt | ||||
---|---|---|---|---|---|---|---|---|
系数 Coefficient | 校正拟合优度 Adjusted R2 (%) | 系数 Coefficient | 校正拟合优度 Adjusted R2 (%) | 系数 Coefficient | 校正拟合优度 Adjusted R2 (%) | 系数 Coefficient | 校正拟合优度Adjusted R2 (%) | |
时间因素Time factor | -0.149 | 43.74 | -0.078 | 42.78 | -0.070 | 15.01 | -0.138 | -47.70 |
地区因素Regional factor | 0.083 | -107.98 | -0.436 | 28.66 | -0.450 | -18.20 | -0.987 | -48.42 |
变量类型Variable types | -0.378 | -0.71 | 0.124 | -13.37 | 0.469 | 13.87 | -2.532 | 11.52 |
抽样方式Sampling method | 0.361 | 18.29 | -0.063 | -17.50 | -1.733 | -32.31 | ||
回归模型Regression model | -0.657 | 84.17 | 0.224 | -18.84 | 0.160 | -19.24 | 1.445 | -128.49 |
调节变量 Moderator variable | 家庭劳动力数量Labor | 草场面积Area | ||||
---|---|---|---|---|---|---|
系数Coefficient | t2 | 校正拟合优度Adjusted R2 (%) | 系数Coefficient | t2 | 校正拟合优度Adjusted R2 (%) | |
时间因素Time factor | -0.199** | 0.028 | 71.64 | |||
地区因素Regional factor | 0.402 | 0.052 | 51.49 | 0.942 | ||
抽样方式Sampling method | 1.284** | |||||
回归模型Regression model | 0.783 | |||||
变量类型Variable types | 1.591* |
表7 综合Meta回归分析
Table 7 Comprehensive Meta regression analysis
调节变量 Moderator variable | 家庭劳动力数量Labor | 草场面积Area | ||||
---|---|---|---|---|---|---|
系数Coefficient | t2 | 校正拟合优度Adjusted R2 (%) | 系数Coefficient | t2 | 校正拟合优度Adjusted R2 (%) | |
时间因素Time factor | -0.199** | 0.028 | 71.64 | |||
地区因素Regional factor | 0.402 | 0.052 | 51.49 | 0.942 | ||
抽样方式Sampling method | 1.284** | |||||
回归模型Regression model | 0.783 | |||||
变量类型Variable types | 1.591* |
分组对象 Grouping object | 亚组 Subgroup | 家庭劳动力数量Labor | 草场面积Area | ||||||
---|---|---|---|---|---|---|---|---|---|
E | SE | Z | P | E | SE | Z | P | ||
地区Region | 东部地区Eastern region | 0.098 | 0.165 | 0.594 | 0.553 | 0.407 | 0.158 | 2.575 | 0.010 |
西部地区Western region | 0.055 | 0.172 | 0.321 | 0.748 | 0.647 | 0.212 | 3.054 | 0.002 | |
中部地区Central region | 0.531 | 0.151 | 3.511 | 0.000 | 0.195 | 0.241 | 0.812 | 0.417 | |
抽样方式Sampling method | 非随机Nonrandom | 0.040 | 0.162 | 0.245 | 0.806 | ||||
随机Random | 0.403 | 0.146 | 2.758 | 0.006 | |||||
变量类型Variable types | 连续变量Continuous variable | 0.296 | 0.152 | 1.948 | 0.051 | ||||
分段变量Segment variable | 0.163 | 0.149 | 1.093 | 0.274 | |||||
政策时间Policy time | 第一轮The first round | 0.326 | 0.215 | 1.516 | 0.130 | ||||
第二轮The second round | 0.407 | 0.158 | 2.575 | 0.010 |
表8 家庭劳动力数量和草场面积的亚组分析
Table 8 Subgroup analysis of the number of family labor and grassland area
分组对象 Grouping object | 亚组 Subgroup | 家庭劳动力数量Labor | 草场面积Area | ||||||
---|---|---|---|---|---|---|---|---|---|
E | SE | Z | P | E | SE | Z | P | ||
地区Region | 东部地区Eastern region | 0.098 | 0.165 | 0.594 | 0.553 | 0.407 | 0.158 | 2.575 | 0.010 |
西部地区Western region | 0.055 | 0.172 | 0.321 | 0.748 | 0.647 | 0.212 | 3.054 | 0.002 | |
中部地区Central region | 0.531 | 0.151 | 3.511 | 0.000 | 0.195 | 0.241 | 0.812 | 0.417 | |
抽样方式Sampling method | 非随机Nonrandom | 0.040 | 0.162 | 0.245 | 0.806 | ||||
随机Random | 0.403 | 0.146 | 2.758 | 0.006 | |||||
变量类型Variable types | 连续变量Continuous variable | 0.296 | 0.152 | 1.948 | 0.051 | ||||
分段变量Segment variable | 0.163 | 0.149 | 1.093 | 0.274 | |||||
政策时间Policy time | 第一轮The first round | 0.326 | 0.215 | 1.516 | 0.130 | ||||
第二轮The second round | 0.407 | 0.158 | 2.575 | 0.010 |
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