Arid Land Geography ›› 2024, Vol. 47 ›› Issue (7): 1210-1219.doi: 10.12118/j.issn.1000-6060.2023.604
• Regional Development • Previous Articles Next Articles
ZHU Aiai(), YIN Songkui(), LIU Qionghui
Received:
2023-10-24
Revised:
2024-01-05
Online:
2024-07-25
Published:
2024-07-30
Contact:
YIN Songkui
E-mail:m17689315403@163.com;yinsongkui@163.com
ZHU Aiai, YIN Songkui, LIU Qionghui. Spatial and temporal differentiation and influencing factors of agricultural ecological efficiency in northwest China[J].Arid Land Geography, 2024, 47(7): 1210-1219.
Tab. 2
CO2 emissions in northwest China at the city scale from 2010 to 2020"
统计量 | 2010年 | 2011年 | 2012年 | 2013年 | 2014年 | 2015年 | 2016年 | 2017年 | 2018年 | 2019年 | 2020年 |
---|---|---|---|---|---|---|---|---|---|---|---|
平均值 | 1.677 | 1.732 | 1.748 | 1.809 | 1.863 | 1.893 | 1.904 | 1.714 | 1.707 | 1.679 | 1.870 |
中位数 | 1.428 | 1.483 | 1.510 | 1.573 | 1.643 | 1.644 | 1.747 | 1.458 | 1.451 | 1.482 | 1.628 |
标准差 | 1.149 | 1.182 | 1.199 | 1.265 | 1.231 | 1.275 | 1.284 | 1.169 | 1.151 | 1.117 | 1.268 |
观测数 | 51 | 51 | 51 | 51 | 51 | 51 | 51 | 51 | 51 | 51 | 51 |
Tab. 3
Statistics of agricultural eco-efficiency in northwest China at the city scale from 2010 to 2020"
年份 | 2010年 | 2011年 | 2012年 | 2013年 | 2014年 | 2015年 | 2016年 | 2017年 | 2018年 | 2019年 | 2020年 |
---|---|---|---|---|---|---|---|---|---|---|---|
中位数 | 0.512 | 0.187 | 0.514 | 0.608 | 0.553 | 0.562 | 0.585 | 0.640 | 1.012 | 0.851 | 1.001 |
差异系数 | 0.600 | 1.147 | 0.596 | 0.549 | 0.636 | 0.558 | 0.548 | 0.539 | 0.447 | 0.471 | 0.491 |
偏度系数 | 1.097 | 1.655 | 0.991 | 0.977 | 0.757 | 1.036 | 0.950 | 0.837 | 0.528 | 0.501 | 0.658 |
峰度系数 | 0.315 | 1.594 | 0.055 | 0.151 | -0.039 | 0.223 | 0.180 | 0.052 | -0.056 | -0.084 | -0.098 |
Tab. 4
Dagum Gini coefficient and contribution rates of agricultural eco-efficiency in northwest China from 2010 to 2020"
年份 | 基尼系数 | 贡献率/% | ||||||
---|---|---|---|---|---|---|---|---|
总体 | 组内 | 组间 | 超变密度 | 组内 | 组间 | 超变密度 | ||
2010 | 0.317 | 0.056 | 0.141 | 0.121 | 17.545 | 44.382 | 38.073 | |
2011 | 0.544 | 0.104 | 0.227 | 0.213 | 19.161 | 41.639 | 39.200 | |
2012 | 0.318 | 0.061 | 0.127 | 0.130 | 19.337 | 39.912 | 40.751 | |
2013 | 0.296 | 0.057 | 0.112 | 0.127 | 19.340 | 37.779 | 42.881 | |
2014 | 0.349 | 0.060 | 0.160 | 0.129 | 17.305 | 45.829 | 36.866 | |
2015 | 0.297 | 0.060 | 0.105 | 0.133 | 20.084 | 35.260 | 44.657 | |
2016 | 0.295 | 0.059 | 0.095 | 0.141 | 19.962 | 32.280 | 47.758 | |
2017 | 0.294 | 0.062 | 0.060 | 0.172 | 21.041 | 20.371 | 58.588 | |
2018 | 0.247 | 0.051 | 0.063 | 0.134 | 20.521 | 25.359 | 54.120 | |
2019 | 0.263 | 0.049 | 0.080 | 0.134 | 18.805 | 30.394 | 50.801 | |
2020 | 0.271 | 0.057 | 0.066 | 0.148 | 20.908 | 24.299 | 54.793 |
Tab. 5
Global Moran’s I of agricultural eco-efficiency in northwest China from 2010 to 2020"
年份 | Moran’s I | Z值 | P值 |
---|---|---|---|
2010 | 0.068 | 3.555 | 0.000*** |
2011 | 0.061 | 3.342 | 0.000*** |
2012 | 0.053 | 2.922 | 0.002*** |
2013 | 0.047 | 2.690 | 0.004*** |
2014 | 0.073 | 3.710 | 0.000*** |
2015 | 0.041 | 2.431 | 0.008*** |
2016 | 0.016 | 1.473 | 0.070* |
2017 | -0.016 | -0.207 | 0.418 |
2018 | -0.034 | -0.523 | 0.300 |
2019 | 0.018 | 1.546 | 0.061* |
2020 | 0.024 | 1.763 | 0.039** |
均值 | 0.032 | - | - |
Tab. 6
Indicators of influencing factors of agricultural ecological efficiency in northwest China"
一级指标 | 二级指标 | 指标解释 |
---|---|---|
农业资源禀赋 | 劳均耕地面积(X1) | 耕地面积/农业从业人员 |
农业种植结构(X2) | 粮食作物种植面积/总播种面积 | |
经济发展水平 | 农村居民收入水平(X3) 农村居民收入水平滞后一期(X3(T-1)) | 农村居民人均可支配收入 |
城镇化水平(X4) | 城镇人口/总人口 | |
农业投入强度 | 农业机械密度(X5) | 农业机械总动力/农作物播种面积 |
化肥使用强度(X6) | 化肥施用量/农作物播种面积 |
Tab. 7
Spatial model regression results"
变量 | 双固定效应 | 空间误差模型 | 空间滞后模型 | 空间杜宾模型 | 稳健性检验 |
---|---|---|---|---|---|
X1 | 0.011***(3.00) | 0.011***(4.09) | 0.011***(4.05) | 0.014***(4.43) | 0.011***(4.05) |
X2 | -0.034(-0.59) | -0.041(-0.73) | -0.039(-0.70) | -0.032(-0.55) | -0.047(-0.84) |
X3 | 0.017(1.60) | 0.016*(1.75) | 0.016*(1.79) | 0.009(0.89) | - |
X3(T-1) | - | - | - | - | 0.021**(2.28) |
X4 | 0.003*(1.75) | 0.003***(3.19) | 0.003***(3.25) | 0.003*(1.77) | 0.004***(3.34) |
X5 | -0.002**(-2.09) | -0.001**(-2.07) | -0.002**(-2.09) | -0.001*(-1.94) | -0.001**(-2.03) |
X6 | -0.024*(-1.89) | -0.022*(-1.80) | -0.023*(-1.83) | -0.018(-1.41) | -0.021*(-1.69) |
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