农业社会化服务如何影响粮食生态效率——以黄河流域71个地级市为例

doi:10.12118/j.issn.1000-6060.2024.542

Abstract

Abstract:

The development of agricultural socialized services is a critical component of agricultural modernization. Assessing their contribution to grain ecological efficiency under the “dual-security” framework of grain and ecology is essential for achieving sustainable agricultural development. This study employs panel data from 71 prefecture-level cities in the Yellow River Basin from 2011 to 2020 to examine the spatial spillover and nonlinear effects of agricultural socialized services on grain ecological efficiency. The results reveal that: (1) During the study period, grain ecological efficiency in urban agglomerations within the Yellow River Basin exhibited a clear upward trend. Spatially, efficiency levels were unevenly distributed, with cities rated as excellent or above primarily located in the midstream and downstream regions, while moderate- and low-efficiency areas were concentrated upstream. (2) Agricultural socialized services exert a significant positive spatial spillover effect on grain ecological efficiency, enhancing not only local performance but also positively influencing adjacent regions. This finding remains robust across multiple tests. (3) The effect of agricultural socialized services on grain ecological efficiency exhibits a complex dual-threshold behavior related to the development of per capita planting scale. Specifically, as planting scale increases, the positive impact of agricultural socialized services follows a nonlinear diminishing trend.

Key words: agricultural socialization service, grain ecological efficiency, spatial Durbin model, threshold effect model, Yellow River Basin

ZHONG Jiawei, ZHENG Jun, ZHANG Mingyue. How does agricultural socialization service affect grain eco-efficiency: A case study of 71 prefecture-level cities in the Yellow River Basin[J].Arid Land Geography, 2025, 48(8): 1385-1395.

Figures/Tables 9

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类型	指标	指标说明
投入指标	劳动力投入	农林牧渔业从业人数×（农业产值/农林牧渔总产值）×（粮食播种面积/农作物播种总面积）
	土地投入	粮食作物播种面积
	灌溉投入	有效灌溉面积×（粮食播种面积/农作物播种面积）
	农资投入	农用机械动力×（粮食播种面积/农作物播种面积）
	农资投入	化肥施用量×（粮食播种面积/农作物播种面积）
期望产出	经济效应产出	粮食产量
非期望产出	碳排放量	利用碳排放系数测算的农业碳排放量×（粮食播种面积/农作物播种面积）

指标	2011年	2012年	2013年	2014年	2015年	2016年	2017年	2018年	2019年	2020年
Moran’s I	0.03	0.01	0.02	0.01	0.01	0.03	0.04	0.05	0.08	0.01
Z值	3.10	2.01	2.11	1.96	1.66	2.91	3.61	4.49	5.66	1.68
P值	0.00	0.02	0.02	0.03	0.05	0.00	0.00	0.00	0.00	0.05

检验项目	反地理距离权重矩阵
检验项目	统计量	P值
空间误差模型的拉格朗日乘数检验	21.09	0.00
基于稳健的空间误差模型的拉格朗日乘数检验	5.49	0.01
空间滞后模型的拉格朗日乘数检验	35.55	0.00
基于稳健的空间滞后模型的拉格朗日乘数检验	19.94	0.00
豪斯曼检验	89.32	0.00
个体固定效应检验	3.55	0.46
时间固定效应检验	368.48	0.00
模型选择	时间固定效应模型

变量	模型系数	空间滞后项	Spatial-rho	直接效应	间接效应	总效应
农业社会化服务	0.76^***	-0.12	0.45^***	0.77^***	0.41^***	1.18^***
农业社会化服务	（36.23）	（-0.74）	（3.51）	（35.51）	（2.84）	（8.04）
城镇化水平	0.01^**	-0.01^***		0.01^**	-0.01^**	-0.01^*
城镇化水平	（2.02）	（-2.86）		（2.50）	（-2.47）	（-1.86）
人均种植规模	-0.09^*	1.36		-0.08^*	0.31	0.23
人均种植规模	（-1.95）	（1.19）		（-1.93）	（0.48）	（0.35）
机械化率	0.01^*	0.19		0.01^*	-0.00	0.00
机械化率	（1.83）	（0.60）		（1.82）	（-0.07）	（0.16）
财政支农力度	0.01	-0.01		0.05	2.47	2.51
财政支农力度	（0.03）	（-0.29）		（0.27）	（1.21）	（1.22）

变量	替换模型		替换矩阵
变量	空间误差模型	空间滞后模型	经济地理嵌套矩阵
农业社会化服务	0.76^***	0.76^***	0.89^***
农业社会化服务	（35.86）	（35.74）	（48.76）
城镇化水平	0.00^***	0.01^**	-0.00
城镇化水平	（2.61）	（2.52）	（-1.47）
人均种植规模	-0.09^**	-0.10^**	-0.14
人均种植规模	（-2.16）	（-2.20）	（-0.93）
机械化率	0.00^*	0.01^*	0.08^***
机械化率	（1.79）	（1.87）	（3.08）
财政支农力度	0.00	0.04^*	0.01^***
财政支农力度	（0.02）	（1.83）	（6.06）

How does agricultural socialization service affect grain eco-efficiency: A case study of 71 prefecture-level cities in the Yellow River Basin

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门槛个数	门槛值	F值	P值	10%临界值	5%临界值	1%临界值
单一门槛	0.77	143.58	0.00	19.33	23.88	33.35
双重门槛	0.84	130.81	0.00	17.06	22.85	29.08
三重门槛	0.85	33.21	0.25	57.07	67.44	86.42

变量	粮食生态效率	P值
人均种植规模≤0.77	0.83^***	0.00
人均种植规模≤0.77	（38.30）	0.00
0.77<人均种植规模≤0.84	0.78^*	0.07
0.77<人均种植规模≤0.84	（1.77）	0.07
人均种植规模>0.84	0.54^***	0.00
人均种植规模>0.84	（15.80）	0.00
控制变量	控制
常数项	0.17^***	0.00
常数项	（3.59）

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