Impact and mechanism of agricultural productive services on agro-ecological efficiency
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摘要:
农业生产性服务通过将技术、信息、人才等有效引入农业生产环节, 为实现农业规模化经营, 进而为提高农业生态效率提供新路径。本文基于2005—2021年的中国30个省份(自治区、直辖市, 不包括香港、澳门、台湾和西藏, 下同)面板数据, 构建超效率SBM模型测算各省份的农业生态效率, 绘制核密度图分析农业生态效率的时间演变趋势, 并比较不同地区、不同省份间农业生态效率的差异; 采用双向固定模型分析了农业生产性服务对农业生态效率的影响; 采用中介效应模型分析了农地经营规模、农业种植结构和农业技术推广的中介作用。结果表明: 2005—2021年全国及各区域农业生态效率均呈上升趋势, 全国农业生态效率从2005年的0.388上升到2021年的0.893; 且几乎始终呈东部地区>西部地区>中部地区的趋势, 粮食主销区农业生态效率高于粮食主产区和粮食产销平衡区。各省份间农业生态效率差异较大, 其中青海、上海、海南和北京等省(市)农业生态效率一直较高, 而山西、安徽、甘肃和江西等省份农业生态效率一直较低。农业生产性服务显著提高了农业生态效率, 在进行多种稳健性检验后, 结果仍然成立; 中介效应的估计结果表明, 农业生产性服务能够通过扩大农地经营规模、调整农业种植结构和促进农业技术推广提高农业生态效率; 相较于其他地区, 农业生产性服务对西部地区和粮食产销平衡区的农业生态效率提高作用更加明显。因此, 为提高农业生态效率, 应进一步完善农业生产性服务体系, 促进农地规模经营, 健全耕地保护补贴机制, 防止耕地“非粮化”, 完善农机装备技术创新。
Abstract:Agricultural productive services as soft inputs in the production process offer a new path for realizing large-scale agricultural operations and improving agro-ecological efficiency by effectively integrating technology, information, and talent into agricultural production. Based on provincial panel data in China (not including Hong Kong, Macao, Taiwan and Xizang of China, the same as below) from 2005 to 2021, this study constructed a super-efficiency slack-based measure (SBM) model to measure the agro-ecological efficiency at provincial level. A kernel density map was created to analyze the temporal evolution trends in agro-ecological efficiency and to compare its differences across various regions and provinces. A two-way fixed model was used to examine the effects and mechanisms of agricultural productive services on agro-ecological efficiency. The mediating effect model was used to analyze the mediating role of farmland management scale, agricultural planting structure, and agricultural technology extension. The results showed that from 2005 to 2021, the agro-ecological efficiency of the entire country and each region showed an upward trend. China’s agro-ecological efficiency rose from 0.388 in 2005 to 0.893 in 2021. The efficiency consistently ranked as follows: eastern region > western region > central region, and major grain-sales area > major grain-production area ≈ production-sales balance area. There were significant differences in agro-ecological efficiency among the provinces (municipalities, autonomous regions). Qinghai, Shanghai, Hainan and Beijing consistently exhibited high agro-ecological efficiency, while Shanxi, Anhui, Gansu, and Jiangxi had low agro-ecological efficiency. Agricultural productivity services significantly improved agro-ecological efficiency, with results remaining valid even after endogeneity and various robustness tests. The estimation results of the intermediary effect showed that agricultural productive services improved agro-ecological efficiency by expanding the scale of farmland management, adjusting the agricultural planting structure, and promoting the extension of agricultural technologies. Compared with the eastern region, agricultural productive services in the western region had an evident effect on agro-ecological efficiency, whereas agricultural productive services in the central region showed no significant impact on agro-ecological efficiency. Compared with the major grain-producing areas, agricultural productive services in the production-sales balance areas had a profound effect on the improvement of agro-ecological efficiency. Therefore, to enhance agroecological efficiency, the agricultural production service system should be further improved by vigorously cultivating and developing specialized and diversified service entities, promoting large-scale management of agricultural land, leveraging the advantages of large-scale service operations provided by agricultural production service organizations, improving the subsidy mechanism for cultivated land protection to prevent the “non-grain” conversion of cultivated land, and improving the technological innovation of agricultural machinery and equipment by accelerating the research, development, and promotion of low-carbon and high-efficiency technologies.
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图 1 农业生产性服务对农业生态效率影响的作用机制
Figure 1. Mechanism of the impact of agricultural productive services on agro-ecological efficiency
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图 2 2005—2021年中国及各区域农业生态效率和中国农业生产性服务变化趋势
本研究中全国数据不包括香港、澳门、台湾和西藏。
Figure 2. Changes in agro-ecological efficiency and agricultural productive services in China and different regions from 2005 to 2021
Whole country data in this study did not include Hong Kong, Macao, Taiwan and Xizang of China.
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图 3 2005—2021年中国农业生态效率的核密度估计
Figure 3. Kernel density estimation of agro-ecological efficiency in China from 2005 to 2021
表 1 农业生态效率测算指标的选取与解释
Table 1 Selection and interpretation of relevant indicators of agro-ecological efficiency measurement
变量分类
Variable classification变量
Variable变量解释
Variable explanation资源投入
Resource input土地投入 Land input (×103 hm2) 农作物播种面积 Crop sown area 劳动力投入 Labor input (×104 persons) 农业从业人员 Number of employees in agriculture 机械投入 Machinery input (×104 kW) 农业机械总动力 Total power of agricultural machinery 用水投入 Water input (×103 hm2) 有效灌溉面积 Effectively irrigated area 能源投入 Energy input (×104 t) 农用柴油使用量 Agricultural diesel usage 化肥投入 Fertilizer input (×104 t) 农用化肥施用量 Amount of chemical fertilizer applied 农药投入 Pesticide input (×104 t) 农药使用量 Pesticide use 农膜投入 Agricultural film input (×104 t) 农膜使用量 Amount of agricultural film used 期望产出
Expected output农业总产值
Gross agricultural output (×108 ¥)农业总产值
Gross agricultural output非期望产出
Undesired output农业碳排放
Agricultural carbon emissions (×104 t)根据碳排系数法所得
Calculate based on the carbon emission coefficient method农业面源污染
Agricultural non-point source pollution (×104 t)化肥、农药、农膜的残留物[26]
Residues from chemical fertilizers, pesticides and agricultural film[26]农业总产值以2005年为不变价剔除价格变化影响所得。Gross agricultural output is calculated at constant prices in 2005 excluding the effects of price changes. 
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表 2 农业生产性服务对农业生态效率影响的相关变量描述性统计结果
Table 2 Descriptive statistical results of variables related to the impact of agricultural productive services on agro-ecological efficiency
变量类型
Variable type变量名称
Variable name变量说明
Variable interpretation均值
Mean value标准差
Standard deviation最小值
Minimum value最大值
Maximum value被解释变量
Explained variable农业生态效率
Agro-ecological efficiency (AEE)基于SBM模型测算所得
Measured based on Slack-Based Measure Model (SBM)0.490 0.242 0.170 1.068 核心解释变量
Core explanatory variable农业生产性服务
Agricultural productive services (APS)农林牧渔服务业总产值/农林牧渔从业人数
Gross output value of agriculture, forestry, animal and fishery services / number of employees in agriculture, forestry, animal and fishery (×104 ¥∙cap.−1)0.155 0.120 0.007 0.808 控制变量
Control variable财政支农
Financial support for agriculture (FSA)地方财政农林水事务支出/地方一般预算支出
Expenditure on agriculture, forestry and water affairs
of local finance / expenditure of local general budget0.102 0.039 0.015 0.204 环境规制
Environment regulation
(ER)环保节能支出/地方一般预算支出
Expenditure on environmental protection and energy conservation / expenditure of local general budget0.030 0.012 0.0004 0.094 农业市场化水平
Agricultural marketization level (AML)农村居民人均经营纯收入/农村居民人均纯收入
Operating income per capita of rural residents /
net income per capita of rural residents0.442 0.151 0.049 0.876 受灾面积
Area affected (AA)农作物受灾面积
Crop area affected by natural disaster (×107 hm2)0.099 0.095 0.0002 0.739 农业产业结构
Agricultural industrial structure (AIS)农业总产值/农林牧渔总产值
Gross agricultural output value / gross output
value of agriculture, forestry, animal and fishery0.521 0.084 0.339 0.740 复种指数
Multiple cropping index (MCI)农作物播种面积/耕地面积
Crop sown area / cultivated area1.840 0.579 0.311 3.251 中介变量
Mediator
variable农地经营规模
Scale of farmland management (FMS)农作物播种面积/农业劳动力
Crop sown area / agricultural labor force
[×103 hm2∙(104 cap.)−1]6.658 3.793 1.578 22.752 农业种植结构
Agricultural cultivation structure (ACS)粮食作物播种面积/农作物播种面积
Sown area of grain crops / sown area of crops0.659 0.139 0.355 0.971 农业技术推广
Agricultural technology extension (ATE)农业机械服务组织参与农户数
Number of households participating in agricultural machinery service organizations (×106 persons)0.050 0.079 0.0004 0.591
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表 3 2005年、2013年和2021年中国不同省份(直辖市、自治区)农业生态效率测算结果
Table 3 Estimation results of agro-ecological efficiency in different provinces (municipalities, autonomous regions) of China in 2005, 2013 and 2021
省(直辖市、自治区) Province (municipality, autonomous region) 2005 2013 2021 北京 Beijing 0.6159 1.0018 1.0684 天津 Tianjin 0.3205 0.4108 1.0278 河北 Hebei 0.2217 0.3217 1.0222 山西 Shanxi 0.1698 0.2145 0.3790 内蒙古 Inner Mongolia 0.2723 0.2682 0.4144 辽宁 Liaoning 0.3021 0.3946 0.6582 吉林 Jilin 0.2965 0.3516 1.0219 黑龙江 Heilongjiang 0.2663 0.2545 0.4595 上海 Shanghai 1.0003 1.0018 1.0183 江苏 Jiangsu 0.3190 0.5127 1.0149 浙江 Zhejiang 0.3077 0.3954 1.0504 安徽 Anhui 0.1949 0.2493 0.4112 福建 Fujian 0.3523 0.4802 1.0305 江西 Jiangxi 0.2499 0.3034 0.6170 山东 Shandong 0.2791 0.4460 1.0226 河南 Henan 0.2888 0.4053 1.0190 湖北 Hubei 0.2979 0.3359 1.0177 湖南 Hunan 0.3025 0.3717 0.6558 广东 Guangdong 0.4557 0.5452 1.0197 广西 Guangxi 0.3046 0.3698 1.0173 海南 Hainan 1.0167 0.5038 1.0376 重庆 Chongqing 0.3356 0.4577 1.0187 四川 Sichuan 0.3472 0.4086 1.0366 贵州 Guizhou 0.3635 0.3585 1.0501 云南 Yunnan 0.2342 0.2637 1.0372 陕西 Shaanxi 0.3632 0.4963 1.0160 甘肃 Gansu 0.2367 0.2368 0.5722 青海 Qinghai 1.0348 0.4364 1.0519 宁夏 Ningxia 0.4663 0.2640 1.0079 新疆 Xinjiang 0.4102 0.5449 1.0234
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表 4 农业生产性服务对农业生态效率影响的基准回归结果
Table 4 Baseline regression test results of impact of agricultural productive services on agro-ecological efficiency
变量
Variable模型1 Model 1 模型2 Model 2 模型3 Model 3 模型4 Model 4 系数
Coefficient标准误
Standard error系数
Coefficient标准误
Standard error系数
Coefficient标准误
Standard error系数
Coefficient标准误
Standard errorAPS 0.411*** 0.095 0.300*** 0.091 0.269*** 0.091 0.334*** 0.100 FSA −1.301*** 0.346 −1.311*** 0.343 −1.208*** 0.355 ER 1.967*** 0.692 2.157*** 0.691 1.870*** 0.696 AML −0.114 0.081 −0.128* 0.077 AA −0.137** 0.068 −0.135** 0.066 AIS −0.174 0.216 MCI −0.068*** 0.022 常数项 Constant 0.427*** 0.015 0.518*** 0.051 0.582*** 0.061 0.793*** 0.144 年份固定
Year fixed控制
Controlled控制
Controlled控制
Controlled控制
Controlled控制
Controlled控制
Controlled控制
Controlled控制
Controlled省份固定
Province fixed控制
Controlled控制
Controlled控制
Controlled控制
Controlled控制
Controlled控制
Controlled控制
Controlled控制
ControlledN 510 510 510 510 R2 0.848 0.861 0.863 0.867 APS: 农业生产性服务; FSA: 财政支农; ER: 环境规制; AML: 农业市场化水平; AA: 受灾面积; AIS: 农业产业结构; MCI: 复种指数。*: P<0.1; **: P<0.05; ***: P<0.01. APS: agricultural productive services; FSA: financial support for agriculture; ER: environment regulation; AML: agricultural marketization level; AA: area affected; AIS: agricultural industrial structure; MCI: multiple cropping index.
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表 5 农业生产性服务对农业生态效率影响的内生性检验结果
Table 5 Endogenous test results of impact of agricultural productive services on agro-ecological efficiency
变量 Variable 阶段1 (农业生产性服务)
Phase 1 (agricultural productive services)阶段2 (农业生态效率)
Phase 2 (agro-ecological efficiency)系数 Coefficient 标准误 Standard error 系数 Coefficient 标准误 Standard error 农业生产性服务 Agricultural productive services 0.3533*** 0.1678 工具变量 Tool variable 1.0205*** 0.0285 控制变量 Control variable 控制 Controlled 控制 Controlled 年份固定 Year fixed 控制 Controlled 控制 Controlled 省份固定 Province fixed 控制 Controlled 控制 Controlled N 480 不可识别检验LM统计量
The LM statistic of the test is not identifiable49.289*** 弱工具变量检验Wald F统计量
Weak instrumental variables test for Wald F statistics4348.140 ***: P<0.01.
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表 6 农业生产性服务对农业生态效率影响的稳健性检验结果
Table 6 Robustness test results of impact of agricultural productive services on agro-ecological efficiency
变量 Variable 模型5: 普通最小二乘法(OLS)
Model 5: ordinary least squares (OLS)模型6: 缩尾处理
Model 6: tail reduction模型7: 剔除直辖市
Model 7: eliminate municipalities系数
Coefficient标准误
Standard error系数
Coefficient标准误
Standard error系数
Coefficient标准误
Standard error农业生产性服务
Agricultural productive services0.741*** 0.075 0.334*** 0.100 0.471*** 0.093 常数项 Constant 0.760*** 0.066 0.793*** 0.144 0.624*** 0.140 控制变量 Control variable 控制 Controlled 控制 Controlled 控制 Controlled 年份固定 Year fixed 无控制 Uncontrolled 控制 Controlled 控制 Controlled 省份固定 Province fixed 无控制 Uncontrolled 控制 Controlled 控制 Controlled N 510 510 442 R2 0.446 0.867 0.794 ***: P<0.01.
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表 7 农业生产性服务对农业生态效率影响的中介效应检验结果
Table 7 Results of mediating effect test on effect of agricultural productive services on agro-ecological efficiency
变量 Variable 模型8 Model 8 模型9 Model 9 模型10 Model 10 FMS AEE ACS AEE ATE AEE APS 1.906*** (0.810) 0.294*** (0.101) 0.067** (0.030) 0.316*** (0.101) 0.438*** (0.081) 0.211*** (0.103) FMS 0.021** (0.008) ACS 0.274* (0.161) ATE 0.282*** (0.118) 常数项 Constant 3.286** (1.315) 0.723*** (0.134) 0.637*** (0.055) 0.619*** (0.147) 0.040 (0.036) 0.782*** (0.141) 控制变量 Control variable 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 年份固定 Year fixed 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 省份固定 Province fixed 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled N 510 510 510 510 510 510 R2 0.967 0.870 0.950 0.868 0.805 0.765 Bootstrap 检验的置信区间
Confidence interval of bootstrap test(0.2346, 0.3766) (0.1896, 0.5268) (0.1994, 0.4343) APS: 农业生产性服务; FMS: 农地经营规模; ACS: 农业种植结构; ATE: 农业技术推广; AEE: 农业生态效率。括号内数据为省级层面的聚类稳健标准误。*: P<0.1; **: P<0.05; ***: P<0.01. APS: agricultural productive services; FMS: scale of farmland management; ACS: agricultural cultivation structure; ATE: agricultural technology extension; AEE: agro-ecological efficiency. Values in parentheses are the clustering robustness criteria at the provincial level.
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表 8 农业生产性服务对农业生态效率影响的异质性分析结果
Table 8 Heterogeneity analysis of impact of agricultural productive services on agro-ecological efficiency
变量 Variable 模型11 Model 11 模型12 Model 12 模型13 Model 13 模型14 Model 14 模型15 Model 15 模型16 Model 16 东部地区
Eastern region中部地区
Central region西部地区
Western region粮食主产区
Major grain-production
area粮食主销区
Major grain-sales
area粮食产销平衡区
Production-sales balance
areaAPS 0.346** (0.137) 0.224 (0.217) 1.115*** (0.251) 0.400*** (0.107) −0.404 (0.549) 1.465*** (0.292) 常数项 Constant 1.177*** (0.223) 0.491** (0.187) 0.481* (0.281) 0.523*** (0.148) 1.307*** (0.320) 0.876*** (0.315) 控制变量 Control variable 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 年份固定 Year fixed 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 省份固定 Province fixed 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled 控制 Controlled N 204 119 187 221 119 170 R2 0.894 0.866 0.872 0.890 0.858 0.882 APS: 农业生产性服务。括号内数据为省级层面的聚类稳健标准误。*: P<0.1; **: P<0.05; ***: P<0.01. APS: agricultural productive services. Values in parentheses are the clustering robustness criteria at the provincial level.
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