农机服务对水稻家庭农场全要素生产率的影响研究——以长江流域612户水稻家庭农场为例

doi:10.13733/j.jcam.issn.2095-5553.2023.09.032

摘要/Abstract

摘要： 农机服务作为现代农业科技力量的支撑，能有效提升农业全要素生产率，保障国家粮食安全、保证农民持续增收、实现农业可持续发展。文章使用数据包络分析和Tobit回归分析，基于长江流域612户水稻家庭农场的生产经营状况，对农机服务影响水稻家庭农场全要素生产率及“农机服务主体”和“农机服务机器类型”影响的异质性进行研究，并借助中介模型进一步探讨农机服务影响水稻家庭农场全要素生产率的作用机制。结果表明：农机服务能正向影响水稻家庭农场全要素生产率；不同农机服务主体对水稻家庭农场全要素生产率的影响主次顺序为：本地合作社或公司、外地公司、其他农户、自我服务，且大中型农机要比小型农机更有利于提升水稻家庭农场全要素生产率；农机服务通过“劳动替代”和“规模变动”对水稻家庭农场全要素生产率产生影响。长江流域各地区应积极培育本土化、综合化农机服务组织，鼓励支持大型化、智能化农业机械的升级与应用，提高水稻家庭农场农业生产环节的农机服务应用率，进而减少劳动力的投入，推动土地的规模化经营，优化农业生产的要素配置，以实现全要素生产率的提升。

关键词: 农机服务, 水稻家庭农场, 全要素生产率, 异质性, 中介效应

Abstract: As the support of modern agricultural science and technology, agricultural machinery service can effectively improve the agricultural total factor productivity, ensure the national food security, ensure the continuous increase of farmers income and achieve the sustainable agricultural development. The article uses data envelope analysis and Tobit regression analysis, based on the production and operation status of 612 rice family farms in the Yangtze River basin, studies the impact of agricultural machinery service on the total factor productivity of rice family farms and the heterogeneity of the impact of “agricultural machinery service subject” and “agricultural machinery service machine type”, and further explores the mechanism of agricultural machinery service affecting total factor productivity of rice family farm by means of intermediary model. The results show that agricultural machinery service can positively affect the total factor productivity of rice family farm; the influence of different agricultural machinery service subjects on the total factor productivity of rice family farm is as follows: local cooperatives or companies>nonlocal companies>other farmers>selfservice, and large and mediumsized agricultural machinery is more conducive to improving the total factor productivity of rice family farm than small agricultural machinery; agricultural machinery service has an impact on the total factor productivity of rice family farm through “labor substitution” and “scale change”. All regions in the Yangtze River Basin should actively cultivate localized and comprehensive agricultural machinery service organizations, encourage and support the upgrading and application of largescale and intelligent agricultural machinery and equipment, vigorously improve the application rate of agricultural machinery service in agricultural production links of rice family farms, and then reduce labor input, promote the largescale management of land, and optimize the allocation of agricultural production factors, so as to improve the total factor productivity.

Key words: agricultural mechanization service, rice family farm, total factor productivity, heterogeneity, mesomeric effect

中图分类号:

F326.11

黄大勇, , 朱洋洋, 于秋月, 陈永红. 农机服务对水稻家庭农场全要素生产率的影响研究——以长江流域612户水稻家庭农场为例[J]. 中国农机化学报, 2023, 44(9): 227-237.

Huang Dayong, , Zhu Yangyang, Yu Qiuyue, Chen Yonghong. Study on the impact of agricultural machinery services on total factor productivity of rice family farms: A case study of 612 rice family farms in the Yangtze River Basin[J]. Journal of Chinese Agricultural Mechanization, 2023, 44(9): 227-237.

参考文献

［1］　高思涵, 吴海涛. 典型家庭农场组织化程度对生产效率的影响分析［J］.农业经济问题, 2021(3): 88-99.
Gao Sihan, Wu Haitao. Analysis on the influence of organizational degree to production efficiency in typical family farm ［J］. Issues in Agricultural Economy, 2021(3): 88-99.
［2］　闵锐, 李谷成. 环境约束条件下的中国粮食全要素生产率增长与分解——基于省域面板数据与序列MalmquistLuenberger指数的观察［J］. 经济评论, 2012(5): 34-42.
Min Rui, Li Gucheng. A study on growth and decomposition of Chinas grain TFP growth under environmental constrains: Empirical analysis based on provincial panel data and sequential MalmquistLuenberger index ［J］. Economic Review, 2012(5): 34-42.
［3］　钟甫宁, 陆五一, 徐志刚. 农村劳动力外出务工不利于粮食生产吗?——对农户要素替代与种植结构调整行为及约束条件的解析［J］. 中国农村经济, 2016(7): 36-47.
［4］　周娟. 基于生产力分化的农村社会阶层重塑及其影响——农业社会化服务的视角［J］. 中国农村观察, 2017(5): 61-73.
Zhou Juan. The reconstruction of rural social stratum based on productivity differentiation and its influence: From the perspective of agricultural socialized services ［J］. China Rural Survey, 2017(5): 61-73.
［5］　Park G A， McDonald G A, Devkota M, et al. Increasing yield stability and input efficiencies with costeffective mechanization in Nepal ［J］. Field Crops Research, 2018(228): 93-101.
［6］　杨宇, 李容, 吴明凤. 土地细碎化对农户购买农机作业服务的约束路径分析［J］. 农业技术经济, 2018(10): 17-25.
Yang Yu, Li Rong, Wu Mingfeng. The constraints of land fragmentation on farmers agricultural machinery services purchase ［J］. Journal of Agrotechnical Economics， 2018(10): 17-25.
［7］　胡祎, 张正河. 农机服务对小麦生产技术效率有影响吗?［J］. 中国农村经济, 2018(5): 68-83.
Hu Yi, Zhang Zhenghe. The impact of agricultural machinery service on technical efficiency wheat production ［J］. Chinese Rural Economy, 2018(5): 68-83.
［8］　王颜齐, 郭翔宇. 种植户农业雇佣生产行为选择及其影响效应分析——基于黑龙江和内蒙古大豆种植户的面板数据［J］. 中国农村经济, 2018(4): 106-120.
Wang Yanqi, Guo Xianyu. The behavior of agricultural production with wage labor and its efficiency: An analysis based on panel data on soybean growers in Heilongjiang and Inner Mongolia ［J］. Chinese Rural Economy, 2018(4): 106-120.
［9］　杨万江, 李琪. 新型经营主体生产性服务对水稻生产技术效率的影响研究——基于12省1926户农户调研数据［J］. 华中农业大学学报(社会科学版), 2017(5): 12-19, 144.
Yang Wanjiang, Li Qi. Study on effect of new agricultural management entities productive service on rice production technical efficiencybased on household survey data of 1965 farmers in 12 provinces ［J］. Journal of Huazhong Agricultural University(Social Sciences Edition), 2017(5): 12-19, 144.
［10］　王正丹. 农业机械化水平对农村劳动力转移的影响研究——基于中国31个省的面板数据［D］. 成都：西南财经大学, 2019.
Wang Zhengdan. Research on the Impact of agricultural mechanization level on the transfer of rural labour—Based on panel data from 31 Chinese provinces ［D］. Chengdu: Southwestern University of Finance and Economics, 2019.
［11］　郑晶, 高孟菲. 农业机械化、农村劳动力转移对农业全要素生产率的影响研究——基于中国大陆31个省（市、自治区）面板数据的实证检验［J］. 福建论坛(人文社会科学版), 2021(8): 59-71.
［12］　罗必良. 论服务规模经营——从纵向分工到横向分工及连片专业化［J］. 中国农村经济, 2017(11): 2-16.
Luo Biliang. Service scale management: vertical division of labor, horizontal division of labor and specialization of connected farmland ［J］. Chinese Rural Economy, 2017(11): 2-16.
［13］　张宗毅, 杜志雄. 农业生产性服务决策的经济分析——以农机作业服务为例［J］. 财贸经济, 2018, 39(4): 146-160.
Zhang Zongyi, Du Zhixiong.Economic analysis of farmers decisionmaking on agricultural production services—Taking agricultural machinery operation service as example ［J］. Finance & Trade Economics, 2018, 39(4): 146-160.
［14］　陈涛, 陈池波. 人口外流背景下县域城镇化与农村人口空心化耦合评价研究［J］. 农业经济问题, 2017, 38(4): 58-66, 111.
Chen Tao, Chen Chibo. Analysis on coupling between county level urbanization and rural population hollowing under the background of escaping migration ［J］. Issues in Agricultural Economy, 2017, 38(4): 58-66, 111.
［15］　王欧, 唐轲, 郑华懋. 农业机械对劳动力替代强度和粮食产出的影响［J］. 中国农村经济, 2016(12): 46-59.
［16］　罗明忠, 邱海兰. 农机社会化服务采纳、禀赋差异与农村经济相对贫困缓解［J］. 南方经济, 2021(2): 1-18.
Luo Mingzhong, Qiu Hailan. Agricultural machinery socialization service adoption, endowment difference and alleviation of rural economic relative poverty ［J］. South China Journal of Economics, 2021(2): 1-18.
［17］　徐春光. 又到跨区机收时——诸城“麦客”备战跨区作业面面观［J］. 当代农机, 2014(5): 9-11.
［18］　孔令成, 郑少锋. 家庭农场的经营效率及适度规模——基于松江模式的DEA模型分析［J］. 西北农林科技大学学报(社会科学版), 2016, 16(5): 107-118.
Kong Lingcheng, Zheng Shaofeng. Research on operating efficiency and moderate scale of family farm—Based on DEA models analysis of Songjiang model ［J］. Journal of Northwest A & F University(Social Science Edition), 2016, 16(5): 107-118.
［19］　张扬. 试论我国新型农业经营主体形成的条件与路径——基于农业要素集聚的视角分析［J］. 当代经济科学, 2014, 36(3): 112-117, 128.
Zhang Yang. The conditions and paths for forming a new subject of Chinese agricultural operation ［J］. Modern Economic Science, 2014, 36(3): 112-117, 128.
［20］　Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision making units ［J］. European Journal of Operational Research, 1978, 2(6): 429-444.
［21］　李谷成, 李烨阳, 周晓时. 农业机械化、劳动力转移与农民收入增长——孰因孰果?［J］.中国农村经济, 2018(11): 112-127.
Li Gucheng, Li Yeyang, Zhou Xiaoshi. Agricultural mechanization, labor transfer and the growth of farmers income: A reexamination of causality ［J］. Chinese Rural Economy, 2018(11): 112-127.
［22］　宦梅丽, 侯云先. 农机服务、农村劳动力结构变化与中国粮食生产技术效率［J］. 华中农业大学学报(社会科学版), 2021(1): 69-80, 177.
（上接第221页）
［11］　王荣, 史再峰, 高荣华, 等. 多变环境下基于多尺度卷积网络的猪个体识别［J］. 江西农业大学学报, 2020, 42(2): 391-400.
Wang Rong, Shi Zaifeng, Gao Ronghua, et al. Individual identification of pigs based on multiscale convolutional network in a variable environment ［J］. Acta Agriculturae Universitatis Jiangxiensis, 2020, 42(2): 391-400.
［12］　魏斌. 基于深度学习的羊脸检测和识别［D］. 杨凌: 西北农林科技大学, 2020.
［13］　韩安琪. 基于深度迁移学习的小样本人脸识别研究［D］. 长沙: 国防科技大学, 2018.
［14］　黄振文, 谢凯, 文畅, 等. 迁移学习模型下的小样本人脸识别算法［J］. 长江大学学报(自然科学版), 2019, 16(7): 88-94.
［15］　王柯力, 袁红春. 基于迁移学习的水产动物图像识别方法［J］. 计算机应用, 2018, 38(5): 1304-1308, 1326.
Wang Keli, Yuan Hongchun. Aquatic animal image classification method based on transfer learning ［J］. Journal of Computer Applications, 2018, 38(5): 1304-1308, 1326.
［16］　Wang H, Qin J, Hou Q, et al. Cattle face recognition method based on parameter transfer and deep learning ［J］. Journal of Physics: Conference Series, 2020, 1453(1): 012054.
［17］　李彦冬, 郝宗波, 雷航. 卷积神经网络研究综述［J］. 计算机应用, 2016, 36(9): 2508-2515, 2565.
Li Yandong, Hao Zongbo, Lei Hang. Survey of convolutional neural network ［J］. Journal of Computer Applications, 2016, 36(9): 2508-2515, 2565.
［18］　Sethi D, Arora K, Susan S. Transfer learning by deep tuning of pretrained networks for pulmonary nodule detection ［C］. 2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS) IEEE, 2020.
［19］　He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition ［C］. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
［20］　许景辉, 邵明烨, 王一琛, 等. 基于迁移学习的卷积神经网络玉米病害图像识别［J］. 农业机械学报, 2020, 51(2): 230-236, 253.
Xu Jinghui, Shao Mingye, Wang Yichen, et al. Recognition of corn leaf spot and rust based on transfer learning with convolutional neural network ［J］. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(2): 230-236, 253.
［21］　Banan A, Nasiri A, TaheriGaravand A. Deep learningbased appearance features extraction for automated carp species identification ［J］. Aquacultural Engineering, 2020, 89: 134-139.

[1]	宋宇, 毕文泰, 张君慧. 锚定效应视角下农户农机服务采纳行为研究——以秸秆深翻还田技术为例[J]. 中国农机化学报, 2023, 44(6): 230-238.
[2]	戴浩, 魏君英, 刘子宸. 非农就业、农机服务外包对粮食产量影响[J]. 中国农机化学报, 2023, 44(6): 244-250.
[3]	谢会强, 吴晓迪, 杨丽莎. 农村普惠金融对农业绿色全要素生产率的影响研究——基于空间溢出效应的视角[J]. 中国农机化学报, 2023, 44(4): 239-247.
[4]	蒋健, 唐小平, 李双双. 农村人口老龄化对农业全要素生产率的影响研究[J]. 中国农机化学报, 2023, 44(2): 230-240.
[5]	李佳芳, 杨俊孝. 农机社会化服务对土地规模经营的影响——基于服务外包和供给的双重视角[J]. 中国农机化学报, 2022, 43(8): 182-188.
[6]	赵和萍, 苏向辉, 马瑛, 曾德鹏, 林文姬, 杨宏伟. 碳中和愿景下异质性农户绿色生态农业技术采纳意愿研究#br# ——基于西部典型农牧区对比分析#br#[J]. 中国农机化学报, 2022, 43(8): 216-223.
[7]	陈喜, 陆建珍, 王凯. 异质性视角下甘薯生产技术效率及影响因素研究[J]. 中国农机化学报, 2022, 43(4): 74-82.
[8]	陈昕, 胡友, 祁春节. 互联网使用对农机服务采纳的影响及其异质性[J]. 中国农机化学报, 2022, 43(10): 196-203.
[9]	刘成;唐晶;喻璨聪;杨雪;彭玮;冯中朝;. 我国农机服务投入对粮食生产技术效率的影响——基于不同土地规模视角[J]. 中国农机化学报, 2021, 42(4): 205-210.
[10]	王洋;代首寒;许佳彬;. 农机服务对中国粮食生产效率影响研究[J]. 中国农机化学报, 2021, 42(3): 197-205.
[11]	唐小平, 蒋健, 李双双. 我国农业机械化对种植业全要素生产率的影响——基于农村人口老龄化的面板门槛模型[J]. 中国农机化学报, 2021, 42(12): 204-213.
[12]	赵闰;石研研;金雪婷;张晓泉;. 江苏农业机械化转型升级对策研究[J]. 中国农机化学报, 2020, 41(8): 217-222.
[13]	刘相汝;李容;. 土地细碎背景下连片种植对农户获取地块规模经济的影响——以农机作业服务费为例[J]. 中国农机化学报, 2020, 41(3): 185-191.
[14]	廖敏;杨建国;胡红;刘一潭;. 新形势下四川省农业机械化发展对策研究[J]. 中国农机化学报, 2020, 41(12): 183-188.
[15]	吴萍;刘小伟;吴迪;赵静;. 农机生产性服务模式创新研究——来自山东与江苏的实践[J]. 中国农机化学报, 2019, 40(3): 221-226.