基于PSM-SFA两阶段模型的农业生产创新——来自北京市示范户与非示范户的实证

Agricultural Production Innovation based on the PSM-SFA Two Stage Model—Empirical Analysis on Model and Non-modal Household in Beijing

基于倾向得分匹配(PSM)与随机前沿分析(SFA)两阶段模型,在测算技术采用的农业生产创新无偏效果基础上,以北京市示范户与非示范户为例,着重分析农户管理能力对农业生产创新效果的影响,并据此探究保障农业可持续发展的有效途径。主要结论包括:农业生产创新整体效果不明显,不同管理能力农户采用技术的生产创新效果差异较大;非示范户产出主要依赖于土地、肥料,技术采用效率较低;示范户要素投入结构合理且效果明显,年轻、富有经验与专业化程度高尤具优势。因此,继续鼓励具有"新型职业农民"特质农户率先采用新技术,既有利于推动向专业与规模化的农业生产模式转型,又是促进农业技术扩散,提升农户管理能力、保障增收的可持续性路径。

This paper applied the two-stage model combines the Propensity Score Matching （PSM） with the Stochastic Frontier Analysis （SFA） to estimate the contribution of technology adoption on the output without sample bias,and then researched on the effect difference from China＇s agricultural production innovation and its sustainability path from the perspective of managerial ability based on model and non-modal households in Beijing. The results showed that the technology adoption income effect is not obvious now. Comparatively speaking,for the non-model households,fertilizer input is inefficient,land factor has been over counted on ,their adoption of new technologies can hardly get benefit due to their low level managerial ability; while the technical input structure of the model households is reasonable and they can use all these three techniques to improve technical efficiency and better income with relatively high managerial ability. In addition ,the model households of younger age, more experience ,higher specialization level have more comparative advantage. Therefore, new agricultural production innovation adoption by model households who work as the new occupation farmers should be encouraged ,because this way can not only help transfer the agricultural production mode from traditional to specialized and proper-scaled and get more income increase,but also induce other non-model farmers＇ technology application in a larger range and help them improve their managerial ability to guarantee income increase which can be a sustainable path for China＇s agricultural innovation and development.