农户粮食生产投资调整意愿与行为差异研究——基于京津冀609户粮农的调查

Differences of Willingness and Behavior of Farmers to Adjust Investment in Grain Production——Based on the Survey of 609 Grain Farmers in Beijing,Tianjin and Hebei

基于京津冀609户粮农的调研数据,构建多分类Logit模型,分析资本投入、劳动投入与意愿、农户经营特征对农户粮食生产投资调整行为的影响,发现灌溉成本、机械成本、务农人数、农地流转意愿、农户经营规模和种粮收入比例等因素对农户种粮投资调整意愿影响显著。然而现实中,大部分有粮食生产投资调整意愿的农户,在短期内只有少数实际进行了调整。从微观适应性预期和宏观劳动投入与资本投入互竞双视角对农户种粮投资调整意愿与行为差异原因进行分析,发现微观上农户调整粮食种植结构和种植面积都需要一定时间,不是马上就可以实施的;宏观上物质资本的短期产出弹性小于长期产出弹性,使大部分有调整投资意愿的农户实际上短期内没有落实调整行为。因此,应完善粮食生产可变要素的成本控制机制,加强基础设施建设和农业大数据技术研究,合理引导农户粮食生产投资调整预期和行为。

Based on the survey data of 609 grain farmers in Beijing,Tianjin and Hebei,the Multinomial Logit Models were constructed to analyze the effects of capital input,labor input and willingness on the adjustment behavior of farmers’grain production investment.It was found that irrigation cost,machinery cost,number of farmers,willingness to transfer agricultural land,scale of farmers’operation and proportion of grain production income have significant influence on farmers’willingness to adjust their grain planting investment.However,in reality,most of the farmers who have the willingness to adjust their investment in grain production have actually adjusted a few in a short period of time.From the perspective of micro-adaptability expectation and competition between macro-labor input and capital input,this paper analyses the reasons for the difference of farmers’willingness and behavior in grain-growing investment adjustment.It is found that it takes a certain time for farmers to adjust grain-growing structure and planting area on micro-level,and it is not possible to implement it immediately;on macro-level,the short-term output elasticity of physical capital is less than the long-term output elasticity,so that most farmers who have adjusted their willingness to invest do not actually implement adjustments in the short term.Therefore,it is necessary to improve the cost control mechanism for variable factors in food production,strengthen infrastructure construction and agricultural big data technology research,and rationally guide farmers’food production investment to adjust expectations and behaviors.