市场行情、信息渠道对农户生产周期调整的影响——以蛋鸡养殖场(户)最佳淘汰日龄为例

为探究市场行情、信息渠道对农户生产周期调整的影响，以蛋鸡产业为例，基于利润最大化理论，采用C-D生产函数测定2020年蛋鸡养殖场(户)调研样本的最佳淘汰日龄，并进一步利用Probit模型探讨最佳淘汰日龄决策的影响因素。结果表明:1)2020年蛋鸡养殖场(户)调研样本的最佳淘汰日龄为461.99日龄。2)以最佳淘汰日龄上下浮动20 d划分出最佳淘汰日龄区间，能够做出最佳淘汰日龄决策的养殖场(户)占比14.37%，提前淘汰和延后淘汰的养殖场(户)占比分别为24.76%和60.87%，以延后淘汰养殖决策为主。3)分析最佳淘汰日龄决策的影响因素可知，饲料价格、淘汰鸡价格、非洲猪瘟疫情以及养殖者的行情预判均会增加养殖户提前或延后淘汰的概率。从信息渠道的角度来看，亲朋好友的信息更有助于最佳淘汰日龄决策，政府渠道的信息增加养殖户提前或延后淘汰的概率，而互联网、龙头企业的信息渠道对此并无显著影响。此外，养殖户的周期决策也会受到生猪产业等畜禽产业的影响。因此，政府及行业应加大开展蛋鸡养殖周期科学决策培训，增强对最佳淘汰日龄的科学认识，从上下游产业链的角度完善重要农业生产资料与农产品的价格发布机制，从不同产业间关联的角度，加强突发事件背景下蛋鸡产业与生猪产业等畜禽产业间的价格联动监测预警。

Impacts of market situation and information channels on farmers' production period adjustment behavior: A case study of optimal elimination day-old from layer farmers

In order to explore the impact of market situation and information channels on farmers'' production period adjustment behavior, taking the laying hens industry as an example, this study employs Cobb-Douglas production function to estimate the optimal elimination day-old and uses the Probit model to explore the factors that influence the optimal elimination day-old decisions. The results showed that: 1)The optimal elimination day-old of this sample was 461. 99 day-old. 2)The optimal elimination day-old interval was determined by ±20 days of its optimal elimination day-old, 14. 37% farmers were able to make the optimal elimination day-old decisions, while 24. 76% farmers made the early elimination decisions, and 60. 87% farmers made delayed elimination decisions. The delayed elimination decisions were the most common among all farmers. 3)By analyzing the determining factors of optimal elimination day-old, market situation, such as feed prices, prices of eliminated chicken, African swine fever epidemic and farmers'' market forecasts, could increase the probabilities of early or delayed elimination. From the perspective of information channels, information from relatives and friends is more useful in making the best elimination age decisions, while information from government channels increases the probabilities of early or late elimination. However, information channels from internet and leading companies do not show significant effects on elimination day-old decisions. In addition, farmers'' cyclical decisions can be influenced by related livestock industries(e. g. the pig industry). Therefore, government and laying hen industry should provide more training to scientifically instruct the farmers'' decision making of breeding cycle of laying hens and enhance farmers'' scientific awareness of the optimal elimination day-old. Moreover, the price release mechanisms of important agricultural production materials and agricultural products need to be improved from upstream and downstream chains. From the viewpoint of industry linkages among various industries, strengthening the monitoring and early warning of price linkages between livestock and poultry industries in the context of unexpected events are also of great importance.