黄淮海地区农户苜蓿种植行为影响因素分析

为分析黄淮海地区农户种植苜蓿的影响因素，该研究以黄淮海地区的苜蓿种植主体-农户为研究对象，通过建立苜蓿种植面积供给反应模型，利用统计数据及调查数据，证明黄淮海地区农户苜蓿种植并不遵循种植周期内收益最大化原则。通过建立幼稚价格预期模型，计算了各因素对黄淮海地区苜蓿种植面积的影响程度，证明针对其他作物的种植补贴不会显著影响苜蓿种植面积，增加苜蓿供给能有效降低饲料粮供给压力。该研究提出苜蓿种植应当减少行政干预，增加良种、技术、信息的服务供给，培育苜蓿种植专业农户，并根据苜蓿的需求特点，结合畜牧业发展及环境改善需要，制定种养结合的苜蓿种植目标。该研究对于满足居民消费升级需求，促进黄淮海地区畜牧业健康发展与生态环境提升具有重要意义。

Empirical analysis of factors affecting alfalfa plantation behavior of farmers in Huang-huai-hai region

Abstract: Planting alfalfa can not only promote the development of animal husbandry and meet the needs of the consumers for livestock, but also improve soil fertility and the ecological environment. Farmers are the main alfalfa growers in Huang-Huai-Hai region, in this paper, a supply response model of alfalfa planting area has been developed, with statistical data and investigation data, the effects of alfalfa prices and alfalfa area in last term were calculated. The results show that alfalfa planting area only depended on the alfalfa production price in last year and this means that the annual alfalfa price will influence the decision of farmers' willingness of planting alfalfa. The elasticity of alfalfa planting area to alfalfa export price is 0.837, and the T value is 7.528. Above results proved that there was short-term speculation behavior for the alfalfa planting farmers in Huang-Huai-Hai region. Farmers in this area do not follow principle of maximum profit in alfalfa planting. At the same time, it proved that na?ve price prediction model can be used to explain the farmers' alfalfa planting behavior. in the na?ve price prediction model, factors affecting the farmers' planting alfalfa behavior include alfalfa planting area in last year, the prices of other crops in this area, the planting subsidies, the region effect and fixed effect. Because there is no alfalfa price data, the actual export price of alfalfa products was used to replace alfalfa domestic price. The estimation results show that both the R2 and adjust R2 are greater than 0.95, and the F-statistic value is significant at 99% confidence level, and the Durbin-Watson statistic is 2.2, which proved that naive simulation model is very suitable for simulating the factors that may influence alfalfa planting in Huang-Huai-Hai region. According to the calculation results, in short term, if the cotton price rise 10%, the alfalfa planting area will decrease 7.16%. If the wheat price rise 10%, the alfalfa planting area will decrease 7.38%, and it will take 2 years to achieve the target from the old status to new balance. In long term, if the cotton price rise 10%, the alfalfa planting area will decrease 14.32%, and if the wheat price rise 10%, the alfalfa planting area will decrease 14.76%. These mean that the goal of alfalfa growers in Huang-Huai-Hai region is to make the expected return maximum; this is consistent with the expected results. In short term, if maize price rise 10%, the alfalfa planting area will increase 11.44%. and in long term, the alfalfa planting area will increase 22.88%.This is not consistent with the expected results. This is because that maize is mainly used as animal feed, as the same as alfalfa. The results also show that the planting subsides for other crops do not significantly affect planting alfalfa. Increasing the supply of alfalfa can effectively decrease the maize price in this region. According to the calculation results and investigation, this study suggests the government should reduce administrative intervention, provide the supply of improved seed, practical technology, information services, and increase the number of professional farmers planting alfalfa. According to characteristics of alfalfa demand and the goals of animal husbandry development and environmental improvement, government should develop the alfalfa production plan.