| 摘要: |
| ［目的］利用农户微观调查数据，识别影响农户粮食（小麦、水稻、玉米）收获损失的主要因素，分解各因素的影响大小。［方法］文章采用OLS回归方法识别粮食收获损失影响因素； 利用基于R2的夏普里值分解方法，分解出各因素的影响大小。［结果］（1）目前农户粮食收获环节损失均高于国家机械化生产技术要求，并且在收割环节损失率要远高于田间运输环节损失、脱粒环节损失和清粮环节损失小麦、水稻、玉米的平均收获损失率。（2）导致粮食收获损失的前五大因素依次是，小麦：异常天气、过熟期收获、严重虫害、小规模种植、未购买农机服务，合计解释了5767%的收获损失； 水稻：严重虫害、异常天气、间作套种、不富裕的人手、对收获粗糙的态度，合计解释了5074%的收获损失； 玉米：严重虫害、异常天气、赶种下茬作物、对收获粗糙的态度、较高的非农就业劳动力比例，合计解释了4694%的收获损失。（3）天气和虫害是造成粮食收获损失的最主要因素，分别解释了2917%的小麦收获损失、3839%的水稻收获损失和3091%的玉米收获损失。［结论］恶劣天气和严重虫害是导致农户粮食收获损失的两个最重要的因素。此外，农户可以通过购买农机服务、改进对收获的态度、收获期间保障充足的人手等方式降低粮食收获损失。 |
| 关键词: 农户三大主粮收获损失影响因素识别夏普里值分解法 |
| DOI： |
| 分类号:F3261 |
| 基金项目:粮食公益性行业科研专项“粮食产后损失浪费调查及评估技术研究——粮食收获环节损失浪费调查”（201513004-2）； 中国农业大学基本科研业务费专项资金项目“农民工市民化、土地流转配给与生产效率损失”（2019TC084）； 北京市社会科学基金项目‘三权分置’下北京市农地规模经营现状及效果评价”（17LJB003）； 北京食品安全政策与战略研究基地项目“日韩食品安全监管体系发展及其对中国的启示”； 教育部人文社会科学研究规划基金项目“土地流转配给与农户生产效率损失研究”（18YJA790122） |
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| DECOMPOSITION ANALYSIS OF INFLUENCING FACTORS AFFECTING HOUSEHOLDS′ GRAIN HARVEST LOSS |
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Chen Wei, Zhu Junfeng
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College of Economics and Management, China Agricultural University, Beijing 100083, China
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| Abstract: |
| Using the micro survey data of farmers, the main factors affecting the harvest losses of farmers′ food (wheat, rice, corn) were identified, and the influence of various factors was decomposed. The OLS regression method was used to identify the influencing factors of grain harvest loss, and the shapley based decomposition of the R Square method was used to decompose the influence of various factors. As a result, three conclusions were showed as follows. Firstly, the loss rate of the grain harvest was relatively high at present, which were all higher than the national mechanized production technical standard. Further analysis found that the loss rate of wheat, rice and maize in the harvesting process was much higher than other processes, such as threshing, field transportation and grain cleaning. Secondly, the top five factors leading to the loss of grain harvesting in turn, wheat: abnormal weather, over ripe harvest, severe pests, small planting scale, and unsold agricultural machinery services, explained 57.67% of harvest losses; rice: severe pests, abnormal weather, intercropping, and less wealthy The rough working attitude explained 50.74% of the harvest loss; corn: serious pests, abnormal weather, squatting crops, rough working attitude, high proportion of non agricultural employment labor, and explained 46.94% of the total loss. Thirdly, abnormal weather and serious pests during the harvest period explained 29.17% of the farmers′ wheat harvest losses, 38.39% of the farmers′ rice harvest losses and 30.91% of the farmers′ corn harvest losses. In general, abnormal weather and serious pests are still the two most important factors leading to farmers′ loss of grain harvest, but farmers can reduce harvest losses by purchasing agricultural machinery services, improving operational attitudes, and using social services to ensure adequate manpower. |
| Key words: farmer three main grain harvest loss influencing factors shapley value |
