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甘肃省秦巴山区农民生计模式影响因素分析——基于二元logistic模型的实证研究 被引量:3

Analysis on Influencing Factors of Farmers' Livelihood Mode in Qinba Mountain of Gansu Province:An Empirical Study Based on Binary Logistic Model
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摘要 探究甘肃省秦巴山区农户的生计模式影响因素有助于提高农户生计水平,实现生计模式多样化。本文以甘肃省秦巴山区的文县、康县和西和县为例,通过问卷调查分析了农户的各项生计资本现状,并采用二元logistic模型剖析农户生计模式选择中的具体影响因素。研究结果表明:(1)秦巴山区农户传统生计模式的自然环境基础表现出极大的脆弱性,耕地面积极少,且碎片化现象严重;(2)当前研究区域农户的生计模式选择较为单一,主要有农业单一型和非农型两种;(3)耕地面积和生产工具对农业单一型农户生计模式选择的影响较大,但不具有显著性;(4)主要劳动力受教育程度、家庭中有干部和健康状况等因素是决定农户由农业单一型向非农型转化的关键因子,同时家庭固定资本、获得信贷的机会、现金收入等也对农业单一型向非农型生计模式转化起到促进作用。 Exploring the influencing factors of farmers ’ livelihood in Qinba Mountain of Gansu Province not only helps to improvethe living conditions of farmers, but diversifies their living modes. This paper takes Wenxian County, Kangxian County and XiheCounty as examples to find out farmers ’ status of livelihood capital by questionnaire survey, and analyze the typical factors with binarylogistic model. The results show as follows:( 1 ) The natural environment shows great vulnerability for the livelihood as the arable land area is very small with serious fragmentation. ( 2 ) In the study area,relatively narrow, only two modes can be choose, which is agriculture or non- agriculture. (3) Ttools have obvious influence on the choice of living mode of agricultural single-type farmers, but not significant. (4) The key factors such as laborers ’ education degree, a carder in a family and health condition determine the transformation of farmers from agricultural single type to non-agricultural type. (5) Fami ly fixed c a p ita l, access to c re dit opportunities and cash income also promote farmerstransformation from agricultural single type to non-agricultural type.
作者 王爽 侯庆丰 WANG Shuang;HOU Qing-feng(School of Manegement, Gansu Agricultural University, Lanzhou, Gansu, 730070, Chin)
出处 《西华大学学报(哲学社会科学版)》 2018年第3期101-107,共7页 Journal of Xihua University(Philosophy & Social Sciences)
基金 国家社科基金项目"甘肃省地震灾区农村灾后恢复重建问题研究"(编号:09XJY014)
关键词 农民生计模式 秦巴山贫困区 二元LOGISTIC模型 farmer’s livelihood mode the poverty area of Qinba Mountain binary logistic model
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