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引用本文:刘宽斌,熊雪,聂凤英.贫困地区农户对自然灾害风险规避和响应分析[J].中国农业资源与区划,2020,41(1):289~296
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贫困地区农户对自然灾害风险规避和响应分析
刘宽斌1,熊雪1,聂凤英2※
1.西南大学经济管理学院,重庆400715; 2.中国农业科学院农业信息研究所,北京100081
摘要:
[目的]研究影响贫困地区农户应对自然灾害风险,减少经济损失的因素,并分析农户采取应对损失的措施。[方法]利用2015年云南、贵州和陕西3省6县经历过自然灾害的819农户作为研究对象。采用Logit模型研究影响贫困地区农户有效规避自然灾害风险的因素,并进一步分析农户在遭受自然灾害后采取的响应策略。[结果]研究表明农户户主的受教育程度越高、与外界市场接触越紧密,则农户规避自然灾害风险能力越强; 农户收入中农业收入比重高、家庭贫穷、家庭收入来源过于集中均不利于农户规避自然灾害风险。通过分析农户应对自然灾害损失的策略发现,农户在自然灾害冲击下,较多采用被动的应对策略,不善于拓展新的收入来源。采用降低生活质量、减少生活必要支出、寻找新的收入来源、金融手段和出售生产生活资料这5种应对策略的农户分别占整体受灾农户的1636%、647%、1465%、537%、403%和1135%。[结论]为了增强贫困地区农户规避自然灾害风险的能力,首先需要加大对贫困地区的教育投资; 其次,增加贫困地区与外界沟通交流的渠道,可以在偏远地区多修公路等; 最后,应当积极引导农户拓展农业生产以外的收入来源,将收入来源多样化,降低农户农业收入在家庭收入中的比重,有效增强贫困地区农户应对自然灾害风险的能力。
关键词:  农户自然灾害风险规避响应策略Logit模型
DOI:
分类号:F328
基金项目:国家自然科学基金国际合作与交流项目“精准扶贫与互联网扶贫的实施机制与效果评估研究”(71661147001); 国家社会科学基金重大项目“精准扶贫战略实施的动态监测与成效评价研究”(16ZDA021); “中央高校基本科研业务费专项资金”(SWU1909781); “中央高校基本科研业务费专项资金”(SWU1909779); 中国人民大学中国扶贫研究院课题(CAPRI2019B05)
THE ABILITY OF AVOIDING NATURAL DISASTERS AND THE RESPONSE STRATEGIES OF HOUSEHOLD IN POOR AREAS
Liu Kuanbin1, Xiong Xue1, Nie Fengying2※
1. College of Economic and Management, Southwest University, Chongqing 400715, China;2. Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Abstract:
This research aims to study the factors that affect farmers in poor areas to deal with natural disaster risks and reduce economic losses, and analyzes the measures taken by farmers to deal with losses. This research took 819 farmers who experienced natural disasters in six counties in Yunnan, Guizhou and Shaanxi provinces in 2015 as the research object, and used the Logit model to study the risk evasion ability of rural households from natural disaster in natural disaster stricken areas, then further analyzed the response strategies of the farm households when facing natural disaster. Through research, the results showed that the higher education level of household head of a household and closer contact with outside markets were factors that could enhance the ability of farmers to avoid damage from natural disasters. And the method of decentralizing household income sources was an effective way to reduce the impact of natural disasters on families. It was also found that these households with higher the proportion of income from the agricultural industry were more vulnerable when facing natural disaster. The empirical results also revealed the phenomenon that poor families were more vulnerable to natural disasters. Through analyzing the response strategies of natural disasters of farmers faced with natural disaster, it was found that those families who had been hit by natural disasters did not have the will or idea to actively expand their sources of income. These households in rural areas tended to adopt passive coping strategies when facing the impact of natural disasters. This research divided the coping strategies into six different aspects, namely reducing the quality of life of the family, reducing necessary living expenses, finding new sources of income, overcoming the hardship by borrowing money from financial institution or relatives and selling household goods for living. Other coping styles were classified as a single class. The proportion of farmers taking these six coping strategies were 16.36%, 6.47%, 14.65%, 5.37%, 4.03% and 11.35%, respectively. Summarily, in order to enhance the natural disaster evasion ability of rural households in natural disaster stricken areas and reduce the impact of natural disasters, firstly, it is necessary to increase investment in education in rural areas; secondly, the local government should actively build channels for external communication in rural areas and pave roads to poor area; finally, actively guide farmers to expand sources of income other than agricultural production, diversify sources of income, and reduce the proportion of agricultural income in household income. These methods are effectively ways to reduce the impact of natural disasters on farmers.
Key words:  household  natural disaster  risk aversion  response strategy  Logit model
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