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脱贫农户返贫风险评估及防范机制构建的实证分析
引用本文:蔡洁,马舒悦,夏显力.脱贫农户返贫风险评估及防范机制构建的实证分析[J].长安大学学报(社会科学版),2023,0(2):103-116.
作者姓名:蔡洁  马舒悦  夏显力
作者单位:(1. 长安大学 人文学院,陕西 西安 710064; 2. 西北农林科技大学经济管理学院,陕西 杨凌 712100)
摘    要:识别脱贫农户返贫风险并制定有效的治理策略是现阶段解决脱贫攻坚和乡村振兴有效衔接的关键所在,也是实现农民共同富裕的重要任务。针对脱贫农户生活水平不稳定可能导致的返贫问题,基于陕南脱贫农户的实地调查数据,构建返贫风险指标评价体系并利用物元模型评估脱贫农户返贫风险程度,深层次剖析返贫风险的影响因素,建立脱贫农户返贫防范机制。研究认为:陕南大部分脱贫农户处于一般风险水平,且差异较小; 脱贫农户成员健康状况、遭遇自然灾害风险、环境污染影响农产品质量风险和社会关系网是导致陕南脱贫农户可能返贫的重要因素,说明脱贫区的政策制度、自然环境和资源禀赋、脱贫农户个体能力是陕南脱贫农户可能返贫的影响因素; 建立依据事前防御、事中处理、事后追踪体系的全过程性风险预警机制,加强脱贫农户思想观念培育,注重内生动力提升,提高脱贫农户对外部环境变化的适应能力,打造能够产生经济效益的优势产业,促进生态农业、农旅产业、文化产业发展,改善升级乡村教育医疗,提高道路水利、信息网络、天然气能源等基础设施建设,促进脱贫农户社会资本积累,提高可持续生计水平和社会参与能力。

关 键 词:脱贫农户  返贫风险防范  物元可拓模型  陕南地区  内生动力  信息风险

Empirical analysis on risk assessment and prevention mechanism construction of farmer households lifted out of poverty returning to poverty
CAI Jie,MA Shuyue,XIA Xianli.Empirical analysis on risk assessment and prevention mechanism construction of farmer households lifted out of poverty returning to poverty[J].Journal of Chang'an University(Social Sciences Edition),2023,0(2):103-116.
Authors:CAI Jie  MA Shuyue  XIA Xianli
Institution:(1. School of Humanities, Chang'an University, Xi'an 710064, Shaanxi, China; 2. School of Economics and Management, Northwest University of Agriculture and Forestry Science and Technology, Yangling 712100, Shaanxi, China)
Abstract:Identifying the risk of farmer households lifted out of poverty returning to poverty and formulating effective governance strategies are the key to enabling the effective connection between poverty alleviation and rural revitalization at this stage, and they are also the essential task of realizing the common prosperity of farmers and rural areas. In terms of the problem of farmer households lifted out of poverty potentially returning to poverty due to unstable living standards, and based on the field survey data of farmer households lifted out of poverty in southern Shaanxi, this paper constructs a risk index evaluation system of returning to poverty and uses the matter-element model to evaluate their risk of returning to poverty, analyzes the influencing factors of the risk of returning to poverty in depth, and establishes a mechanism to prevent the farmer households lifted out of poverty from returning to poverty. The research shows that most of the farmer households lifted out of poverty in southern Shaanxi are at a general risk level with low discrepancy; the health status of members of farmer households lifted out of poverty, the risk of natural disasters, the risk of environmental pollution affecting the quality of agricultural products and the social network are important factors that may lead to their return to poverty. This indicates that the policy system, natural environment, and resource endowment of areas that have shaken off poverty, and the individual abilities of the farmer households lifted out of poverty are the influencing factors for the farmer households lifted out of poverty in southern Shaanxi to potentially return to poverty. The proposed solutions include: establish a whole-process risk early warning mechanism based on pre-defense, in-process processing, and post-event tracking system, strengthen the ideological education of the farmer households lifted out of poverty, pay attention to the improvement of endogenous power, improve the adaptability of farmer households lifted out of poverty to external environmental changes, create advantageous industries that can produce economic benefits, promote the development of ecological agriculture, agricultural tourism industry, and cultural industry, improve and upgrade rural education and medical care, improve infrastructure construction such as road water conservancy, information network, natural gas energy, promote the accumulation of social capital of farmer households lifted out of poverty, and improve the level of sustainable livelihood and social participation capability.
Keywords:farmer households lifted out of poverty  prevention of the risk of returning to poverty  matter-element scalable model  southern Shaanxi region  endogenous power  information risk
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