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作 者:平卫英[1] 游龙 Ping Weiying;You Long
机构地区:[1]江西财经大学统计与数据科学学院,江西南昌330013
出 处:《企业经济》2024年第12期91-100,共10页Enterprise Economy
基 金:国家社会科学基金重大项目“后扶贫时代中国城乡相对贫困统计测度与治理机制研究”(项目编号:20&ZD131)。
摘 要:脱贫攻坚任务完成后,城市相对贫困成为减贫的主要挑战。本研究基于随机森林和Logistic回归模型,依据2020年中国家庭追踪调查数据,构建城市家庭多维相对贫困指标体系,探究中国城市家庭多维相对贫困特征及返贫风险。随机森林模型分析显示,中国城市家庭多维相对贫困系数存在显著差异,其中家庭收入和家庭资产维度对中国城市家庭多维相对贫困影响较大,而生活水平维度的影响相对较小。Logistic回归结果显示,处于低返贫风险的家庭占比最多,中度风险家庭最少,高风险家庭居中。基于以上分析,本文提出以下建议:加强贫困监测,制定合理发展规划;推动就业创业,增强脱贫内生动力;强化企业支持,构建贫困家庭互助网络;激发扶贫活力,推动可持续发展。After the completion of the task of poverty alleviation,urban relative poverty will become the main challenge of poverty reduction.Based on Random Forest and Logistic Regression models,this study constructed a multi-dimensional relative poverty index system of urban households based on the data of the 2020 China Household Panel Survey,and explored the characteristics of multidimensional relative poverty and the risk of returning to poverty among urban households in China.The Random Forest model analysis shows that there are significant differences in the multidimensional relative poverty coefficient in Chinese urban households,in which family income and family asset dimension have great influence on the multidimensional relative poverty in Chinese urban households,while the living standard dimension is relatively small.Logistic Regression analysis reveals that households at low risk of returning to poverty constitute the largest group,while those at moderate risk are the smallest,and high-risk households lie in between.Based on these findings,we propose the following recommendations:strengthen poverty monitoring and formulate rational development plans;promote employment and entrepreneurship to enhance the internal impetus for poverty alleviation;reinforce corporate support to establish mutual assistance networks for impoverished families;and stimulate the vitality of poverty alleviation to ensure sustainable development.
关 键 词:多维相对贫困 返贫风险 中国城市家庭 随机森林 LOGISTIC回归
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