{"title":"Vulnerability to Rural Multidimensional Poverty in Southern Ethiopia","authors":"Fassil Eshetu, Jema Haji, Mengistu Ketema, Abule Mehare","doi":"10.1007/s40609-022-00253-8","DOIUrl":null,"url":null,"abstract":"<p>While few studies have quantified the extent and examined the determinants of static multidimensional poverty, studies on the extent and determinants of dynamic rural multidimensional poverty are scarce. This study quantified the extent and examined the determinants of vulnerability to rural multidimensional poverty using the Chaudhri (2002) approach and the generalized ordered logit model respectively. Data were gathered from 415 random rural households in 2021 in southern Ethiopia. The study showed that the levels of rural multidimensional poverty and the vulnerability to rural multidimensional poverty are 72.3 and 84% respectively. This suggests that vulnerability is more widespread compared to current poverty. Besides, 66 (15.90%), 220 (53.10%), and 129 (31.08%) households are non-vulnerable (<span>\\(V<0.50\\)</span>), moderately vulnerable, and extremely vulnerable (<span>\\(V\\ge 0.56\\)</span>) to future poverty respectively. About 276 (66.51%) and 97(23.37%) households are in chronic, and transitory rural multidimensional poverty. Of 349 vulnerable households, 129 (36.96%) of households are extremely vulnerable to future poverty. Of 173 extremely poor households, 167 (96.53%) households are extremely vulnerable to future deprivation. Female-headed households are more extremely vulnerable compared to male-headed households. Regression results highlighted that land size (β = − 3.07, <i>t</i> = − 4.65, <i>p</i> < 0.001), tropical livestock unit (β = − 0.67, <i>t</i> = − 4.32, <i>p</i> < 0.001), credit (β = -3.93, <i>t</i> = − 3.69, <i>p</i> < 0.001), mobiles per household (β = − 0.58, <i>t</i> = − 4.21, <i>p</i> < 0.001), extension visits (β = − 0.33, <i>t</i> = − 3.81, <i>p</i> < 0.001), death of animals (β = 2.21, <i>t</i> = 3.37, <i>p</i> < 0.001), age of household head (β = − 0.17, <i>t</i> = − 4.84, <i>p</i> < 0.001), being male-headed (β = − 0.88, <i>t</i> = − 2.15, <i>p</i> < 0.01), and crop failure (β = 1.38, <i>t</i> = 3.91, <i>p</i> < 0.001) are significantly affecting vulnerability to rural poverty. Hence, rural poverty reduction strategies need to aim not only to reduce current or ex-post poverty but also to prevent ex-ante or future poverty. The findings underscore the importance of promoting access to rural land, credit, extension services, irrigation, information technology, and education to reduce vulnerability to future deprivation of rural households.</p>","PeriodicalId":51927,"journal":{"name":"Global Social Welfare","volume":"20 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Social Welfare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40609-022-00253-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL WORK","Score":null,"Total":0}
引用次数: 0
Abstract
While few studies have quantified the extent and examined the determinants of static multidimensional poverty, studies on the extent and determinants of dynamic rural multidimensional poverty are scarce. This study quantified the extent and examined the determinants of vulnerability to rural multidimensional poverty using the Chaudhri (2002) approach and the generalized ordered logit model respectively. Data were gathered from 415 random rural households in 2021 in southern Ethiopia. The study showed that the levels of rural multidimensional poverty and the vulnerability to rural multidimensional poverty are 72.3 and 84% respectively. This suggests that vulnerability is more widespread compared to current poverty. Besides, 66 (15.90%), 220 (53.10%), and 129 (31.08%) households are non-vulnerable (\(V<0.50\)), moderately vulnerable, and extremely vulnerable (\(V\ge 0.56\)) to future poverty respectively. About 276 (66.51%) and 97(23.37%) households are in chronic, and transitory rural multidimensional poverty. Of 349 vulnerable households, 129 (36.96%) of households are extremely vulnerable to future poverty. Of 173 extremely poor households, 167 (96.53%) households are extremely vulnerable to future deprivation. Female-headed households are more extremely vulnerable compared to male-headed households. Regression results highlighted that land size (β = − 3.07, t = − 4.65, p < 0.001), tropical livestock unit (β = − 0.67, t = − 4.32, p < 0.001), credit (β = -3.93, t = − 3.69, p < 0.001), mobiles per household (β = − 0.58, t = − 4.21, p < 0.001), extension visits (β = − 0.33, t = − 3.81, p < 0.001), death of animals (β = 2.21, t = 3.37, p < 0.001), age of household head (β = − 0.17, t = − 4.84, p < 0.001), being male-headed (β = − 0.88, t = − 2.15, p < 0.01), and crop failure (β = 1.38, t = 3.91, p < 0.001) are significantly affecting vulnerability to rural poverty. Hence, rural poverty reduction strategies need to aim not only to reduce current or ex-post poverty but also to prevent ex-ante or future poverty. The findings underscore the importance of promoting access to rural land, credit, extension services, irrigation, information technology, and education to reduce vulnerability to future deprivation of rural households.
虽然很少有研究量化了静态多维贫困的程度并审查了其决定因素,但关于动态农村多维贫困的程度和决定因素的研究却很少。本研究分别使用Chaudhri(2002)方法和广义有序logit模型量化了农村多维贫困脆弱性的程度,并考察了脆弱性的决定因素。数据于2021年从埃塞俄比亚南部的415个随机农村家庭中收集。研究表明,农村多维贫困水平和农村多维贫困脆弱性分别为72.3和84% respectively. This suggests that vulnerability is more widespread compared to current poverty. Besides, 66 (15.90%), 220 (53.10%), and 129 (31.08%) households are non-vulnerable (\(V<0.50\)), moderately vulnerable, and extremely vulnerable (\(V\ge 0.56\)) to future poverty respectively. About 276 (66.51%) and 97(23.37%) households are in chronic, and transitory rural multidimensional poverty. Of 349 vulnerable households, 129 (36.96%) of households are extremely vulnerable to future poverty. Of 173 extremely poor households, 167 (96.53%) households are extremely vulnerable to future deprivation. Female-headed households are more extremely vulnerable compared to male-headed households. Regression results highlighted that land size (β = − 3.07, t = − 4.65, p < 0.001), tropical livestock unit (β = − 0.67, t = − 4.32, p < 0.001), credit (β = -3.93, t = − 3.69, p < 0.001), mobiles per household (β = − 0.58, t = − 4.21, p < 0.001), extension visits (β = − 0.33, t = − 3.81, p < 0.001), death of animals (β = 2.21, t = 3.37, p < 0.001), age of household head (β = − 0.17, t = − 4.84, p < 0.001), being male-headed (β = − 0.88, t = − 2.15, p < 0.01), and crop failure (β = 1.38, t = 3.91, p < 0.001) are significantly affecting vulnerability to rural poverty. Hence, rural poverty reduction strategies need to aim not only to reduce current or ex-post poverty but also to prevent ex-ante or future poverty. The findings underscore the importance of promoting access to rural land, credit, extension services, irrigation, information technology, and education to reduce vulnerability to future deprivation of rural households.
期刊介绍:
This journal brings together research that informs the fields of global social work, social development, and social welfare policy and practice. It serves as an outlet for manuscripts and brief reports of interdisciplinary applied research which advance knowledge about global threats to the well-being of individuals, groups, families and communities. This research spans the full range of problems including global poverty, food and housing insecurity, economic development, environmental safety, social determinants of health, maternal and child health, mental health, addiction, disease and illness, gender and income inequality, human rights and social justice, access to health care and social resources, strengthening care and service delivery, trauma, crises, and responses to natural disasters, war, violence, population movements and trafficking, war and refugees, immigration/migration, human trafficking, orphans and vulnerable children. Research that recognizes the significant link between individuals, families and communities and their external environments, as well as the interrelatedness of race, cultural, context and poverty, will be particularly welcome.