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      Vulnerability of rural households to climate-induced shocks in Lokka Abaya district, Sidama zone, southern Ethiopia

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          Abstract

          This study was conducted in rural communities of Lokka Abaya district, Sidama zone, southern Ethiopia to assess vulnerability status of men and women households to climate-induced shocks and stress. This article is based on household survey, focus group discussion and key informant interviews. A total of 258 smallholder farmers were selected from three villages using stratified random sampling. A combination of social, economic and environmental indicators was employed to develop the vulnerability index of each household head and estimate quantitatively that is vulnerability is estimated as a function of adaptive capacity, exposure and sensitivity of households. The results indicated that farmers had poor access to public services including access to affordable credit, market, health services and climate information. The survey revealed that droughts, floods, soil erosion, pests and diseases were climate-related challenges in the study area. Regarding vulnerability of households to climate variability, results indicated that around 8.5% and 18.2% of male- and female-headed households, respectively, were highly vulnerable whilst 41% and 45.5% of male- and female-headed households, respectively, were moderately vulnerable. The results confirmed that 37.7% and 27.3% of male- and female-headed households, respectively, were less vulnerable. The rest 12.8% men and 9% women were not vulnerable. Therefore, there is a need to enhance access to affordable credit, market, climate information, health, income diversification of farmers, soil and water conservation and afforestation of hilly areas if farmers need to be climate resilient.

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          Estimating wealth effects without expenditure data—or tears: An application to educational enrollments in states of India

          Using data from India, we estimate the relationship between household wealth and children’s school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children’s enrollment across Indian states. On average a “rich” child is 31 percentage points more likely to be enrolled than a “poor” child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.
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            Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems

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              Climate change and Africa

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                Author and article information

                Journal
                Jamba
                Jamba
                JAMBA
                Jàmbá : Journal of Disaster Risk Studies
                AOSIS
                2072-845X
                1996-1421
                25 May 2021
                2021
                : 13
                : 1
                : 1051
                Affiliations
                [1 ]Department of General Forestry, Wondo Genet College of Forestry and Natural Resources, Hawassa University, Hawassa, Ethiopia
                Author notes
                Corresponding author: Muluken Mekuyie, mulukenmekuyie@ 123456gmail.com
                Author information
                https://orcid.org/0000-0002-5948-2273
                Article
                JAMBA-13-1051
                10.4102/jamba.v13i1.1051
                8182566
                9a316c93-992c-490c-af1b-9050ac1ae088
                © 2021. The Authors

                Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License.

                History
                : 02 September 2020
                : 07 April 2021
                Categories
                Original Research

                adaptive capacity,vulnerability index,exposure,drought,vulnerable households,sensitivity,rural community

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