July 10, 2021 Thesis Open Access

Sultan Asfaw Oljira

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  <identifier identifierType="DOI">10.20372/nadre:14091</identifier>
  <creators>
    <creator>
      <creatorName>Sultan Asfaw Oljira</creatorName>
    </creator>
  </creators>
  <titles>
    <title>Households' Multidimensional Poverty: The Case of Nekemte Town</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-07-10</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Thesis</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://nadre.ethernet.edu.et/record/14091</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.20372/nadre:14090</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://nadre.ethernet.edu.et/communities/20-25</relatedIdentifier>
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  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Advisor: Daniel Masresha (PhD)&lt;/p&gt;

&lt;p&gt;The study aimed at analyzing households&amp;rsquo; multidimensional poverty in Nekemte town. To achieve this objective, the study used both primary and secondary data. The primary data was collected from 379 sample households of Nekemte town through interview and questionnaire. It was based on cross sectional data collected during 2020/21. Alkire Foster multidimensional poverty measurement: counting approach was employed to analyze the extent of multidimensional poverty in the study area. In this methodology, three dimensions (education, health and living standard) and eleven indicators were used. The result revealed that 20.6% of the population is under multidimensional poverty with average intensity and MPI of 41.5% and 8.55% respectively. Living standard dimension was the highest contributor to MPI followed by education dimension. To identify factors that determine households&amp;rsquo; multidimensional poverty in the town, binary logit model was employed. The logit model result indicated that household heads&amp;rsquo; educational level, family size and dependency ratio, income level, house ownership, saving habit, social capital significantly influence households&amp;rsquo; poverty in the town. Based on the findings, the study suggests improving economic activities, promoting access to education and improving saving habit. Moreover, improved targeting devices can be useful instruments in reducing poverty, in particular to reach those in severe poverty.&lt;/p&gt;

&lt;p&gt;Key words: Multidimensional poverty, Nekemte town, Ethiopia, indicators, household&lt;/p&gt;</description>
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