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dc.contributor.advisor Lesaoana, M.
dc.contributor.advisor Lahiri, P.
dc.contributor.author Mokobane, Reshoketswe
dc.date.accessioned 2019-12-04T08:08:37Z
dc.date.available 2019-12-04T08:08:37Z
dc.date.issued 2019
dc.identifier.uri http://hdl.handle.net/10386/2945
dc.description Thesis (Ph.D. (Statistics)) -- University of Limpopo, 2019 en_US
dc.description.abstract This study presents the application of Direct and Indirect methods of Small AreaEstimation(SAE)techniques. Thestudyisaimedatestimatingthetrends and the proportions of households accessing water, sanitation, and electricity for lighting at small areas of the Limpopo Province, South Africa. The study modified Statistics South Africa’s General Household Survey series 2009-2015 and Census 2011 data. The option categories of three variables: Water, Sanitation and Electricity for lighting, were re-coded. Empirical Bayes and Hierarchical Bayes models known as Markov Chain Monte Carlo (MCMC) methods were used to refine estimates in SAS. The Census 2011 data aggregated in ‘Supercross’ was used to validate the results obtained from the models. The SAE methods were applied to account for the census undercoverage counts and rates. It was found that the electricity services were more prioritised than water and sanitation in the Capricorn District of the Limpopo Province. The greatest challenge, however, lies with the poor provision of sanitation services in the country, particularly in the small rural areas. The key point is to suggestpolicyconsiderationstotheSouthAfricangovernmentforfutureequitable provisioning of water, sanitation and electricity services across the country. en_US
dc.format.extent xvii, 142 leaves en_US
dc.language.iso en en_US
dc.relation.requires Adobe Acrobat Reader en_US
dc.subject Small Area Estimation en_US
dc.subject Basic services en_US
dc.subject Water en_US
dc.subject Sanitation en_US
dc.subject Electricity en_US
dc.subject Household en_US
dc.subject Accessibility en_US
dc.subject Census data en_US
dc.subject Hierarchical Bayes en_US
dc.subject.lcsh Sampling (Statistics) en_US
dc.subject.lcsh Estimation theory en_US
dc.subject.lcsh Small area statistics en_US
dc.title Application of small area estimation techniques in modelling accessibility of water, sanitation and electricity in South Africa : the case of Capricorn District en_US
dc.type Thesis en_US


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