Application of small area estimation techniques in modelling accessibility of water, sanitation and electricity in South Africa : the case of Capricorn District - Mokobane, Reshoketswe (My University, 2019)
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.
Thesis (Ph.D. (Statistics)) -- University of Limpopo, 2019
Keywords: Small Area Estimation; Basic services; Water; Sanitation; Electricity; Household; Accessibility; Census data; Hierarchical Bayes; Sampling (Statistics); Estimation theory; Small area statistics