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dc.contributor.advisorDe la Rey, T.
dc.contributor.advisorDe Jongh, D.C.J.
dc.contributor.advisorVan Vuuren, G.W.
dc.contributor.authorFourie, Erika
dc.date.accessioned2015-11-19T10:31:18Z
dc.date.available2015-11-19T10:31:18Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/10394/15156
dc.descriptionPhD (Risk analysis), North-West University, Potchefstroom Campus, 2015en_US
dc.description.abstractThe objectives of the research study are to review existing subnational credit rating methodologies and their applicability in the South African context, to develop the quantitative parts of credit rating methodologies for two provincial departments (Department of Health and Department of Education) that best predict future payment behaviour, to test the appropriateness of the proposed methodologies and to construct the datasets needed. The literature study includes background information regarding the uniqueness of South Africa’s provinces and credit rating methodologies in general. This is followed by information on subnational credit rating methodologies, including a review of existing subnational credit rating methodologies and an assessment of the applicability of the information provided in the South African context. Lastly, the applicable laws and regulations within the South African regulatory framework are provided. The knowledge gained from the literature study is applied to the data that have been collected to predict the two departments’ future payment behaviour. Linear regression modelling is used to identify the factors that best predict future payment behaviour and to assign weights to the identified factors in a scientific manner. The resulting payment behaviour models can be viewed as the quantitative part of the credit ratings. This is followed by a discussion on further investigations to improve the models. The developed models (both the simple and the advanced models) are tested with regard to prediction accuracies using RAG (Red, Amber or Green) statuses. This is followed by recommendations regarding future model usage that conclude that the department-specific models outperform the generic models in terms of prediction accuracies.en_US
dc.language.isoenen_US
dc.subjectSubnational governmentsen_US
dc.subjectSubnational credit rating methodologiesen_US
dc.subjectDepartment of Healthen_US
dc.subjectDepartment of Educationen_US
dc.subjectPayment behaviouren_US
dc.subjectLinear regression modellingen_US
dc.subjectRAG statusesen_US
dc.subjectPrediction accuracyen_US
dc.subjectSubnasionale regeringsen_US
dc.subjectSubnasionale kredietgraderingsmetodologieëen_US
dc.subjectDepartement van Gesondheiden_US
dc.subjectDepartement van Onderwysen_US
dc.subjectBetalingsgedragen_US
dc.subjectLineêre regressiemodelleen_US
dc.subjectROG statusseen_US
dc.subjectVoorspellingsakkuraatheiden_US
dc.titleReview of subnational credit rating methodologies and their applicability in South Africaen
dc.typeThesisen_US
dc.description.thesistypeDoctoralen_US
dc.contributor.researchID10943587 - De la Rey, Tanja (Supervisor)
dc.contributor.researchID11844647 - De Jongh, Wawid Cornelius Johannes (Supervisor)
dc.contributor.researchID12001333 - Van Vuuren, Gary Wayne (Supervisor)


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