Modelling South African social unrest between 1997 and 2016

Show simple item record

dc.contributor.advisor Beyers, Frederik Johannes Conradie
dc.contributor.coadvisor Van Staden, Paul J.
dc.contributor.coadvisor Venter, Marli
dc.contributor.postgraduate Smart, Sally-Anne
dc.date.accessioned 2020-01-27T08:08:58Z
dc.date.available 2020-01-27T08:08:58Z
dc.date.created 2020-04-16
dc.date.issued 2019
dc.description Dissertation (MSc (Actuarial Mathematics))--University of Pretoria, 2019. en_ZA
dc.description.abstract Social unrest, terrorism and other forms of political violence events are highly unpredictable. These events are driven by human intent and intelligence, both of which are extremely difficult to model accurately. This has resulted in a scarcity of insurance products that cover these types of perils. Links have been found between the incidence of political violence and various economic and socioeconomic variables, but to date no relationships have been identified in South Africa. The aim of this study was to address this. Firstly, by identifying relationships between the incidence of social unrest events and economic and socio-economic variables in South Africa and secondly by using these interactions to model social unrest. Spearman’s rank correlation and trendline analysis were used to compare the direction and strength of the relationships that exist between protests and the economic and socio-economic variables. To gain additional insight with regards to South African protests, daily, monthly, quarterly and annual protest models were created. This was done using four different modelling techniques, namely univariate time series, linear regression, lagged regression and the VAR (1) model. The forecasting abilities of the models were analysed using both a one-step and n-step forecasting procedure. Variations in relationships for different types of protests were also considered for five different subcategories. Spearman’s rank correlation and trendline analysis showed that the relationships between protests and economic and socio-economic variables were sensitive to changes in data frequency and the use of either national or provincial data. The daily, monthly, quarterly and annual models all had power in explaining the variation that was observed in the protest data. The annual univariate model had the highest explanatory power (R2 = 0.8721) this was followed by the quarterly VAR (1) model (R2 = 0.8659), while the monthly lagged regression model had a R2 of 0.8138. The one-step forecasting procedure found that the monthly lagged regression model outperformed the monthly VAR (1) model in the short term. The converse was seen for the short-term performance of the quarterly models. In the long term, the VAR (1) model outperformed the other models. Limitations were identified within the lagged regression model’s forecasting abilities. As a model’s long-term forecasting ability is important in the insurance world, the VAR (1) model was deemed as the best modelling technique for South African social unrest. Further model limitations were identified when the subcategories of protests were considered. This study demonstrates that with the use of the applicable economic and socio-economic variables, social unrest events in South Africa can be modelled. en_ZA
dc.description.availability Unrestricted en_ZA
dc.description.degree MSc (Actuarial Mathematics) en_ZA
dc.description.department Insurance and Actuarial Science en_ZA
dc.description.sponsorship Absa Chair in Actuarial Science (UP) en_ZA
dc.description.sponsorship South African Department of Science and Technology (DST) Risk Research Platform, under coordination of the North-West University (NWU) en_ZA
dc.identifier.citation Smart, S 2019, Modelling South African social unrest between 1997 and 2016, MSc Actuarial Mathematics Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/72929> en_ZA
dc.identifier.other A2020 en_ZA
dc.identifier.uri http://hdl.handle.net/2263/72929
dc.language.iso en en_ZA
dc.publisher University of Pretoria
dc.rights © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subject UCTD en_ZA
dc.subject Social unrest en_ZA
dc.subject Protests en_ZA
dc.subject South Africa en_ZA
dc.subject Insurance en_ZA
dc.subject Modelling techniques en_ZA
dc.subject VAR (1) model en_ZA
dc.title Modelling South African social unrest between 1997 and 2016 en_ZA
dc.type Dissertation en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record