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Modelling South African social unrest between 1997 and 2016
Dissertation (MSc (Actuarial Mathematics))--University of Pretoria, 2019.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2020
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| _version_ | 1867613676313247744 |
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| access_status_str | Open Access |
| author2 | Beyers, Frederik Johannes Conradie |
| author_browse | Beyers, Frederik Johannes Conradie |
| author_facet | Beyers, Frederik Johannes Conradie |
| collection | Thesis |
| dc_rights_str_mv | © 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. |
| description | Dissertation (MSc (Actuarial Mathematics))--University of Pretoria, 2019. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/72929 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:39:56.028Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/72929 Modelling South African social unrest between 1997 and 2016 Beyers, Frederik Johannes Conradie sallyannesmart@gmail.com Van Staden, Paul J. Venter, Marli Smart, Sally-Anne UCTD Social unrest Protests South Africa Insurance Modelling techniques VAR (1) model Natural and agricultural sciences theses SDG-08 Natural and agricultural sciences theses SDG-10 Natural and agricultural sciences theses SDG-16 Dissertation (MSc (Actuarial Mathematics))--University of Pretoria, 2019. 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. Absa Chair in Actuarial Science (UP) South African Department of Science and Technology (DST) Risk Research Platform, under coordination of the North-West University (NWU) bs2025 Insurance and Actuarial Science MSc (Actuarial Mathematics) Unrestricted SDG-08: Decent work and economic growth SDG-10: Reduced inequalities SDG-12: Responsible consumption and production 2020-01-27T08:08:58Z 2020-01-27T08:08:58Z 2020-04-16 2019 Dissertation 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> A2020 http://hdl.handle.net/2263/72929 en © 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. application/pdf University of Pretoria |
| spellingShingle | UCTD Social unrest Protests South Africa Insurance Modelling techniques VAR (1) model Natural and agricultural sciences theses SDG-08 Natural and agricultural sciences theses SDG-10 Natural and agricultural sciences theses SDG-16 Modelling South African social unrest between 1997 and 2016 |
| title | Modelling South African social unrest between 1997 and 2016 |
| title_full | Modelling South African social unrest between 1997 and 2016 |
| title_fullStr | Modelling South African social unrest between 1997 and 2016 |
| title_full_unstemmed | Modelling South African social unrest between 1997 and 2016 |
| title_short | Modelling South African social unrest between 1997 and 2016 |
| title_sort | modelling south african social unrest between 1997 and 2016 |
| topic | UCTD Social unrest Protests South Africa Insurance Modelling techniques VAR (1) model Natural and agricultural sciences theses SDG-08 Natural and agricultural sciences theses SDG-10 Natural and agricultural sciences theses SDG-16 |
| url | http://hdl.handle.net/2263/72929 |