The aim of this thesis is to attempt to address gaps in the forced displacement-conflict escalation literature, as well as in the literature on conflict forecasting. By posing the question To what extent can data on forced displacement improve accuracy of conflict escalation forecasts?, the aim is to explore the possible bidirectional relationship between forced displacement and armed conflict, as well as how such a relationship may be beneficial for conflict forecasts. Through utilizing Random Forest classifiers and regressors, two hypotheses are tested: 1) Increasing numbers of displaced persons are associated with escalating violence, and 2) Incorporating forced displacement data into conflict forecasting models can improve the accuracy of conflict timing prediction. The obtained results offer support for both hypotheses, in turn providing two contributions to the field of peace and conflict studies. First, that the relationship between displacement and conflict escalation is not strictly causal. Second, data on displacement magnitudes can improve conflict escalation forecasts.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-531162 |
Date | January 2024 |
Creators | Matić, Marina |
Publisher | Uppsala universitet, Institutionen för freds- och konfliktforskning |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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