Determinants of terrorism in the MENA region: a Bayesian Model Averaging based approach

Zohra Aroussi, Mekki Hamdaoui and Mounir Smida
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Zohra Aroussi: Faculty of Economic Sciences and Management of Sousse, University of Sousse, Sousse, Tunisia
Mounir Smida: Faculty of Economic Sciences and Management of Sousse, University of Sousse, Sousse, Tunisia

Journal of Economic Analysis, 2024, vol. 3, issue 3, 1-24

Abstract: In this work we aim to identify potential determinants and seek to predict terrorism attack. Thus, to eliminate uncertainty linked to explanatory variables we used the BMA method. We show that, contrary to expectations terrorism in MENA region is no longer purely of economic origin but mainly due to political problems, education, financial development and countries’ demographic characteristics. Likewise, we find that national, international and global terrorism are not of same origins even they present many common roots. In the end, we show that it is possible to predict majority of attacks based on a small number of indicators measuring political risk, financial development and income inequalities.

Keywords: Terrorism; MENA; Bayesian Model Averaging; Logit; Early warning system (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:bba:j00001:v:3:y:2024:i:3:p:1-24:d:213

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