Determinants of Recurrence of Terrorist Attacks.
Global Analysis with Panel Data
DOI:
https://doi.org/10.30854/anf.v31.n56.2023.956Keywords:
Terrorism, Terrorist attacks, Recurrence, Stochastic models, Panel dataAbstract
Objective: The objective of this study is to establish the determinants of the number of terrorist attacks in a territory over time. Methodology: Elements of both the theory of the attack claims and the recurrence of attacks are incorporated, to obtain a deeper analytical spectrum. Secondly, a negative binomial stochastic model with panel data is implemented, characterized by being dynamic to avoid endogeneity problems. The information used comes from the Global Terrorism Database, Big Allied and Dangerous, Political Terror Scale, and World Bank databases. Results: The initial results obtained indicate that the probability of terrorist attacks increases when there is a history of armed assault, a high educational level, suicide attacks, and attacks on civilians, while it decreases with high female labor participation and low corruption rates. Alternatively, the research found sufficient empirical evidence to affirm that the attack claims help to explain the phenomenon of the number of attacks by including civilian targets, the number of fatalities, armed assaults, and suicides. Conclusions: If variables from the number of attack theories are incorporated, such as female labor participation, variation in GDP per capita, education expenditures, and the corruption index, the results are significantly more robust. This broadens the argumentative spectrum and enhances the explanatory capacity of the variables amongst themselves.
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