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ABSTRACT
Statistical modelling of terrorism has advanced the understanding of its underlying drivers. However, numerous questions remain, some have not been empirically tested, and regional dynamics differ. In recent decades, the Middle East/North Africa (MENA) and Central Asia have been focal points of terrorism. An extensive review of global and regional statistical models of terrorism at the country-year level was conducted and hypotheses re-tested on a database for MENA and Central Asia for years 1998–2017. The analysis indicates that the primary drivers of terrorism in this region are corruption, war, state terror, weak democracy, and unemployment. Fuel exports, ethnic and religious fractionalization, youth bulges, and internally displaced persons (IDPs) have little or no statistically significant relationship to terrorism in the region. Collectively, these results indicate that certain factors can anticipate terrorism in the region. Further analysis indicates that some factors have the potential to erupt suddenly and therefore require constant monitoring and sound contingency planning.
Acknowledgments
The views expressed are the authors’ own and in no way reflect the official position of the United States Department of Defense.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. The Global Terrorism Database definition of terrorism was used in this study because the Global Terrorism Index is based on their data, and it provides a broad, inclusive definition of terrorism as the use of violence by non-state actors. This definition covers alternative terms such as Violent Non-State Actors (VNSAs), Violent Extremist Organizations (VEOs), and most Non-State Armed Groups (NSAGs). The definition is, “the threatened or actual use of illegal force and violence by a non-state actor to attain a political, economic, religious, or social goal through fear, coercion, or intimidation (Global Terrorism Database, Citation2019).”
2. The “Oil Curse” refers to the negative influence dependence on easily exploited, valuable resources on state stability (Lujala, Citation2010).
3. In 1998, the Global Terrorism Database, upon which the GTI is based, altered its definition of terrorism. Only data post-1998 were used to ensure the consistent application of the definition in the database.
4. Battle deaths was chosen instead of a binary variable presence/absence of war in order to provide a quantitative measure of the severity of war’s effect on a population.
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Notes on contributors
Lawrence A. Kuznar
Dr. Lawrence A. Kuznar is emeritus professor of anthropology, Purdue University, Fort Wayne and Chief Cultural Sciences officer for NSI, Inc. He conducts anthropological research relevant to counterterrorism and other areas of national security. His research includes discourse analysis of ISIS leadership, Eastern European State and non-State Actors, Iranian and North Korean leadership to provide leading indicators of intent and behaviour. He has developed computational models of genocide in Darfur and tribal factionalism in New Guinea, mathematical models of inequality and conflict, and integrated socio-cultural databases for predicting illicit nuclear trade and bioterrorism. He has also served on the HSCB Technical Progress Evaluation panel, and a panel for National Counterterrorism Center (NCTC) net assessment.
Jeffrey Day
Jeffrey E. Day is a Principal Data Scientist at National Security Innovation, Inc. Mr. Day specializes in applied statistical modeling in both the commercial and government sectors. His research efforts include discourse analysis, text analytics, machine learning models, forecasting, and behavioral and attitudinal segmentation across various domain spaces. Mr. Day has a B.A. and M.A. in Political Science for Southern Illinois University.