On the Frequency of Severe Terrorist Events

Department of Government, University of Essex, Colchester, England, United Kingdom
Journal of Conflict Resolution (Impact Factor: 2.24). 07/2006; 51(1). DOI: 10.1177/0022002706296157
Source: arXiv


In the spirit of Richardson's original (1948) study of the statistics of deadly conflicts, we study the frequency and severity of terrorist attacks worldwide since 1968. We show that these events are uniformly characterized by the phenomenon of scale invariance, i.e., the frequency scales as an inverse power of the severity, P(x) ~ x^-alpha. We find that this property is a robust feature of terrorism, persisting when we control for economic development of the target country, the type of weapon used, and even for short time-scales. Further, we show that the center of the distribution oscillates slightly with a period of roughly tau ~ 13 years, that there exist significant temporal correlations in the frequency of severe events, and that current models of event incidence cannot account for these variations or the scale invariance property of global terrorism. Finally, we describe a simple toy model for the generation of these statistics, and briefly discuss its implications.

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    • "For example, Bogen and Jones [1] applied a PL distribution to approximate empirical data of victim/event rates and used the PL function to predict mortality due to terrorism through the year 2080. Clauset et al [3] studied the frequency and the number of casualties (deaths and injuries) of terrorist attacks. They observed scale-invariance behavior, where the frequency of the events was an inverse power of the number of casualties. "

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    • "Security-relevant activities are generally heavy-tailed, as they are conducted by a small number of people compared to the overall population. The corresponding heavy-tailed distributions require special methods in order to apply algorithmic reasoning (Clauset et al., 2007). General statistical assumptions about what can be reasonably expected as the next event do not work, because these are 'distributions without expectations' (Janert, 2010: 201). "
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