The proliferation of terrorism worldwide raises the risk that terrorist strategies could evolve from conventional methods (e.g. suicide attacks) to biological, chemical and even radioactive and nuclear attacks (commonly abbreviated as CBRN) which are potentially much more dangerous. The authors make three contributions toward a better understanding of this risk and how it responds to counterterrorism measures.
The authors develop a game that captures the terrorists’ potential strategic substitution between conventional and CBRN-type attacks; the authors calibrate the parameters of the game to real data using a novel calibration method and a partially unique dataset; they estimate the heavy-tailed distribution of attack severity and thus the probability of a successful attack, the underlying effort to launch an attack and the intrinsic difficulty of launching different types of attacks.
The authors find that in equilibrium, CBRN attacks, though less likely and more difficult to execute, are more deadly. In the end, the trade-off between, on one hand, the greater difficulty of carrying out a CBRN attack, and on the other, the greater deadliness of such an attack, points to a level of optimal counterterrorism spending by governments that weighs toward defending against CBRN attacks. The authors discuss these results and compare them with the actual level of counterterrorism spending by the US Government.
The framework of the game allows for substitution between the conventional and CBRN weapon types. These aspects of this paper, together with the unique calibration methodology, and the use of some unique terrorism data for the first time, are what distinguish this work from similar game theoretic papers in this area.
This work was supported by a grant from the U.S. Department of Homeland Security, Domestic Nuclear Detection Office (DNDO) Academic Research Initiative Grant No. 2014-DN-077-ARI074-02 as well as by the National Science Foundation Academic Research Initiative (ARI) with the National Consortium for the Study of Terrorism and Responses to Terrorism (START). The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Department of Homeland Security, DNDO or START.
The authors have benefitted from discussion with other project participants, notably John Sawyer, and Gary Ackerman. They also thank the participants of a conference on Validating Models of Adversary Behavior at the State University of New York at Buffalo (June 2015) especially Vicki Bier and Jun Zhuang, as well as the participants of workshops at the Universities of Wisconsin and Minnesota, for helpful comments and criticism.
Mohtadi, H. and Weber, B. (2020), "Terrorism risk and optimal policy response: theory and empirics", Indian Growth and Development Review, Vol. 13 No. 2, pp. 449-468. https://doi.org/10.1108/IGDR-08-2019-0090
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