Catastrophe and Rational Policy: Case of National Security

33 Pages Posted: 30 Jul 2019

See all articles by Hamid Mohtadi

Hamid Mohtadi

University of Wisconsin - Milwaukee

Bryan Weber

City University of New York (CUNY) - Economics Department

Date Written: June 05, 2019

Abstract

Predicting catastrophes sometimes involves heavy-tailed distributions with no mean, eluding proactive policy since expected cost-benefit based analysis fails. We study US government counterterrorism policy, given heightened risk of terrorism. However, terrorism involves human behavior. We synthesize the behavioral and statistical aspects within an adversary-defender game. Calibration to extensive data shows that sometimes Weibull with its heavy tail, but finite mean, fits best and rational policy is feasible. Here, we find US counterterrorism expenditures are nearly optimal and then estimate terrorists’ unobserved parameters, e.g. difficulty to attack. Other times Generalized-Pareto, with no mean, fits best and rational policy fails. Here, we offer practical “work-around”.

Keywords: public policy, catastrophe, national security, terrorism, heavy tail distributions, game

JEL Classification: H56, D81, C46

Suggested Citation

Mohtadi, Hamid and Weber, Bryan, Catastrophe and Rational Policy: Case of National Security (June 05, 2019). Available at SSRN: https://ssrn.com/abstract=3427257 or http://dx.doi.org/10.2139/ssrn.3427257

Hamid Mohtadi (Contact Author)

University of Wisconsin - Milwaukee ( email )

Department of Economics
Milwaukee, WI 53211
United States

Bryan Weber

City University of New York (CUNY) - Economics Department ( email )

Building 3N Room 213C
New York, NC
United States

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