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Catastrophe And Rational Policy: Case Of National Security

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  • Hamid Mohtadi
  • Bryan S. Weber

Abstract

Predicting catastrophes involves heavy‐tailed distributions with no mean, eluding proactive policy as expected cost‐benefit analysis fails. We study US government counterterrorism policy, given heightened risk of terrorism. But terrorism also involves human behavior. We synthesize the behavioral and statistical aspects in an adversary‐defender game. Calibration to extensive data shows that where a Weibull distribution is the best predictor, US counterterrorism policy is rational (and optimal). Here, we estimate the adversary's unobserved variables, e.g., difficulty of an attack. We also find cases where the best predictor is a Generalized‐Pareto with no finite mean and rational policy fails. Here, we offer “work‐arounds”. (JEL H56, D81, C46)

Suggested Citation

  • Hamid Mohtadi & Bryan S. Weber, 2021. "Catastrophe And Rational Policy: Case Of National Security," Economic Inquiry, Western Economic Association International, vol. 59(1), pages 140-161, January.
    • Handle: RePEc:bla:ecinqu:v:59:y:2021:i:1:p:140-161
    DOI: 10.1111/ecin.12925
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • H56 - Public Economics - - National Government Expenditures and Related Policies - - - National Security and War
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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