CATASTROPHE AND RATIONAL POLICY: CASE OF NATIONAL SECURITY.
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...
| Publicado en: | Economic Inquiry Vol. 59; no. 1; pp. 140 - 162 |
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| Autores principales: | , |
| Formato: | Artículo |
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Wiley-Blackwell
Jan2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=147223346&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 147223346 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00952583 EIQ jtl: Economic Inquiry issn: 00952583 maglogo: Y pubinfo: dt: Jan2021 vid: 59 iid: 1 pid: 480 pub: Wiley-Blackwell artinfo: ui: 147223346 10.1111/ecin.12925 ppf: 140 ppct: 22 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P size: 695KB tig: atl: CATASTROPHE AND RATIONAL POLICY: CASE OF NATIONAL SECURITY. aug: au: Mohtadi, Hamid Weber, Bryan S. affil: Department of Economics, University of Wisconsin‐Milwaukee, Milwaukee WI, USA Department of Economics, City University of New York, New York NY, USA su: Terrorism National security Quantitative research Disasters Calibration Counterterrorism sug: subj: Terrorism National security Quantitative research National Security Disasters Calibration Counterterrorism ab: 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". pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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