The Socio-Economic Determinants of Terrorism: A Bayesian Model Averaging Approach

22 Pages Posted: 21 Jun 2018 Last revised: 10 Sep 2018

See all articles by Marcos Sanso-Navarro

Marcos Sanso-Navarro

Universidad de Zaragoza

María Vera-Cabello

Centro Universitario de la Defensa de Zaragoza

Date Written: September 4, 2018

Abstract

This paper introduces model uncertainty into the empirical study of the determinants of terrorism at country level. This is done by adopting a Bayesian model averaging approach and accounting for the over-dispersed count data nature of terrorist attacks. Both a broad measure of terrorism and incidents per capita have been analyzed. Our results suggest that, among the set of regressors considered, those reflecting labor market conditions and economic prospects tend to receive high posterior inclusion probabilities. These findings are robust to changes in the model specification and sample composition and are not meaningfully affected by the generalized linear regression model applied. Evidence of a geographically heterogeneous relationship between terrorism and its determinants is also provided.

Keywords: Terrorism Determinants, Model Uncertainty, Bayesian Model Averaging, Generalized Linear Models

JEL Classification: C11, C25, C52, D74, H56

Suggested Citation

Sanso-Navarro, Marcos and Vera-Cabello, María, The Socio-Economic Determinants of Terrorism: A Bayesian Model Averaging Approach (September 4, 2018). Available at SSRN: https://ssrn.com/abstract=3192379 or http://dx.doi.org/10.2139/ssrn.3192379

Marcos Sanso-Navarro (Contact Author)

Universidad de Zaragoza ( email )

Facultad de Economía y Empresa
Departamento de Análisis Económico
Zaragoza, 50005
Spain
+34 876 554 629 (Phone)

HOME PAGE: http://personal.unizar.es/marcossn

María Vera-Cabello

Centro Universitario de la Defensa de Zaragoza ( email )

Academia General Militar, Ctra. de Huesca, s/n
Zaragoza, Zaragoza 50009
Spain

Register to save articles to
your library

Register

Paper statistics

Downloads
43
Abstract Views
280
PlumX Metrics