Interrupted Time Series Analysis in the Study of Terrorism

Robert Apel, Henda Y. Hsu

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

Empirically informed counter-terrorism interventions are essential to effectively reducing terrorist violence and implementing sound policy. Interrupted time series analysis provides a rigorous methodology to carry out this important undertaking. In this chapter, we detail the standard approach to interrupted time series analysis in both univariate and multivariate settings, specifically autoregressive integrated moving average (ARIMA) and vector autoregression (VAR). An assessment of the impact of U.S. embassy fortifications provides an illustration of the statistical procedures, and sheds light on the issue of the intended and unintended consequences of security interventions. Our preliminary analysis suggests that enhancing U.S. embassy security reduced attacks on U.S. diplomatic targets without increasing attacks elsewhere. Rather, the hardening of U.S embassies resulted in a reduction of attacks against other U.S. interests.

Original languageEnglish (US)
Title of host publicationThe Handbook of the Criminology of Terrorism
Publisherwiley
Pages276-293
Number of pages18
ISBN (Electronic)9781118923986
ISBN (Print)9781118923955
DOIs
StatePublished - Jan 13 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Social Sciences(all)

Keywords

  • Autoregressive integrated moving average (ARIMA)
  • Time series analysis
  • U.S. embassy fortifications
  • Vector autoregression (VAR)

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