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Original Articles

Understanding Insurgency Violence: A Quantitative Analysis of the Political Violence in Northern Ireland 1969–1999

Pages 705-725 | Received 20 May 2008, Accepted 22 Nov 2008, Published online: 22 Jul 2009
 

Abstract

The main argument examined in this article is that the escalation of political violence in Northern Ireland between 1969–1999 resulted because of the state's reliance on repression and this had conflicting effects contributing to the rise in violence. Perhaps the most important finding reached by this research was that a state's reliance on repression is positively associated with more insurgent violence. This research suggests that variations in outcomes to the use of force by a democratic state may result because one may assume a linear model exists when in reality the true relationship maybe curvilinear.

Notes

∗Indicates the best performing model.MSE equals Mean Square Error.

1. Lichbach's (1987) substitution effect asserts that people who have grievances with the government seek to maximize their goals by substituting nonviolent protest for violent protest and vice-versa depending on whether the government responds with accommodative or coercive policies. This research contends that this substitution effect had tremendous negative ramifications in Northern Ireland.

2. The Lagrange Multiplier Test was applied to each of these models to test for autocorrelation problems and none were evident (CitationGujarati 1995).

3. The Cook-Weisberg test for heteroskedasticity using fitted values of shootings C1, bombings C2, and deaths C3 revealed no heteroskedasticity problems as the Probability > chi2s were insignificant (CitationGujarati 1995).

4. These graphs were drawn in Stata using Gary King's Clarify Scripts program in conjunction with a program called Polygraph developed by Dr. Marc Rosenblum and Dr. Michael Hess at the University of New Orleans (CitationKing, Tomz, and Wittenberg 2000). Rosenblum and Hess's program does not improve Clarify, but simply takes a cumbersome manual process and makes it easier. This program takes estimates and mean predicted values that Clarify generates, and puts them into variables that can be graphed. So, instead of going through a cumbersome process of running Clarify a step at a time this program does all the steps at once and creates graphable points.

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