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Microcycles of Violence: Evidence from Terrorist Attacks by ETA and the FMLN

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Abstract

Recent research has demonstrated that individual crimes elevate the risk for subsequent crimes nearby, a phenomenon termed “near-repeats.” Yet these assessments only reveal global patterns of event interdependence, ignoring the possibility that individual events may be part of localized bursts of activity, or microcycles. In this study, we propose a method for identifying and analyzing criminal microcycles; groups of events that are proximate to each other in both space and time. We use the Global Terrorism Database (GTD) to analyze over 4,000 terrorist attacks attributed to the FMLN in El Salvador and the ETA in Spain; two terrorist organizations that were both extremely active and violent but differed greatly in terms of history, grievances and motives. Based on the definition developed, we find strong support for the conclusion that many of the terrorist attacks attributed to these two distinctive groups were part of violent microcycles and that the spatio-temporal attack patterns of these two groups exhibit substantial similarities. Our logistic regression analysis shows that for both ETA and the FMLN, compared to other tactics used by terrorists, bombings and non-lethal attacks are more likely to be part of microcycles and that compared to attacks which occur elsewhere, attacks aimed at national or provincial capitals or areas of specific strategic interest to the terrorist organization are more likely to be part of microcycles. Finally, for the FMLN only, compared to other attacks, those on military and government targets were more likely part of microcycles. We argue that these methods could be useful more generally for understanding the situational and temporal distribution of crime.

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Notes

  1. We regard our focus on terrorism as a logical extension in that much research (e.g., Wilkinson 1986; Hoffman 1998; Pape 2005; Dugan et al. 2005; Kydd and Walter 2006; Enders and Sandler 2006; Clarke and Newman 2006) suggests that terrorism is even more likely than more ordinary crime to be carefully planned. Thus, Crenshaw (1998: 7) characterizes terrorist violence as “an expression of political strategy” and claims that it represents “a willful choice made by an organization for political and strategic reasons.” And Sandler and Arce (2003: 320) point out that the predictable responses of terrorist groups to changes in sanctions and rewards aimed at constraining their behavior is strong evidence for advanced planning.

  2. While our analysis of ETA starts in 1970, the organization was actually founded in 1959 and it claimed its first fatality in 1968 (Reinares 2004; Sanchez-Cuenca 2009).

  3. According to Sanchez-Cuenca (2009: 3), Basque nationalism is strongest in Vizcaya, Guipuzcoa and the north of Navarra and is much weaker in the three French provinces, in the South of Navarra and in Alava.

  4. These categories are mutually exclusive. For example, we categorize assassinations that use explosives as “assassinations” while “bombings” refer to the more indiscriminate use of explosives in markets, police stations, and other public places.

  5. Data from 1993 were lost by PGIS in an office move and we have never been able to successfully restore them. We, therefore, treat 1993 as missing.

  6. Another difference between the GTD and other datasets of terrorist activity is the inclusion of attacks against the military and police, actions that are sometimes classified in other open source data bases as insurgent actions and distinct from terrorist attacks. While theoretical differences regarding strategies of insurgency compared to terrorism exist, broad criteria for inclusion here allows us to examine a wide range of violent group behavior by these two organizations.

  7. For example, if a source said only that “a group of armed members of FMLN stormed a village in the Chalatenango department, approximately 60 km from San Salvador,” we could not infer an exact latitude and longitude of the location. However, in such cases we did collect information on the department (or 1st administrative subdivision) and where applicable, the municipality (2nd administrative subdivision).

  8. Because attacks geocoded to the same centroid of a city may in actuality have occurred in different parts of the same city, it is more accurate to refer to these patterns as “near-repeat victimizations.”

  9. A majority of those missing geo-coordinates were attacks within the Basque Country where the specific village location was not provided in the original source.

  10. While others have noted that analyses using geocoded data with less than 85% non-missing data may produce unstable results (Ratcliffe 2004), the impact of missing data on our analysis is likely to be conservative because the majority of these events would likely have increased, rather than decreased, the number of near-repeats and microcycles observed. For example, in El Salvador, 422 of the 699 attacks with no latitude or longitude (60.4%) were terrorist strikes against power poles or other electrical infrastructure in rural areas—often occurring on the same day. Thus, if specific geocoded information on these cases had been available, these repeated coordinated attacks against electrical infrastructure would have resulted in a larger number of cases falling into microcycles.

  11. Sanchez-Cuenca (2009: 613) reports only three ETA-related casualties between 1968 and 1970, the year when our analysis begins.

  12. On the eve of Franco’s death in 1975, ETA split into two organizations, the political-military ETA (ETApm) and the military ETA (ETAm). ETApm, the larger and more powerful of the two, favored political participation and in 1981, renounced the use of terrorism and began full participation in electoral politics. While the analysis included ETApm, ETAm, and other ETA affiliates (Iraultza, Grupo Vasco Iraultza, Iraultza Aske), most of the attacks and fatalities attributed to ETA in our data base were actually carried out by ETAm (LaFree et al. 2011).

  13. Including the ETA cases, GTD recorded a total of 2,958 terrorist attacks against Spain during the study period. Other major groups responsible for these attacks included the First of October Antifascist Resistance Group (or GRAPO; 207 attacks; 7%); Terra Lliure (or TL; 61 attacks; 2.0%); and the Revolutionary Anti-Fascist Patriotic Front (or FRAP; 47 attacks; 1.6%).

  14. Those groups include: Fuerzas Populares de Liberación (FPL), Fuerzas Armadas de Liberación (FAL), Ejército Revolucionario del Pueblo (ERP), Fuerzas Armadas de la Resistencia Nacional (RN-FARN), and the Ejército Revolucionario de los Trabajadores Centroamericanos (ERTC). A variety of youth organizations were also merged into the FMLN at the same time.

  15. In results not presented here, we did include the additional attacks by these leftist groups and found few substantive differences with the results presented (analyses available on request).

  16. We selected these areas for El Salvador because they served as critical locations for training facilities, staging operations and popular support for the FMLN (Wood 2003). By the end of the Salvadoran Civil War, the FMLN occupied a significant portion of both Usulután and Chalatenango departments (25.3 and 17%, respectively). Usulután was also the site of extensive agricultural reforms that were integral to the grievances of the FMLN and played a strategic role for the FMLN commanders. Morazán was also a strategic resource base for the FMLN throughout the conflict.

  17. Statistical significance for the test result (Z) is determined through a Monte Carlo simulation approach using random permutations of the temporal distance matrix, recalculating a test result after each permutation. A set of 999 permutations are performed, generating a probability distribution for Z under the assumption that the space–time matching is random.

  18. Given the comparatively low occurrence rates of terrorism, we use two as a minimum number of linked events.

  19. We conducted several additional analyses to test the robustness of these results by grouping all attacks from a more generic movement in each country (Basque Resistance and Salvadoran Left), as well as all attacks from both generic movements and those with unknown group attributions. The results from those analyses did not produce substantial differences in substantive results and are available from the authors upon request.

  20. The pattern of significant results at 50 miles from an attack by FMLN is likely in large part a condition of the size of the country. El Salvador is a small, densely populated country covering an area the size of Massachusetts (~8,100 square miles) and roughly 170 miles from East to West: a 50-mile boundary covers nearly one-third of the country.

  21. In general, increasing the critical spatial distance for including attacks within microcycles should allow more nearby events to be included in each burst, resulting in longer cycles that account for more of the total events within that specific perpetrator categorization. For attacks by the FMLN, moving from a critical distance of 5 miles to 10 miles actually produced cycles that were longer (by almost three days on average), yet these longer cycles did not have substantially more events within them than those created by the smaller critical distances (13.3 events/cycle compared with 12.5 events/cycle, respectively).

  22. In results not presented here, we also ran the same regression models for microcycles constructed at 2 weeks and 10 miles and found no substantive differences (results available on request).

  23. It is substantively important to make between-group comparisons in these analyses among organizations and countries. However, as noted by Allison (1999) in limited dependent variable regression, differences in the degree of unobserved heterogeneity in the disturbance term can produce cross-group comparisons that are incorrect. To correct for this possibility, Allison (1999) suggests employing models that allow for interaction effects to be calculated and do not assume equality of heterogeneity in the error terms of the groups that are being compared. However, Williams (2009) suggests a method that does not require that an additional parameter be added to the model and is not limited by the assumption that at least one estimate is the same in the populations being compared. In general, it is preferable to use the heterogeneous choice model to better understand the potential impacts of differences in the error variance without the more restrictive assumptions of unrestricted interactions. Following this reasoning, we estimated heterogeneous choice models on a combined dataset of ETA and FMLN events using group membership (FMLN = 1) as a determinant of the residual variation. While residual variation is present between groups in microcycle inclusion, the difference is not statistically significant once interactions between group membership and each predictor are included. Overall, the results differ little from the standard use of z-scores to identify statistically significant differences, so we have decided to present results from the logistic regression analysis, which will be more familiar to readers. However, the alternative results are available from the authors on request.

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Acknowledgments

Support for this research was provided by the Science and Technology Directorate of the U.S. Department of Homeland Security through the National Consortium for the Study of Terrorism and Responses to Terrorism (START), grant number N00140510629. Any opinions, findings, and conclusions or recommendations in this document are those of the authors and do not necessarily reflect views of the Department of Homeland Security. We would like to thank Joshua Freilich, Thomas Loughran, Erin Miller, Jacob Shapiro, David Weisburd, the editors of JQC, and the comments of two anonymous reviewers for their help in improving this manuscript.

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    Brandon Behlendorf, Gary LaFree & Richard Legault

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Behlendorf, B., LaFree, G. & Legault, R. Microcycles of Violence: Evidence from Terrorist Attacks by ETA and the FMLN. J Quant Criminol 28, 49–75 (2012). https://doi.org/10.1007/s10940-011-9153-7

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