Journal of Quantitative Criminology

, Volume 28, Issue 1, pp 49–75 | Cite as

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

Original Paper


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.


Spatial analysis Terrorism Near-repeat Bursts ETA FMLN Microcycle Spain El Salvador 


  1. Alexander Y, Pluchinsky D (eds) (1992) Europe’s last red terrorists: the fighting communist organizations. Frank Cass Publishers, Washington, DCGoogle Scholar
  2. Allison P (1999) Comparing logit and probit coefficients across groups. Soc Meth Res 28:186–208CrossRefGoogle Scholar
  3. Bapat NA (2007) The internationalization of terrorist campaigns. Conf Manage Peace Sci 24:265–280CrossRefGoogle Scholar
  4. Barabasi AL (2005) The origin of bursts and heavy tails in humans dynamics. Nature 435:207–211CrossRefGoogle Scholar
  5. Benmelech E, Berrebi C, Klor EF (2010) Economic conditions and the quality of suicide terrorism. C.E.P.R. Discussion papersGoogle Scholar
  6. Bernasco W (2008) Them again? Same-offender involvement in repeat and near repeat burglaries. Eur J Crim 5:411–431CrossRefGoogle Scholar
  7. Berrebi C, Lakdawalla D (2007) How does terrorism risk vary across space and time? An analysis based on the Israeli experience. Def Peace Econ 18:113–191CrossRefGoogle Scholar
  8. Bohorquez JC, Gourley S, Dixon AR, Spagat M, Johnson NF (2009) Common ecology quantified human insurgency. Nature 462:911–914CrossRefGoogle Scholar
  9. Bracamonte JAM, Spencer DE (1995) Strategy and tactics of Salvadoran FMLN guerrillas: last battle of the cold war, blueprint for future conflicts. Praeger, CTGoogle Scholar
  10. Braga AA (2001) The effects of hot spots policing on crime. Ann Am Acad Pol Soc Sci 578:104–125CrossRefGoogle Scholar
  11. Braga AA, Bond B (2008) Policing crime and disorder hot spots: a randomized controlled trial. Criminology 46:577–607CrossRefGoogle Scholar
  12. Braga AA, Papachristos AV, Hureau DM (2010) The concentration and stability of gun violence at micro places in Boston, 1980–2008. J Quant Crim 26:33–53CrossRefGoogle Scholar
  13. Burke R (2006) Counter-terrorism for emergency responders. CRC Press, Boca RatonCrossRefGoogle Scholar
  14. Chainey S, Tompson L, Uhlig S (2008) The utility of hotspot mapping for predicting spatial patterns of crime. Secur J 21:4–28CrossRefGoogle Scholar
  15. Clarke RV, Newman GR (2006) Outsmarting the terrorists. Praeger, New YorkGoogle Scholar
  16. Cohen A (1983) Comparing regression coefficients across subsamples: a study of the statistical test. Soc Meth Res 12:77–94CrossRefGoogle Scholar
  17. Crenshaw M (1998) The logic of terrorism: terrorist behavior as a product of choice. Terr Counter Terr 2:54–64Google Scholar
  18. Dugan L (2010) The series hazard model: an alternative to time series for event data. J Quant Crim. doi:10.1007/s10940-010-9127-1. Accessed 1/5/2011
  19. Dugan L, LaFree G, Piquero AR (2005) Testing a rational choice model of airline hijackings. Criminology 43:1031–1066CrossRefGoogle Scholar
  20. Enders W, Sandler T (2006) The political economy of terrorism. Cambridge University Press, New YorkGoogle Scholar
  21. Farrell G, Pease K (eds) (2001) Repeat victimization. Criminal Justice Press, MonseyGoogle Scholar
  22. Friestad DE (1978) Descriptive analysis of terrorist targets in a crime prevention through environmental design context. Unpublished dissertation, Florida State UniversityGoogle Scholar
  23. Goh KI, Barabasi AL (2008) Burstiness and memory in complex systems. Europhysics Lett 48002:p1–p5Google Scholar
  24. Goodwin J (2006) A theory of categorical terrorism. Soc Forces 84:2027–2046CrossRefGoogle Scholar
  25. Grenier Y (1999) The emergence of insurgency in El Salvador: ideology and political will. University of Pittsburgh Press, PittsburghGoogle Scholar
  26. Groff ER, Weisburd D, Yang SM (2010) Is it important to examine crime at a local “micro” level? A longitudinal analysis of street to street variability in crime trajectories. J Quant Crim 26:7–32CrossRefGoogle Scholar
  27. Grubesic TH, Mack EA (2008) Spatio-temporal interaction of urban crime. J Quant Crim 24:285–306CrossRefGoogle Scholar
  28. Harries KD (1981) Alternative denominators in conventional crime rates. In: Brantingham PJ, Brantingham PL (eds) Environmental criminology. Sage, London, pp 147–165Google Scholar
  29. Hipp JR (2007) Block, tract and levels of aggregation: neighborhood structure and crime and disorder as a case in point. Am Soc Rev 72:659–680CrossRefGoogle Scholar
  30. Hoffman B (1998) Inside terrorism. Columbia Univ Press, New YorkGoogle Scholar
  31. Johnson SD, Braithwaite A (2009) Spatio-temporal modeling of insurgency in Iraq. In: Freilich JD, Newman GR (eds) Reducing terrorism through situational crime prevention. Criminal Justice Press, Monsey, pp 9–32Google Scholar
  32. Johnson SD, Bowers KJ, Hirschfield AFG (1997) New insights into the spatial and temporal distribution of repeat victimization. Br J Criminol 37:224–241Google Scholar
  33. Johnson SD, Bernasco W, Bowers KJ, Elffers H, Ratcliffe J, Rengert G, Townsley M (2007) Space-time patterns of risk: a cross national assessment of residential burglary victimization. J Quant Criminol 23:201–219CrossRefGoogle Scholar
  34. Johnson SD, Summers L, Pease K (2009) Offender as forager? A direct test of the boost account of victimization. J Quant Crim 25:181–200CrossRefGoogle Scholar
  35. Kalyvas SN (2006) The logic of violence in civil war. Cambridge University Press, CambridgeGoogle Scholar
  36. Kalyvas SN (2008) Promises and pitfalls of an emerging research program: The microdynamics of civil war. In: Kalyvas SN, Shapiro I, Masoud T (eds) Order, conflict, and violence. Cambridge University Press, New York, pp 397–421CrossRefGoogle Scholar
  37. Kennedy LW, Caplan JM, Piza E (forthcoming) Risk clusters, hotspots, and spatial intelligence: risk terrain modeling as an algorithm for police resource allocation strategies. J Quant Crim. doi:10.1007/s10940-010-9126-2
  38. Knox G (1964) Epidemiology of childhood leukemia in Northumberland and Durham. Br J Prev Soc Med 18:17–24Google Scholar
  39. Krueger AB, Laitin DD (2008) Kto kogo? A cross-country study of the origins and targets of terrorism. In: Keefer P, Loayza N (eds) Terrorism, economic development, and political openness. Cambridge University Press, New York, pp 148–173CrossRefGoogle Scholar
  40. Kydd AH, Walter BF (2006) The strategies of terrorism. Int Secur 31:49–80CrossRefGoogle Scholar
  41. LaFree G (forthcoming) Generating terrorism event databases: results from the Global Terrorism Database, 1970 to 2008. In: Lum C, Kennedy L (eds) Evidence-based counter terrorism. Springer, New YorkGoogle Scholar
  42. LaFree G, Dugan L (2007) Introducing the global terrorism database. Polit Viol Terror 19:181–204CrossRefGoogle Scholar
  43. LaFree G, Dugan L (2009) Research on terrorism and countering terrorism. In: Tonry M (ed) Crime and justice: a review of research, vol 38. University of Chicago Press, Chicago, pp 413–477Google Scholar
  44. LaFree G, Dugan L (forthcoming) Trends in global terrorism, 1970–2008. In: Hewitt JJ, Wilkenfeld J, Gurr TR (eds) Peace and conflict: 2012. Paradigm Publishers, BoulderGoogle Scholar
  45. LaFree G, Dugan L, Korte R (2009) The impact of British counterterrorist strategies on political violence in Northern Ireland: comparing deterrence and backlash models. Criminology 47:17–45CrossRefGoogle Scholar
  46. LaFree G, Dugan L, Xie M, Singh P (2011) Spatial and temporal patterns of terrorist attacks by ETA 1970 to 2007. J Quant Criminol. doi:10.1007/s10940-011-9133-y.
  47. Li Q (2005) Does democracy promote or reduce transnational terrorist incidents? J Conf Resol 49:278–297CrossRefGoogle Scholar
  48. Lohman AD, Flint C (2010) The geography of insurgency. Geog Compass 4:1154–1166CrossRefGoogle Scholar
  49. Lyall J (2009) Does indiscriminate violence incite insurgent attacks? Evidence from Chechnya. J Conf Resol 53:331–362CrossRefGoogle Scholar
  50. Madsen RE, Kauchak D, Elkan C (2005) Modeling word burstiness using the Dirichlet distribution. In: Proceedings of the 22nd international conference on machine learningGoogle Scholar
  51. McClintock C (1998) Revolutionary movements in Latin America. US Institute of Peace Press, Washington, DCGoogle Scholar
  52. Murshed M, Gates S (2005) Spatial-horizontal inequality and the Maoist insurgency in Nepal. Rev Dev Econ 9:121–134CrossRefGoogle Scholar
  53. Nagin DS, Land KC (1993) Age, criminal careers, and population heterogeneity: specification and estimation of a nonparametic, mixed Poisson model. Criminology 31:327–362CrossRefGoogle Scholar
  54. North BV, Curtis D, Sham PC (2002) A note on the calculation of empirical p values from Monte Carlo procedures. Am J Hum Gen 71:439–441CrossRefGoogle Scholar
  55. Pape RA (2003) The strategic logic of suicide terrorism. Am Pol Sci Rev 97:1–19CrossRefGoogle Scholar
  56. Pape RA (2005) Dying to win. Random House, New YorkGoogle Scholar
  57. Paternoster R, Brame R, Mazerolle P, Piquero A (1998) Using the correct statistical test for the equality of regression coefficients. Criminology 36:859–866CrossRefGoogle Scholar
  58. Pease K (1998) Repeat victimization: taking stock. Crime detection and prevention series, paper 90. Home Office, LondonGoogle Scholar
  59. Polvi N, Looman T, Humphries C, Pease K (1991) The time course of repeat burglary victimization. Br J Criminol 31:411–414Google Scholar
  60. Quetelet A (1984) Research on the propensity for crime at different ages (first edition 1831; translated by Sylvester, S). Anderson, CincinnatiGoogle Scholar
  61. Rapoport DC (1971) Assassination and terrorism. CBC Merchandising, TorontoGoogle Scholar
  62. Ratcliffe JH (2004) Geocoding crime and a first estimate of a minimum acceptable hit rate. Int J Geogl Info Sci 18:61–72CrossRefGoogle Scholar
  63. Ratcliffe JH, Rengert GF (2008) Near-repeat patterns in Philadelphia shootings. Secur J 21:58–76CrossRefGoogle Scholar
  64. Reinares F (2004) Who are the terrorists? Analyzing changes in sociological profile among members of ETA. Stud Conf Terror 27:465–488CrossRefGoogle Scholar
  65. Sanchez-Cuenca I (2009) The persistence of nationalist terrorism: the case of ETA. In: Mulaj K (ed) Violent non-state actors in contemporary world politics. Columbia University Press, New YorkGoogle Scholar
  66. Sandler T, Arce MDG (2003) Terrorism and game theory. Sim Gaming 34:319–337CrossRefGoogle Scholar
  67. Savitch HV (2007) Cities in a time of terror: space, territory and local resilience. ME Sharpe, ArmonkGoogle Scholar
  68. Shaw CR (1929) Delinquency areas. Univ. of Chicago Press, OxfordGoogle Scholar
  69. Shellman SM (2008) Coding disaggregated intrastate conflict: machine processing the behavior of substate actors over time and space. Polit Anal 16:464–477CrossRefGoogle Scholar
  70. Sherman L (1995) Hot spots of crime and criminal career of places. In: Eck JE, Weisburd DM (eds) Crime and place: crime prevention studies, vol 4. Police Executive Research Forum, Washington, DC, pp 35–52Google Scholar
  71. Sherman L, Weisburd D (1995) General deterrent effects of police patrol in crime ‘hot spots’: a randomized, controlled trial. Just Q 12:625–648CrossRefGoogle Scholar
  72. Sherman L, Gartin P, Buerger M (1989) Hot spots of predatory crime: routine activities and the criminology of place. Criminology 27:27–55CrossRefGoogle Scholar
  73. Short MB, D’Orsogna MR, Brantingham J, Tita GE (2009) Measuring and modeling repeat and near-repeat burglary effects. J Quant Criminol 25:325–339CrossRefGoogle Scholar
  74. Siebeneck LK, Medina RM, Yamada I, Hepner GF (2009) Spatial and temporal analyses of terrorist incidents in Iraq, 2004–2006. Stud Conf Terror 32:591–610CrossRefGoogle Scholar
  75. Siqueira K, Sandler T (2007) Terrorism backlash, terrorism mitigation, and policy delegation. J Pub Econ 91:1800–1815CrossRefGoogle Scholar
  76. Smith PD, Rose TA (2006) Blast wave propagation in city streets—an overview. Prog Struct Eng Ma 8:16–28CrossRefGoogle Scholar
  77. Smith BL, Cothren J, Roberts P, Damphousse KR (2008) Geospatial analysis of terrorist activities. National Institute of Justice Final Report. Department of Justice, Washington, DCGoogle Scholar
  78. Suttles GD (1972) The social construction of communities. University of Chicago Press, ChicagoGoogle Scholar
  79. Townsley M (2007) Near repeat burglary chains: describing the physical and network properties of a network of close burglary pairs. Presented at the Crime Hot Spots: behavioral, computation, and mathematical models symposium, 01/31/2007Google Scholar
  80. Townsley M, Johnson SD, Ratcliffe JH (2008) Space-time dynamics of insurgent activity in Iraq. Security J 21:139–146CrossRefGoogle Scholar
  81. Vasquez A (2005) Exact results for the Barabási Model of human dynamics. Phys Rev Lett 95:248701Google Scholar
  82. Vasquez A, Oliveira JG, Deszo Z, Goh KI, Kondor I, Barabasi AL (2006) Modeling bursts and heavy tails in human dynamics. Phys Rev E 73:036127CrossRefGoogle Scholar
  83. Wilkinson P (1986) Terrorism and the liberal state, 2nd edn. New York University Press, New YorkGoogle Scholar
  84. Williams R (2009) Using heterogeneous choice models to compare logit and probit coefficients across groups. Soc Meth Res 37:531–559CrossRefGoogle Scholar
  85. Wilson MA, Scholes A, Brocklehurst E (2010) A behavioural analysis of terrorist action: the assassination and bombing campaigns of ETA between 1980 and 2007. Brit J Crim 50:690–707CrossRefGoogle Scholar
  86. Wood EJ (2003) Rebel collective action and civil war in El Salvador. Cambridge University Press, New YorkGoogle Scholar
  87. Yang SM (2010) Assessing the spatio-temporal relationship between disorder and violence. J Quant Crim 26:139–163CrossRefGoogle Scholar
  88. Zhu JF, Han XP, Wang BH (2010) Statistical property and model for the inter-event time of terrorism attacks. Chin Phys Lett 27:068902CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Brandon Behlendorf
    • 1
  • Gary LaFree
    • 1
  • Richard Legault
    • 1
  1. 1.University of MarylandCollege ParkUSA

Personalised recommendations