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Spatial and Temporal Patterns of Terrorist Attacks by ETA 1970 to 2007

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Abstract

Rational choice perspectives maintain that seemingly irrational behavior on the part of terrorist organizations may nevertheless reflect strategic planning. In this paper we examine spatial and temporal patterns of terrorist attacks by the Spanish group ETA between 1970 and 2007. Our analysis is guided by a public announcement by ETA in 1978 that the group would shift from emphasizing attacks in the Basque territory to instead launch attacks more widely in the hopes of exhausting the Spanish government and forcing it to abandon the Basque territory. This announcement suggests that prior to the end of 1978 ETA attacks were based mostly on controlling territory in the Basque region that they hoped to rule; and after 1978 the organization decided to instead undertake a prolonged war of attrition. Accordingly, we argue that before the end of 1978 ETA was mostly perpetrating control attacks (attacking only within the Basque territories) and that the diffusion of attacks between provinces was mostly contagious (spreading contiguously). After the 1978 proclamation, we argue that the attack strategy shifted toward attrition (attacking in areas outside of the Basque territories) and that the attacks were more likely to diffuse hierarchically (spreading to more distant locations). As predicted, we find that after ETA moved toward a more attrition based attack strategy, subsequent attacks were significantly more likely to occur outside the Basque region and to target non-adjacent regions (consistent with hierarchical diffusion). We also find that hierarchical diffusion was more common when a longer time elapsed between attacks (a likely consequence of the fact that more distant attacks require more resources and planning) and that attacks against Madrid were unlikely to be followed immediately by more attacks on Madrid or surrounding provinces. After ETA announced a shift in policy, they maintained a highly dispersed attack strategy even during their period of decline. Using information about where and when prior attacks occurred could provide useful information for policy makers countering groups like ETA.

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Notes

  1. 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.

  2. The current analyses are based on GTD data downloaded on May 1, 2009.

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

  4. 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. Most of the attacks and fatalities attributed to ETA in our data base were actually carried out by ETAm.

  5. 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; 7.0%); Terra Lliure (or TL; 61 attacks; 2.0%); and the Revolutionary Anti-Fascist Patriotic Front (or FRAP; 47 attacks; 1.6%).

  6. The proportion of attributed terrorist attacks in Spain from the GTD is relatively high compared to the data base as a whole. Of the 3,235 attacks in the GTD from 1970 to 2007, no terrorist group is attributed in only 594 (18.4%) of the cases.

  7. The match rate exceeds the minimum threshold of 85% suggested by Ratcliffe (2004). We were unable to geocode the remaining attacks either because the GTD data did not include city-level information or because the city listed in the database was matched to multiple locations.

  8. In supplementary analysis, we also tested for structural changes in the time series of ETA attacks by using Andrews’ (1993) and Bai and Perron’s (1998, 2003) methods for identifying structural breaks in time series (data outputs available upon request). The analysis used quarterly counts of ETA attacks from 1970 to 2007. The goal of the analysis was to test the null hypothesis that the level of ETA attacks remained constant over the study period, and a rejection of the null hypothesis would indicate potential break points in the series. Before conducting the structural change test, diagnostic checks were conducted on the series for stationarity and autocorrelation. The analysis identified an autoregressive model with 4 lags and a constant term as the best fitting model for the series, in which the residuals were white noise. Thus, using this autoregressive model, we projected the break points with the R package strucchange function breakpoints using the standard trimming value of 15% at each end of the series (Zeileis et al. 2002). Based on this analysis, we detected only one break in the third quarter of 1979, which is consistent with the fact that this is the high point of ETA attacks over the nearly four decades spanned by the data (for similar methods, see McDowall and Loftin 2005). We note in passing that a break point in the series based purely on a statistical test closely resembles the break point we expected, based on ETA’s stated policy shift.

  9. This table is adapted from tables A1 and A2 in Cohen and Tita (1999).

  10. There were a total of 416 transitions in period 1 of which 388 transitions were stationary. The 416 transitions are based on a total of 52 provinces (47 in Spain and 5 in France) where each province has 8 year-to-year transitions (1970–1971, 1971–1972, so on). In each year, for each province, we calculated a LISA statistic. Then, we compare the LISA statistic in year t to the LISA statistic in year t + 1 and classify the change as either stationary or change using the rules specified in Table 1. Using this information, we counted the number of provinces that had zero attacks in each year and its transition was classified as stationary. This results in a total of 373 transitions. So the percentage reported in the text is 373/388 = 96.1%. We used the same procedure for period 2 and found that out of the 1,230 stationary transitions, there were 1,039 transitions involving a count of 0 attacks in a given year. So the percentage is 1,039/1,230 = 84.5%.

  11. We determined statistical significance by first using binomial distributions—B (n, 0.5)—to calculate the exact probabilities of obtaining the observed sample. For example, in period 1, there were 12 decreases: 7 from adjacent units and 5 from non-adjacent units. Thus, using B (12, 0.5) and assuming that the probability of decrease from adjacent units is equal to the probability of decrease from non-adjacent units, we get p = 0.16 (decreases from adjacent units = 7)—which is within the range of chance variation. To verify our conclusions, we also used significance tests for a single proportion. The null hypothesis is H0: p = 0.5. The z statistics are calculated as \( Z = {\frac{{\hat{p} - 0.5}}{{\sqrt {{\raise0.7ex\hbox{${\left( {0.5 \times 0.5} \right)}$} \!\mathord{\left/ {\vphantom {{\left( {0.5 \times 0.5} \right)} n}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{$n$}}} }}} \). This method produced the same results as the first method and all of the statistically significant cells have a Z-value larger than 1.96.

  12. Of the 16 increases in attacks originating in period 1, 4 adjacent increases and 0 non-adjacent increases can be attributed to one of the provinces in the BAC (4/15 = 25%). For the 86 increases in attacks in period 2, 4 adjacent increases and 0 non-adjacent increases can be attributed to the BAC (4/86 = 4.7%). Thus, in support of our arguments, increases in attacks in non-BAC provinces were more likely to occur in the second than in the first period.

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Acknowledgments

Support for this research was provided by the 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 want to thank David McDowall for his assistance with the analysis and Erin Miller and Brandon Behlendorf for database support.

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Authors and Affiliations

  1. University of Maryland, College Park, MD, USA

    Gary LaFree & Laura Dugan

  2. Arizona State University, Phoenix, AZ, USA

    Min Xie

  3. Excelsior College, Albany, NY, USA

    Piyusha Singh

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  1. Gary LaFree
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Correspondence to Gary LaFree.

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LaFree, G., Dugan, L., Xie, M. et al. Spatial and Temporal Patterns of Terrorist Attacks by ETA 1970 to 2007. J Quant Criminol 28, 7–29 (2012). https://doi.org/10.1007/s10940-011-9133-y

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