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Arrests and convictions but not sentence length deter terrorism in 28 European Union member states

Nature Human Behaviour volume 7, pages 1878–1889 (2023)Cite this article

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Abstract

While countries differ in how they handle terrorism, criminal justice systems in Europe and elsewhere treat terrorism similar to other crime, with police, prosecutors, judges, courts and penal systems carrying out similar functions of investigations, apprehension, charging, convicting and overseeing punishments, respectively. We address a dearth of research on potential deterrent effects against terrorism by analysing data on terrorism offending, arrests, charges, convictions and sentencing over 16 years in 28 European Union member states. Applying both count and dynamic panel data models across multiple specifications, we find that increased probability of apprehension and punishment demonstrate an inverse relationship with terrorism offending, while the rate of charged individuals is associated with a small increase in terrorism. The results for sentence length are less clear but also indicate potential backlash effects. These findings unveil overlaps between crime and terrorism in terms of deterrent effects and have implications for both the research agenda and policy discussion.

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Fig. 1: Raw number of incidents per country (2007–2021).
Fig. 2: IHS-transformed variables.
Fig. 3: Heat map of the total number of incidents reported (2007–2021).
Fig. 4: Effects of deterrence variables on terrorism incident rates.

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Data availability

The datasets generated and/or analysed during the current study are available at https://doi.org/10.5281/zenodo.8196717.

Code availability

The syntax used to produce the analysis during the current study is available at https://doi.org/10.5281/zenodo.8196717.

References

  1. LaFree, G., Weerman, F. & Bijleveld, C. Editor’s introduction: terrorism and violent extremism. J. Quant. Criminol. 36, 399–405 (2020).

    Article  Google Scholar 

  2. Sageman, M. The stagnation in terrorism research. Terror. Polit. Violence 26, 565–580 (2014).

    Article  Google Scholar 

  3. Wolfowicz, M., Litmanovitz, Y., Weisburd, D. & Hasisi, B. Cognitive and behavioral radicalization: a systematic review of the putative risk and protective factors. Campbell Syst. Rev. 17, e1174 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  4. 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).

    Article  Google Scholar 

  5. Hasisi, B., Perry, S., Ilan, Y. & Wolfowicz, M. Concentrated and close to home: the spatial clustering and distance decay of lone terrorist vehicular attacks. J. Quant. Criminol. 36, 607–645 (2020).

    Article  Google Scholar 

  6. Perry, S. The application of the ‘law of crime concentration’ to terrorism: the Jerusalem case study. J. Quant. Criminol. 36, 583–605 (2020).

    Article  Google Scholar 

  7. Marchment, Z., Gill, P. & Morrison, J. Risk factors for violent dissident republican incidents in Belfast: a comparison of bombings and bomb hoaxes. J. Quant. Criminol. 36, 647–666 (2020).

    Article  Google Scholar 

  8. Hasisi, B., Carmel, T., Weisburd, D. & Wolfowicz, M. Crime and terror: examining criminal risk factors for terrorist recidivism. J. Quant. Criminol. 36, 449–472 (2020).

    Article  Google Scholar 

  9. Marchment, Z. & Gill, P. Spatial decision making of terrorist target selection: introducing the TRACK framework. Stud. Confl. Terror. 45, 862–880 (2022).

    Article  Google Scholar 

  10. Johnson, N. F. et al. Simple mathematical law benchmarks human confrontations. Sci. Rep. 3, 1–6 (2013).

    Article  Google Scholar 

  11. LaFree, G., Dugan, L. & Korte, R. The impact of British counterterrorist strategies on political violence in Northern Ireland: comparing deterrence and backlash models. Criminology 47, 17–45 (2009).

    Article  Google Scholar 

  12. Perry, S. & Hasisi, B. Rational choice rewards and the jihadist suicide bomber. Terror. Polit. Violence 27, 53–80 (2015).

    Article  Google Scholar 

  13. Clarke, R. V. & Newman, G. R. Outsmarting the Terrorists (Praeger Security International, 2006).

  14. Dugan, L., LaFree, G. & Piquero, A. R. Testing a rational choice model of airline hijackings. Criminology 43, 1031–1065 (2005).

    Article  Google Scholar 

  15. Freilich, J. D., Gruenewald, J. & Mandala, M. Situational crime prevention and terrorism: an assessment of 10 years of research. Crim. Justice Policy Rev. 30, 1283–1311 (2019).

    Article  Google Scholar 

  16. Newman, G. R. & Hsu, H. Y. in Countering Terrorism: Psychosocial Strategies (eds Kumar, U. & Mandal, M. K.) 227–249 (Sage, 2012).

  17. Morris, N. A. & LaFree, G. in The Handbook of the Criminology of Terrorism (eds LaFree, G. & Freilich, J. D.) 93–117 (John Wiley & Sons, 2016).

  18. Gassebner, M. & Luechinger, S. Lock, stock, and barrel: a comprehensive assessment of the determinants of terror. Public Choice 149, 235–261 (2011).

    Article  Google Scholar 

  19. LaFree, G. & Schwarzenbach, A. Micro and macro-level risk factors for extremism and terrorism: toward a criminology of extremist violence. Monatsschr. Kriminol. 104, 184–202 (2021).

    Google Scholar 

  20. Hasisi, B., Perry, S. & Wolfowicz, M. in Oxford Research Encyclopedia of Criminology and Criminal Justice (eds Erez, E. & Ibarra, P.) (Oxford Univ. Press, 2020).

  21. Onat, I. & San, S. in From Territorial Defeat to Global ISIS: Lessons Learned (eds Goldstone, J. A. et al.) 178–192 (IOS, 2021).

  22. Lynch, J. P. in Criminologists on Terrorism and Homeland Security (eds Forst, B., Greene, J. R. & Lynch, J. P.) 151–182 (Cambridge Univ. Press, 2011).

  23. Becker, G. Crime and punishment: an economic approach. J. Polit. Econ. 75, 169–217 (1968).

    Article  Google Scholar 

  24. Ehrlich, I. Deterrence: evidence and inference. Yale Law J. 85, 209–227 (1975).

  25. Apel, R. & Nagin, D. S. in Crime and Public Policy (eds Wilson, J. Q. & Petersilia, J.) 411–436 (Oxford Univ. Press, 2011).

  26. Durlauf, S. N. & Nagin, D. S. Imprisonment and crime: can both be reduced? Criminol. Public Policy 10, 13–54 (2011).

    Article  Google Scholar 

  27. Nagin, D. S. Deterrence: a review of the evidence by a criminologist for economists. Annu. Rev. Econ. 5, 83–105 (2013).

    Article  Google Scholar 

  28. Nagin, D. S. Deterrence in the twenty-first century. Crime Justice 42, 199–263 (2013).

    Article  Google Scholar 

  29. Pratt, T. C., Cullen, F. T., Blevins, K. R., Daigle, L. E. & Madensen, T. D. in Taking Stock (eds Cullen, F. T., Wright, J. P. & Blevins, K. R.) 367–395 (Routledge, 2017).

  30. Harding, D. J., Morenoff, J. D., Nguyen, A. P., Bushway, S. D. & Binswanger, I. A. A natural experiment study of the effects of imprisonment on violence in the community. Nat. Hum. Behav. 3, 671–677 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Mendes, S. M. & McDonald, M. D. Putting severity of punishment back in the deterrence package. Policy Stud. J. 29, 588–610 (2001).

    Article  Google Scholar 

  32. Bun, M. J., Kelaher, R., Sarafidis, V. & Weatherburn, D. Crime, deterrence and punishment revisited. Empir. Econ. 59, 2303–2333 (2020).

    Article  Google Scholar 

  33. Andenaes, J. General prevention revisited: research and policy implications. J. Crim. Law Criminol. 66, 338–365 (1975).

  34. Cook, P. J. & Khmilevska, N. Cross-national patterns in crime rates. Crime Justice 33, 331–345 (2005).

    Article  Google Scholar 

  35. Pare, P. P. Indicators of police performance and their relationships with homicide rates across 77 nations. Int. Crim. Justice Rev. 24, 254–270 (2014).

    Article  Google Scholar 

  36. Nivette, A. E. Cross-national predictors of crime: a meta-analysis. Homicide Stud. 15, 103–131 (2011).

    Article  Google Scholar 

  37. Mourtgos, S. M. & Adams, I. T. The effect of prosecutorial actions on deterrence: a county-level analysis. Crim. Justice Policy Rev. 31, 479–499 (2020).

    Article  Google Scholar 

  38. Germani, A. R., Pergolizzi, A. & Reganati, F. Illegal trafficking and unsustainable waste management in Italy: evidence at the regional level. J. Secur. Sustain. Issues 4, 369–389 (2015).

    Google Scholar 

  39. Charles, K. K. & Durlauf, S. N. Pitfalls in the use of time series methods to study deterrence and capital punishment. J. Quant. Criminol. 29, 45–66 (2013).

    Article  Google Scholar 

  40. Mullins, S. Parallels between crime and terrorism: a social psychological perspective. Stud. Confl. Terror. 32, 811–830 (2009).

    Article  Google Scholar 

  41. Mullins, S. & Wither, J. K. Terrorism and organized crime. Connections 15, 65–82 (2016).

    Article  Google Scholar 

  42. Zubrzycki, W. Similarities and differences between organized crime and terrorism. Intern. Secur. 7, 53–70 (2015).

  43. LaFree, G. & Dugan, L. How does studying terrorism compare to studying crime. Terror. Counter-terror. Criminol. Perspect. 5, 53–74 (2004).

    Article  Google Scholar 

  44. Miller, G. D. Terrorist decision making and the deterrence problem. Stud. Confl. Terror. 36, 132–151 (2013).

    Article  Google Scholar 

  45. Ekelund, R. B. Jr, Jackson, J. D., Ressler, R. W. & Tollison, R. D. Marginal deterrence and multiple murders. South. Econ. J. 72, 521–541 (2006).

    Google Scholar 

  46. Carson, J. V., Dugan, L. & Yang, S. M. A comprehensive application of rational choice theory: how costs imposed by, and benefits derived from, the US federal government affect incidents perpetrated by the radical eco-movement. J. Quant. Criminol. 36, 701–724 (2020).

    Article  Google Scholar 

  47. Gill, P., Marchment, Z., Corner, E. & Bouhana, N. Terrorist decision-making in the context of risk, attack planning and attack commission. Stud. Confl. Terror. 43, 145–170 (2020).

    Article  Google Scholar 

  48. Perry, S., Apel, R., Newman, G. R. & Clarke, R. V. The situational prevention of terrorism: an evaluation of the Israeli West Bank barrier. J. Quant. Criminol. 33, 727–751 (2017).

    Article  Google Scholar 

  49. Freilich, J. D. & LaFree, G. Criminology theory and terrorism: introduction to the special issue. Terror. Polit. Violence 27, 1–8 (2015).

    Article  Google Scholar 

  50. Baez, S. et al. Outcome-oriented moral evaluation in terrorists. Nat. Hum. Behav. 1, 1–9 (2017).

    Google Scholar 

  51. Nivette, A. E. et al. A global analysis of the impact of COVID-19 stay-at-home restrictions on crime. Nat. Hum. Behav. 5, 868–877 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Ackerman, G. & Peterson, H. Terrorism and COVID-19. Perspect. Terror. 14, 59–73 (2020).

    Google Scholar 

  53. Basit, A. COVID-19: a challenge or opportunity for terrorist groups? J. Policing Intell. Count. Terror. 15, 263–275 (2020).

    Article  Google Scholar 

  54. Marone, F. Hate in the time of coronavirus: exploring the impact of the COVID-19 pandemic on violent extremism and terrorism in the West. Secur. J. 35, 205–225 (2022).

    Article  Google Scholar 

  55. Argomaniz, J. & Vidal-Diez, A. Examining deterrence and backlash effects in counter-terrorism: the case of ETA. Terror. Polit. Violence 27, 160–181 (2015).

    Article  Google Scholar 

  56. Hsu, H. Y. & McDowall, D. Examining the state repression–terrorism nexus: dynamic relationships among repressive counterterrorism actions, terrorist targets, and deadly terrorist violence in Israel. Criminol. Public Policy 19, 483–514 (2020).

    Article  Google Scholar 

  57. Safer-Lichtenstein, A. An explicit consideration of unintended consequences from counterterrorism policy: the case of radical eco-groups. Stud. Confl. Terror. 42, 407–428 (2019).

    Article  Google Scholar 

  58. Le Vine, V. T. & Salert, B. A. Does a coercive official response deter terrorism? The case of the PLO. Terror. Polit. Violence 8, 22–49 (1996).

    Article  Google Scholar 

  59. Kaplan, E. H., Mintz, A. & Mishal, S. Tactical prevention of suicide bombings in Israel. Interfaces 36, 553–561 (2006).

    Article  Google Scholar 

  60. Hussain, S. E. Terrorism in Pakistan: Incident Patterns, Terrorists’ Characteristics, and the Impact of Terrorist Arrests on Terrorism (Univ. of Pennsylvania, 2010).

  61. Freilich, J. D., Bejan, V., Parkin, W. S., Chermak, S. M. & Gruenewald, J. An intervention analysis of fatal far-right extremist violence within a vector-autoregressive framework. Dyn. Asymmetric Confl. 13, 143–171 (2020).

    Article  Google Scholar 

  62. Hafez, M. M. Suicide Bombers in Iraq: The Strategy and Ideology of Martyrdom (US Institute of Peace Press, 2007).

  63. Fisher, U. Deterrence, terrorism, and American values. Homel. Secur. Aff. 3, 1–16 (2007).

  64. Gómez, A. et al. Willingness to sacrifice among convicted Islamist terrorists versus violent gang members and other criminals. Sci. Rep. 12, 1–15 (2022).

    Article  Google Scholar 

  65. Gill, P., Horgan, J., Corner, E. & Silver, J. Indicators of lone actor violent events: the problems of low base rates and long observational periods. J. Threat Assess. Manage. 3, 165–173 (2016).

  66. Sageman, M. The implication of terrorism’s extremely low base rate. Terror. Polit. Violence 33, 302–311 (2021).

    Article  Google Scholar 

  67. Lum, C., Kennedy, L. W. & Sherley, A. Is counter-terrorism policy evidence-based? What works, what harms, and what is unknown. Psicothema 20, 35–42 (2008).

    PubMed  Google Scholar 

  68. Allan, G., Burton, M. & Pratt, A. Terrorism in Great Britain: The Statistics (House of Commons Library, 2022).

  69. Brooks, R. A. Muslim ‘homegrown’ terrorism in the United States: how serious is the threat? Int. Secur. 36, 7–47 (2011).

    Article  Google Scholar 

  70. Addison, M. in Violent Politics (ed. Addison, M.) 132–144 (Palgrave Macmillan, 2002).

  71. Shields, C. A., Smith, B. L. & Damphousse, K. R. in The Handbook of the Criminology of Terrorism (eds LaFree, G. & Freilich, J. D.) 495–507 (John Wiley & Sons, 2016).

  72. Jetter, M. & Stadelmann, D. Terror per capita. South. Econ. J. 86, 286–304 (2019).

    Article  Google Scholar 

  73. European Union Terrorism Situation and Trend Report (TE-SAT) 2007 (Europol, 2007); https://www.europol.europa.eu/cms/sites/default/files/documents/tesat2007_1.pdf

  74. European Union Terrorism Situation and Trend Report (TE-SAT) 2008 (Europol, 2008); https://www.europol.europa.eu/cms/sites/default/files/documents/tesat2008_1.pdf

  75. European Union Terrorism Situation and Trend Report (TE-SAT) 2009 (Europol, 2009); https://www.europol.europa.eu/cms/sites/default/files/documents/tesat2009_1.pdf

  76. European Union Terrorism Situation and Trend Report (TE-SAT) 2010 (Europol, 2010); https://www.europol.europa.eu/cms/sites/default/files/documents/tesat2010_1.pdf

  77. European Union Terrorism Situation and Trend Report (TE-SAT) 2011 (Europol, 2011); https://www.europol.europa.eu/cms/sites/default/files/documents/te-sat2011_0.pdf

  78. European Union Terrorism Situation and Trend Report (TE-SAT) 2012 (Europol, 2012); https://www.europol.europa.eu/cms/sites/default/files/documents/te-sat2012_0.pdf

  79. European Union Terrorism Situation and Trend Report (TE-SAT) 2013 (Europol, 2013); https://www.europol.europa.eu/cms/sites/default/files/documents/europol_te-sat2013_lr_0.pdf

  80. European Union Terrorism Situation and Trend Report (TE-SAT) 2014 (Europol, 2014); https://www.europol.europa.eu/cms/sites/default/files/documents/europol_tsat14_web_1%20%281%29.pdf

  81. European Union Terrorism Situation and Trend Report (TE-SAT) 2015 (Europol, 2015); https://www.europol.europa.eu/cms/sites/default/files/documents/p_europol_tsat15_09jun15_low-rev.pdf

  82. European Union Terrorism Situation and Trend Report (TE-SAT) 2016 (Europol, 2016); https://www.europol.europa.eu/cms/sites/default/files/documents/europol_tesat_2016.pdf

  83. European Union Terrorism Situation and Trend Report (TE-SAT) 2017 (Europol, 2017); https://www.europol.europa.eu/tesat/2017/

  84. European Union Terrorism Situation and Trend Report (TE-SAT) 2018 (Europol, 2018); https://www.europol.europa.eu/cms/sites/default/files/documents/tesat_2018_1.pdf

  85. European Union Terrorism Situation and Trend Report (TE-SAT) 2019 (Europol, 2019); https://www.europol.europa.eu/cms/sites/default/files/documents/tesat_2019_final.pdf

  86. European Union Terrorism Situation and Trend Report (TE-SAT) 2020 (Europol, 2020); https://www.europol.europa.eu/cms/sites/default/files/documents/european_union_terrorism_situation_and_trend_report_te-sat_2020_0.pdf

  87. European Union Terrorism Situation and Trend Report (TE-SAT) 2021 (Europol, 2021); https://www.europol.europa.eu/cms/sites/default/files/documents/tesat_2021_0.pdf

  88. European Union Terrorism Situation and Trend Report (TE-SAT) 2022 (Europol, 2022); https://www.europol.europa.eu/cms/sites/default/files/documents/Tesat_Report_2022_0.pdf

  89. Hegghammer, T. & Ketchley, N. Plots, attacks, and the measurement of terrorism. Preprint at SocArXiv https://osf.io/preprints/socarxiv/t72yj/ (2021).

  90. Hegghammer, T. & Nesser, P. Assessing the Islamic State’s commitment to attacking the West. Perspect. Terror. 9, 14–30 (2015).

    Google Scholar 

  91. START Global Terrorism Database Codebook: Methodology, Inclusion Criteria, and Variables (Univ. of Maryland, 2021).

  92. McCann, W. S. Who said we were terrorists? Issues with terrorism data and inclusion criteria. Stud. Confl. Terror. 46, 964–984 (2023).

  93. Campedelli, G. M., Bartulovic, M. & Carley, K. M. Learning future terrorist targets through temporal meta-graphs. Sci. Rep. 11, 8533 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Global Terrorism Index 2022: Measuring the Impact of Terrorism (Institute for Economics and Peace, 2022).

  95. World Development Indicators (2022): Population Total (World Bank, 2022); https://databank.worldbank.org/indicator/SP.POP.TOTL/1ff4a498/Popular-Indicators#

  96. Dynamic Database of European Judicial Systems (2022): European Judicial Systems (European Commission for the Efficiency of Justice, 2022); https://public.tableau.com/app/profile/cepej/viz/QuantitativeDataEN/Tables?publish=yes

  97. Human Development Index (HDI) (United Nations Development Programme, 2022); https://hdr.undp.org/data-center/human-development-index#/indicies/HDI

  98. Park, S. Cutbacks revisited: the relationship between resources and performance. Public Manage. Rev. 21, 515–536 (2019).

    Article  Google Scholar 

  99. Pratt, T. C. & Cullen, F. T. Assessing macro-level predictors and theories of crime: a meta-analysis. Crime Justice 32, 373–450 (2005).

    Article  Google Scholar 

  100. Government Finance Statistics (GFS) (International Monetary Fund, 2022); https://data.imf.org/?sk=a0867067-d23c-4ebc-ad23-d3b015045405

  101. Sah, R. K. Social osmosis and patterns of crime. J. Polit. Econ. 99, 1272–1295 (1991).

    Article  Google Scholar 

  102. Glaeser, E. L., Sacerdote, B. & Scheinkman, J. A. Crime and social interactions. Q. J. Econ. 111, 507–548 (1996).

    Article  Google Scholar 

  103. Chamlin, M. B. Crime and arrests: an autoregressive integrated moving average (ARIMA) approach. J. Quant. Criminol. 4, 247–258 (1988).

    Article  Google Scholar 

  104. Duru, H., Onat, I., Akyuz, K. & Akbas, H. Microcycles of terrorist violence in Turkey: a spatio-temporal analysis of the PKK attacks. Asian J. Criminol. 16, 235–256 (2021).

    Article  Google Scholar 

  105. Decker, S. H. & Kohfeld, C. W. Crimes, crime rates, arrests, and arrest ratios: implications for deterrence theory. Criminology 23, 437–450 (1985).

    Article  Google Scholar 

  106. Dills, A. K., Miron, J. A. & Summers, G. in The Economics of Crime: Lessons for and from Latin America (eds Di Tella, R., Edwards, S. & Schargrodsky, E.) 269–302 (Univ. of Chicago Press, 2010).

  107. Kellett, A. et al. Terrorism in Canada 1960–1989 (Public Safety Canada, 1991); https://www.publicsafety.gc.ca/lbrr/archives/hv%206433.c2%20t4%201990-eng.pdf

  108. Cubukcu, S. ‘The Dark Figure’ of Terrorism: Understanding the Reporting and Non-reporting of Terrorist Events (American Univ., 2016).

  109. Cubukcu, S. & Forst, B. Measuring terrorism. Homicide Stud. 22, 94–116 (2018).

    Article  Google Scholar 

  110. Zimring, F. E. & Hawkins, G. What kind of drug war? Soc. Justice 18, 104–121 (1991).

    Google Scholar 

  111. Young, W. & Brown, M. Cross-national comparisons of imprisonment. Crime Justice 17, 1–49 (1993).

    Article  Google Scholar 

  112. Tonry, M. & Farrington, D. P. Punishment and crime across space and time. Crime Justice 33, 1–39 (2005).

    Article  Google Scholar 

  113. Arellano, M. & Bond, S. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58, 277–297 (1991).

    Article  Google Scholar 

  114. Bun, M. J. Identifying the impact of deterrence on crime: internal versus external instruments. Appl. Econ. Lett. 22, 204–208 (2015).

    Article  Google Scholar 

  115. Wan, W. Y., Moffatt, S., Jones, C. & Weatherburn, D. The effect of arrest and imprisonment on crime. Crime Justice Bull. 158, 1–20 (2012).

  116. Fajnzylber, P., Lederman, D. & Loayza, N. What causes violent crime? Eur. Econ. Rev. 46, 1323–1357 (2002).

    Article  Google Scholar 

  117. Neumayer, E. Good policy can lower violent crime: evidence from a cross-national panel of homicide rates, 1980–97. J. Peace Res. 40, 619–640 (2003).

    Article  Google Scholar 

  118. LaFree, G. & Jiang, B. Does globalization reduce personal violence? The impact of international trade on cross-national homicide rates. Soc. Forces. 102, 353–376 (2023).

  119. Rivera, M. The sources of social violence in Latin America: an empirical analysis of homicide rates, 1980–2010. J. Peace Res. 53, 84–99 (2016).

    Article  Google Scholar 

  120. Rosenfeld, R. & Fornango, R. The relationship between crime and stop, question, and frisk rates in New York City neighborhoods. Justice Q. 34, 931–951 (2017).

    Article  Google Scholar 

  121. Burbidge, J. B., Magee, L. & Robb, A. L. Alternative transformations to handle extreme values of the dependent variable. J. Am. Stat. Assoc. 83, 123–127 (1988).

    Article  Google Scholar 

  122. MacKinnon, J. G. & Magee, L. Transforming the dependent variable in regression models. Int. Econ. Rev. 31, 315–339 (1990).

  123. Pence, K. M. The role of wealth transformations: an application to estimating the effect of tax incentives on saving. Contrib. Econ. Anal. Policy 5, 1–26 (2006).

  124. Hansen, L. P. Large sample properties of generalized method of moments estimators. Econometrica. 50, 1029–1054 (1982).

  125. Windmeijer, F. A finite sample correction for the variance of linear efficient two-step GMM estimators. J. Econ. 126, 25–51 (2005).

    Article  Google Scholar 

  126. Roodman, D. How to do xtabond2: an introduction to difference and system GMM in Stata. Stata J. 9, 86–136 (2009).

    Article  Google Scholar 

  127. Lai, B. ‘Draining the swamp’: an empirical examination of the production of international terrorism, 1968–1998. Confl. Manage. Peace Sci. 24, 297–310 (2007).

    Article  Google Scholar 

  128. Enders, W. & Sandler, T. Distribution of transnational terrorism among countries by income class and geography after 9/11. Int. Stud. Q. 50, 367–393 (2006).

    Article  Google Scholar 

  129. Mullins, C. W. & Young, J. K. Cultures of violence and acts of terror: applying a legitimation–habituation model to terrorism. Crime Delinq. 58, 28–56 (2012).

    Article  Google Scholar 

  130. Piazza, J. A. Types of minority discrimination and terrorism. Confl. Manage. Peace Sci. 29, 521–546 (2012).

    Article  Google Scholar 

  131. Drakos, K. & Gofas, A. In search of the average transnational terrorist attack venue. Def. Peace Econ. 17, 73–93 (2006).

    Article  Google Scholar 

  132. Young, J. K. & Dugan, L. Veto players and terror. J. Peace Res. 48, 19–33 (2011).

    Article  Google Scholar 

  133. Chiricos, T. G. & Waldo, G. P. Punishment and crime: an examination of some empirical evidence. Soc. Probl. 18, 200–217 (1970).

    Article  Google Scholar 

  134. Pogarsky, G. & Loughran, T. A. The policy-to-perceptions link in deterrence: time to retire the clearance rate. Criminol. Public Policy 15, 777–790 (2016).

  135. Tittle, C. R. Crime rates and legal sanctions. Soc. Probl. 16, 409–423 (1969).

    Article  Google Scholar 

  136. Levitt, S. D. The relationship between crime reporting and police: implications for the use of uniform crime reports. J. Quant. Criminol. 14, 61–81 (1998).

    Article  Google Scholar 

  137. Levitt, S. D. Why do increased arrest rates appear to reduce crime: deterrence, incapacitation, or measurement error? Econ. Inq. 36, 353–372 (1998).

    Article  Google Scholar 

  138. Logan, C. H., Bailey, W. C., Gray, L. N. & Martin, J. D. On punishment and crime (Chiricos and Waldo, 1970): some methodological commentary. Soc. Probl. 19, 280–289 (1971).

    Article  Google Scholar 

  139. Tittle, C. R. & Rowe, A. R. Certainty of arrest and crime rates: a further test of the deterrence hypothesis. Soc. Forces 52, 455–462 (1974).

    Article  Google Scholar 

  140. Gibbs, J. P. & Firebaugh, G. The artifact issue in deterrence research. Criminology 28, 347–367 (1990).

    Article  Google Scholar 

  141. Wooldridge, J. M. Econometrics: Panel Data Methods (Springer, 2009).

  142. Wooldridge, J. M. Quasi-maximum likelihood estimation and testing for nonlinear models with endogenous explanatory variables. J. Econ. 182, 226–234 (2014).

    Article  Google Scholar 

  143. Gourieroux, C., Monfort, A. & Trognon, A. Pseudo maximum likelihood methods: applications to Poisson models. Econometrica. 52, 701–720 (1984).

  144. Correia, S., Guimarães, P. & Zylkin, T. Fast Poisson estimation with high-dimensional fixed effects. Stata J. 20, 95–115 (2020).

    Article  Google Scholar 

  145. Silva, J. S. & Tenreyro, S. Further simulation evidence on the performance of the Poisson pseudo-maximum likelihood estimator. Econ. Lett. 112, 220–222 (2011).

    Article  Google Scholar 

  146. Allison, P. Do we really need zero-inflated models? Statistical Horizons http://statisticalhorizons.com/zero-inflated-models (2012).

  147. Fisher, W. H., Hartwell, S. W. & Deng, X. Managing inflation: on the use and potential misuse of zero-inflated count regression models. Crime Delinq. 63, 77–87 (2017).

    Article  Google Scholar 

  148. Du Bois, C. & Buts, C. Military support and transnational terrorism. Def. Peace Econ. 27, 626–643 (2016).

    Article  Google Scholar 

  149. Johnson, T. L., Johnson, N. N., Sabol, W. J. & Snively, D. T. Law enforcement agencies’ college education hiring requirements and racial differences in police-related fatalities. J. Police Crim. Psychol. 37, 681–698 (2022).

    Article  Google Scholar 

  150. Ajide, K. B. & Alimi, O. Y. Natural resource rents, inequality, and terrorism in Africa. Def. Peace Econ. 33, 712–730 (2022).

    Article  Google Scholar 

  151. Carter, D. B. & Ying, L. The gravity of transnational terrorism. J. Confl. Resolut. 65, 813–849 (2021).

    Article  Google Scholar 

  152. Worrall, J. L. & Pratt, T. C. On the consequences of ignoring unobserved heterogeneity when estimating macro-level models of crime. Soc. Sci. Res. 33, 79–105 (2004).

    Article  Google Scholar 

Download references

Acknowledgements

We received partial funding through a research contract from the Canadian Network for Research on Terrorism, Security, and Society and the Institute for Futures Studies, Sweden, provided to M.W. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Authors and Affiliations

  1. Institute of Criminology, Faculty of Law, Hebrew University of Jerusalem, Jerusalem, Israel

    Michael Wolfowicz

  2. Department of Security and Crime Science, University College London, London, UK

    Michael Wolfowicz, Amber Seaward & Paul Gill

  3. Department of Sociology and Social Research, University of Trento, Trento, Italy

    Gian Maria Campedelli

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  1. Michael Wolfowicz
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  4. Paul Gill
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Contributions

M.W. and P.G. developed the concept and design of the studies. A.S. contributed to data collection, processing and performing the initial analyses. M.W. and G.M.C. carried out the analyses, produced all tables and figures, and prepared the manuscript. The development and editing of the manuscript were overseen by P.G.

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Correspondence to Michael Wolfowicz.

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Extended data

Extended Data Table 1 GMM models specified with contemporaneous measures of control variables
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Extended Data Table 2 Poisson Pseudo-Maximum Likelihood Models with contemporaneous measures of control variables – dependent variable is count of attacks
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Extended Data Table 3 GMM models specified with exclusion of explanatory variables
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Extended Data Table 4 Poisson Pseudo-Maximum Likelihood models specified with exclusion of explanatory variables
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Extended Data Table 5 GMM models specified with additional control variables
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Extended Data Table 6 Poisson Pseudo-Maximum Likelihood Models specified with additional controls
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Extended Data Table 7 Zero-inflated Poisson regression models with fixed effects dummies
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Wolfowicz, M., Campedelli, G.M., Seaward, A. et al. Arrests and convictions but not sentence length deter terrorism in 28 European Union member states. Nat Hum Behav 7, 1878–1889 (2023). https://doi.org/10.1038/s41562-023-01695-6

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