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Detecting a copycat effect in school shootings using spatio‐temporal panel count models

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  • Karsten Schweikert
  • Manuel Huth
  • Mark Gius

Abstract

School shootings are often motivated by the perpetrators' desire for media attention and notoriety. As school shootings receive intense regional and national media coverage, a high likelihood for copycat attacks can be expected. We investigate whether a copycat effect can be detected in US state‐level school shooting data from 1990 to 2017. We do so by estimating spatio‐temporal panel count models and control for socio‐economic characteristics, as well as state and Federal gun control laws. Positive spatial and temporal dependence indicate that the risk for additional school shootings in the same and neighboring states increases after the initial attack.

Suggested Citation

  • Karsten Schweikert & Manuel Huth & Mark Gius, 2021. "Detecting a copycat effect in school shootings using spatio‐temporal panel count models," Contemporary Economic Policy, Western Economic Association International, vol. 39(4), pages 719-736, October.
    • Handle: RePEc:bla:coecpo:v:39:y:2021:i:4:p:719-736
    DOI: 10.1111/coep.12532
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    1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LLC, vol. 3(1), pages 1-31, March.
    2. Maya Rossin-Slater & Molly Schnell & Hannes Schwandt & Sam Trejo & Lindsey Uniat, 2020. "Local exposure to school shootings and youth antidepressant use," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(38), pages 23484-23489, September.
    3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    4. Luca, Michael & Malhotra, Deepak & Poliquin, Christopher, 2020. "The impact of mass shootings on gun policy," Journal of Public Economics, Elsevier, vol. 181(C).
    5. M Ensar Yesilyurt & J Paul Elhorst, 2017. "Impacts of neighboring countries on military expenditures," Journal of Peace Research, Peace Research Institute Oslo, vol. 54(6), pages 777-790, November.
    6. Patrick Sevestre & Laszlo Matyas, 2008. "The Econometrics of Panel Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00279977, HAL.
    7. Wooldridge, Jeffrey M., 1997. "Multiplicative Panel Data Models Without the Strict Exogeneity Assumption," Econometric Theory, Cambridge University Press, vol. 13(5), pages 667-678, October.
    8. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
    9. Lambert, Dayton M. & Brown, Jason P. & Florax, Raymond J.G.M., 2010. "A two-step estimator for a spatial lag model of counts: Theory, small sample performance and an application," Regional Science and Urban Economics, Elsevier, vol. 40(4), pages 241-252, July.
    10. Benjamin M. Blau & Devon H. Gorry & Chip Wade, 2016. "Guns, laws and public shootings in the United States," Applied Economics, Taylor & Francis Journals, vol. 48(49), pages 4732-4746, October.
    11. John Mullahy, 1997. "Instrumental-Variable Estimation Of Count Data Models: Applications To Models Of Cigarette Smoking Behavior," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 586-593, November.
    12. Anandasivam Gopal & Brad N Greenwood, 2017. "Traders, guns, and money: The effects of mass shootings on stock prices of firearm manufacturers in the U.S," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-29, May.
    13. Mark Gius, 2018. "The effects of state and Federal gun control laws on school shootings," Applied Economics Letters, Taylor & Francis Journals, vol. 25(5), pages 317-320, March.
    14. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    15. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    16. Brodeur, Abel & Yousaf, Hasin, 2019. "The Economics of Mass Shootings," IZA Discussion Papers 12728, Institute of Labor Economics (IZA).
    17. Abouk, Rahi & Adams, Scott, 2013. "School shootings and private school enrollment," Economics Letters, Elsevier, vol. 118(2), pages 297-299.
    18. Matthew Lang, 2013. "Firearm Background Checks and Suicide," Economic Journal, Royal Economic Society, vol. 123(12), pages 1085-1099, December.
    19. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    20. Elhorst, J. Paul, 2008. "Serial and spatial error correlation," Economics Letters, Elsevier, vol. 100(3), pages 422-424, September.
    21. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    22. Roman Liesenfeld & Jean‐François Richard & Jan Vogler, 2017. "Likelihood‐Based Inference and Prediction in Spatio‐Temporal Panel Count Models for Urban Crimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 600-620, April.
    23. Mark Gius, 2014. "An examination of the effects of concealed weapons laws and assault weapons bans on state-level murder rates," Applied Economics Letters, Taylor & Francis Journals, vol. 21(4), pages 265-267, March.
    24. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, February.
    25. Claudia Czado & Holger Schabenberger & Vinzenz Erhardt, 2014. "Non nested model selection for spatial count regression models with application to health insurance," Statistical Papers, Springer, vol. 55(2), pages 455-476, May.
    26. Chamberlain, Gary, 1992. "Sequential Moment Restrictions in Panel Data: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 20-26, January.
    27. A. R. Pah & J. Hagan & A. L. Jennings & A. Jain & K. Albrecht & A. J. Hockenberry & L. A. N. Amaral, 2017. "Economic insecurity and the rise in gun violence at US schools," Nature Human Behaviour, Nature, vol. 1(2), pages 1-6, February.
    28. José L Torrecilla & Lara Quijano-Sánchez & Federico Liberatore & Juan J López-Ossorio & José L González-Álvarez, 2019. "Evolution and study of a copycat effect in intimate partner homicides: A lesson from Spanish femicides," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-26, June.
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