Self-Protection versus Fear of Stricter Firearm Regulations: Examining the Drivers of Firearm Acquisitions in the Aftermath of a Mass Shooting

Maurizio Porfiri, Roni Barak-Ventura, Manuel Ruiz Marín

Research output: Contribution to journalArticlepeer-review

Abstract

Discovering causal mechanisms underlying firearm acquisition can provide critical insight into firearm-related violence in the United States. Here, we established an information-theoretic framework to address the long-disputed dichotomy between self-protection and fear of firearm regulations as potential drivers of firearm acquisition in the aftermath of a mass shooting. We collected data on mass shootings, federal background checks, media output on firearm control and shootings, and firearm safety laws from 1999 to 2017. First, we conducted a cluster analysis to partition States according to the restrictiveness of their firearm-related legal environment. Then, we performed a transfer entropy analysis to unveil causal relationships at the State-level in the Wiener-Granger sense. The analysis suggests that fear of stricter firearm regulations is a stronger driver than the desire of self-protection for firearm acquisitions. This fear is likely to cross State borders, thereby shaping a collective pattern of firearm acquisition throughout the Nation. Surges in firearm acquisition after mass shootings have been widely documented in the United States for decades, but their underlying cause is yet to be fully elucidated. Do people purchase guns for self-protection, as they fear to be the next victims of a mass shooting? Or do they acquire guns because they fear firearms will be curtailed by upcoming policy actions? Or are they driven by both these fears? Answering these questions requires overcoming traditional correlation analysis through statistically principled approaches that can infer causal relationships from time-series. Here, we present a detailed information-theoretic analysis of State-level firearm acquisitions, which takes into consideration the location of mass shootings, State-to-State interactions, and firearm-related legal environment. Disentangling causation from correlation is critical in firearm research toward empowering policy makers with strong, objective support for effective policy solutions. Why are surges in firearm sales observed after a mass shooting? Are people concerned for their safety, as they worry that another mass shooting could take place? Or are they afraid that their access to firearms could be curtailed by stricter regulations? An information-theoretic framework is established to address these questions, utilizing State-level data on mass shootings and federal background checks, along with media coverage from different sources of shootings and firearm control.

Original languageEnglish (US)
Article number100082
JournalPatterns
Volume1
Issue number6
DOIs
StatePublished - Sep 11 2020

Keywords

  • DSML 5: Mainstream: Data science output is well understood and (nearly) universally adopted
  • firearm
  • information theory
  • mass shooting
  • media
  • newspaper
  • policy
  • spatial data
  • symbolic dynamics
  • time-series
  • transfer entropy

ASJC Scopus subject areas

  • Decision Sciences(all)

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