Right‐to‐Carry Laws and Violent Crime: A Comprehensive Assessment Using Panel Data and a State‐Level Synthetic Control Analysis

By John J Donohue, Abhay P. Aneja, Kyle D. Weber. Journal of Empirical Legal Studies, 2019

172 citations recorded by the source corpus.

This paper uses more complete state panel data (through 2014) and new statistical techniques to estimate the impact on violent crime when states adopt right-to-carry (RTC) concealed handgun laws. Our preferred panel data regression specification, unlike the statistical model of Lott and Mustard that had previously been offered as evidence of crime-reducing RTC laws, both satisfies the parallel trends assumption and generates statistically significant estimates showing RTC laws increase overall violent crime. Our synthetic control approach also strongly confirms that RTC laws are associated with 13-15 percent higher aggregate violent crime rates ten years after adoption. Using a consensus estimate of the elasticity of crime with respect to incarceration of 0.15, the average RTC state would need to roughly double its prison population to offset the increase in violent crime caused by RTC adoption.

Subfields: Health, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/f15a14a503c5d1c275d49c370a66b553d613943d

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Citations in the corpus

The Augmented Synthetic Control Method (2018, methodology): “This proposal is similar to the leave-one-out cross validation proposed by Doudchenko and Imbens (2017), who select hyperparameters by holding out control units and minimizing the MSE of the control units in the post-treatment time T .”
Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects (2021, background): “(Donohue et al., 2019), country-level per-capita GDP (Abadie et al.”