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

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  • John J. Donohue
  • Abhay Aneja
  • Kyle D. Weber

Abstract

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.

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  • John J. Donohue & Abhay Aneja & Kyle D. Weber, 2017. "Right-to-Carry Laws and Violent Crime: A Comprehensive Assessment Using Panel Data and a State-Level Synthetic Control Analysis," NBER Working Papers 23510, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:23510
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    More about this item

    JEL classification:

    • K0 - Law and Economics - - General
    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
    • K4 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior
    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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    1. Right-to-Carry Laws and Violent Crime: A Comprehensive Assessment Using Panel Data, the LASSO, and a State-Level Synthetic Controls Analysis (NBER 2018) in ReplicationWiki

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