持枪权法律和暴力犯罪:使用面板数据和国家级综合控制分析的综合评估

J. Donohue, Abhay P. Aneja, Kyle D. Weber
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引用次数: 30

摘要

2005年,美国国家研究委员会(NRC)关于枪支和暴力的报告承认,在实施持枪权(RTC)隐藏手枪法的州,暴力犯罪在通过后的时期(相对于国家犯罪模式)更高,但由于模型依赖,该小组无法从当时存在的小组数据证据中确定这些法律的真正因果关系。本研究使用了额外14年的面板数据(截至2014年),捕获了额外的11个RTC采用和新的统计技术,以查看是否可以得出更有说服力和更有力的结论。我们首选的面板数据回归规范(“DAW模型”)和布伦南中心(BC)模型,以及洛特和马斯塔德(LM)和穆迪和马维尔(MM)的其他统计模型,以前被作为减少犯罪的RTC法律的证据,现在一致地得出估计,当运行在最完整的数据上时,RTC法律增加了整体暴力犯罪和/或谋杀。然后,我们使用Alberto Abadie和Javier Gardeazabal(2003)的综合控制方法来生成针对特定州的RTC法律对犯罪影响的估计。我们的主要发现是,在所有四种规格(DAW, BC, LM和MM)下,RTC法律与较高的总体暴力犯罪率相关,并且与RTC法律通过相关的有害影响的大小随着时间的推移而上升。在RTC法律通过十年后,暴力犯罪估计比没有RTC法律的情况下高出13-15%。与面板数据设置不同,这些结果对作为预测因子的协变量不敏感。从RTC法律中估计的暴力犯罪增加的幅度是实质性的,使用关于监禁的犯罪弹性的共识估计为0.15,平均RTC州将不得不将其监狱人口增加一倍,以抵消RTC引起的暴力犯罪增加。
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Right-to-Carry Laws and Violent Crime: A Comprehensive Assessment Using Panel Data and a State-Level Synthetic Controls Analysis
The 2005 report of the National Research Council (NRC) on Firearms and Violence recognized that violent crime was higher in the post-passage period (relative to national crime patterns) for states adopting right-to-carry (RTC) concealed handgun laws, but because of model dependence the panel was unable to identify the true causal effect of these laws from the then-existing panel data evidence. This study uses 14 additional years of panel data (through 2014) capturing an additional 11 RTC adoptions and new statistical techniques to see if more convincing and robust conclusions can emerge. Our preferred panel data regression specification (the “DAW model”) and the Brennan Center (BC) model, as well as other statistical models by Lott and Mustard (LM) and Moody and Marvell (MM) that had previously been offered as evidence of crime-reducing RTC laws, now consistently generate estimates showing RTC laws increase overall violent crime and/or murder when run on the most complete data. We then use the synthetic control approach of Alberto Abadie and Javier Gardeazabal (2003) to generate state-specific estimates of the impact of RTC laws on crime. Our major finding is that under all four specifications (DAW, BC, LM, and MM), RTC laws are associated with higher aggregate violent crime rates, and the size of the deleterious effects that are associated with the passage of RTC laws climbs over time. Ten years after the adoption of RTC laws, violent crime is estimated to be 13-15% percent higher than it would have been without the RTC law. Unlike the panel data setting, these results are not sensitive to the covariates included as predictors. The magnitude of the estimated increase in violent crime from RTC laws is substantial in that, using a consensus estimate for the elasticity of crime with respect to incarceration of .15, the average RTC state would have to double its prison population to counteract the RTC-induced increase in violent crime.
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