Shooting Down the More Guns, Less Crime Hypothesis

I. Ayres, J. Donohue
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引用次数: 215

Abstract

John Lott and David Mustard have used regression analysis to argue forcefully that 'shall-issue' laws (which give citizens an unimpeded right to secure permits for concealed weapons) reduce violent crime. While certain facially plausible statistical models appear to generate this conclusion, more refined analyses of more recent state and county data undermine the more guns, less crime hypothesis. The most robust finding on the state data is that certain property crimes rise with passage of shall- issue laws, although the absence of any clear theory as to why this would be the case tends to undercut any strong conclusions. Estimating more statistically preferred disaggregated models on more complete county data, we show that in most states shall- issue laws have been associated with more crime and that the apparent stimulus to crime tends to be especially strong for those states that adopted in the last decade. While there are substantial concerns about model reliability and robustness, we present estimates based on disaggregated county data models that on net the passage of the law in 24 jurisdictions has increased the annual cost of crime slightly -- somewhere on the order of half a billion dollars. We also provide an illustration of how our jurisdiction-specific regression model has the capacity to generate more nuanced assessments concerning which states might profit from or be harmed by a particular legal intervention.
击落更多的枪支,更少的犯罪假设
约翰·洛特(John Lott)和大卫·马斯塔德(David Mustard)使用回归分析有力地论证了“应颁布”法律(赋予公民不受阻碍地获得隐藏武器许可的权利)减少了暴力犯罪。虽然某些表面上看似合理的统计模型似乎得出了这一结论,但对最近州和县数据进行的更精细的分析却推翻了“持枪越多,犯罪越少”的假设。国家数据中最有力的发现是,某些财产犯罪随着颁布法律的通过而上升,尽管缺乏任何明确的理论来解释为什么会出现这种情况,往往会削弱任何强有力的结论。通过对更完整的县数据进行统计分析,我们发现,在大多数州,颁布法律与更多的犯罪有关,而对犯罪的明显刺激在过去十年中采用的州尤为强烈。尽管对模型的可靠性和稳健性存在很大的担忧,但我们基于分解的县数据模型提出了估计,即在24个司法管辖区通过法律后,每年的犯罪成本略有增加——大约在5亿美元左右。我们还提供了一个例子,说明我们的特定管辖权回归模型如何能够产生更细致入微的评估,以确定哪些国家可能从特定的法律干预中受益或受到损害。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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