{"title":"支持枪支越多,犯罪越少假说的最新失败","authors":"J. Donohue, I. Ayres","doi":"10.2139/ssrn.392584","DOIUrl":null,"url":null,"abstract":"John Lott, Florenz Plassman, and John Whitley (\"LPW\") have criticized our article, Shooting Down the More Guns, Less Crime Hypothesis, by arguing that some aggregated statistical models that we criticized support their \"more guns, less crime\" claim (which leads them to say we \"misread\" our results) and by offering new regressions on an expanded county data set. We maintain, however, as we did in our original article, that the aggregated models favored by LPW are flawed by a serious selection effect problem (and in any event we show that the findings LPW point to are undermined by controls for pre-existing state trends in crime). Indeed, we illustrate that simply dropping the states that adopted concealed carry laws during the crack epidemic leads to estimates that concealed carry laws strongly increase crime (which underscores the importance of the omitted crack phenomenon in driving the initial Lott and Mustard results). Moreover, we discovered that the ostensibly supportive results obtained by LPW after extending their county set to 2000 were caused by some mis-coding errors they made in extending their data. When we correct these errors, their findings are reversed: LPW's preferred spline model fails to generate a statistically significant effect for any crime category, while the only significant results in the other possible models show the laws to be associated with increases in various property crimes (and in one case for rape).","PeriodicalId":171240,"journal":{"name":"Yale Law School","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"57","resultStr":"{\"title\":\"The Latest Misfires in Support of the More Guns, Less Crime Hypothesis\",\"authors\":\"J. Donohue, I. Ayres\",\"doi\":\"10.2139/ssrn.392584\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"John Lott, Florenz Plassman, and John Whitley (\\\"LPW\\\") have criticized our article, Shooting Down the More Guns, Less Crime Hypothesis, by arguing that some aggregated statistical models that we criticized support their \\\"more guns, less crime\\\" claim (which leads them to say we \\\"misread\\\" our results) and by offering new regressions on an expanded county data set. We maintain, however, as we did in our original article, that the aggregated models favored by LPW are flawed by a serious selection effect problem (and in any event we show that the findings LPW point to are undermined by controls for pre-existing state trends in crime). Indeed, we illustrate that simply dropping the states that adopted concealed carry laws during the crack epidemic leads to estimates that concealed carry laws strongly increase crime (which underscores the importance of the omitted crack phenomenon in driving the initial Lott and Mustard results). Moreover, we discovered that the ostensibly supportive results obtained by LPW after extending their county set to 2000 were caused by some mis-coding errors they made in extending their data. When we correct these errors, their findings are reversed: LPW's preferred spline model fails to generate a statistically significant effect for any crime category, while the only significant results in the other possible models show the laws to be associated with increases in various property crimes (and in one case for rape).\",\"PeriodicalId\":171240,\"journal\":{\"name\":\"Yale Law School\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"57\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Yale Law School\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.392584\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Yale Law School","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.392584","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 57
摘要
John Lott, Florenz Plassman和John Whitley(“LPW”)批评了我们的文章《打倒更多的枪支,更少的犯罪假设》,他们认为我们批评的一些汇总统计模型支持他们的“更多的枪支,更少的犯罪”的说法(这导致他们说我们“误读”了我们的结果),并在扩大的县数据集上提供了新的回归。然而,正如我们在最初的文章中所做的那样,我们坚持认为,LPW青睐的汇总模型存在严重的选择效应问题(无论如何,我们都表明,LPW所指出的发现被犯罪中既存在状态趋势的控制所破坏)。事实上,我们说明,在可卡因流行期间,简单地放弃采用隐蔽携带法律的州,就会得出隐蔽携带法律大大增加犯罪的估计(这强调了忽略可卡因现象在推动最初洛特和芥末结果中的重要性)。此外,我们发现LPW将县集扩展到2000后得到的表面上支持的结果是由于他们在扩展数据时犯了一些编码错误。当我们纠正这些错误时,他们的发现是相反的:LPW的首选样条模型未能对任何犯罪类别产生统计上显著的影响,而其他可能的模型中唯一显著的结果表明,法律与各种财产犯罪的增加有关(其中一个案例是强奸)。
The Latest Misfires in Support of the More Guns, Less Crime Hypothesis
John Lott, Florenz Plassman, and John Whitley ("LPW") have criticized our article, Shooting Down the More Guns, Less Crime Hypothesis, by arguing that some aggregated statistical models that we criticized support their "more guns, less crime" claim (which leads them to say we "misread" our results) and by offering new regressions on an expanded county data set. We maintain, however, as we did in our original article, that the aggregated models favored by LPW are flawed by a serious selection effect problem (and in any event we show that the findings LPW point to are undermined by controls for pre-existing state trends in crime). Indeed, we illustrate that simply dropping the states that adopted concealed carry laws during the crack epidemic leads to estimates that concealed carry laws strongly increase crime (which underscores the importance of the omitted crack phenomenon in driving the initial Lott and Mustard results). Moreover, we discovered that the ostensibly supportive results obtained by LPW after extending their county set to 2000 were caused by some mis-coding errors they made in extending their data. When we correct these errors, their findings are reversed: LPW's preferred spline model fails to generate a statistically significant effect for any crime category, while the only significant results in the other possible models show the laws to be associated with increases in various property crimes (and in one case for rape).