Junior Miss Pageant 2000 Series Vol140
Jannet Nevels
Summary: There is supportive evidence that shall-issue concealed-carry laws may increase total and firearm homicides. Evidence for the effect of permitless-carry laws on total homicides is inconclusive. Evidence that shall-issue concealed-carry laws may increase violent crime is limited.
Some studies find that right-to-carry laws reduce violent crime, others find that the effects are negligible, and still others find that such laws increase violent crime. The committee concludes that it is not possible to reach any scientifically supported conclusion because of (a) the sensitivity of the empirical results to seemingly minor changes in model specification, (b) a lack of robustness of the results to the inclusion of more recent years of data (during which there were many more law changes than in the earlier period), and (c) the statistical imprecision of the results. The evidence to date does not adequately indicate either the sign or the magnitude of a causal link between the passage of right-to-carry laws and crime rates. Furthermore, this uncertainty is not likely to be resolved with the existing data and methods. If further headway is to be made, in the committee's judgment, new analytical approaches and data are needed (p. 7).
In addition to the sensitivity of results to minor changes in model specification noted by the NRC report, these early studies suffered from multiple serious problems with data and methodology that lead us to discount their value for informing this synthesis of evidence on the effects of shall-issue laws. These problems include the following:
Finally, we regard a majority of these early studies as having been superseded by later work by the same authors that improved on their earlier contributions to this literature. As a result, we focus on their later efforts to evaluate the effect of shall-issue laws.
We first describe studies published since 2004 that aimed to estimate the effects of concealed-carry laws on violent crime using county-level data. We then turn to studies that focused on state-level data, then studies that employed city-level data. We conclude by discussing results from a set of studies in which the objective was not to identify the effects of shall-issue laws but that nonetheless present estimates that may be considered part of the evidence base for how concealed-carry policies influence violent crime outcomes (e.g., some studies of the effects of abortion rates on violent crime include shall-issue laws as a covariate in their models).
Many important shortcomings of county-level crime data identified through the early studies of shall-issue laws (see the table above) resulted from the fact that large numbers of county police agencies do not report crime statistics to the Federal Bureau of Investigation (FBI). Moreover, the way that county crime statistics address these missing data changed abruptly in the early 1990s, making data from the earlier part of the series not comparable with later data, according to the National Archive of Criminal Justice Data (undated). Nevertheless, several analyses have continued to use county-level crime data to evaluate law effects, or they have used homicide data from the Centers for Disease Control and Prevention (CDC)'s National Vital Statistics System, which has less of a problem with missing data (Loftin, McDowall, and Fetzer, 2008).[1]
Aneja, Donohue, and Zhang (2014) analyzed the county-level data set used in NRC (2004) that was extended through 2006 and state-level data through 2010. The authors corrected the NRC analyses for several errors that they identified, including data-coding errors related to the timing of shall-issue legislation, an endogenous control variable (arrest rate), and a failure to cluster standard errors at the state level. The authors argued that the decision in NRC (2004) not to cluster the standard errors of the county-level analyses at the state level was incorrect and showed that CIs were badly misestimated when clustering was not accounted for. In their preferred county-level specification including state trend effects, they found no statistically significant effects of shall-issue laws on either the level or trend of any of seven crime rates, and they found only one suggestive effect across the 14 effects they tested.
Moody et al. (2014), responding to an earlier version of the Aneja, Donohue, and Zhang (2014) paper, reestimated their models after adding many more demographic control variables, robbery and assault rates, and a lagged outcome as a predictor meant to capture unmeasured state differences associated with crime rates. Moody et al. (2014) offered statistical tests suggesting that the model with added covariates predicted the data significantly better, which the authors interpreted as evidence that estimates in Aneja, Donohue, and Zhang (2014) suffered from omitted-variable biases. The revised hybrid model results in Moody et al. (2014) suggested that shall-issue laws significantly reduced the trends in rape and murder rates. They found no significant association between shall-issue laws and either assault or robbery rates. The fact that their model predicted a given outcome better than the Aneja, Donohue, and Zhang (2014) model is not sufficient to demonstrate the claim that the latter's model suffered from omitted-variable bias or that the model preferred by Moody et al. (2014) offered a less biased estimate. An overfit model can predict the data exceptionally well while producing biased and unreliable coefficient estimates.
Hepburn et al. (2004) evaluated the effects of shall-issue laws on homicide rates using data from 1979 to 1998 in a study that came out too late to be reviewed in either the NRC (2004) or the Hahn et al. (2005) reviews of firearm research. Using a negative binomial model with two-way fixed effects and controlling for demographic and economic variables, including a proxy for gun ownership, the authors found uncertain effects for shall-issue laws on state homicide rates. Estimated effects remained uncertain in subgroup analyses of adults aged 25 or older and of white men aged 35 or older (see the first figure below).
Using a panel of state data, Lott (2010) provided an update of his earlier analyses examining the effect of shall-issue laws on violent crime. His preferred specification included a set of dummy variables that indicated different time intervals before and after shall-issue legislation was in effect for states that passed such legislation. Many of Lott's modeling results were presented as figures and did not indicate statistical significance. Detailed results were provided only for an analysis of homicide rates. These included information on the statistical significance of each coefficient in the model but not for a test comparing post-implementation time intervals with pre-implementation time intervals. Lott interpreted the pattern of effects as demonstrating that homicides declined significantly after implementation of shall-issue laws, but he did not provide test statistics or sufficient description to clarify what specific effect was observed. The author also included coefficients and their statistical significance from dummy and spline models similar to those from his earlier work, but he did not include standard errors or test statistics. All of the preferred models appear to have had a ratio of estimated parameters to observations that was less than one to ten, meaning the model may have been overfit, and thus the reported estimates and their CIs may be unreliable. Similarly, it does not appear that Lott used any adjustments for serial correlation in his panel data, so some of the effects reported as statistically significant might not be after correcting these analyses (Schell, Griffin, and Morral, 2018; Aneja, Donohue, and Zhang, 2014; Helland and Tabarrok, 2004).
DeSimone, Markowitz, and Xu (2013) evaluated the effects of child-access prevention laws on nonfatal injuries using data from 1988 to 2003, but they included sensitivity analyses that controlled for shall-issue laws. Using fixed-effects Poisson regression models, they found that shall-issue laws were significantly associated with firearm assault injuries for children under age 18, as well as for adults. Specifically, their estimate suggests that, after a state implemented a shall-issue law, assault injury rates were more than double what would have been expected without the law (see the second figure below), which would be extraordinary if true. However, the estimated effects of shall-issue laws in this study were based primarily on implementation in one state that changed its law during the study time frame (Arizona); thus, the study offers little evidence that the observed effects are due to the change in the law rather than to other factors affecting the state's assault rate that occurred around the same time the law was changed.
Webster, Crifasi, and Vernick (2014) analyzed state-level data from 1999 to 2010, using generalized least-squares regression models to estimate the effect of shall-issue laws on age-adjusted homicide rates. They found suggestive effects indicating an association between the implementation of shall-issue laws and a 10-percent increase in rates of nonfirearm homicide, a 6-percent increase in rates of total homicide, and an 11-percent increase in rates of murder and nonnegligent manslaughter.[2] However, their estimates showed an uncertain association between shall-issue laws and firearm homicide rates. The statistical model used to arrive at these results used a large number of estimated parameters relative to observations (a ratio of about one to eight), meaning the model may have been overfit, and thus its estimates and their apparent statistical significance could provide little generalizable information about the true causal effects of shall-issue laws.
Gius (2014) examined the effect of shall-issue laws on gun-related murder rates using state-level data from 1980 to 2009. He found that states with may-issue or more-restrictive policies had higher gun-related murder rates than shall-issue states. Relative to states with shall-issue laws, states with more-restrictive firearm-carry policies had rates of firearm homicide that were 11 percent higher (see the second figure below). However, this model did not statistically adjust for the known serial correlation in these panel data, which has been shown to result in misleadingly small standard errors (Schell, Griffin, and Morral, 2018; Aneja, Donohue, and Zhang, 2014; Helland and Tabarrok, 2004). For this reason, the apparently significant effect observed in this study could be invalid.
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