John Patrick
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They did.
Studies Exploring the Effects of Shall-Issue Concealed-Carry Laws on Violent Crime, 1997–2004
Study Significant Effect Reported (Main Specification)
Lott and Mustard (1997)a Decrease in violent crime, murders, rapes,
and assaults
Bartley and Cohen (1998) Decrease in violent crime robust to alternate
model specifications
Black and Nagin (1998) Increase in assaults
Bronars and Lott (1998) Decrease in murders and rapes, displacement
of crime to other jurisdictions
Lott (1998a)a Decrease in violent crime in most states
implementing the law
Lott (1998b)a Decrease in violent crime; increase in
property crime
Ludwig (1998) None detected
Ayres and Donohue (1999)a Increase in property crime
Lott and Landes (1999)a Decrease in murders and injuries from
multiple-victim public shootings
Lott (2000)a Decrease in all crime categories
Benson and Mast (2001) Decrease in violent crime, murders,
rapes, and robberies
Duggan (2001) Decrease in assaults
Moody (2001)a Decrease in violent crime
Olson and Maltz (2001) Decrease in firearm murders
Plassmann and Tideman (2001) Decrease in murders and rapes;
increase in robberies
Lott and Whitley (2003)a Decrease in violent crime, murders,
rapes, and robberies
Plassmann and Whitley (2003)b Decrease in rapes and robberies
Rubin and Dezhbakhsh (2003) Decrease in murders; increase in
robberies
Ayres and Donohue (2003a)a Increase in more crime categories
than saw a decrease
Ayres and Donohue (2003b)a Increase or no effect in all crime
categories
Donohue (2003)a Mixed; effects were sensitive to model
specifications and data
Helland and Tabarrok (2004) Increase in property crime, auto
thefts, and larcenies
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:
Lott and Mustard's data set used county population values that did not correspond to the crime statistics available for counties, especially those with weak reporting of crime statistics (Maltz and Targonski, 2002). Lott and Whitley (2003) discounted these and other concerns about the quality of county crime rate data, describing them as typical of the types of measurement error commonly encountered in statistical analyses. Furthermore, they suggested that the findings in Lott (2000) persisted even when analyzing the subset of counties with minimal error in crime statistics. After reviewing this exchange, the NRC panel disagreed with Lott and Whitley that the original effects reported by Lott (2000) survived this test: "The committee concludes that it is at least possible that errors in the [Uniform Crime Reporting] data may account for some of Lott's results" (NRC, 2004, p. 137).
Many of these studies followed the example of Lott and Mustard (1997) by including arrest rates as a model covariate. This led to these analyses excluding large numbers of counties that had no crimes of a given type and therefore an undefined arrest rate, an approach that differentially excluded locations where the introduction of shall-issue laws could have led only to an increase in crime rates (Ayres and Donohue, 2003a).
There were errors in the classification of shall-issue states in the Lott and Mustard data set that were only later corrected (Ayres and Donohue, 2003a). There were multiple errors detected in the data sets used by Lott (1998b, 2000) and by Plassmann and Whitley (2003), and Plassmann subsequently acknowledged these errors to the NRC (NRC, 2004, p. 136). Correction of these errors eliminated many of the significant effects reported by Plassmann and Whitley (2003) (Ayres and Donohue, 2003a).
Nearly all of the studies listed in the table above failed to control for serial correlation in the panel data set; the exceptions were Duggan (2001), Olson and Maltz (2001), Plassmann and Whitley (2003), Ayres and Donohue (2003a, 2003b), and Helland and Tabarrok (2004). This led to gross exaggerations of the statistical significance of study results and greatly elevated the risk of finding statistically significant effects that were in the opposite direction of any true effect (Schell, Griffin, and Morral, 2018; Moody and Marvell, 2018b; Aneja, Donohue, and Zhang, 2014; Helland and Tabarrok, 2004).
Most of the studies used the large number of covariates first included in the Lott and Mustard (1997) analyses, which had a ratio of estimated parameters to observations of between one to eight and one to 14 across analyses. When the proportion of estimated parameters is this high, there is considerable risk that the statistical models are overfit, and the law effects that they estimate thus may not be generalizable. Among few exceptions, the models of Ludwig (1998) and Moody (2001) did not suffer from this problem.
Effects of Concealed-Carry Laws on Violent Crime | RAND
As they say, “There are lies, damned lies and then there are statistics!”