Measures of Gun Ownership Levels for Macro-Level Crime and Violence Research

Kleck, Gary

doi:10.1177/0022427803256229

Cited by 121 publications

(129 citation statements)

References 35 publications

(53 reference statements)

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“…This proxy (a) seems reasonable as in a society with zero guns, FSS will be zero, and in a society where everyone has access to guns, all else equal, it very likely will achieve its maximum value. (b) is confirmed to function in the way intended by other studies (Azrael, Cook and Miller 2004;Kleck 2004), at least for the cross-section. (c) is supported by evidence that with increased availability of firearms the number of shooting suicides increases (see Klieve, Barnes and De Leo 2009;Klieve, Sveticic and De Leo 2009;Leenaars et al 2003;Kellermann et al 1992 Methods: The panel of ratios is analyzed by a two-way (individual and time) fixed effects panel model on the logarithms.…”

Section: Introduction ½ áòøöó ù ø óòsupporting

confidence: 78%

The Social Costs of Gun Ownership: Spurious Regression and Unfounded Public Policy Advocacy

Westphal

2013

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This version: July 8, 2013 Terms of use: Documents in AbstractIn 2006, a study, published in the Journal of Public Economics, employing a panel regression of 200 U.S. counties across 20 years, found a significant elasticity of homicides with respect to firearms ownership. Based on this finding the authors made the public policy recommendation of taxing gun ownership. However that study fell prey to the ratio fallacy, a trap known since 1896. All the "explanatory power" (goodness-of-fit-wise and significance-wise) of the original analysis was due to regional and intertemporal differences and population being explained by itself. When the ratio fallacy is accounted for, all authors' results can no longer be found. This is illustrated in this paper using a balanced panel from the data for 1980 to 2004. My findings are robust to (i) alternative specifications not subject to the ratio problem, (ii) using only data from 1980 to 1999 as in the original paper, (iii) using an unbalanced panel for 1980 to either 1999 or 2004, (iv) applying weighting as done by the original authors and (v) using data aggregated at the state level.JEL Classifications: C51; H21; I18; K42 Keywords: Gun Ownership; Social Costs; Ratio Fallacy; Spurious Regression a Thanks to participants of a Brown Bag Seminar held at Philipps-University Marburg and to participants of a Seminar on replication studies held at University of Göttingen both in which some good thoughts on the problem were had. Thanks to Bernd Hayo for contributing the 'moving averages' solution for the noisy proxy mentioned in section 7 and to Florian Neumeier for contributing the growth model used in section 6.4.

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Section: Introduction ½ áòøöó ù ø óòsupporting

confidence: 78%

The Social Costs of Gun Ownership: Spurious Regression and Unfounded Public Policy Advocacy

Westphal

2013

SSRN Journal

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“…Kleck (2004) shows, however, that most of the measures used in prior studies have poor validity. The main exception is the percent of suicides committed with guns (PSG), which correlates strongly in cross-section with direct survey measures across cities, states, and nations.…”

Section: Prior Researchmentioning

confidence: 99%

“…Typically, data on gun levels are sparse, noisy, or simply unavailable. Researchers have responded by using a diverse set of proxy measures (Kleck, 2004). In cross-section, this gives a feasible estimating equation…”

Section: Prior Researchmentioning

confidence: 99%

“…The result is that empirical researchers face a classic problem of endogeneity bias: unless it is successfully addressed, what is asserted to be the impact of gun levels on crime rates will in fact also include the impact of crime rates on gun levels, and estimates of the former will typically be biased upwards. Second, measurement of gun levels is subject to welldocumented problems (Kleck, 2004). Given the shortcomings in the available direct measures of gun levels, researchers have commonly used proxy measures instead.…”

Section: Introductionmentioning

confidence: 99%

“…We adopt instead a cross-section approach: we use U.S. county-level data for 1990, and we proxy gun prevalence levels by the percent of suicides committed with guns, which recent research indicates is the best measure of gun levels for cross-sectional research (Kleck 2004). We instrument gun levels with three plausibly exogenous instruments: subscriptions to outdoor sports magazines, voting preferences in the 1988 Presidential election, and numbers of military veterans.…”

Section: Introductionmentioning

confidence: 99%

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Estimating the Causal Effect of Gun Prevalence on Homicide Rates: A Local Average Treatment Effect Approach

2012

Self Cite

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E S ABSTRACT Estimating the Causal Effect of Gun Prevalence on Homicide Rates: A Local Average Treatment Effect Approach *This paper uses a "local average treatment effect" (LATE) framework in an attempt to disentangle the separate effects of criminal and noncriminal gun prevalence on violence rates. We first show that a number of previous studies have failed to properly address the problems of endogeneity, proxy validity, or heterogeneity in criminality. We demonstrate that the time series proxy problem is severe; previous panel data studies have used proxies that are essentially uncorrelated in time series with direct measures of gun relevance. We adopt instead a cross-section approach: we use U.S. county-level data for 1990, and we proxy gun prevalence levels by the percent of suicides committed with guns, which recent research indicates is the best measure of gun levels for cross-sectional research. We instrument gun levels with three plausibly exogenous instruments: subscriptions to outdoor sports magazines, voting preferences in the 1988 Presidential election, and numbers of military veterans. In our LATE framework, the estimated impact of gun prevalence is a weighted average of a possibly negative impact of noncriminal gun prevalence on homicide and a presumed positive impact of criminal gun prevalence. We find evidence of a significant negative impact, and interpret it as primarily "local to noncriminals", i.e., primarily determined by a negative deterrent effect of noncriminal gun prevalence. The beneficiaries of the reduced level of violence may include substantial numbers of (urban) criminals, the murders of whom decrease via spillovers from noncriminal gun prevalence.

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Geographic and Demographic Differences in the Proportion of Individuals Living in Households With a Firearm, 1990-2018

Morral,

Smart,

Schell

et al. 2024

JAMA Netw Open

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ImportanceMeasures of the proportion of individuals living in households with a firearm (HFR), over time, across states, and by demographic groups are needed to evaluate disparities in firearm violence and the effects of firearm policies.ObjectiveTo estimate HFR across states, years, and demographic groups in the US.Design, Setting, and ParticipantsIn this survey study, substate HFR totals from 1990 to 2018 were estimated using bayesian multilevel regression with poststratification to analyze survey data on HFR from the Behavioral Risk Factor Surveillance System and the General Social Survey. HFR was estimated for 16 substate demographic groups defined by gender, race, marital status, and urbanicity in each state and year.ExposuresSurvey responses indicating household firearm ownership were analyzed and compared with a common proxy for firearm ownership, the fraction of suicides completed with a firearm (FSS).Main Outcome and MeasureHFR, FSS, and their correlations and differences.ResultsAmong US adults in 2018, HFR was significantly higher among married, nonurban, non-Hispanic White and American Indian male individuals (65.0%; 95% credible interval [CI], 61.5%-68.7%) compared with their unmarried, urban, female counterparts from other racial and ethnic groups (7.3%; 95% CIs, 6.0%-9.2%). Marginal HFR rates for larger demographic groups also revealed important differences, with racial minority groups and urban dwellers having less than half the HFR of either White and American Indian (39.5%; 95% CI, 37.4%-42.9% vs 17.2%; 95% CI, 15.5%-19.9%) or nonurban populations (46.0%; 95% CI, 43.8%-49.5% vs 23.1%; 95% CI, 21.3%-26.2%). Population growth among groups less likely to own firearms, rather than changes in ownership within demographic groups, explains 30% of the 7 percentage point decline in HFR nationally from 1990 to 2018. Comparing HFR estimates with FSS revealed the expected high overall correlation across states (r = 0.84), but scaled FSS differed from HFR by as many as 20 percentage points for some states and demographic groups.Conclusions and RelevanceThis survey study of HFR providing detailed, publicly available HFR estimates highlights key disparities among individuals in households with firearms across states and demographic groups; it also identifies potential biases in the use of FSS as a proxy for firearm ownership rates. These findings are essential for researchers, policymakers, and public health experts looking to address geographic and demographic disparities in firearm violence.

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Measures of Gun Ownership Levels for Macro-Level Crime and Violence Research

Cited by 121 publications

References 35 publications

The Social Costs of Gun Ownership: Spurious Regression and Unfounded Public Policy Advocacy

The Social Costs of Gun Ownership: Spurious Regression and Unfounded Public Policy Advocacy

Estimating the Causal Effect of Gun Prevalence on Homicide Rates: A Local Average Treatment Effect Approach

Geographic and Demographic Differences in the Proportion of Individuals Living in Households With a Firearm, 1990-2018

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