Wellford C.S., Pepper J.V. - Firearms and Violence[c] What Do We Know[q] (2005)(en)

148	FIREARMS AND VIOLENCE

Auto Theft

	20
Change	10
	0
Percentage
	-10
	-20
	-30
	-10	-5	0	5	10
		Years Relative to Law Passage

	10		Burglary
Change	0
	-10
Peercentage
	-20
	-30
	-40
	-10	-5	0	5	10

Years Relative to Law Passage

	30		Larceny
Crime	20
	10
Percentage	0
	-10
	-20
	-30
	-10	-5	0	5	10

Years Relative to Law Passage

FIGURE 6-4 Year-by-year estimates of the percentage change in disaggregate property crimes (normalized to adoption date of right-to-carry law, year 0).

Estimate, o bottom of 95% confidence interval (CI), | Top of 95% CI

RIGHT-TO-CARRY LAWS

149

passed right-to-carry laws did not on average experience statistically significant crime declines relative to states that did not pass such laws.

There are two points to make about the no-controls results. First, the no-controls results provide a characterization of the data that shows that, if there is any effect, it is not obvious in the dummy variable model. What do estimates from that model mean? The model says that crime rates differ across counties and, moreover, that they change from one year to the next in the same proportionate way across all counties in the United States. Over and above this variation, there is a one-time change in the mean level of crime as states adopt right-to-carry laws. So these estimates indicate that, for the period 1977-1992, states adopting right-to-carry laws saw roughly no change in their violent crime rates and 8.5 percent increases in their property crime rates, relative to national time patterns. Estimating the model using data to 2000 shows that states adopting right-to-carry laws saw 12.9 percent increases in violent crime—and 21.2 percent increases in property crime—relative to national time patterns. The first-blush evidence provided by these no-controls models is thus not supportive of the theory that right- to-carry laws reduce crime.

A final lesson to draw from the no-controls dummy variable results is that the results are sensitive to the inclusion of controls. That is, whether one concludes that right-to-carry laws increase or decrease crime based on models of this sort depends on which control variables are included. Such laws have no obvious effect in the model without controls (and therefore no clear level effect in the raw data). Moreover, as demonstrated above, seemingly minor changes to the set of control variables substantially alter the estimated effects. Given that researchers might reasonably argue about which controls belong in the model and that the results are sensitive to the set of covariates, the committee is not sanguine about the prospects for measuring the effect of right-to-carry laws on crime. Note that this is distinct from whether such laws affect crime. Rather, in our view, any effect they have on crime is not likely to be detected in a convincing and robust fashion.

Estimates from the trend model are less sensitive to the inclusion of controls. While the no-control point estimates displayed in the third and fourth rows of Table 6-6 are smaller than in the model with controls, most of these estimates are negative and statistically significant. The trend model without controls shows reductions in violent and property crime trends following the passage of right-to-carry laws for both sample endpoints. For murder, however, the results are positive when using the 2000 endpoint, negative when using the 1992 endpoint, and statistically insignificant in both cases.

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TABLE 6-7 Trend Model with Varying Postlaw Change Durations
			Controlsa	Violent
		Years		Crime	Murder	Rape
1.	Baseline	2000	Yes	–0.95	–2.03	–2.81
	comm estimateb
	from row 1 of
	Table 6-6
	SE			(0.18)**	(0.26)**	(0.20)**
2.	6 years	2000	Yes	–0.97	–1.11	–2.90
	SE			(0.29)**	(0.42)**	(0.33)**
3.	5 years	2000	Yes	–0.65	0.05	–2.45
	SE			(0.35)	(0.50)	(0.40)**
4.	4 years	2000	Yes	–0.27	0.48	–0.74
	SE			(0.44)	(0.63)	(0.50)

aThe regressions use the covariates and specification from the original Lott and Mustard (1997) models that do not control for state poverty, unemployment, death penalty execution rates, or regional time trends. The controls include the arrest rate for the crime category in question (AOVIOICP), population density in the county, real per capita income variables (RPCPI RPCUI RPCIM RPCRPO), county population (POPC), and variables for the percentage of the population that is in each of many race × age × gender categories (e.g., PBM1019 is the percentage of the population that is black, male, and between ages 10 and 19).

CONCLUSIONS

The literature on right-to-carry laws summarized in this chapter has obtained conflicting estimates of their effects on crime. Estimation results have proven to be very sensitive to the precise specification used and time period examined. The initial model specification, when extended to new data, does not show evidence that passage of right-to-carry laws reduces crime. The estimated effects are highly sensitive to seemingly minor changes in the model specification and control variables. No link between right-to- carry laws and changes in crime is apparent in the raw data, even in the initial sample; it is only once numerous covariates are included that the negative results in the early data emerge. While the trend models show a reduction in the crime growth rate following the adoption of right-to-carry laws, these trend reductions occur long after law adoption, casting serious doubt on the proposition that the trend models estimated in the literature reflect effects of the law change. Finally, some of the point estimates are imprecise. Thus, the committee concludes that with the current evidence it is not possible to determine that there is a causal link between the passage of right-to-carry laws and crime rates.

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Aggravated		Property
Assault	Robbery	Crimes	Auto Theft	Burglary	Larceny
–1.92	–2.58	–0.01	–0.49	–2.13	–0.73
(0.20)**	(0.22)**	(0.13)	(0.19)*	(0.14)**	(0.13)**
–1.06	–1.88	0.11	1.40	–1.13	0.33
(0.32)**	(0.36)**	(0.21)	(0.31)**	(0.23)**	(0.22)
–0.83	–1.63	0.28	1.83	–0.77	0.36
(0.39)*	(0.43)**	(0.25)	(0.37)**	(0.27)**	(0.26)
–0.34	–1.36	0.44	2.03	–0.47	0.31
(0.49)	(0.55)*	(0.32)	(0.47)**	(0.35)	(0.33)

bUsing the revised new data set, for the full available time period (1977-2000).

NOTES: All samples start in 1977. All estimates use the trend model. Rows 2 through 4 of this table restrict the sample to include only years falling fixed numbers of years past the law change. For example, row 2 includes all the prelaw-change years, the year of the law change (year 0), plus 5 additional years, for a total of 6 years after the prelaw-change period. SE = standard error. Standard errors are in parentheses, where * = significant at 5% and ** = significant at 1%.

It is also the committee’s view that additional analysis along the lines of the current literature is unlikely to yield results that will persuasively demonstrate a causal link between right-to-carry laws and crime rates (unless substantial numbers of states were to adopt or repeal right-to-carry laws), because of the sensitivity of the results to model specification. Furthermore, the usefulness of future crime data for studying the effects of right-to- carry laws will decrease as the time elapsed since enactment of the laws increases.

If further headway is to be made on this question, new analytical approaches and data sets will need to be used. For example, studies that more carefully analyze changes in actual gun-carrying behavior at the county or even the local level in response to these laws may have greater power in identifying the impact of such laws. Surveys of criminals or quantitative measures of criminal behavior might also shed light on the extent to which crime is affected by such laws.

7

Firearms and Suicide

While much attention surrounding the debate over firearms has focused on criminal violence in general, and homicide in particular, suicide is the most common cause of firearm-related death in the

United States (National Center for Health Statistics, 2003; see Table 3- 3). Do guns increase the lethality or frequency of suicide attempts? A large body of literature links the availability of firearms to the fraction of suicides committed with a gun. Yet, a central policy question is whether changes in the availability of firearms lead to changes in the overall risk of suicide.

Despite the clear associations between firearms and gun suicide, answering this broader question is difficult. Box 7-1 sketches out a conceptual framework describing various mechanisms by which firearms may be associated with rates of suicide. The fundamental issue is the degree to which a suicidal person would simply switch to using other methods if firearms were less available. On one hand, if substitutes were easily enough available, then gun restrictions might change the typical method of suicide yet have no effect on the overall risk of suicide at all. On the other hand, there are at least two mechanisms by which guns might directly cause an increase in the risk of completed suicide. First, guns may provide a uniquely efficient method of self-destruction so that access to a gun could lead to a higher rate of completed suicide. It is often stated, for example, that easy access to firearms could increase the rate of completed suicide among persons with transient suicidal feelings because such access might increase the likelihood of an attempt with a lethal outcome. Second, the induction hypothesis proposes that the le-

152

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153

BOX 7-1

Conceptual Framework

Why might firearms access be associated with rates of suicide?

Direct Causality: Firearms might directly increase the risk of suicide. The instrumentality hypothesis proposes that if guns were inherently more lethal than other methods, then access to a gun could lead to a higher rate of completed suicide. The method selection or induction hypothesis proposes that firearms might be preferred over other methods because their quickness and effectiveness might decrease some of the other “costs” of a suicide attempt.

Spurious Correlation: Firearms might be associated with suicide but have no direct effect. Instead, there may be unmeasured confounders associated with both access to firearms and the propensity to commit suicide. In this case, if substitutes were easily enough available, gun access restrictions might reduce the incidence of gun suicide yet have no effect on the overall risk of suicide. Two examples highlight this possibility:

•Reverse Causality: The risk of suicide might increase or decrease the likelihood of gun ownership. On one hand, some persons who are planning to commit suicide may seek out a gun specifically for this purpose (Cummings et al., 1997b;

Wintemute et al., 1999). On the other hand, family members might remove firearms from the home of someone who has made suicide attempts in the past.

•Other Confounders: Finally, there could be unmeasured and confounding

“third factors” associated with both suicide risk and gun ownership, which could lead to an apparent (but noncausal) association between guns and suicide. Indi- vidual-level confounders might include propensities for social isolation and mistrust of others. For example, if persons who are prone to own guns because of their mistrust of others were also at greater risk for suicide, whether or not they owned guns, there could be a noncausal statistical association between gun ownership and suicide. Community-level confounders could also explain a link between gun ownership and suicide risk. For example, high levels of “social capital” might be associated with lower rates of defensive gun ownership, as well as with higher levels of social support for individuals at risk for suicide (Hemenway et al.,

2001). Defensive gun use may also be correlated with particular cultural attitudes toward mental health services and individual problem-solving strategies; for accidental historical reasons or for specific cultural reasons, communities with higher levels of defensive gun ownership might also be communities that invest less heavily in “safety net” public services or with less access to mental health services.

thality of a gun might itself increase the likelihood of a suicide attempt among gun owners: persons who would prefer the efficiency of a gun would be less likely to make an attempt if a gun were not available. Ultimately, it is an empirical question whether access restrictions lead to substantial reductions in the rates of suicide.

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In this chapter we review studies of the relationship between household gun ownership and the risk of suicide.1 We review both studies that assess the relationships at aggregated geographic levels and those that look at the relationship between access and suicide at the level of the individual or household. Many studies conducted at aggregate levels rely on proxy measures of gun ownership; because these are so widely used, we devote special attention to discussing the pros and cons of using proxies for household gun ownership in ecological studies. Many individual-level studies of suicide use retrospective, case-control study designs; because the strengths and limitations of such a study design may be unfamiliar to some readers, we also discuss this methodology in some detail, with an explanation of the measures of association used in case-control studies presented in an appendix to the chapter. We then summarize the handful of studies that have evaluated the effects of specific gun laws on suicide. The final section presents the committee’s conclusions.

ECOLOGICAL STUDIES OF GUN OWNERSHIP

AND THE OVERALL RISK OF SUICIDE

The great majority of research on suicide and gun ownership has been “ecological,” in which the unit of observation is the community rather than the individual, comparing measures of household gun ownership rates to the rates of completed suicide. In some cases, the comparisons are allowed to vary over time; in all cases, comparisons are made across several geographic regions. Ecological studies of gun ownership and suicide in the United States are summarized in Table 7-1.

Cross-Sectional Associations

Almost all ecological studies using cross-sectional data, both within the United States and across countries, have found that both gun suicide rates and the fraction of suicides committed with a gun are higher in geographic areas with a higher prevalence of household gun ownership. This association has been reported by investigators across the spectrum of the gun control debate. It has been found across cities, states, regions, and nations (Kleck and Patterson, 1993; Azrael et al., 2004; Killias, 2001), and it contrasts with the more variable association between gun ownership rates and the fraction of homicides committed with a gun.

1Studies were identified using various search engines, by a search for book chapters and unpublished studies identified through personal communication with researchers in the field, and by review of the reference lists of previous publications. A particular effort was made to find studies in the firearms policy literature, reviewed for other chapters of this volume, which may have examined suicide as a secondary focus of the investigation.

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155

However, the most important policy question is not whether gun access increases the risk of gun suicide, but whether gun access increases the overall risk of suicide. Many cross-sectional studies have reported a positive, bivariate association between gun ownership rates and overall suicide rates across cities, states, and regions of the United States, but the relationship is much smaller and less precise than the association between gun ownership rates and gun suicide rates. The association between gun ownership and overall suicide also appears to be sensitive to the details of the measures and the statistical models being used.

U.S. Studies

Several ecological studies by Birckmayer and Hemenway (2001) and by Miller et al. (2002a, 2002c) have focused on age-specific suicide rates by region and state. Their gun ownership measures include survey estimates of handgun and overall gun ownership from the GSS and, as a proxy measure, the fraction of suicides committed with a firearm. Before controlling for other social variables, Birckmayer and Hemenway find a positive association between regional GSS-reported rates of gun ownership and age-specific rates of suicide in every age group. After controlling for divorce, education, unemployment, urbanization, poverty, and alcohol consumption, they find a modest positive association between gun ownership and suicide risk for youth ages 15 to 24 (b = .35, 95% confidence interval .05 to .65) and for adults age 65 and over (b = .62, 95% C.I. .40-.84), but not for working-age adults between ages 25 and 64. Subsequent studies from the same research group use other model specifications, with varying results. For example, Miller et al. (2002a) do not incorporate control variables; they find a positive association between gun ownership and overall suicide rates in all age groups (incidence rate ratio 1.14; 95% CI 1.01-1.24) and a negative association between gun ownership and nongun suicide (IRR .87, 95% CI

.77-.97) that is more pronounced for persons 45 years and older, suggesting greater substitution among methods in older age groups.

Duggan (2003) undertook a similar age-specific analysis, using subscriptions to the gun magazine Guns & Ammo as his proxy for gun ownership. Like Miller et al., Duggan did not include other covariates in his regression models and, like Miller et al., he found a positive and significant bivariate association between gun ownership and suicide across states. But Duggan also found a significant positive association between gun magazine subscription and nongun suicide for youth ages 10 to 19. The association between the gun proxy and nongun suicide shifts from positive to negative between ages 20 and 69 and becomes negative and statistically significant for persons over age 69. He concludes that the positive association between gun magazine subscriptions and nongun suicide among youth is evidence

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TABLE 7-1 Ecological Studies of Associations Between Firearms Prevalence and Suicide in the United States

	Unit of	Gun	Subjects;
Source	Analysis	Measure	Strata
Duggan	50 states	Proxy: Guns	10 yr. age
(2003)	1996	& Ammo	groups
Hemenway	9 regions	Survey: GSS
and Miller	1988-1997	(household
(2002)		handgun
		ownership)

Miller et al.	9 regions	Survey: GSS,	Children
(2002b)	50 states	BRFSS	5-14
	1988-1997	Proxy: Cook
		index, FS/S
		(adult only)
Miller et al.	9 regions	Survey: GSS,	Adult
(2002c)	50 states	BRFSS	women
	1988-1997	Proxy: Cook
		index , FS/S
Miller et al.	9 regions	Survey: GSS,	10-yr. age
(2002a)	50 states	BRFSS	groups
	1988-1997	Proxy: Cook
		index, FS/S
Birckmayer	9 regions	GSS	10-yr age
and	1979-1994		groups
Hemenway
(2001)
Azrael et al.	9 regions	Survey: GSS,
(2004)	50 states	BRFSS, HICRC
	1994-1998	Proxies: FS/S,
		UFDR,
		Guns & Ammo,
		NRA
		membership

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	Results:	Results:	Results:
	Guns and	Guns and	Guns and
Control	Gun	Nongun	Overall
Variables	Suicides	Suicides	Suicides
None	all ages +	10-19: +	all ages +
		20-69: 0
		70+: –
Major	+	–	+
depression,
suicidal
thoughts, and
urbanization, OR
education, OR
unemployment,
OR
alcohol
consumption
Poverty,	+	0	+
education,
urbanization
Poverty,	+	BRFSS:+	+
urbanization		Others: 0
None	all ages +	<45: 0	all ages +
		45+: –
Divorce,	15-24: +	0	15-24: +
education,	25-44: 0		25-64:0
unemployment,	45-84: +		65+: +
urbanization
None	+	n/a	n/a

continued