Effects of Maryland's Law Banning "Saturday Night Special" Handguns on Homicides

Daniel W. Webster, Jon S. Vernick and Lisa M. Hepburn

From the Center for Injury Research and Policy and the Center for Gun Policy and Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Small, inexpensive, often poorly made handguns known as "Saturday night specials" are disproportionately involved in crime. Maryland banned the sale of Saturday night specials effective January 1, 1990. During the 2 years between the law's passage in 1988 and its effective date, legal handgun sales in Maryland were 34% higher than expected (p = 0.09). Interrupted time-series analysis of age-adjusted homicide rates for 1975–1998 with statistical controls for trends in two neighboring states, social and economic variables, and temporal patterns in Maryland's homicide rates was used to assess the effect of the law. Estimates of the Saturday night special ban effects depended on the assumption made about the timing of the law's effects. Models that assumed a delayed or gradual effect of the Saturday night special ban produced estimates indicating that firearm homicide rates were 6.8–11.5% lower than would have been expected without the Saturday night special ban (p <= 0.05). The model that assumed an immediate, constant change in response to the law showed no law effect, unless an outlier was excluded from the analysis. Excluding this outlier, the model estimated a 15% increase in firearm homicides associated with the Saturday night special ban. None of the models revealed significant law effects on nonfirearm homicides.

evaluation studies; firearms; homicide; violence

Abbreviations: AR, autoregressive; ARIMA, autoregressive integrated moving average


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
"Saturday night specials" or "junk guns" are colloquial names for small, inexpensive handguns of low quality. Saturday night specials' short barrel length (usually <=3 inches or 7.62 cm) makes them easy to conceal but decreases their accuracy. Low quality materials and construction make Saturday night specials prone to malfunctions. For these reasons, Saturday night specials are generally viewed as unreliable weapons for self-defense and a potential hazard to consumers (1Go). Saturday night specials have traditionally been low-caliber weapons, but many Saturday night specials now being produced fire medium- and high-caliber ammunition (2Go) and, consequently, are more deadly (3Go).

Saturday night specials are prominent among handguns involved in crime. In 1993, Saturday night special handguns accounted for eight of the 10 gun models most commonly confiscated by law enforcement agencies in California (1Go). In 1999, Saturday night specials accounted for five of the top 10 firearm models recovered by police in a geographically diverse set of 32 US cities and seven of the top 10 firearm models recovered from juveniles (4Go).

The involvement of Saturday night specials in crime appears to be disproportionate to their share of the handgun market. Comparing police trace requests per 1,000 guns manufactured over a 4-year period, Wintemute (1Go) found that handguns made by manufacturers that specialize in Saturday night specials were 3.4 times more likely to be traced to crime than were handguns made by manufacturers that do not produce Saturday night specials. Handgun purchasers with a history of arrest are more likely than other handgun purchasers to select a Saturday night special (5Go). Among handgun purchasers with no prior criminal record, Saturday night special purchasers were more likely than other purchasers to be involved in crimes subsequent to their gun purchase (5Go).

Although Saturday night specials appear to be overrepresented in crime, the effects of Saturday night special bans on violent crime are uncertain. Although some criminals may prefer small, inexpensive handguns, they may still be able to find acceptable weapon substitutes when Saturday night special sales are prohibited. Furthermore, Saturday night special bans may deter handgun acquisition by low-income persons; opponents of Saturday night special bans argue that this will leave poor persons less able to defend themselves against violent crime.

Four states enacted laws in the late 1960s and early 1970s requiring that handguns sold by licensed dealers meet certain standards that, in effect, banned the sale of Saturday night specials by licensed dealers. Kleck and Patterson (6Go) examined the effects of these four state laws using a cross-sectional design and 1990 city-level data. After controlling for a broad range of variables related to levels of violence including other gun laws, they found no statistically significant effects of Saturday night special bans on violent crime. However, the cross-sectional, quasi-experimental design of the study leaves its findings vulnerable to potential biases.

In May 1988, Maryland passed a law that was intended as a ban of the sale of Saturday night special handguns. The law created a Handgun Roster Board to determine which handguns could be legally sold in Maryland as of January 1, 1990. The law instructs the Board to consider nine factors when deciding whether to approve a particular gun model for sale, including its concealability, quality, reliability, and utility for legitimate uses (7Go). Opponents of the legislation mounted a highly publicized but unsuccessful campaign to overturn the law via a referendum in November 1988 (8Go).

Increases in gun sales prior to the implementation of restrictions on new gun sales can be an unintended "side effect" of gun control laws (9Go). Evaluations of gun control laws, therefore, may need to account for this effect. During 1988, potential handgun buyers in Maryland were likely to see news stories and advertisements and/or to receive mailings from antiban groups that informed them that it would no longer be possible to buy inexpensive handguns from licensed dealers after the law's effective date. Information disseminated by some groups working to overturn the law via referendum suggested that all handguns might be banned for sale after the law's effective date. Gun dealers also had an incentive to clear out their inventories of handguns that were likely to be banned as of January 1, 1990. Together, these conditions could have led to an increase in handgun sales in Maryland during the period just prior to the law's effective date.

The current study was designed to estimate the effect of Maryland's ban of Saturday night specials on homicide rates. In contrast to many previous evaluations of gun control laws, our evaluation examined several different methods for specifying the temporal relation between the law and hypothesized effects on homicides. These specifications were informed by analyses of the association between Maryland's Saturday night special ban and handgun sales by licensed dealers in the state.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Study design
To estimate the association between Maryland's Saturday night special ban and homicide rates, we used an interrupted time-series design, with the homicide rates of two neighboring comparison states used as covariates in the statistical models. Trends for firearm and nonfirearm homicide rates were analyzed separately to determine whether changes were specific to gun homicides and to examine possible weapon substitution effects.

Data
The annual age-adjusted homicide rate was the primary outcome for the study. Homicide data for the years 1975–1998 were obtained from the National Center for Health Statistics' multiple cause of death data files using International Classification of Diseases, Ninth Revision, external cause of death codes E960–969. Population data were obtained from the US Census Bureau. Age-adjusted homicide rates were calculated using the direct method with the age structure of the 1980 population as the standard.

The intermediate outcome of interest was annual per capita handgun sales by licensed dealers in Maryland. Data on this outcome were provided by the Maryland State Police for the years 1976 through 1998. Comparable data were obtained from the neighboring state of Pennsylvania but were available only from 1983 through 1998. Historical data on handgun sales were not available from other nearby states for a large portion of the study period.

Covariates considered in the statistical models are discussed below. Income and poverty data for the years 1975–1998 were collected from US Census documents (10Go, 11Go). Data on unemployment were obtained from the US Bureau of Labor Statistics (12Go).

Analyses
Estimating law effects on handgun sales.
For per capita sales of handguns, we examined whether handgun sales during the period between the law's passage and its effective date (1988–1989), and then the period after Saturday night specials were banned (1990–1998), were significantly different from what would have been expected if the law had not been passed. To test these hypotheses, we used auto-regressive integrated moving average (ARIMA) time-series analytical techniques (13Go) with covariates. Dummy variables were included in the models to represent the pre- and postlaw periods.

ARIMA models can be used to identify and control for autocorrelation in the data and to predict the value of an outcome variable at a given time (Yt) based upon previous values of that variable (e.g., Yt-1, Yt-2) and exogenous variables (Xt). For accurate estimation of the effect of an intervention using ARIMA models, the time series being analyzed must be stationary, that is, have a constant mean and variance over time. To obtain a constant mean, the series was first differenced so that the new series represented the annual change in handguns legally sold per capita (Yt' = Yt - Yt-1). Exogenous variables for these analyses include indicators of purchasing power (per capita income, median family income, household poverty rate, male unemployment), lagged firearm homicide rates (a correlate of the demand for handguns) (14Go, 15Go), and per capita handgun sales in Pennsylvania. Covariates not significantly associated with the annual change in handgun sales were excluded from the final model.

Estimating law effects on homicides.
Homicide rates in Maryland were increasing rapidly before the law was implemented and, therefore, the series was transformed into first differences (yt - yt-1) to produce a stationary series for analysis. Thus, the outcome modeled was the annual change in homicide rates rather than the actual rates.

Explanatory variables considered for inclusion in each of the models were as follows: the percentage of adult males that were unemployed, the percentage of the population below the poverty line, per capita income, and the percentage of the population whose race was Black. Homicide trends within the United States vary by region (16Go) and are influenced by factors that are difficult to measure directly, such as drug markets and changing social norms (17Go). To control for unmeasured factors common to the mid-Atlantic region, we included age-adjusted homicide rates for the neighboring states of Pennsylvania and Virginia as covariates in the models.

Although not the primary focus of this study, the initial effects of a second gun control law, the Maryland Gun Violence Act of 1996, effective October 1, 1996, were controlled for in the model. This law had three main provisions: 1) To deter gun trafficking, each eligible handgun purchaser was limited to one handgun purchase per month; 2) criminal background checks and registration for handguns sold by private gun owners were mandated; and 3) greater authority was given to police and judges to confiscate firearms owned by domestic violence offenders. The effects of this law were assessed using a dummy variable that indicated whether the law was in effect for all or most of the year.

Because the outcome time series was differenced, all explanatory variables were also differenced. Cross-correlation functions were calculated to determine whether any of the explanatory variables should be lagged. Explanatory variables were removed one by one from each model in a backward, step-by-step fashion if the variable did not have a theoretically plausible and statistically significant effect on homicide rates (p < 0.10), and if its removal from the model did not change the estimated effect of the law by more than 10 percent.

The manner in which the pre- and postlaw effects of the Saturday night special ban were specified in the models was informed by our analysis of the law's effects on handgun sales. Alternative transfer functions were used to contrast four different ways to estimate the temporal relation between the Saturday night special ban and the annual change in homicide rates: 1) an immediate, constant effect beginning in 1990; 2) a delayed, constant effect beginning 1 year after the law's effective date; 3) an immediate, gradual effect that increased linearly during the first 4 years the law was in effect; and 4) a delayed, gradual effect that increased linearly for 4 years beginning 1 year after the law went into effect. The rationale behind the gradual effect models is based on previous research indicating that, among in-production Saturday night specials traced to youth crime, approximately 35 percent are connected to crimes within a year of their first sale, and the vast majority were sold less than 4 years before their involvement in crime (18Go). Only slight increases in the cumulative number of a "cohort" of Saturday night specials sold in a given year were traced to crime more than 4 years after their sale.

The adequacy of the models was assessed to ensure that the residuals were randomly distributed over time with no evidence of autocorrelation. In addition to carefully examining temporal plots of the residuals, we formally tested whether the models produced systematic error in predicting Maryland's homicide trends. To test whether there was any linear trend in the error term, we regressed the year variable on the model error term. Evidence of autocorrelation in the error term was assessed by examining the autocorrelation function and the partial autocorrelation function of the residuals for final models. Overall model fit was assessed by visual inspection of plots of the observed and model-predicted trends and by the Akaike Information Criterion statistic (19Go).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Saturday night special ban effects on handgun sales from licensed dealers
Our final model of per capita handgun sales in Maryland included per capita handgun sales in Pennsylvania, lagged firearm homicide rates in Maryland, and the prelaw and postlaw dummy variables. The prelaw period between the introduction of the legislation in early 1988 and its ultimate implementation on January 1, 1990, was associated with annual changes in those years that were 34 percent higher than would have been expected if there had been no Saturday night special ban prelaw effect (p = 0.09). The annual change in per capita handgun sales dropped sharply in the first year the Saturday night special ban was in effect and was 15 percent lower during the entire postlaw period of 1990–1998 than would have been expected with no Saturday night special ban. However, this difference was not statistically significant.

Effect of Saturday night special ban on homicide rates
Table 1 summarizes the model estimates for the effects of Maryland's Saturday night special ban and of the 1996 gun law on age-adjusted firearm homicide rates for each of the four alternative models for specifying the timing of the effects of the Saturday night special ban. In addition to the law-related variables, each model includes the following covariates that were significantly associated with annual changes in firearm homicide rates: age-adjusted firearm homicide rates for both Pennsylvania and Virginia, Maryland's male unemployment rate, and autoregressive (AR) process parameters of order 2 (AR(1) and AR(2)). The statistically significant negative AR(1) and AR(2) parameters in each model indicated that the change in firearm homicide rates in year t was negatively associated with the change in firearm homicide rates in the previous 2 years.


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TABLE 1. Estimates of the effects of Maryland's 1990 ban of SNS{dagger} handguns and the Maryland Gun Violence Act of 1996 on age-adjusted firearm homicide rates under various assumptions about the timing of hypothesized SNS ban postlaw effects{ddagger}

 
Table 1 depicts the model estimates for the gun law variables under four assumptions about the temporal relation between the post-Saturday night special ban effects and firearm homicide rates. The immediate, constant post-Saturday night special ban model estimated a 7.2 percent increase associated with the postlaw effects of the Saturday night special ban that was not statistically significant. Each of the three alternative postlaw effect specifications produced statistically significant negative associations between the Saturday night special ban and firearm homicide rates. These estimates ranged from -6.8 percent (95 percent confidence interval: -13.2, -0.3 percent) for the delayed start, gradual effect model to -11.5 percent (95 percent confidence interval: -17.3, -2.4 percent) for the delayed start, constant effect model. The model that assumed an immediate but gradual effect of the Saturday night special ban estimated that Maryland's age-adjusted firearm homicide rates were 8.6 percent lower (95 percent confidence interval: -14.5, -2.6) during the post-Saturday night special ban period than would have been expected without the ban. This model produced the best model fit of the four alternative models; the model that assumed an immediate, constant law effect fit the observed data least well.

Figure 1 contrasts trends in age-adjusted firearm homicide rates in Maryland with the rates predicted by the model that assumed a gradual Saturday night special ban effect beginning in 1990. In the postlaw period, the figure shows the observed rates in relation to those expected in the absence of the Saturday night special ban.



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FIGURE 1. Observed age-adjusted firearm homicide rates in Maryland during 1975–1998 versus rates predicted by an autoregressive integrated moving average regression model that assumes a gradual effect of the state's 1990 ban of "Saturday night special" handguns. During 1990–1998 the predicted series represents the rates that would have been expected without the Saturday night special ban.

 
The models revealed no statistically significant pre-Saturday night special ban effects on firearm homicides. However, the introduction of Maryland's 1996 gun law was associated with statistically significant reductions in firearm homicide rates ranging from 10.3 to 11.4 percent.

An analysis of model residuals revealed the presence of an outlier (year 1976) that, when excluded, had a significant effect on one of the four Saturday night special ban estimates. When the Saturday night special ban effect was assumed to be immediate and constant and the 1976 observation was excluded from the analysis, the ban was associated with a 15.1 percent increase in firearm homicide rates (95 percent confidence interval: 7.1, 23.1), and the preban effect was associated with a 12.1 percent increase (95 percent confidence interval: 5.9, 18.3).

The Saturday night special ban effect estimates under each of the four models were also sensitive to the inclusion of the AR(1) and AR(2) parameters in the models to control for autocorrelation in the model residuals. When these pa-rameters are not included in the models, none of the Saturday night special ban effect estimates is statistically significant.

Each of the four post-Saturday night special ban specifications was also used in models that assessed whether age-adjusted nonfirearm homicide rates changed in response to the law (table 2). The ARIMA analysis indicated that an AR(4) model reflected the autocorrelation structure of this time series. Thus, each of the models included statistically significant AR(4) parameters. None of the other covariates was independently associated with changes in nonfirearm homicide rates, and excluding them from the models did not significantly affect the law-related estimates. There were no gun law effect estimates that approached statistical significance in any of the four alternative models.


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TABLE 2. Estimates of the effects of Maryland's 1990 ban of SNS* handguns and the Maryland Gun Violence Act of 1996 on age-adjusted nonfirearm homicide rates under various assumptions about the timing of hypothesized SNS ban effects{dagger}

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
This study demonstrates that estimates of the effects of Maryland's ban of Saturday night specials are highly dependent upon whether the intervention model assumed the full effects of the law would be realized immediately after its implementation. Models that assumed a delayed and/or gradual effect of the Saturday night special ban estimated statistically significant reductions in firearm homicide rates ranging from 6.8 to 11.5 percent associated with the ban and fit the data better than the immediate, constant law effect model. The magnitude of these effect estimates is consistent with our prior research that indicated crime guns recovered in 1996 and 1997 in Baltimore, Maryland, were much less likely to be banned Saturday night specials than was the case in 15 other cities without a Saturday night special ban (8.7 percent vs. 19.7 percent of crime guns) (20Go).

A model based on an immediate, constant law effect assumption produced an estimate of a statistically significant 15 percent increase in firearm homicide rates associated with the Saturday night special ban and a 12 percent increase associated with the 2-year, preban period. This law effect model is suspect on theoretical grounds for three reasons. First, the sharp rise in handgun sales during the 2 years prior to the law's effective date suggests that any effects of Saturday night special sales prevented in 1990 would likely be offset by increased sales in 1988 and 1989. Second, Saturday night special sales prevented during 1990 could decrease homicide risks for several years after the prevented sale. Finally, it seems logically inconsistent that both the prelaw period of higher handgun sales and the Saturday night special ban would each increase homicides.

The plausibility of our estimates of the effects of the law on homicides should also be evaluated within the context of relevant theories about how Saturday night special handgun availability might influence homicide rates. Many homicides stem from spontaneous altercations that end in gunfire (21Go). Ready access to a firearm can increase the lethality of violent altercations because firearms are much more lethal than other personal weapons (21Go, 22Go). Prohibiting the sale of Saturday night special handguns could reduce the likelihood of these fatal encounters by either decreasing handgun ownership (particularly among high-risk persons) by making handguns more expensive or decreasing the incidence of concealed gun carrying. Aggregate handgun sales in Maryland were 15 percent lower after the ban than would have been expected without the law. However, this reduction was not significantly significant. Because legal purchasers of Saturday night specials are more likely than other handgun purchasers to have been arrested prior to the purchase and to be subsequently arrested for violent crimes involving guns (5Go), the ban may have nevertheless significantly reduced handgun acquisition by persons at increased risk of homicide perpetration. The law may have also reduced concealed gun carrying by banning the sale of easily concealable handguns. Efforts to deter illegal gun carrying in high-crime areas have been shown to significantly reduce criminal shootings (23Go, 24Go).

The fact that the law's effects were specific to homicides committed with firearms increases the likelihood that the effects are attributable to the gun law and not to unmeasured factors that affect trends for all homicides. Furthermore, there was no evidence that the reduction in firearm homicide rates associated with the law was negated by an increase in homicides committed with other weapons.

Opponents of the law predicted that it would leave low-income citizens more vulnerable to crime by increasing the price of handguns and would increase the lethality of shootings, because criminals would acquire higher caliber substitutes for Saturday night specials. We could not examine these possible intermediate effects with the data available. Absent such data, the net effects of the law suggest that any negative consequences for homicide rates were apparently outweighed by the law's benefits.

Study limitations
This study did not assess the effects of Maryland's law on nonfatal violent crimes because of inadequacies of available surveillance systems. The Federal Bureau of Investigation's system of uniform crime reports is the only surveillance system that collects longitudinal data on nonfatal crime at the state or local level. Several analyses of this system caution against using data from the uniform crime reports on nonfatal crimes to make comparisons across time and place because of potential inconsistencies in reporting (25GoGo–27Go).

Homicide rates are determined by a multitude of factors, many of which cannot be measured by studies of this type. However, our models were accurate in predicting changes in firearm homicide rates in Maryland over time (figure 1). We used changes in regional homicide rates, as well as historical patterns of homicide rates within Maryland, in an attempt to control for variation that could not be accounted for by standard social, demographic, and economic covariates.

We could not control for the effects of one potentially relevant policy change, because its timing was so coincident with the implementation of the Saturday night special ban. A law that increased penalties for drug crimes committed with firearms went into effect in Maryland on July 1, 1989. It is possible that some or all of the estimated beneficial effects of the Saturday night special ban are attributable to this sentence enhancement law. However, previous research on the effects of laws that increase penalties for crimes committed with firearms has shown mixed results (28Go, 29Go). The most comprehensive and recent analysis found no evidence that these laws reduce homicides or other violent crimes (28Go). Furthermore, if the law did have a deterrent effect on homicides, one would expect these effects to be realized relatively soon after the law was adopted and to be relatively constant over time. Our data indicate, however, that homicide rates were higher than what would have been expected in 1989 and that reductions in homicide rates were most pronounced 2–4 years after the sentence enhancement law was implemented.

Finally, the study carefully assesses the effects of a single state's ban of Saturday night specials. Our findings may not generalize to other states that have banned Saturday night specials, and they may not accurately predict the effects of subsequent bans of Saturday night specials.

Conclusions
The findings from this study and our prior study of the effects of Maryland's Saturday night special ban on handguns used in crime (20Go) provide important lessons for gun policy development, implementation, and evaluation. Banning a particular category of guns is likely to significantly increase sales for those guns after the laws are passed but before they go into effect (14Go), and this should be considered in evaluations of such laws. Strategies for mitigating preban spikes in handgun sales include laws restricting handgun purchases to one per eligible buyer per month and limiting the amount of time between passage of such laws and their implementation. Our findings that Maryland's one-gun-per-month law was associated with a significant decrease in firearm homicide rates suggest that such laws may also have important independent effects. The findings concerning the effects of this law, however, must be viewed as preliminary because they are based on only 2 full years of postlaw data.

Our findings concerning the effects of Maryland's ban of Saturday night special handguns clearly demonstrate how gun law effect estimates can be sensitive to the assumptions made about the plausible timing of their effects. Further development and testing of theories about mechanisms by which specific gun control laws could affect gun availability to high-risk persons are needed. The implications of this research should inform future development of models to assess the ultimate impact of these laws on lethal violence.


    ACKNOWLEDGMENTS
 
This research was supported by grant R49/CCR302486 from the Centers for Disease Control and Prevention to the Johns Hopkins Center for Injury Research and Policy.


    NOTES
 
Correspondence to Dr. Daniel W. Webster, Center for Gun Policy and Research, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, Rm. 593, Baltimore, MD 21205-1996 (e-mail: dwebster{at}jhsph.edu).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Wintemute GJ. Ring of fire: the handgun makers of southern California. Sacramento, CA: Violence Prevention Research Program, University of California, Davis, 1994.
  2. Wintemute GJ. Firearm design and firearm violence: handguns in the 1990s. JAMA 1996;275:1749–53.[ISI][Medline]
  3. Zimring FE. The medium is the message: firearm caliber as a determinant of death from assault. J Leg Stud 1972;1:97–123.
  4. Bureau of Alcohol, Tobacco, and Firearms. Crime gun trace reports (1999) national report. Washington, DC: US Department of the Treasury, November 2000.
  5. Wintemute GJ, Parham CA, Wright MA, et al. Weapons of choice: previous criminal history, later criminal activity, and firearm preference among legally authorized young adult purchasers of handguns. J Trauma 1998;44:155–60.[ISI][Medline]
  6. Kleck G, Patterson EB. The impact of gun control and gun ownership levels on violence rates. J Quant Criminol 1993;9:249–88.
  7. MD Code Ann. § 36J(b)(2)(i)-(ix).
  8. Teret SP, Alexander GR, Bailey LA. The passage of Maryland's gun law: data and advocacy for injury prevention. J Public Health Policy 1990;11:26–38.[Medline]
  9. Roth JA, Koper CS. Impacts of the 1994 assault weapons ban: 1994–1996. Washington, DC: National Institute of Justice, March 1999.
  10. US Bureau of the Census. Statistical abstract of the United States. Washington, DC: US Bureau of the Census, 1975–1995.
  11. US Bureau of the Census. Current population report, consumer income, series P-60, poverty in the United States. Washington, DC: US Bureau of the Census, 1990–1996.
  12. US Bureau of Labor Statistics. Geographic profile of employment and unemployment. Washington, DC: US Department of Labor, 1975–1994.
  13. Box GEP, Jenkins GM. Time series analysis forecasting and control. 2nd ed. San Francisco, CA: Holden-Day, 1976.
  14. Kleck G. The relationship between gun ownership levels and rates of violence in the United States. In: Kates DB Jr, ed. Firearms and violence: issues in public policy. Cambridge, MA: Ballinger, 1984:99–135.
  15. McDowall D, Loftin C. Collective security and the demand for legal handguns. Am J Sociol 1983;88:1146–61.[ISI]
  16. Fox JA, Zawitz MW. Homicide trends in the United States: regional trends. Washington, DC: Bureau of Justice Statistics, US Department of Justice, March 2001. (http://www.ojp.usdoj.gov/bjs/homicide/region.htm).
  17. Blumstein A, Rivara FP, Rosenfeld R. The rise and decline of homicide—and why. Annu Rev Public Health 2000;21:505–41.[ISI][Medline]
  18. Kennedy DM, Piehl AM, Braga AA. Youth violence in Boston: gun markets, serious youth offenders, and a use-reduction strategy. Law Contemp Prob 1996;59:147–96.[ISI]
  19. Akaike H. A Bayesian extension of the minimum AIC procedure of autoregressive model fitting. Biometrika 1979;66:237–42.[ISI]
  20. Vernick JS, Webster DW, Hepburn LM. Effects of Maryland's law banning Saturday night special handguns on crime guns. Inj Prev 1999;5:259–63.[Abstract/Free Full Text]
  21. Cook PJ. The technology of personal violence. In: Tonry M, ed. Crime and justice: a review of the research. Vol 14. Chicago, IL: University of Chicago Press, 1991:1–71.
  22. Zimring FE, Zuehl J. Victim injury death in urban robbery: a Chicago study. J Leg Stud 1986;15:1–40.[ISI]
  23. Villaveces A, Cummings P, Espitia VE, et al. Effect of a ban on carrying firearms on homicide rates in 2 Colombian cities. JAMA 2000;283:1205–9.[Abstract/Free Full Text]
  24. Sherman LW, Rogan DR. Effects of gun seizures on gun violence: "hot spots" patrol in Kansas City. Justice Q 1995;12:673–93.
  25. Schneider VW, Wiersema B. Limits and use of the uniform crime reports. In: MacKenzie DL, Baunach PJ, Roberg RR, eds. Measuring crime: large-scale, long-range efforts. Albany, NY: State University of New York Press, 1990:21–48.
  26. Deidman D, Couzens M. Getting the crime rate down: political pressure and crime reporting. Law Soc Rev 1974;8:457–93.
  27. McCleary R, Nienstedt BC, Erven JM. Uniform crime reports as organizational outcomes: three time-series experiments. Soc Probl 1982;29:361–72.[ISI]
  28. McDowall D, Loftin C, Wiersema B. A comparative study of the preventive effects of mandatory sentencing laws for gun crimes. J Crim Law Criminol 1992;83:378–94.[ISI]
  29. Marvel TB, Moody CE. The impact of enhanced prison terms on felonies committed with guns. Criminology 1995;33:247–81.[ISI]
Received for publication December 11, 2000. Accepted for publication September 13, 2001.