A Farewell to Firearms? Guns and Murders Through the Looking Glass of Cost-Be...
Thesis_Final_Draft
1. Drew J Wilkie
ECON 3610-001
Spring 2016
Final Paper
An Econometric Analysis of Firearm Death Rates in the United States
In recent years, gun control has reemerged as a topic of national debate in the
United States. Highly publicized mass shootings in South Carolina, Connecticut, Colorado,
California, and other states have caused policymakers and pundits to bring forth numerous
proposed explanations for why the U.S. experiences the highest rate of death due to
firearms among the world’s major industrialized nations (Gunpolicy.org, 2016).
This paper will examine some of these proposed explanations for high firearm death
rates in America, in an attempt to determine whether or not there is a measurable amount
of validity to any these claims. It is my hope that this work will shed some light on the
potential causes of what has become such a contentious and politically-charged issue.
Literature Review
Republican lawmakers, such as Speaker of the House Paul Ryan, have claimed that
mental illness is the primary driver of the high rate of gun death in America. The CEO of
the National Rifle Association, Wayne LaPierre, has also drawn the correlation between
firearm death rates and mental health (Kliff, 2012). On the other hand, Democrats such as
President Barack Obama and Secretary of State Hillary Clinton have argued that weak gun
laws are to blame (HillaryClinton.com, 2016). Furthermore, reports and data released by
the Centers for Disease Control have suggested that poverty and unemployment may be
primary factors in gun death rates. In one CDC study, 86% of gun violence perpetrators in
Delaware were found to have been unemployed in the quarter preceding the commission of
the crime (Sumner et al., 2015).
2. The effectiveness of gun control has been studied in the past. Data from Australia
have suggested that gun control reform, and the tightening of gun laws, have the effect of
reducing firearm death rates. In one study, researchers found that in the roughly two
decades before gun control reforms, there were thirteen mass shootings in Australia; in the
decade following such reforms, there were zero mass shootings (Chapman et al, 2006).
Furthermore, that same study found that declines in firearm death rates doubled their pace
after gun control reforms took place.
Researchers in Canada obtained similar results when studying the effects of more
stringent gun laws on male suicide rates, noting an overall drop in total suicides after such
laws were passed (Gagne et al., 2010).
Researchers in the U.S. have also examined the effectiveness of gun laws on
mortality rates in this country. One study found that the three laws which most effectively
reduced firearm death rates were universal background checks, ammunition background
checks, and ID requirement for firearms (Kalesan et al., 2016).
This study also suggests that strict gun laws may play a greater role in reducing
suicides and gun deaths than would an increased focus on mental health, given that suicide
is often highly correlated with acute and/or chronic mental illness. Despite mentally ill
people having an increased risk of committing suicide (with suicides accounting for over
50% of firearm deaths in the U.S.), and despite the focus of the media on mass shootings
committed by mentally ill gunmen, epidemiological studies have shown that people with
mental illness are actually rarely violent (Swanson et al., 2015).
3. Data and Methodology
In examining the causes of firearm death rates in the U.S., I sought to test variables
which would reflect some of the prevailing theories being discussed in the media, within
the context of the existing literature on the subject.
Firearm death rates per 100,000 people in 2014, by state, (dependent variable)
were obtained from the U.S. Centers for Disease Control and Prevention. Firearm death
rates comprise all types of mortality as a result of firearms, such as homicides, suicides,
justified shootings, and negligent discharges.
Unemployment rates in 2014, by state, were obtained from the U.S. Bureau of Labor
Statistics. Data on personal income per capita in 2014, by state, were obtained from the
U.S. Bureau of Economic Analysis. The natural log of income per capita was used here, due
to the absolute values of income being much greater than the values of the other variables
in the model. The 2014 Gini index for each state was obtained from the U.S. Census Bureau.
These three economic variables were used in order to test the potential effects of poverty
and inequality on firearm death rates.
Data on the estimated percentage of people with any mental illness in 2014, by
state, were obtained from the U.S. Substance Abuse and Mental Health Services
Administration. Lastly, data on the relative strength of state gun laws were obtained from
the U.S. Law Center to Prevent Gun Violence. The LCPGV utilizes a point system which
ranks each state by the relative strength of its gun laws.
It is important to note that firearm death rates are not included as a variable in
these rankings, which if included, could corrupt the data. It is also important to note that
the states are ranked from 1 to 50 on the relative strength of their gun laws, with 50 being
4. the weakest laws in the nation, and 1 being the strongest. Therefore, the b3(Laws) variable
will have a positive sign, as weak laws will have a higher state ranking, and theoretically,
will correlate with higher death rates. The preliminary hypothesized regression equation
is as follows:
Firearm Death Rate = b0 + b1(UE) – b2(LogIncome) + b3(Laws) + b4(MI) - b5(Gini)
The independent variables are: unemployment rate (UE), log personal income per
capita (LogIncome), gun laws ranking (Laws), estimated percentage of people with a
mental illness (MI), and the state Gini coefficient (Gini).
Empirical Results
Figure 1 Coefficient Standard Error T-Stat P-Value VIF
Intercept 13.15182591 39.15714841 0.335872923 0.738563107 n/a
UE Rate 0.847543636* 0.32590996 2.600545366 0.012626737 1.512
Log Income -0.966889309 3.270880369 -0.295605219 0.768922158 2.166
GunLaws Rank 0.203394185* 0.029680636 6.852756943 1.87964E-08 1.658
Mental Illness 0.425345727 0.259537925 1.6388577 0.108374902 1.495
Gini Index -20.30429415 20.00752752 -1.014832749 0.315733723 1.398
Figure 2 Mean Median Mode Range
UE Rate 5.746 6 6.8 5.2
Log Income 10.705 10.704 n/a 0.633
GunLaws Rank 25.16 24 44 49
Mental Illness 18.704 18.815 19.81 7.69
Gini Index 0.462 0.463 0.482 0.093
The resultant model has a sample size of n = 50, and at the 5% level of significance,
has an adjusted R2 value of .68, indicating that the data fit the model fairly well. Of the five
variables utilized in this study, the strength of a state’s gun laws, and the state’s
unemployment rate, were the statistically significant variables in the model (indicated by
an asterisk in Figure 1).
5. The stronger a state’s gun laws, the higher on the ranking list it will be, and
therefore, the lower its rank digit will be. Thus, for each downgrade in the strength of its
gun laws, a state’s gun death rate increases by .203 deaths per 100,000 people.
Furthermore, with each unit increase in a state’s unemployment rate, that state’s gun death
rate increases by .847 deaths per 100,000 people.
The other three variables in the model were not significant at the 5% level. Personal
income per capita and the Gini index each have a negative effect on gun death rates,
whereas a state’s estimated percentage of mentally ill people has a positive effect on gun
death rates.
Theoretical Considerations and Conclusions
The results of this study lend credence to the liberal explanations for the high rate of
deaths by firearm in the U.S., specifically that weak gun laws and poor economic well-being
are to blame. Interestingly, this model suggests that unemployment has a substantially
higher effect on the rate of gun deaths than does gun control. This could be due to the fact
that unemployed citizens are more likely to resort to crime in order to survive and make
ends meet. It could also be due to the psychological effects of unemployment and poor
economic outlook, such as depression and anxiety, which correlate with an elevated risk of
suicide. Self-inflicted gunshot wounds are the most common method of committing suicide
in the United States.
While this particular model does not suffer from multicollinearity or
heteroskedasticity, there are factors to consider beyond the scope of these data. For
instance, major cities (such as Denver, New York, and Chicago) tend to have gun laws that
are stricter than those of the states in which they are located. Major cities also tend to see
6. higher levels of personal income per capita, and higher levels of inequality. Therefore, in
rural states that happen to have a major city, city data could skew the data for the rest of
the state. An additional study which focuses on specific geographic areas within a
particular state could help solve this problem.
Furthermore, it would be interesting to create a similar study that is longitudinal in
nature, in order to investigate the effects of increased or decreased gun control over time.
However, such a study is beyond the scope of this assignment, and a complete data set
could be difficult to gather.
Ultimately, the results of this study are not groundbreaking. It has been well
established through studies conducted around the world, especially in Europe, Australia,
and Canada, that stricter gun laws are strongly correlated with low rates of gun death.
Furthermore, one need not look further than inner city neighborhoods in the U.S. to see
that economic privation and crime almost always exist alongside elevated rates of gun
violence and death.
Gun control is a controversial issue in this country, given the fact that our
Constitution includes the Second Amendment, which rather ambiguously guarantees
American citizens the right to keep and bear arms. Furthermore, it is extremely unlikely
that the Second Amendment will ever be fully repealed. However, the ambiguity inherent
in its verbiage allows some legislative flexibility with regard to firearms management, and
it is my hope that this ambiguity allows common sense gun control to become the norm in
this country, instead of remaining the exception. Lastly, an increased focus on lifting the
poor out of poverty through employment opportunities would more than likely have a
profound impact on reducing the rate of gun deaths.
7. Bibliography
Chapman, S., Alpers, P., Agho, K., & Jones, M. (2006). Australia's 1996 gun law reforms: Faster
falls in firearm deaths, firearm suicides, and a decade without mass shootings. Injury
Prevention, 12(6), 365-372. doi:10.1136/ip.2006.013714
Firearm Mortality by State: 2014. (2016, February 03). Retrieved March 1, 2016, from
http://www.cdc.gov/nchs/pressroom/sosmap/Firearm.htm
Gagne, M., Robitaille, Y., Hamel, D., & St-Laurent, D. (2010). Firearms regulation and
declining rates of male suicide in Quebec. Injury Prevention, 16(4), 247-253.
doi:10.1136/ip.2009.022491
Gini Index by State: 2014. (2014). Retrieved April 11, 2016, from
http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml
Kalesan, B., Mobily, M. E., Keiser, O., Fagan, J. A., & Galea, S. (2016). Firearm legislation and
firearm mortality in the USA: A cross-sectional, state-level study. The Lancet.
doi:10.1016/s0140-6736(15)01026-0
Kliff, S. (2012, December 21). The NRA wants an ‘active’ mental illness database [Web log
post]. Retrieved March 15, 2016, from
https://www.washingtonpost.com/news/wonk/wp/2012/12/21/the-nra-wants-an-active-
mental-illness-database-thirty-eight-states-have-that-now/
Law Center to Prevent Gun Violence - Annual Gun Law State Scorecard 2014. (2014). Retrieved
March 1, 2016, from http://gunlawscorecard.org/
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the USA, 2001-2010. Archives of Disease in Childhood, 99(4), 331-335.
doi:10.1136/archdischild-2013-304642
8. Sumner, S., Mercy, J., Hillis, S., Maenner, M., & Socias, C. (2015). Elevated Rates of Urban
Firearm Violence and Opportunities for Prevention—Wilmington, Delaware (Rep.).
Washington, DC: National Center for Injury Prevention and Control Centers for Disease
Control and Prevention
Swanson, J. W., Mcginty, E. E., Fazel, S., & Mays, V. M. (2015). Mental illness and reduction of
gun violence and suicide: Bringing epidemiologic research to policy. Annals of
Epidemiology, 25(5), 366-376. doi:10.1016/j.annepidem.2014.03.004
Substance Abuse and Mental Health Services Administration, Center for Behavioral Health
Statistics and Quality. (February 28, 2014). The NSDUH Report: State Estimates of
Adult Mental Illness from the 2011 and 2012 National Surveys on Drug Use and
Health. Rockville, MD.
Unemployment Rates for States. (2016, February 26). Retrieved March 10, 2016, from
http://www.bls.gov/lau/lastrk14.htm
University of Sydney: Guns in the United States - Firearms, gun laws and gun control. (2016).
Retrieved April 10, 2016, from http://www.gunpolicy.org/firearms/region/united-states
