Amicus Curiae Brief — United States, Petitioner v. Zackey Rahimi

Supreme Court briefOct 4, 2023

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No. 22-915

In the

Supreme Court of the United States

__________________

UNITED STATES,

Petitioner,

ZACKEY RAHIMI,

Respondent.

__________________

On Writ of Certiorari to the United States

Court of Appeals for the Fifth Circuit

__________________

BRIEF OF AMICUS CURIAE

CRIME PREVENTION RESEARCH CENTER

IN SUPPORT OF RESPONDENT

__________________

STEVEN W. DULAN

Counsel of Record

LAW OFFICES OF STEVEN W. DULAN, PLC

5311 Park Lake Road

East Lansing, MI 48823

(517) 332-3149

swdulan@stevenwdulan.com

Counsel for Amicus Curiae

Becker Gallagher · Cincinnati, OH · Washington, D.C. · 800.890.5001

TABLE OF CONTENTS

TABLE OF AUTHORITIES ....................................... ii

INTEREST OF AMICUS CURIAE............................. 1

SUMMARY OF ARGUMENT ..................................... 1

ARGUMENT ................................................................ 2

A. The Empirical Theory ............................................ 6

1. Literature Review ......................................... 13

2. Methodology .................................................. 15

3. Data ............................................................... 18

4. Results........................................................... 23

5. Robustness checks ........................................ 28

CONCLUSION .......................................................... 35

TABLE OF AUTHORITIES

Cases

District of Columbia v. Heller,

554 U.S. 570 (2008) .............................................. 2, 5

Kanter v. Barr,

919 F.3d 437 (7th Cir. 2019) .................................... 9

McDonald v. City of Chicago, Ill,

561 U.S. 742, 130 S. Ct. 3020,

177 L. Ed. 2d 894 (2010) .................................. 2, 3, 4

New York State Rifle & Pistol Ass'n, Inc. v. Bruen,

142 S. Ct. 2111, 213 L. Ed. 2d 387 (2022) ... 2, 3, 5, 9

State v. Miranda,

98 Ariz. 18, 401 P.2d 721 (1965), rev'd, 384 U.S.

436, 86 S. Ct. 1602, 16 L. Ed. 2d 694 (1966) ....... 4, 5

State v. Miranda,

104 Ariz. 174, 450 P.2d 364 (1969) .......................... 5

Statutes

18 U.S.C. § 922(g)(8)

............................. 2, 5-7, 12-16, 20, 23-25, 27, 29-35

Other Authorities

Ann Arbor, MI: Inter-university Consortium for

Political and Social Research [distributor],

2021-09-22.

https://www.openicpsr.org/openicpsr/project/10

0699/version/V11/view ........................................... 18

iii

Arthur Z. Berg, John R. Lott, Jr., and Gary A.

Mauser, “Expert Views on Gun Laws.”

Regulation, Winter 2019-2020, Vol. 42 ................. 15

Cameron, A.C. and Trivedi, P.K. (1998).

Regression Analysis of Count Data. Cambridge,

UK .......................................................................... 16

Clément

Chaisemartin

and

Xavier

D’Haultfoeuille,

Two-Way

Fixed

Effects

Estimators with Heterogeneous Treatment

Effects Am. Econ. Rev. 2020 .......................... 6, 7, 14

Alberto Chong and Pascual Restrepo, “Regulatory

Protective Measures and Risky Behavior:

Should We Be Saved from Ourselves?”

University of Ottawa Working paper, March

2014

(https://papers.ssrn.com/sol3/papers.cfm?abstra

ct_id=2405494) ....................................................... 12

Crime Prevention Research Center, “Updated:

Murder and homicide rates before and after gun

bans,” Crime Prevention Research Center, April

16,

2016,

(https://crimeresearch.org/2016/04/murder-andhomicide-rates-before-and-after-gun-bans/) ......... 10

Carolina Diez et al., State Intimate Partner

Violence-Related Firearm Laws and Intimate

Partner Homicide Rates in the United States,

1991 to 2005, Annals of Internal Med. (2017),

(https://www.acpjournals.org/doi/full/10.7326/M

16-2849) .............................................................. 6, 13

Donohue, J.J. and Levitt, S.D. (2020). The Impact

of Legalized Abortion on Crime over the Last

Two Decades. American Law and Economics

Review..................................................................... 21

Hahab Falahi, Jasem Mohamadi, Hojjat Sayyadi,

Iraj Pakzad, Ayoub Rashidi, Razi Naserifar,

Jahangir Abdil, Azra Kenarkoohi, “COVID-19

Vaccination, Peltzman Effect and Possible

Increase in Highrisk Behaviors: A Growing

Concern Related to Risk Compensation and

Reduced Compliance to Public Health

Protective Measures after Vaccines Rollout,”

Infect Disord Drug Targets. 2022;22(8):8-12,

(https://pubmed.ncbi.nlm.nih.gov/35440338/)....... 11

Eberhard Feess, “On the interplay of public and

private law enforcement with multiple victims,”

European Journal of Law and Economics,

(2015), Vol 39 ......................................................... 12

Federal Judicial Center, Reference Manual on

Scientific Evidence (3rd Edition). Washington,

DC: National Academies Press.............................. 23

John Fritze, “How a Second Amendment case at

the Supreme Court is putting gun rights groups

in a jam,” USA Today, July 12, 2023,

(https://www.usatoday.com/story/news/politics/

2023/07/12/guns-supreme-court-secondamendment-rahimi/70383454007/) ......................... 8

Fryer, R.G., Heaton, P.S., Levitt, S.D., Murphy,

K.M. (2013). Measuring Crack Cocaine and Its

Impact. Economic Inquiry ..................................... 22

Hendry, D. F. (1995) Dynamic Econometrics.

Oxford University Press, Oxford, UK; Owen, D.

and Weatherston, C.R. (2004) .............................. 17

Katharina Henk, Florian Rosing, Fabian Wolff,

Svenja B. Frenzel, Rolf van Dick, Valerie A.

Erkens, Jan A. Häusser, Andreas Mojzisch, and

Diana Boer, “An examination and extension of

the Peltzman effect during the Covid-19

pandemic,” Curr Res Ecol Soc Psychol. 2023; 4:

100091. Published online 2023 Jan 26.,

(https://www.ncbi.nlm.nih.gov/pmc/articles/PM

C9888029/) ............................................................. 11

Arielle Kaim, Mor Saban, “Are we suffering from

the Peltzman effect? Risk perception among

recovered and vaccinated people during the

COVID-19 pandemic in Israel,” Public Health,

Vol.

209,

August

2022,

(https://www.sciencedirect.com/science/article/p

ii/S0033350622001457) .................................... 11, 12

Kaplan, Jacob. Jacob Kaplan’s Concatenated

Files: Uniform Crime Reporting (UCR) Program

Data: Supplementary Homicide Reports (SHR),

1976-2020 ............................................................... 18

John R. Lott, Jr., More Guns, Less Crime:

Understanding Crime and Gun Control Laws,

University of Chicago Press, 3rd edition, 2010...... 10

John R. Lott, Jr. and Carl Moody, “Does the

Federal law forbidding people under domestic

violence restraining orders from possessing

firearms save lives?” Economics, Law, and

Policy, Vol. 6, No. 3, December 2023 ....................... 5

C. Kevin Marshall, Why Can’t Martha Stewart

Have a Gun?, 32 Harv. J.L. & Pub. Pol’y (Spring

2009),

(https://papers.ssrn.com/sol3/papers.cfm?abstra

ct_id=1367231) ......................................................... 9

Muelbauer, J. and Nunziata, L. (2004).

Forecasting (and explaining) US Business

Cycles, CEPR Discussion Papers 4584 ................. 18

Antonio Nicita and Simona Benedettini, “Does the

Enforcement Design Exacerbate the ‘Peltzman

Effect’? Evidence from Driver Record Point and

Road Safety in Italy,” University of Siena

Working

Paper,

March

2010,

(https://papers.ssrn.com/sol3/papers.cfm?abstra

ct_id=1568095) ....................................................... 11

Peltzman, Sam (1975). The effects of automobile

safety regulation. Journal of Political Economy ... 11

Steven Peterson, George Hoffer, and Edward

Millner, “Are Drivers of Air-Bag-Equipped Cars

More Aggressive? A Test of the OffsettingBehavior Hypothesis,” Journal of Law and

Economics (Oct. 1995)............................................ 11

Rao, B.B. and Singh, R. (2006). Demand for money

for fiji with PcGets. Applied Economics Letters .... 18

Raissian, K.M. (2016), Hold Your Fire: Did the

1996 Federal Gun Control Act Expansion

Reduce Domestic Homicides?. J. Pol. Anal.

Manage. .............................................................. 7, 14

Reade, J. J. (2007). Modeling and forecasting

football attendances. Oxonomics ........................... 18

vii

Brit Trogen and Arthur Caplan, “Risk

Compensation and COVID-19 Vaccines,” Ann

Intern Med. 2021 Mar 2: M20-8251,

(https://www.ncbi.nlm.nih.gov/pmc/articles/PM

C7983310/) ............................................................. 11

Uncertainty of outcome and super 12 attendance:

application of a general-to-specific modeling

strategy,’ Journal of Sports Economics........... 17, 18

Wallin MA, Holliday CN, Zeoli AM. The

Association of Federal and State-level Firearm

Restriction Policies With Intimate Partner

Homicide: A Re-analysis by Race of the Victim.

J Interpers Violence. 2022 Sep;37(1718):NP16509-NP16533.

doi:

10.1177/08862605211021988. Epub 2021 Jun

18. PMID: 34144667 .......................................... 7, 14

Rui Zhang and Quanyan Zhu, “Attack-Aware

Cyber Insurance of Interdependent Computer

Networks,” Net Institute Working Paper,

October

11,

2016

(https://papers.ssrn.com/sol3/papers.cfm?abstra

ct_id=2848576) ....................................................... 12

INTEREST OF AMICUS CURIAE

The Crime Prevention Research Center (CPRC) is

a research and education organization dedicated to

conducting academic quality research on the

relationship between laws regulating the ownership

or use of guns, crime, and public safety; educating the

public on the results of such research; and supporting

other organizations, projects, and initiatives that are

organized and operated for similar purposes. It has

501(C)(3) status, and does not accept donations from

gun or ammunition makers or organizations such as

NRA or any other organization involved in the gun

control debate on either side of the issue. 1

SUMMARY OF ARGUMENT

Precedent makes several things clear: First, the

Second Amendment protects an individual right to

keep and bear arms and is a fundamental right, coequal with other rights ensconced in the Bill of Rights.

It is therefore appropriate to reason by analogy from

precedent developed surrounding those other

amendments when analyzing the Second Amendment.

Second, fundamental constitutional rights should be,

and are, enforced against the government regardless

of stated claims regarding public safety, or other policy

concerns. Third, despite this, social science research

(often highly flawed) is frequently cited to create the

impression that it is necessary to balance citizens’

1 Pursuant to Supreme Court Rule 37.6, the undersigned affirms

that no counsel for a party authored this brief in whole or in part,

and no person or entity other than amicus curiae or its counsel,

made a monetary contribution specifically for the preparation or

submission of this brief.

rights on one side of the scale vs. public safety on the

other. This brief shows that the data, when properly

analyzed, shows otherwise: the law challenged by Mr.

Rahimi (18 U.S.C. § 922(g)(8)) has no beneficial impact

on public safety.

ARGUMENT

In Heller, this Court concluded that just as the

First and Fourth Amendments codified pre-existing

rights, the Second Amendment codified a pre-existing

right. District of Columbia v. Heller, 554 U.S. 570, 592

(2008). The Court analogized to the First and Fourth

Amendments in analyzing the Second Amendment.

Id. at 582. The Court stated:

Just as the First Amendment protects

modern forms of communications, [ ] and

the Fourth Amendment applies to

modern forms of search, [ ], the Second

Amendment extends, prima facie, to all

instruments that constitute bearable

arms, even those that were not in

existence at the time of the founding.

Id. (Internal cites omitted).

In McDonald, this Court rejected the

petitioner’s attempt to get the Court to treat the

Second Amendment with a different set of rules than

it would when considering other guarantees of the Bill

of Rights. McDonald v. City of Chicago, 561 U.S. 742,

780 (2010).

Most recently, this Court, in Bruen, continued

the Second Amendment’s equality with the other

constitutional rights via two comparisons. First, this

Court compared the manner in which it works to how

the First Amendment’s protection in relation to

unpopular speech or the free exercise of religion

works. N.Y. State Rifle & Pistol Ass'n v. Bruen, 142 S.

Ct. 2111, 2156 (2022). Second, the Court directly

compared the Second Amendment to the Sixth

Amendment’s Confrontation Clause. Id. Both of those

comparisons were central to this Court’s decision. Id.

Therefore, by consistently discussing the Second

Amendment in relation to other amendments in the

Bill of Rights, this Court has recognized that the

Second Amendment is equal to other portions of the

Bill of Rights.

“The constitutional right to bear arms in public

for self-defense is not ‘a second-class right, subject to

an entirely different body of rules than the other Bill

of Rights guarantees.’” Bruen at 2156 (quoting

McDonald v. City of Chicago, 561 U.S. 742, 780

(2010)). The Second Amendment is equal to other

constitutionally protected, fundamental rights.

When analyzing and enforcing fundamental

individual rights, this court has consistently rejected

utopian arguments based on fear regarding

hypothetical harms.

The right to keep and bear arms,

however, is not the only constitutional

right that has controversial public safety

implications. All of the constitutional

provisions that impose restrictions on

law enforcement and on the prosecution

of crimes fall into the same category. See,

e.g., Hudson v. Michigan, 547 U.S. 586,

591, 126 S.Ct. 2159, 165 L.Ed.2d 56

(2006) (“The exclusionary rule generates

‘substantial social costs,’ United States v.

Leon, 468 U.S. 897, 907, 104 S.Ct. 3405,

82 L.Ed.2d 677 (1984), which sometimes

include setting the guilty free and the

dangerous at large”); Barker v. Wingo,

407 U.S. 514, 522, 92 S.Ct. 2182, 33

L.Ed.2d 101 (1972) (reflecting on the

serious consequences of dismissal for a

speedy trial violation, which means “a

defendant who may be guilty of a serious

crime will go free”); Miranda v. Arizona,

384 US 436, 517, 86 S.Ct. 1602, 16

L.Ed.2d 694 (1966) (Harlan, J.,

dissenting); id., at 542, 86 S.Ct. 1602

(White, J., dissenting) (objecting that the

Court's rule “[i]n some unknown number

of cases ... will return a killer, a rapist or

other criminal to the streets ... to repeat

his crime”); Mapp v. Ohio, 367 U.S. 643,

659, 81 S.Ct. 1684, 6 L.Ed.2d 1081

(1961). Municipal respondents cite no

case in which we have refrained from

holding that a provision of the Bill of

Rights is binding on the States on the

ground that the right at issue has

disputed public safety implications.

McDonald v. City of Chicago, Ill, 561 U.S. 742, 783;

130 S. Ct. 3020; 177 L. Ed. 2d 894 (2010)

In fact, Miranda himself was convicted of

kidnapping and rape both before his successful appeal

to this Court, and after. See State v. Miranda, 98 Ariz.

18, 401 P.2d 721 (1965), rev'd, 384 U.S. 436, 86 S. Ct.

1602, 16 L. Ed. 2d 694 (1966). See also, State v.

Miranda, 104 Ariz. 174; 450 P.2d 364 (1969). So, in

this case, the Court should similarly not be swayed by

alarms about what harm may result from the full

application

fundamental,

individual

Constitutional right. “Moreover, Heller and McDonald

expressly rejected the application of any ‘judgeempowering interest-balancing inquiry that asks

whether the statute burdens a protected interest in a

way or to an extent that is out of proportion to the

statute’s salutary effects upon other important

governmental interests.’” Bruen, 142 S. Ct. at 2129

(quoting Heller, 554 U.S. at 634).

However, to the extent that any public policy

concerns must be addressed, it must be noted that the

simplistic false dichotomy of “guns versus safety” does

not hold up to thorough scrutiny.

The balance of this brief contains an analysis of

publicly available data by Drs. Lott and Moody from a

paper that is certainly relevant, and has been accepted

for publication; but, is not yet published as of the date

of filing of this brief. 2 It shows that 18 U.S.C.

§ 922(g)(8) has no beneficial impact on domestic

murder, domestic femicide, domestic gun murder, or

domestic gun femicide. No one wants to endanger

2 We based the research portion of this brief on the forthcoming

paper: John R. Lott, Jr. and Carl Moody, “Does the Federal law

forbidding people under domestic violence restraining orders

from possessing firearms save lives?” Economics, Law, and

Policy, Vol. 6, No. 3, December 2023.

lives, and it is important that the impact of such laws

be carefully evaluated.

A. The Empirical Theory

Regardless of the legal arguments with respect

to § 922(g)(8), it may be relevant to determine the

law’s merits. What would be lost if the law is

overturned? We assess the benefits of banning

individuals who are subject to domestic violence

protection orders

from

possessing

firearms.

Alternatively, we are assessing the costs, if any, of

declaring § 922(g)(8) unconstitutional. Previous

studies haven’t specifically looked at the impact of the

federal law. Nor have they taken into account the

large differences in state laws. 3 For example, states

A review of the literature cited by amicus briefs filed as of

September 24, 2023 reveals three major shortcomings. The first

is that the great majority of the cited studies show associations

between firearms and domestic violence, but such associations do

not imply that a particular law, such as 18 U.S.C. § 922(g)(8)

effectively reduces such violence. The second is that none of the

cited studies address the effect of 18 U.S.C. § 922(g)(8) on

domestic murders directly. Instead, the most often cited study

that addresses the effect of prohibiting persons subject to

domestic violence protective orders from possessing firearms is

concerned with the effectiveness of state firearm surrender laws

on domestic murders. (Carolina Diez et al., State Intimate

Partner Violence-Related Firearm Laws and Intimate Partner

Homicide Rates in the United States, 1991 to 2005, Annals of

Internal

Med.

(2017),

https://www.acpjournals.org/doi/full/10.7326/M16-2849.)

Moreover, that study has several problems. (1) It uses a single

dummy variable to measure the effect of the state surrender laws

on domestic murder even though the laws vary widely in their

application and severity. It has been shown (Clément de

Chaisemartin and Xavier D’Haultfoeuille, Two-Way Fixed

Effects Estimators with Heterogeneous Treatment Effects Am.

vary in terms of how long guns can be taken away

without due process.

Zackey Rahimi probably isn’t someone you’d

want as a neighbor. In 2019, Rahimi, a drug dealer

who sold marijuana and cocaine, fired a gun at a

passerby who witnessed him dragging his girlfriend

through a parking lot. 4 Months later, he shot at a

driver he had gotten into an accident with. And in

2020, he assaulted another girlfriend and threatened

her with a gun. Finally, in 2021, Rahimi shot a gun in

Econ. Rev. 2020, 110, 2964-2996) that such studies can be

seriously biased. (2) It uses imputed data to replace missing data

values and does not subject the replacement to a robustness test

to show that it did not affect the results. (3) The authors did not

use clustered standard errors which causes the significance of the

results to be overestimated. (4) The study used only three control

variables, after listing 24 potentially relevant variables, without

testing whether the discarded variables were significant as a

group (a test for possible omitted variable bias).

The Amicus Brief of Public Health Researchers and Lawyers cites

two papers on the 1996 Lautenberg Amendment, not 18 U.S.C.

§ 922(g)(8) (Wallin MA, Holliday CN, Zeoli AM. The Association

of Federal and State-level Firearm Restriction Policies With

Intimate Partner Homicide: A Re-analysis by Race of the Victim.

J Interpers Violence. 2022 Sep;37(17-18):NP16509-NP16533. doi:

10.1177/08862605211021988. Epub 2021 Jun 18. PMID:

34144667 and Raissian, K.M. (2016), Hold Your Fire: Did the

1996 Federal Gun Control Act Expansion Reduce Domestic

Homicides?. J. Pol. Anal. Manage., 35: 67-93). But more

importantly, the two studies also do not take into account the

differences in existing state laws and just use a simple dummy

variable for the Lautenberg Amendment.

https://www.supremecourt.gov/DocketPDF/22/22915/259334/20230317174308399_Rahimi%20Pet%20%20final.pdf

the air when his friend’s credit card was declined. 5

That 2020 assault on his girlfriend led to a domestic

violence restraining order, which forbade Rahimi from

owning guns. But, the use of the domestic violence

restraining order is a second-best approach. Rahimi

had engaged in multiple felonies before a court

granted the order. But if Rahimi had been convicted of

these felonies, or had been detained awaiting trial, or

subject to stringent, enforceable bond conditions

because the court viewed him as a danger to others, he

would also have been banned from obtaining guns.

The theory is straightforward. If people who are

subject to a civil restraining order are dangerous,

prohibiting them from possessing firearms could save

lives. On the other hand, if people under restraining

orders are truly dangerous, then they are unlikely to

obey such a law. Someone who is willing to commit a

serious assault or murder is already facing a

significant prison sentence, a life sentence, or the

death penalty. The additional penalties for illegally

obtaining a gun or violating a protective order are

unlikely to provide marginal deterrence.

Despite a protective order, Mr. Rahimi still

illegally obtained and used a firearm. In any

application of a restraining order, there are false

positives and false negatives. Restraining orders

mistakenly applied to law-abiding individuals will

5 John Fritze, “How a Second Amendment case at the Supreme

Court is putting gun rights groups in a jam,” USA Today, July

12,

2023

(https://www.usatoday.com/story/news/politics/2023/07/12/gunssupreme-court-second-amendment-rahimi/70383454007/).

likely be effective in disarming them, so that they will

not be able to defend themselves and others. As just

noted, at the same time, restraining orders might not

impose a real marginal penalty on those who are truly

dangerous. Thus, the law is most likely to restrain

only those who are most law-abiding and fail to

restrain the most dangerous. Indeed, Federal law

didn’t impose a lifetime ban on felons having guns

until 1968 and California was the first state to impose

a restriction on pistols in 1923. 6

The justification for disarming felons is

commonly accepted as the necessity to protect the

public’s safety. The courts have traded off the

protection of rights versus preventing crime. 7 This

leads to important questions regarding the distinction

between violent felons and non-violent felons and

their relative threats to the community’s physical

safety. There should be even more stringent

questioning of the distinction between felons, who

generally receive a full measure of due process, and

individuals subjected to a civil process where most

defendants obtain only the bare minimum due process

which includes a lower probability of determining guilt.

Presumably, on average, individuals going through a

civil process are less likely to engage in crime with a

firearm than those convicted of a felony. The greater

6 C. Kevin Marshall, Why Can’t Martha Stewart Have a Gun?, 32

Harv.

J.L.

Pub.

Pol’y

(Spring

2009)

(https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1367231).

7 Kanter v. Barr, 919 F.3d 437 (7th Cir. 2019), abrogated by New

York State Rifle & Pistol Ass'n, Inc. v. Bruen, 142 S. Ct. 2111, 213

L. Ed. 2d 387 (2022).

these mistakes the more likely there will be no

statistically significant beneficial effect. To the extent

that innocent people are disarmed, such laws can

increase crime.

As witnessed by the rise in murder rates after

handgun bans in Chicago and Washington, D.C., even

complete gun bans didn’t prevent criminals from

obtaining guns. 8 While gun control advocates argue

that gun bans won't work unless you ban guns

everywhere in a country, every single time around the

world that countries banned all guns or all handguns,

murder/homicide rates have risen. 9 That has been

true even in island nations with no neighbors

supplying guns. One would think that out of

randomness, one time, they would go down or at least

stay the same.

A final consideration is what is known as the

Peltzman effect. Enacting safety measures can cause

people to engage in offsetting behavior. Researchers

have found this in areas from traffic safety regulations

to COVID-19 policies. When people were mandated to

wear seatbelts or had airbags in their cars, people

drove more recklessly and got into accidents more

8 John R. Lott, Jr., More Guns, Less Crime: Understanding Crime

and Gun Control Laws, University of Chicago Press, 3rd edition,

2010, pp. 312-318. Crime Prevention Research Center, “Updated:

Murder and homicide rates before and after gun bans,” Crime

Prevention

Research

Center,

April

16,

2016

(https://crimeresearch.org/2016/04/murder-and-homicide-ratesbefore-and-after-gun-bans/).

9 Ibid.

frequently. 10 There is even evidence that total deaths

rose. With vaccines or mask mandates for COVID-19,

people engaged in fewer safety precautions, such as

not washing their hands as often or rejecting social

distancing. 11 To the extent that people overestimated

Peltzman, Sam (1975). The effects of automobile safety

regulation. Journal of Political Economy 83: 677-726. Steven

Peterson, George Hoffer, and Edward Millner, “Are Drivers of

Air-Bag-Equipped Cars More Aggressive? A Test of the

Offsetting-Behavior Hypothesis,” Journal of Law and Economics

38 (Oct. 1995): 251–64. Antonio Nicita and Simona Benedettini,

“Does the Enforcement Design Exacerbate the ‘Peltzman Effect’?

Evidence from Driver Record Point and Road Safety in Italy,”

University

Siena

Working

Paper,

March

2010

(https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1568095).

Katharina Henk, Florian Rosing, Fabian Wolff, Svenja B.

Frenzel, Rolf van Dick, Valerie A. Erkens, Jan A. Häusser,

Andreas Mojzisch, and Diana Boer, “An examination and

extension of the Peltzman effect during the Covid-19 pandemic,”

Curr Res Ecol Soc Psychol. 2023; 4: 100091. Published online

2023

Jan

26.

(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9888029/).

Hahab Falahi, Jasem Mohamadi, Hojjat Sayyadi, Iraj Pakzad,

Ayoub Rashidi, Razi Naserifar, Jahangir Abdil, Azra

Kenarkoohi, “COVID-19 Vaccination, Peltzman Effect and

Possible Increase in Highrisk Behaviors: A Growing Concern

Related to Risk Compensation and Reduced Compliance to Public

Health Protective Measures after Vaccines Rollout,” Infect

Disord

Drug

Targets.

2022;22(8):8-12

(https://pubmed.ncbi.nlm.nih.gov/35440338/). Brit Trogen and

Arthur Caplan, “Risk Compensation and COVID-19 Vaccines,”

Ann

Intern

Med.

2021

Mar

M20-8251

(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7983310/).

Arielle Kaim, Mor Saban, “Are we suffering from the Peltzman

effect? Risk perception among recovered and vaccinated people

during the COVID-19 pandemic in Israel,” Public Health, Vol.

209,

August

2022,

pp.

19-22

the effectiveness of vaccines or masks in preventing

the spread of the virus, these mandates could actually

increase the spread of the disease. The observation

has also been applied to protective gear in sports,

cyber security, and crime. 12 We are not arguing that

people overestimate the effectiveness of domestic

violence protection orders nor that total acts of

violence will increase, but that this effect by itself

could neutralize some or all of the benefit from the

law.

We look at the impact of § 922(g)(8) on the

number of domestic murders, domestic gun murders,

domestic femicides, and domestic gun femicides.

There is no statistically significant evidence of

benefits from this law in any of those areas. Indeed,

there is evidence that domestic gun murder and

domestic gun femicide increased.

(https://www.sciencedirect.com/science/article/pii/S00333506220

01457).

12 Alberto Chong and Pascual Restrepo, “Regulatory Protective

Measures and Risky Behavior: Should We Be Saved from

Ourselves?” University of Ottawa Working paper, March 2014

(https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2405494).

Rui Zhang and Quanyan Zhu, “Attack-Aware Cyber Insurance of

Interdependent Computer Networks,” Net Institute Working

Paper,

October

11,

2016

(https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2848576).

Eberhard Feess, “On the interplay of public and private law

enforcement with multiple victims,” European Journal of Law

and Economics, (2015), Vol 39, pp. 79-95.

1. Literature Review

A review of the literature cited by amicus briefs

filed as of September 24, 2023 reveals several major

shortcomings. The first is an issue of causation. Many

murders are committed with firearms, but that doesn’t

mean that any particular law will stop them from

getting weapons or that they won’t be able to commit

murder in other ways. In this instance, Rahimi

obtained a gun despite being barred by the protective

order.

The second is that none of the cited studies

address the effect of 18 U.S.C. § 922(g)(8) on domestic

murders directly. Instead, the most often cited study

by Diez et al. that addresses the effect of prohibiting

persons subject to domestic violence protective orders

from possessing firearms is concerned with the

effectiveness of state firearm surrender laws on

domestic murders. 13 The argument is that since these

laws are similar to § 922(g)(8), therefore § 922(g)(8)

also reduces domestic violence. But it is an empirical

question how § 922(g)(8) affects domestic violence.

Finally, and most significantly, these public

health studies are poorly done. They use a single

dummy variable to measure the effect of the state

surrender laws on domestic murder, even though the

laws vary widely in their application and severity. But

13 Carolina Diez et al., State Intimate Partner Violence-Related

Firearm Laws and Intimate Partner Homicide Rates in the

United States, 1991 to 2005, Annals of Internal Med.

(2017), https://www.acpjournals.org/doi/full/10.7326/M16-2849

research shows such studies can be seriously biased. 14

Nor do the various authors use clustered standard

errors, which results in overestimated levels of

statistical significance. In addition, the most

frequently cited study by Diez et al. uses imputed data

to replace missing data values and does not subject the

replacement to a robustness test to show that it did

not affect the results. The study used only three

control variables after listing 24 potentially relevant

variables without testing whether the discarded

variables were significant as a group (a test for

possible omitted variable bias).

The Amicus Brief of Public Health Researchers

and Lawyers cites two papers on the 1996

Lautenberg Amendment, not 18 U.S.C. § 922(g)(8). 15

But more importantly, the two studies also do not take

into account the differences in existing state laws and

just use a simple dummy variable for the Lautenberg

Amendment.

While all the researchers cited by the literature

cited by amicus briefs rely on public health studies, it

is important to recognize how public health research

Clément de Chaisemartin and Xavier D’Haultfoeuille, TwoWay Fixed Effects Estimators with Heterogeneous Treatment

Effects Am. Econ. Rev. 2020, 110, 2964-2996.

15 Wallin MA, Holliday CN, Zeoli AM. The Association of Federal

and State-level Firearm Restriction Policies With Intimate

Partner Homicide: A Re-analysis by Race of the Victim. J

Interpers Violence. 2022 Sep;37(17-18):NP16509-NP16533. doi:

10.1177/08862605211021988. Epub 2021 Jun 18. PMID:

34144667 and Raissian, K.M. (2016), Hold Your Fire: Did the

1996 Federal Gun Control Act Expansion Reduce Domestic

Homicides?. J. Pol. Anal. Manage., 35: 67-93.

differs dramatically from research by criminologists

and economists who are much more skeptical of gun

control. For example, while the largest-ever survey of

120 academics on gun control found that academics

were overall quite skeptical that gun control lowered

murder rates or the frequency of mass public

shootings, the differences between criminologists,

economists, and public health researchers were

stark. 16 Outside of getting rid of gun-free zones or

concealed handgun laws, there is no gun control

regulation that criminologists and economists think

would reduce murders or mass public shootings. By

contrast, public health researchers are more likely to

support barring sales to convicted stalkers or people

convicted of violent misdemeanors and strongly

support gun-free zones.

2. Methodology

We measure the strength of state domestic

violence protective orders (DVPO) by the duration of

the order. Federal law 18 U.S.C. § 922(g) was passed

in 1994. It has no effect in the absence of a state

protection order. We create a dummy variable to

measure its effect, taking the value zero for years

before 1994 and the value one for the remaining years.

We then create two test variables by multiplying the

temporary order duration and the final order duration

variables by the dummy variable for 1994 and later.

16 Arthur Z. Berg, John R. Lott, Jr., and Gary A. Mauser, “Expert

Views on Gun Laws.” Regulation, Winter 2019-2020, Vol. 42, No.

4, pp. 40-47.

Therefore, we are estimating the additional effect of

§ 922(g)(8) given an existing state protection order.

This methodology allows us to estimate a twoway fixed-effects (TWFE) panel data model where we

include state and year dummies. The year dummies

control for events such as recessions, the passage of

other federal laws, and anything else that affects all

states in a given year. This is the most commonly used

econometric methodology for policy analysis. The de

Chaisemartin and D’Haultfoeuille (op.cit.) criticism

does not apply to our model because the test variables

are not simple dummies, instead they are the product

of a continuous variable (state order duration) and a

dummy for 1994.

A DVPO is intended to protect the applicant

against potential violence committed by a domestic

partner. While a person of any gender can request

such an order, women are the primary users. As such,

we investigate several different outcomes: domestic

homicides, domestic homicides of women, domestic

homicides committed by firearms, and femicides by a

domestic partner using firearms. These are count

variables which only take integer values and are the

result of counting (as opposed to ranking). The

appropriate statistical model for such data is the

negative binomial model. 17 The negative binomial is a

generalization of the Poisson model in that it does not

require the mean and variance of the dependent

variable to be equal. The typical case is that the

variance is greater than the mean, which is called

17 Cameron, A.C. and Trivedi, P.K. (1998). Regression Analysis of

Count Data. Cambridge, UK.

overdispersion. We tested for overdispersion in each of

the models reported below. There was significant

overdispersion in every case, justifying the negative

binomial model.

The choice of control variables to include in the

model is crucial because states are continuously

changing the number of police, the number of

incarcerated persons, other laws, etc. If we leave out a

potentially relevant control variable, the omission

biases all estimates including the estimated

coefficients on the test variables. This bias could result

in a spurious regression. On the other hand, including

an irrelevant variable whose true coefficient is zero,

does not bias the estimates, but leads to imprecise

estimates. This imprecision could be so bad that the

estimate of interest, e.g., the effect of DVPO’s on

domestic murders appears to be insignificant when it

is in fact significant.

We address this modeling problem by

estimating two models. The first is a general model

that includes many potentially relevant control

variables. Using many control variables allows us to

avoid omitted variable bias but may cause our

estimates to be imprecise. To avoid the imprecision

problem, we derive a so-called “specific” model with

only the significant control variables. This “general to

specific” modeling methodology has been used

successfully in many applications. 18

18 See: Hendry, D. F. (1995) Dynamic Econometrics. Oxford

University Press, Oxford, UK; Owen, D. and Weatherston, C.R.

(2004). Uncertainty of outcome and super 12 attendance:

application of a general-to-specific modeling strategy,’ Journal of

3. Data

Data on the dependent variables come from

Jacob Kaplan’s Supplementary Homicide Reports

(SHR) produced by the FBI for the years 1976-2020. 19

SHR data for 1980-1983 are missing and most of the

data for the control variables end in 2018. Also, many

of the control variables have missing data for the

District of Columbia. As a result, our sample consists

of the 50 states for the years 1976-1980 and 19842018. Because of the missing observations for 1981-83,

this is an unbalanced panel. In the robustness section,

we restrict the dataset to 1984-2018 to form a

balanced panel.

We define a domestic homicide as one in which

the first victim was related to the first offender as a

husband, wife, boyfriend, girlfriend, common-law

husband, common-law wife, ex-husband, ex-wife, or in

a homosexual relationship. We then determined if the

victim was female and if the offender used a firearm.

Sports Economics 5, 347-370; Muelbauer, J. and Nunziata, L.

(2004). Forecasting (and explaining) US Business Cycles, CEPR

Discussion Papers 4584; Rao, B.B. and Singh, R. (2006). Demand

for money for fiji with PcGets. Applied Economics Letters 13, 987991; Reade, J. J. (2007). Modeling and forecasting football

attendances. Oxonomics 2, pp. 27–32.

19 Kaplan, Jacob. Jacob Kaplan’s Concatenated Files: Uniform

Crime Reporting (UCR) Program Data: Supplementary Homicide

Reports (SHR), 1976-2020. Ann Arbor, MI: Inter-university

Consortium for Political and Social Research [distributor], 202109-22.

https://www.openicpsr.org/openicpsr/project/100699/version/V11

/view

For the policy variables, we examined the law

codes of all fifty states from 1970 to 2023. There are

two types of protective orders. Temporary or

emergency orders are usually issued without the

participation of the respondent. These are usually

short, averaging 27 days (median 14 days), but they

can be as long as two years. The final order, which

replaces any temporary order, is longer,

averaging four years with a median of one year.

However, many states issue permanent orders, which

can be modified or dissolved. To translate these into

numerical values, we had to make several

assumptions. For example, since we don’t know the

respondent’s age or the probability of the order being

appealed or otherwise reduced or rescinded, we

assume that a permanent order lasts 25 years. Since

the numerical values are necessarily arbitrary, we did

robustness checks with these long-duration order

values doubled and halved to see if the results

changed. (The results are not sensitive to these

assumptions.) The control variables are listed in Table

1 along with the means of the dependent variables and

the policy variables of interest.

Table 1: Means and other statistics.

Variable

Domestic

murders

Domestic

femicides

Dom gun

murders

St.

Mean Dev

Min

Max

1587

33.73

43.53

344

1587

23.88

30.18

217

1587

19.59

27.24

241

Dom gun

femicides

Final order,

years

Temp order,

days

Final*§

922(g)(8)

dummy

Temp*§

922(g)(8)

dummy

Prisoners per

capita

Police per

capita

Abortion

Unemployme

nt rate

Employment

per capita

Military per

capita

Construction

per capita

Alcohol per

capita

Crack

Density

Income per

capita

Poverty rate

1587

14.37

19.02

141

1587

3.98

7.40

0.05

42.48

1587

27.13

73.38

0.28

730

1587

3.55

7.26

42.48

1587

68.85

154.

1587

21.19

333.

277.

1.51

50.41

1.31

32.84

161.

730

871.

522.

6.02

1587

5.65

1.88

2.30

14.80

1587

57.90

5.33

37.99

73.07

1587

1.01

0.90

0.27

6.65

1587

3.33

0.75

1.36

6.90

1587

1.91

1.41

0.45

1.10

0.89

-0.70

1587

4.31

13.54

0.08

4.04

7.78

111.

1587

16.80

12.89

3.48

3.71

9.16

2.90

30.45

27.20

1587

Welfare per

capita

Percent gun

suicide

Executions

per capita

Percent

population 1534

Percent black

men 15-34

1587

249.

89.65

0.33

548.

1587

61.10

12.73

100

1587

0.87

3.08

1587

28.92

2.72

23.37

39.81

1587

1.66

1.44

0.07

5.90

Police, prison, and the death penalty all have

deterrent roles. Prison and executions also have

incapacitation effects. These variables are all in per

capita rates. We also lag them to avoid possible

simultaneity. The effective abortion rate for murder is

included because there is substantial evidence that

legalized abortion significantly affects crime rates. 20

Unfortunately, the Donohue and Levitt (2020) sample

ends in 2014 and computation of the effective abortion

rate is complicated. However, it is easy to extrapolate

the series since it is a smooth trend, and we only need

to extrapolate four years.

We include the proportion of the population

between 15 and 34 and the proportion of black males

15-34 because relatively young men largely commit

murder. We have three employment variables: total

employment per capita, indicating the amount of

legitimate

employment

available;

military

20 Donohue, J.J. and Levitt, S.D. (2020). The Impact of Legalized

Abortion on Crime over the Last Two Decades. American Law

and Economics Review 22: 241-302.

employment, since the military concentrates many

young men in certain areas but also sends many young

men out of the country; and construction employment

per capita because the construction industry also

concentrates large numbers of young men. The denser

the population, the more interactions among the

inhabitants, some of which could cause domestic

murder. For this reason, we include population

density as a control variable. We include per capita

consumption of alcohol because alcohol can reduce

inhibitions. We include the unemployment rate, real

personal income per capita, the poverty rate, and real

welfare payments per capita, any of which could affect

domestic murder by altering the stresses associated

with domestic life.

A possibly important factor in any crime

equation using historical data is the emergence of

crack cocaine in the 1980’s. The resulting large

increase in the supply of cocaine caused turf battles

among drug gangs, increasing murder rates. We

control for the crack cocaine epidemic by including the

Fryer crack index, a combination of indicators of

cocaine use compiled by Fryer and his colleagues for

the period of the crack epidemic. 21 There are

continuous values for 1981 to 2000 for each state. We

set pre-1981 values at the 1981 levels and post-2000

values at the 2000 levels. We also include the most

widely used proxy for gun availability -- the proportion

of suicides committed by firearms -- to control for

21 Fryer, R.G., Heaton, P.S., Levitt, S.D., Murphy, K.M. (2013).

Measuring Crack Cocaine and Its Impact. Economic Inquiry

51:1651-1681.

ambient gun ownership. Finally, we also include the

population level since more people can be expected to

be associated with more domestic violence.

4. Results

The next two tables present the primary

results. Table 2 shows the effects of 18 U.S.C.

§ 922(g)(8) on domestic murder and domestic femicide.

The coefficients are presented as incident rate ratios

indicating the percent change in the dependent

variable for a one-unit change in the explanatory

variable. A value of 1 indicates no change, a value

greater than one such as 1.01 indicates that domestic

murders would increase by one percent for a one-year

increase in the average final order. A value less than

one indicates that a one-year increase in final

restraining orders would decrease domestic murders

by one minus the coefficient. For example, the

coefficient on final order years in the first column of

Table 2 is .993 indicating that a one-year increase in

the length of the order would reduce domestic murders

by .007 percent. The corresponding t-statistic is

reported in parentheses below the coefficient. Tstatistics greater than two in absolute value are

considered significant (using the standard five percent

significance level). 22 Significant t-statistics are also

indicated by asterisks.

Table 2 shows that state temporary and final

domestic violence protection orders by themselves do

22 Federal Judicial Center, Reference Manual on Scientific

Evidence (3rd Edition). Washington, DC: National Academies

Press, p.251.

not significantly affect domestic murders or domestic

femicides. The enhancement provided by 18 U.S.C.

§ 922(g)(8) also has no significant effect on domestic

murders or domestic femicides.

Table 3 shows the effects of 18 U.S.C.

§ 922(g)(8) on domestic gun murder and domestic gun

femicide. We again find that neither temporary nor

final domestic violence protection orders significantly

reduce domestic gun murders or domestic gun

femicides. The effect of the § 922(g)(8) working

through temporary orders is a small, but significant,

increase in domestic gun murders. The estimates for

domestic gun femicides show a similarly small effect

but are not consistently significant. The effect of

§ 922(g)(8) working through final orders shows a very

small and insignificant decline in both domestic gun

murders and domestic gun femicides. Overall, 18

U.S.C. § 922(g)(8) has not significantly reduced

domestic murders, domestic femicides, domestic gun

murders, or domestic gun femicides.

Table 2: Results for domestic murder and

domestic femicide

Variables

Temporary

order, days

Final order,

years

Domestic

Murder

General Specific

Domestic

Femicide

General Specific

1.000

(0.602)

1.001

(0.862)

1.001

(1.031)

1.001

(1.364)

0.993

(-1.183)

0.991

(-1.250)

0.993

(-1.101)

0.991

(-1.165)

§ 922(g)(8)

dummy *

temp days

§ 922(g)(8)

dummy*final

years

Number of

prisoners per

capita lagged

Number of

police per

capita lagged

Abortion

Unemployment

Employment

Military

Construction

Alcohol

Crack

Density

Income

1.000

(0.556)

1.000

(1.350)

1.000

(-0.432)

1.000

(0.121)

0.997

(-0.651)

0.994

(-1.103)

0.998

(-0.423)

0.994

(-1.115)

1.000

(-1.356)

1.000

(-1.338)

1.000

(-0.653)

1.000

(-0.302)

0.984

(-0.282)

1.000

(0.0198)

0.958

(-0.788)

1.010

(0.772)

0.993

(-0.460)

1.007

(0.0536)

1.103

(1.798)

1.503*

(2.172)

1.042

(1.411)

0.995

(-0.485)

1.004

1.014

(1.125)

0.995

(-0.300)

1.039

(0.305)

1.087

(1.506)

1.335

(1.541)

1.042

(1.376)

0.985

(-1.540)

1.007

1.078

(1.760)

1.446**

(2.810)

1.076

(1.673)

1.041

(1.044)

1.386*

(2.551)

1.079

(1.666)

0.982*

(-2.135)

Poverty

Welfare

(0.192)

1.011

(1.221)

1.000

(-0.666)

1.014

(1.665)

(0.345)

1.007

(0.779)

1.000

(-0.0126)

Percent gun

suicide lagged 0.997

0.997

0.998

(-1.671) (-1.450) (-1.406) (-1.072)

Executions

per capita

lagged

1.000

1.001

(-0.0873)

(0.414)

Pct pop 15-34 0.982

0.976

(-0.707)

(-0.941)

Pct black men 1.751** 1.613** 1.558** 1.471*

15-34

(3.813)

(3.378)

(3.357)

(3.014)

Note: ***p<.001, p<**.01, p<*.05; negative binomial

model; coefficients are incidence rate ratios; t-ratios in

parentheses; standard errors clustered on states; state

and year effects estimates are suppressed.

Table 3: Domestic gun murder, domestic gun

femicide

Variables

Temporary

order, days

Domestic gun

murder

General Specific

Domestic gun

femicide

General Specific

1.000

(0.274)

1.001

(0.703)

1.000

(0.323)

0.992

(-1.104)

0.991

(-1.402) (-1.351)

Final order,

years

0.994

(-0.965)

1.000

(0.486)

§ 922(g)(8)

dummy

temp days

1.001*

(2.083)

§ 922(g)(8)

dummy

*final order

years

0.993

(-1.329)

Number of

prisoners

per

capita

lagged

1.000

(-0.316)

Number of

police

per

capita

lagged

0.999

(-0.737)

Abortion

0.962

(-0.614)

Unemployment

1.013

(0.808)

Employment 0.990

(-0.461)

Military

0.974

(-0.179)

Construction 1.106

(1.562)

Alcohol

1.648*

(2.317)

Crack

1.072*

(2.041)

1.001**

(2.588)

1.001*

(2.258)

1.001

(1.839)

0.991

(-1.654)

0.996

(-0.786) (-0.826)

1.000

(0.400)

0.999

(-0.434)

0.956

(-0.826)

1.006

(0.411)

0.997

(-0.157)

0.978

(-0.171)

1.088

(1.360)

1.664*** 1.470

(3.373)

(1.850)

1.109*

1.084*

(2.242)

(2.314)

1.589***

(3.524)

1.091**

(2.768)

Density

Income

Poverty

Welfare

0.997

(-0.270)

0.994

(-0.294)

1.015

(1.602)

1.000

(-0.243)

1.016*

(1.995)

0.991

0.984

(-1.075) (-1.537)

0.987

(-0.698)

1.010

(1.143)

1.000

(0.376)

Percent gun

suicide

lagged

0.997

0.998

(-1.112)

(-0.995)

Executions

per

capita

lagged

0.996

0.995

0.998

(-1.356) (-1.889) (-0.727)

Pct pop 1534

0.979

0.968

0.972

(-0.660)

(-1.045) (-1.032)

Pct

black

men 15-34

1.697** 1.525*

1.542** 1.571**

(3.192)

(2.458)

(2.843) (2.997)

Note: ***p<.001, p<**.01, p<*.05; negative binomial

model; coefficients are incidence rate ratios; t-ratios in

parentheses; standard errors clustered on states; state

and year effects estimates are suppressed.

5. Robustness checks

An alternative method for estimating the

impact of a crime policy is to investigate the policy’s

effect on the per capita domestic murder rate. For this

analysis, we apply the standard two-way fixed-effects

model to the rate of domestic murders per one million

people. Table 4 presents the results. The estimates are

very similar to those shown in Tables 2 and 3. 18

U.S.C. § 922(g)(8) does not significantly affect

domestic murder or domestic femicide. The small

positive effect for domestic gun murders which was

significant in Table 3 is not significant in the per

capita fixed-effects model. There is a small but

significant positive effect on domestic gun femicide for

temporary protective orders, but only in the more

precise specific model.

Table 4: Estimates using per capita data

Domestic murder

General Specific

Temporary

order,

days

0.034

(0.87)

Final

order,

years

-0.36

(-1.08)

922(g)(8)

dummy *

temp days -0.015

(-1.13)

922(g)(8)

dummy

*final

order

years

0.033

(0.14)

Domestic femicide

General

Specific

0.038

(1.03)

0.011

(0.40)

0.0071

(0.25)

-0.37

(-1.19)

-0.18

(-0.85)

-0.19

(-0.82)

-0.016

(-1.33)

-0.0061

(-0.59)

0.0046

(0.50)

0.028

(0.12)

0.049

(0.31)

-0.075

(-0.44)

Domestic

gun murder

General Specific

Domestic

gun femicide

General

Specific

Temporary

order,

days

0.026

0.032

0.0044

-0.0025

(1.05)

(1.31)

(0.24)

(-0.14)

Final

order,

years

-0.21

-0.27

-0.24

-0.22

(-0.79)

(-1.01)

(-1.41)

(-1.16)

922(g)(8)

dummy *

temp days 0.00031 -0.0012 0.011

0.027**

(0.032)

(-0.13)

(1.39)

(3.46)

922(g)(8)

dummy

*final

order

years

-0.16

-0.12

0.0034

-0.070

(-0.78)

(-0.62)

(0.027)

(-0.49)

Note: ***p<.001, p<**.01, p<*.05; two-way fixedeffects model; control variables and state and year

effects estimates are suppressed; standard errors

clustered on states.

As noted above, there is some uncertainty as to

how to translate the duration of indefinite or

permanent final orders into numbers that can be

entered into a dataset. We investigate the sensitivity

of the results to these arbitrary values by doubling and

halving the values of any orders over 10 years and re-

running the negative binomial regressions. The

results are reported in Table 5.

Table 5: Doubling and halving long sentences

Domestic

murder

Temporary

order, days

General

Specific

Half X

Domestic

murder

GenSpeceral

ific

1.00

(0.57)

1.00

(0.84)

1.00

(0.65)

1.00

(0.89)

0.98*

(-2.05)

0.99

(-1.70)

1.00

(0.44)

1.00

(1.24)

Final order,

years

1.00

(-0.88)

(-1.07)

922(g)(8)

dummy

temp days

1.00

(0.61)

(1.42)

922(g)(8)

dummy

*final order

years

1.00

0.99

(-0.87)

(-1.27)

Domestic

femicide

Temporary

order, days

General

Specific

1.00

0.99

(-0.40) (-0.89)

Domestic

femicide

GenSpeceral

ific

1.00

(1.00)

1.00

(1.34)

1.00

(1.10)

1.00

(1.42)

1.00

(-1.02)

0.98

(-1.86)

0.99

(-1.55)

Final order,

years

1.00

(-0.82)

922(g)(8)

dummy

temp days

1.00

(-0.39)

(0.19)

922(g)(8)

dummy

*final order

years

1.00

0.99

(-0.65)

(-1.27)

Domestic

femicide

Temporary

order, days

1.00

(0.0044)

General

Specific

1.00

0.99

(-0.22) (-0.92)

Domestic

femicide

GenSpeceral

ific

1.00

(0.23)

1.00

(0.67)

1.00

(0.35)

1.00

(0.76)

0.98

(-1.82)

0.98

(-1.77)

1.00

(1.95)

1.00*

(2.46)

Final order,

years

1.00

(-0.55)

(-0.87)

922(g)(8)

dummy

temp days

1.00*

1.00**

(2.14)

(2.66)

922(g)(8)

dummy

*final order

years

0.99

(-1.52)

(-1.86)

Domestic gun

femicide

Temporary

order, days

1.00

(-0.55)

General

Specific

1.00

0.99

(-0.72) (-1.14)

Domestic gun

femicide

GenSpeceral

ific

1.00

(0.28)

(0.44)

(0.38)

(0.55)

Final order,

years

1.00

0.98*

(-1.04)

(-1.01)

(-2.23) (-2.24)

922(g)(8)

dummy

temp days

1.00*

1.00

1.00*

1.00

(2.34)

(1.91)

(2.08) (1.71)

922(g)(8)

dummy

*final order

years

0.99

1.00

(-1.02)

(-1.04)

(-0.46) (-0.52)

Note: ***p<.001, p<**.01, p<*.05; indefinite long

sentences for final orders are doubled in the first two

columns and halved in columns three and four;

negative binomial model; coefficients are incidence

rate ratios; t-ratios in parentheses; standard errors

clustered on states; control variables, state and year

effects estimates are suppressed.

The results are virtually the same as those

reported in Tables 2 and 3 and they are almost

identical for doubling and halving the order length.

The results appear to be robust to assumptions

concerning final order duration.

The SHR data has missing values for all states

from 1980-1983. The resulting panel is unbalanced. To

get a balanced panel, we estimated the negative

binomial model using data from 1984-2018. The

results are reported in Table 6.

Table 6: Using balanced panel, 1984-2018

Domestic

murder

Temporary

order,

days

Final

order,

years

General

Specific

Domestic

femicide

General

Specific

1.000

(0.457)

1.000

(0.445)

1.001

(0.875)

1.001

(0.944)

0.992

(-1.255)

0.992

(-1.192)

0.992

(-1.224)

0.992

(-1.094)

1.000

(1.306)

1.000

(-0.454)

1.000

(-0.0547)

0.996

(-0.819)

0.999

(-0.345)

0.997

(-0.749)

§ 922(g)(8)

dummy *

temp days 1.000

(0.530)

§ 922(g)(8)

dummy

*final

order

years

0.997

(-0.660)

Domestic gun

murder

Temporary

order,

days

General

Specific

Domestic gun

femicide

General

Specific

1.000

(0.140)

1.000

(0.224)

1.000

(0.222)

1.000

(0.400)

Final

order,

years

0.994

(-1.040)

0.993

(-1.016)

0.990

(-1.520)

0.991

(-1.447)

§ 922(g)(8)

dummy *

temp days 1.001

1.001*

1.001

(1.948)

(2.453)

(2.145) (1.702)

§ 922(g)(8)

dummy

*final

order

years

0.993

0.997

0.996

(-1.357) (-1.451) (-0.707) (-0.838)

Note: ***p<.001, p<**.01, p<*.05; indefinite long

sentences for final orders are doubled in the first two

columns and halved in columns three and four;

negative binomial model; coefficients are incidence

rate ratios; t-ratios in parentheses; standard errors

clustered on states; control variables, state and year

effects estimates are suppressed.

The results are almost identical to those

reported in Tables 2 and 3.

CONCLUSION

We have estimated the enhancement effect of

federal law 18 U.S.C. § 922(g)(8) using a panel of fifty

states over 38 years. The results are remarkably

robust. We find that 18 U.S.C. § 922(g)(8) has no

statistically significant beneficial impact on domestic

murder, domestic femicide, domestic gun murder, or

domestic gun femicide. Additional penalties for

illegally obtaining a gun or violating a protective order

are unlikely to provide marginal deterrence. In the

past, some courts have traded off protection of rights

versus prevention of crime. The debate in the past has

focused on violent versus non-violent felons.

Presumably, on average, individuals going through a

civil process are less likely to engage in crime with a

firearm than those convicted of a felony. Even when

hearings occur, the lower standard of proof in civil

matters means a higher probability of false positives

and thus may inadvertently disarm innocent people.

The statute not only fails to withstand Constitutional

analysis, it fails to accomplish its policy goal.

Therefore, we urge this Court to affirm the decision

below.

Respectfully submitted,

STEVEN W. DULAN

Counsel of Record

LAW OFFICES OF

STEVEN W. DULAN, PLC

5311 Park Lake Road

East Lansing, MI 48823

(517) 332-3149

swdulan@stevenwdulan.com

Counsel for Amicus Curiae

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