Coquitlam College ECON 202 – Final Exams (50 points).docx

Coquitlam College
ECON 202 – Final Exams (50 points)
Spring 2020
Instructor: Kojo Laryea
QUESTION:
The COVID-19 outbreak has struck Canada as well as every
other part of the world since it was first
reported in December 2019 and the disease continues to cause
so much havoc. Although this is a
public health issue, it has managed to hit the global economy
negatively in different ways. The stock
market continues to plummet everyday, with people losing
billions of their wealth; most businesses
have come to a halt and workers have been asked to stay home
in order to reduce the spread of the
deadly virus; the virus is also causing people to fall sick and not
being able to work. This pandemic
has also caused some small-scale businesses to lay-off workers

partly because they are not able to pay
them wages and salaries. The airline industry has come to a
standstill because various countries have
closed their borders and are limiting traveling. Due to this,
airline companies like WestJet are expecting
to lay-off between 20%-50% of their workers if the situation
persists in the coming days. Most
sporting events and leagues around the world have been
suspended. Companies like Nike and Apple
have closed all stores due to this pandemic. Also, Crude oil
prices keep plunging over these few
months.
Throughout the semester, we have discussed various economic
variables and how they are related. We
have also discussed the difference between the Classical and the
Keynesian Economists’ view about
how the economy reacts to shocks in the market. We have also
discussed how the government and
the central bank can use Fiscal Policies and Monetary Policies
respectively to help solve a recession in
an economy.
With reference to everything we discussed in class throughout
the semester, discuss how the COVID-

19 pandemic has affected or is affecting the Canadian economy
and how the government of Canada
together with the Bank of Canada are trying to mitigate the
problem.
Guideline: Your essay should include, but not limited to the
information in this guideline
1. Make sure to discuss how this pandemic will affect Canada’s
GDP and growth rate (makes will
be awarded for explanation and examples.) (5 marks)
2. Make sure to discuss how the pandemic will affect Canada’s
interest rates. (3 marks)
3. Make sure to discuss how the pandemic will have an effect on
Canada’s inflation and also
discuss what the Bank of Canada should do/are doing to
maintain their core values with respect
to inflation. (5 marks)
4. Also, make sure to explain how the pandemic will have an
effect on unemployment. (3 marks)
5. Based on our discussions in class, how do you think this
pandemic will also have an effect on
the nominal exchange rates? (2 mark)

6. Explain the results that can be predicted from Classical
Economists’ view with respect to this
economic shock assuming the shock affects only aggregate
demand (make sure to explain what
will happen to both real and nominal variable) (6 marks)
7. Explain the results that can be predicted from Kaynesian
Economists’ view with respect to this
economic shock. Assuming the shock affects both the AD and
SRAS but not the LRAS, explain
the short run equilibrium, and how the economy will transition
back to its long run equilibrium
using the Supply-Side Adjustment Mechanism. (6 marks)
8. Considering your answer to question 7., what are the
Government of Canada and Bank of
Canada doing to mitigate this situation. Use the AD-AS model
to explain how they can solve
or reduce the economic effects of this pandemic. (10 marks)
9. Clarity and overall structure of the essay. (10 marks)
INSTRUCTIONS:
1. The deadline for this essay is Wednesday, 8th April, and it
will not be extended. If you do not

submit by the deadline, your essay will not be graded and that
will affect your final grade. No
excuses
2. You are required to upload your essay on C4 but not my
email. If you send it via email, it will
not be graded.
3. If I realise that you submit the same essay with another
person, it will have an effect on your
final score, so make sure you do this independently
4. Make sure to provide references of any article that you cite
in your essay.
5. Try to limit to three pages (Spacing at 1.5 lines, Use Time
New Roman 12pt font size).
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Terrorism and Political Violence
ISSN: 0954-6553 (Print) 1556-1836 (Online) Journal homepage:
https://www.tandfonline.com/loi/ftpv20
Repression and Terrorism: A Cross-National
Empirical Analysis of Types of Repression and

Domestic Terrorism
James A. Piazza
To cite this article: James A. Piazza (2017) Repression and
Terrorism: A Cross-National Empirical
Analysis of Types of Repression and Domestic Terrorism,
Terrorism and Political Violence, 29:1,
102-118, DOI: 10.1080/09546553.2014.994061
To link to this article:
https://doi.org/10.1080/09546553.2014.994061
Published online: 23 Feb 2015.
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Repression and Terrorism: A Cross-National
Empirical Analysis of Types of Repression
and Domestic Terrorism
JAMES A. PIAZZA
Department of Political Science, The Pennsylvania State
University,
University Park, Pennsylvania, USA
While some scholars have theorized that repression reduces
terrorism because it
raises the costs of participating in terrorist activity by
dissidents, others argue that
repression stimulates terrorism by either closing off nonviolent
avenues for express-
ing dissent or by provoking or sharpening grievances within a
population. This study
investigates these contradictory sets of expectations by
considering whether or not
different specific types of repression yield different effects on
patterns of terrorism

in 149 countries for the period 1981 to 2006. By assessing the
impact of nine specific
types of repression on domestic terrorism, the study produces
some interesting
findings: while, as expected, forms of repression that close off
nonviolent avenues
of dissent and boost group grievances increase the amount of
domestic terrorism a
country faces, types of repression that raise the costs of terrorist
activity have no
discernible suppressing effect on terrorism.
Keywords dissent, domestic terrorism, regime type, restriction
of freedoms, state
repression
What is the relationship between state repression and terrorist
activity within
countries? Can repression both suppress and stimulate
terrorism? The burgeoning
body of work on regime type and terrorism gives some clues
about these questions.
Investigation of the structural determinants of terrorism has
most consistently found
that democratic regimes experience more terrorist activity than
nondemocratic or
illiberal regimes.1 The common explanation for this finding
limits itself to the obser-
vation that the executive limitations and preservation of
individual rights that are
part and parcel of democratic rule provide a more hospitable
environment for terror-
ists than is found in illiberal regimes.2 Democracies extend
civil liberties to citizens,
place restrictions on policing, extend due process and rights of
the accused to

arrestees, and tolerate a free media. All of these elements make
it easier for terrorist
movements to form, to plan and conduct attacks, to claim credit
for attacks via
media, and to protect their terrorist network if members are
arrested. The overall
conclusion is that the same ingredients that make a democracy
nurturing of civil
society and individual freedoms make it vulnerable to terrorism.
Conversely, regimes
James A. Piazza is Associate Professor in the Department of
Political Science at The
Pennsylvania State University.
Address correspondence to James A. Piazza, Department of
Political Science, The
Pennsylvania State University, University Park, PA 16802,
USA. E-mail: [email protected]
Terrorism and Political Violence, 29:102–118, 2017
Copyright # Taylor & Francis Group, LLC
ISSN: 0954-6553 print=1556-1836 online
DOI: 10.1080/09546553.2014.994061
102
mailto:[email protected]
http://dx.doi.org/10.1080/09546553.2014.994061
that are able to more easily and widely employ repression, such
as dictatorships,
should see reduced terrorist activity. Indeed, it is this line of
reasoning that prompted
commentators after the 9=11 attacks to suggest that countries
reduce their vulner-

ability to terrorism by curtailing or redefining citizens’ rights.3
The above findings would seem to close the book on the
relationship between
regime type and terrorism. However, research by scholars
focusing more specifically
on regime institutional features has substantially complicated
the picture. For
example, there is evidence that terrorist activity is not
uniformly high within liberal
polities and that different institutional elements of liberal
democratic rule have dif-
ferent effects on the level of terrorism a country experiences.
The framework for this
observation was first established by Eyerman,
4 who summarized theoretical wisdom
of the time in noting that some institutions within democratic
rule, such as citizens’
opportunities to engage in political activity and to play a role in
selecting regime lea-
ders, could be expected to dampen terrorism by providing a
nonviolent outlet for
political dissent while other qualities, such as the abundance of
easy targets and
the presence of a free media to amplify the propaganda impact
of terrorist attacks,
might make it more frequent. Eyerman described the first
quality as the ‘‘accessible
system’’ school of thought and the latter as the ‘‘soft target’’
school of thought.
Extending Eyerman, one may presume that illiberal regimes, by
restricting opportu-
nities for free political engagement, might present themselves to
dissidents as
‘‘inaccessible systems,’’ thereby incentivizing terrorism while

also presenting them-
selves as inhospitable or ‘‘hard’’ targets to terrorists by
repressing individual rights,
thereby reducing terrorism.
Subsequent scholarship has examined the intersection of regime
type and regime
institutions, and other features as explanatory variables for
terrorism. Li
5 first pro-
vided direct empirical evidence that, in part, supports the
contention that different
institutional aspects of liberal democracy, such as political
participation in elections
and constraints on executive authority, alternately reduce and
stimulate terrorism,
while Piazza6 found that young democracies are more terrorism-
plagued. Work by
Aksoy and Carter7 finds that among democracies, regimes with
proportional rep-
resentation systems and with higher levels of subnational
district magnitudes see a
more frequent emergence of certain types of terrorist groups.
Leveraging broader
scholarly trends in comparative politics, other current research
has also found that
dictatorships—regimes assumed to be inhospitable to terrorist
movements and
terrorist activity due to their heightened ability to mobilize
repression against
dissenters—are not uniformly impervious to terrorism. Wilson
and Piazza
8 find evi-
dence that among authoritarian regimes, military regimes

experience substantially
more terrorist attacks than do civilian-led, single-party
dictatorships. This is due to
the ability of such regimes to maximize both coercive and co-
optive tools to manage
domestic political dissent. Conrad et al.9 produce a
corresponding finding in their
empirical study of types of dictatorships and terrorism:
authoritarian regimes that
generate higher audience costs—military, single-party, and
dynastic autocracies—
experience more terrorism. Finally, Aksoy et al.10 find that
dictatorships that tolerate
opposition parties within their legislatures see fewer terrorist
groups emerge than
those that exclude opposition parties. This is because such
dictatorships are able to
better manage dissent and channel it into controllable avenues.
We can, therefore, see evidence that both regime type and
specific intra-regime
political institutions and institutional configurations matter as
predictors of terrorist
activity in countries. Can we extend this to say that regime
behaviors vis-à-vis
Repression and Terrorism 103
citizens’ rights—which can be conditioned on or shaped by
regime type and regime
institutions, but are distinct phenomena—matter as well? Some
research suggests, at
least preliminarily, that the answer to this question is yes. For
example, we do know

that regime treatment of citizens in terms of physical integrity
rights and regime
respect for minority rights both affect patterns of terrorism in
countries.11 Coupled
with a more general literature showing that degrees of
preservation of liberal rights
and deployment of repression against political dissent vary
considerably among
democratic regimes, as well as among dictatorships,12 these
scant findings suggest
that particular regime behaviors—whether or not citizens are
subject to political
repression—might predict the circumstances under which
terrorism will occur.
This suggests a closer look at repression, across countries, as a
predictor of ter-
rorism. Regime type is an overly aggregate predictor of
terrorism and disaggregating
repression into specific manifestations, I argue, is a way to
make sense of these
observed divergent and complex relationships. In this study, I
examine the impact
of different types of repression on the amount of domestic
terrorist attacks a country
sustained for the period 1981 to 2006. I undertake this
investigation starting with the
observation that repression can take different forms, affecting
different aspects of
citizens’ political, social, and personal rights. These different
forms, I theorize, could
yield different impacts on patterns of terrorism in countries. In
the next section, I
discuss three such theoretical relationships involving different
mixes of types of
repression that are hypothesized to either suppress or stimulate

terrorist attacks. I
then, in the subsequent section, test these different relationships
using data on nine
different types of repression—restriction of freedoms of speech,
association, move-
ment, religion, political self-determination, access to a free and
independent media,
physical integrity, labor rights, and minority political and
economic rights—as well
as aggregated indices of types of repression. I conclude with a
discussion of the
implications of the findings.
Repression as a Suppressor and Stimulant of Terrorism:
Three Theoretical Stories
In investigating repression, in all of its manifestations, as a
predictor of terrorist
attacks within countries, I identify three theoretical
relationships between forms of
repression and domestic terrorism. This set of three
relationships is intended to be
collectively exhaustive, from a theoretical standpoint. In the
first relationship, I
argue that repression raises the costs for engaging in terrorism
by political dissidents,
thereby reducing terrorist activity in a country. The second
relationship theorizes
that repression closes nonviolent avenues for political dissent,
which incentivizes
engagement in terrorist activity, leading to an increase in
terrorism. The third and
final theoretical relationship considers repression to be a key
ingredient in the forma-
tion and aggravation of group grievances, leading to higher
rates of terrorism in

countries. I discuss each of these relationships in turn.
Repression and Raised Costs of Terrorism
In this first theoretical story, state application of repression to
compel citizen
political support and to quash dissent produces a poor strategic
environment for
would-be terrorists, in a manner consistent with previously
discussed literature
(e.g., Schmid
13). Suppression of citizens’ ability to freely assemble and
engage in
104 J. A. Piazza
autonomous political activity inhibits the ability of terrorist
groups to form, draw
recruits, and plan their activities. Restrictions on media and on
free speech further
curtail the communication and propaganda efforts of terrorist
movements, com-
monly assumed to be the raison d’être of terrorism.14 Finally,
lack of constraints
on police surveillance, arrest, detention, physically punishing
interrogation, and even
disappearances of dissidents that are hallmarks of repressive
states dramatically
enhance the counterterrorism advantages of officials. All of
these elements are essen-
tially the flip side of Eyerman’s15 ‘‘soft target’’ depiction of
democratic regimes.
While liberal democracies are easy venues for terrorist

movements to work within,
illiberal regimes are inhospitable environments that suppress
terrorist activity by
making it more difficult, dangerous, and costly for dissidents to
engage in, and less
likely to be effective in terms of garnering public attention.
This scenario rests heav-
ily on the assumption that the decision of dissidents to engage
in terrorism is driven
by a strategic, rational calculus in which they opt to use the
tactic most likely to
advance their political objectives: to get attention, to influence
an audience, and to
secure concessions from their adversaries. State repression, in
this scenario, makes
the decision to engage in terrorism suboptimal. Therefore, we
should observe states
employing repression under these conditions, and using specific
types of restrictions
that raise the costs of terrorism—restriction of citizens’
movement, control over
independent citizen association, press censorship and
unconstrained policing, deten-
tion and interrogation—to experience less terrorist activity.
Repression and Closed Avenues for Dissent
In the second theoretical story, repressive means employed by
the state actually
incentivize would-be peaceful political dissidents to engage in
terrorism. This is a
scenario consistent with theoretical work by Crenshaw
16 and DeNardo17 and with
some of the empirical findings produced by Li,18 Aksoy and
Carter,19 Aksoy

et al.,20 Bravo and Dias,21 and Wilson and Piazza.22 In this
scenario, state
repressive measures that close legal avenues for political
dissent and redress of grie-
vances incentivizes dissenters to resort to more extreme, extra-
legal measures such as
terrorism. In contrast to the first scenario, suppression of free
speech and inde-
pendent press prompts dissidents to engage in demonstrations of
violence, like ter-
rorism, in order to break through official censorship to call
attention to
political grievances.
23
This theoretical story, therefore, makes use of the flip side of
Eyerman’s24
‘‘accessible system’’ school of thought regarding democracies
and terrorism. In
conditions under which the political system is ‘‘inaccessible,’’
dissidents are more
likely to see value in engaging in political violence and terrorist
activity, despite
the risks of doing so, than would be the case if legal avenues to
engage in dissent were
present. Again, this scenario is informed by some empirical
findings. Using a sample
of Latin American countries, Bravo and Dias25 find that those
that respect political,
civil, and human rights experience less anti-government
terrorist activity. Aksoy
et al.26 and Wilson and Piazza27 determine that dictatorships
that provide some
official opportunity for political dissent, albeit incomplete and

managed, are more
impervious to terrorism than those that do not. And like the first
scenario, it rests
on a rational=strategic actor assumption: dissidents engage in
terrorism because it
is a potentially more profitable course of action relative to
working within the
system.
Repression and Elevation of Group Grievances
In the third theoretical story, state repression also stimulates
terrorism, but via a
different route from the ‘‘Closed Avenues’’ story above. Rather
than altering the
strategic costs and benefits of using terrorism, repression in this
scenario alters the
overall climate of public approval of the government, thereby
affecting the potential
scope and effectiveness of terrorist activities. Experience of
repression de-legitimizes
the state and alienates citizens from government, fostering and
strengthening
anti-state, anti-status quo popular grievances. Repression
creates an environment
that is easily exploited by extremists engaged in terrorism, who
can more profitably
draw support from a sympathetic public, can more easily recruit
new members, can
more easily turn attacks into propaganda tools, and are less
vulnerable to potential
backlash normally generated by terrorist attacks.

28 In instances where state use of
repression is broad and indiscriminate, affecting dissidents and
apolitical bystanders
alike, opportunities for extremist movements to exploit public
outrage are even
greater.29 Furthermore, repressive states may find other states
less likely to cooperate
on counterterrorism efforts such as sharing of information and
extraditing terrorism
suspects because such activities violate internationalized
norms.30
There are several strands of theoretical and empirical support
for this scenario.
Borrowing from a theoretical framework for grievance and
rebellion developed by
Gurr,31 Crenshaw32 and Ross33 demonstrates, using examples
from historical case
studies of terrorist campaigns, that state oppression is an
important precipitant of
group grievances that help terrorist groups overcome collective
action and other
problems standing in the way of recruitment and mobilization of
political violence.
Research by Piazza34 empirically determines that countries
characterized by political
and economic discrimination against ethnic minority groups
experience significantly
more terrorism than countries without minority discrimination.
Moreover, noting
that some qualitative historical literature observes that state use
of repression—
particularly human rights abuses—ultimately undermines
government counterter-
rorism and counterinsurgency efforts by damaging relations

with local populations
and spurring domestic and transnational political opposition,
35 Walsh and Piazza36
find a positive empirical link between government respect for
physical integrity rights
and lower levels of terrorism in a cross-national sample. Bravo
and Dias37 produce
corresponding results for a sample of Latin American countries.
Hypotheses
These three theoretical stories translate into three testable
hypotheses:
H1: Forms of repression that contribute to the raising of the
costs
associated with engaging in terrorism reduce terrorist activity.
H2: Forms of repression that contribute to the closure of
peaceful
avenues for political dissent or redress increase terrorist
activity.
H3: Forms of repression that provoke or exacerbate group
grievances
increase terrorist activity.
In the study, these hypotheses are tested using sets of repression
indicators
developed from existing databases on regime attributes and
behaviors. These include
measures of restriction on citizens’ freedom of movement, both
domestically and
internationally, restriction on freedom of association and

membership in political
106 J. A. Piazza
and social organizations, restriction on electoral self-
determination through voting,
repression of independent labor unions, workplace
organizations, strikes and collec-
tive bargaining rights, restriction of free speech by citizens,
religious repression and
restriction of freedom of conscience, formal and informal
discrimination against
ethnic minorities, press restriction, and censorship and abuse of
citizens’ rights to
physical integrity.
To test the first hypothesis, forms of repression most clearly
associated with
raising the costs of engaging in terrorism by dissidents, or with
producing an inhos-
pitable or suboptimal strategic environment for using terrorism,
are regressed
against counts of terrorism. These include: restriction of
movement and association,
both of which make organizing, planning, and executing
terrorism difficult; press
censorship, which severely discounts the ability to use terrorist
attacks to transmit
propaganda or to influence a wider audience; and physical
integrity rights abuse,
which are associated with the use of torture, indefinite detention
and targeted
assassination=extrajudicial killing of terrorists, terror suspects,
and terrorist group

supporters. These types of repression are hypothesized to reduce
terrorism.
The second hypothesis is tested using forms of repression
reasonably argued to
be associated with closing peaceful avenues of dissent,
including: restriction of elec-
toral self-determination, restriction of free speech, and labor
restriction including
bans on the right to strike or public protest. Also tested along
with these forms of
repression is press censorship, which in the context of this
hypothesis is used to oper-
ationalize reduced opportunity for citizens to express
independent, critical, and
unauthorized political opinions. These types of repression are
hypothesized to
increase terrorism.
The third hypothesis is tested using forms of repression that are
most closely
associated with the provocation and sharpening of grievances in
the population,
including religious repression and ethnic minority
discrimination. Also included in
this category is abuse of physical integrity rights, given that
Walsh and Piazza
38 the-
orize that such abuses often undermine state counterterrorism
efforts because they
aggrieve and alienate the wider population, thereby
hamstringing government efforts
to gather intelligence about terrorists and their supporters and
to garner community
support to fight terrorism.

Analysis
To test the three hypotheses, the study conducts a series of
zero-inflated negative
binomial estimations using the nine individual measures of
repression in 149 coun-
tries for the period 1981 to 2006, the full range of years for
which I have relatively
complete data for all variables. These nine types of repression
constitute the main
independent variables of the study. Seven of the independent
variables are derived
from the Cingranelli and Richards (CIRI) Human Rights Data
project.39 CIRI pro-
vides ordinal scale measures of the status of and protections for
various political,
civil, social, and physical rights within countries for the period
1981 to 2006. I pro-
cess and re-scale many of these to produce a complement of
indicators of repression
of these rights in countries for the same time period to use in
my analyses. These
include measures of Physical Integrity rights abuse, restriction
of movement, free
speech, free association, electoral self-determination, restriction
of women’s empow-
erment, labor rights repression, and religious repression. To
measure abuse of Physi-
cal Integrity rights—protections against physical torture,
political imprisonment,

extrajudicial killing, or disappearance—I subtract eight from
the ‘‘PHYSINT’’
(Physical Integrity) indicator coded by CIRI to produce a scale
between 0 and 8,
where 8 indicates severe repression of physical integrity of
citizens. I measure restric-
tion of movement similarly by adding the two CIRI indicators
for restriction of dom-
estic and foreign movement or travel (‘‘DOMMOV’’ and
‘‘FORMOV’’) and
subtracting the sum from 4, producing a scale where 4 indicates
severe restriction
on citizen movement. Restriction of free speech, free
association, electoral self-
determination, labor rights, and religious rights are similarly re-
scaled in the analysis
by subtracting the original CIRI scores (for ‘‘SPEECH,’’
‘‘ASSOC,’’ ‘‘ELECSD,’’
‘‘WORKER’’ and ‘‘NEW_RELFREE’’) from 2, producing new
scales where 2
indicates severe repression of these rights.
I use data from non-CIRI sources for the remaining two
measures of repression.
I re-code data from the Freedom House Index of Press
Censorship,
40 converting the
original measure into a 10-point index where 10 indicates
severe restriction of media.
I also operationalize repression of minority group rights by
combining two indica-
tors derived from the Minorities at Risk41 database—political
discrimination
(‘‘POLDIS’’) and economic discrimination (‘‘ECDIS’’) suffered
by minority

groups—to construct a singular index scored between 0 and 8,
where 8 indicates
severe minority discrimination.
The dependent variable is a count of domestic terrorist attacks
occurring in a
country-year. This count is derived from data from the Global
Terrorism Database
(GTD) in Enders, Sandler, and Gaibulloev’s
42 study. The types of repression
engaged in by states would seem to most impact the amount of
domestic terrorist
activity—defined as terrorism launched by nationals of a
country targeting
co-nationals or domestic targets within the boundaries of the
country—occurring
within a country. So regressing measures of repression to counts
of domestic terror-
ism is an obvious design element.43 Alternative measures, such
as counts of terrorist
attacks that include transnational terrorism—defined as attacks
by foreigners
against domestic targets—would not seem to be clearly affected
by country-level
attributes such as political repression by a regime. Such attacks
are, therefore,
excluded from the analysis. Because the dependent variable is a
count indicator char-
acterized by significant levels of spatial and temporal
dispersion, and has a prepon-
derance of zero values (67.3% of all observations are zeros), I
utilize a zero-inflated
negative binomial regression estimation technique.
44 My decision to do this is further

buttressed by the results of Vuong tests conducted on all
models, the results of which
are all significant, indicating that a zero-inflated negative
binomial estimation tech-
nique is more efficient than a negative binomial technique that
pools
zero-observations and counts of terrorism.45 Finally, in all
models I also calculate
robust standard errors clustered on country.
Controls
Included in every model estimation are some standard
covariates, frequently found
in other cross-sectional time series empirical studies of
terrorism.46 Because the inde-
pendent variables measure regime behaviors rather than regime
type per se, I also
include a measure of political regime in each estimation. I use
the 21-point Polity
score for this. To hold constant level of economic development
and distribution of
incomes within countries, all specifications include country
Human Development
indices—which measure gross national income, literacy and life
expectancy
108 J. A. Piazza
rates—and national Gini coefficient measures of income
inequality. These are both
expected to be positive predictors of terrorism given that
Piazza47 found that econ-
omically developed countries—specifically countries that score

highly in terms of
human development as measured by the HDI—are more prone to
terrorist attacks
than poor or developing countries,48 and Eyerman49 and Li50
both find countries
with high levels of income inequality experience more
terrorism. To consider the
impact of state capacity to project military force, some of which
may be deployed
in a counterterrorism capacity, I also include the CINC index of
national capacity
from the Correlates of War database. My expectation is that this
will be a negative
predictor of terrorism. Also included are natural logged
measures of national popu-
lation and surface area of countries, both of which have been
found to positively pre-
dict terrorism.
51 The estimations also control for whether or not the country is
engaged in an interstate war and is experiencing a civil or intra-
state war to hold con-
stant other manifestations of violence.52 Because Eyerman53
found that older,
mature regimes are less likely to experience terrorism, the study
also controls for
age of political regime using the ‘‘Durable’’ score from the
Polity IV database.
Finally, all estimations control for past experience of terrorist
attacks.54 All inde-
pendent variables in the study are furthermore lagged one
period, within
country-case, to capture delayed effects and to aid in
determining direction of
causation.

Descriptive statistics for all variables used in the study are
presented in Table 1.
Table 1. Descriptive statistics
Variable Obs. Mean SD Min Max
Domestic terrorist attacks
(Enders et. al 2011)55
4,260 7.49 32.99 0 524
Physical integrity rights abuse 3,837 3.15 2.35 0 8
Restriction of movement 3,916 1.12 1.28 0 4
Restriction of association 3,640 .90 .84 0 2
Restriction of electoral
self-determination
3,645 .86 .84 0 2
Press censorship 4,472 5.92 2.84 1 10
Restriction of free speech 3,645 .95 .73 0 2
Labor repression 3,611 1.01 .78 0 2
Religious repression 3,859 .67 .80 0 2
Minority discrimination 3,011 3.28 3.04 0 8
Human development index 4,214 .66 .19 .22 .956
CINC score 3,980 .006 .019 2.73e-06 .190
Gini coefficient 4,228 42.87 9.19 20.7 84.8
(ln) Population 4,228 1.94 1.76 –2.65 7.18
(ln) Area 4,472 11.83 2.14 5.70 16.64
International war dummy 4,472 .01 .12 0 1
Civil war dummy 4,472 .16 .37 0 1
Regime type (polity) 3,810 1.58 7.43 –10 10
Regime durability 4,228 23.04 28.22 0 197

Table 2. Repression and domestic terrorism: Individual
measures
[1] [2] [3] [4]
Count
1
Zero-
infl
2
Count
1
Zero-
infl
2
Count
1
Zero-
infl
2
Count
1
Zero-
infl
2

Restrict. of movement t-1 .005
(.038)
.115
(.070)
Restrict. of association t-1 .022
(.063)
.129
(.127)
Restrict. of electoral self-
determin. t-1
.210��
(.070)
.047
(.138)
Restrict. of free speech t-1
Labor repression t-1
Religious repression t-1
Minority discrimination t-1
Press censorship t-1
Physical integrity rights abuse t-1
Regime type
(polity) t-1

.011�
(.005)
–.039��
(.008)
.025��
(.007)
–.013
(.013)
.025��
(.008)
–.015
(.015)
.041��
(.009)
–.024
(.016)
Regime durability t-1 –.004
��
(.001)
.005�
(.002)
–.004��
(.001)
.006�

(.002)
–.004��
(.001)
.006�
(.002)
–.004��
(.001)
.006�
(.002)
Human Dev. Index t-1 1.815
��
(.305)
�2.398��
(.494)
1.569��
(.325)
�1.873��
(.578)
1.509��
(.327)
–2.012��
(.594)
1.569��

(.327)
–1.973��
(.583)
CINC score t-1 3.658
�
(2.155)
7.089�
(3.385)
.269
(2.419)
–.201
(4.426)
1.288
(2.458)
1.719
(4.406)
1.275
(2.463)
1.599
(4.363)
Gini coefficient t-1 .038
��
(.006)
–.022�

(.009)
.033��
(.006)
–.015
(.010)
.032��
(.006)
–.016
(.010)
.032��
(.006)
–.017
(.010)
(ln) Population t-1 .479
��
(.044)
–.248��
(.063)
.465��
(.048)
–.210��
(.075)
.440��
(.049)

–.240��
(.079)
.450��
(.048)
–.220��
(.077)
(ln) Area t-1 –.126
��
(.033)
–.027
(.045)
–.097��
(.036)
–.019
(.052)
–.100��
(.037)
–.020
(.053)
–.106��
(.037)
–.028
(.053)
International war

(COW) t-1
–.008
(.204)
.321
(.385)
.231
(.241)
.544
(.529)
.232
(.241)
.483
(.525)
.313
(.243)
.508
(.518)
Civil war
(PRIO) t-1
.875��
(.079)
�1.147��
(.189)
.947��

(.092)
�1.479��
(.265)
.934��
(.088)
�1.391��
(.263)
.958��
(.088)
�1.363��
(.258)
Terrorist attacks t-1 .018
��
(.001)
�1.367��
(.197)
.016��
(.001)
�1.035��
(.167)
.016��
(.001)
�1.025��

(.163)
.016��
(.001)
�1.004��
(.159)
Constant –1.182�
(.493)
4.189��
(.780)
–1.120�
(.516)
3.013��
(.898)
–.932�
(.528)
3.269��
(.932)
–1.124�
(.530)
3.389��
(.922)
N 4,767 3,338 3,274 3,279
Nonzero obs. 1,657 1,343 1,330 1,331
Zero obs. 3,110 2,039 1,944 1,948
LR v2 1294.36�� 1101.06�� 1062.99�� 1073.75��

Vuong test (z) 12.62�� 9.96�� 10.02�� 9.95��
Y¼Counts of domestic terrorist attacks. All models zero-
inflated negative binomial
1Count model, negative binomial.
2Zero-inflated logit (certain zero).
�p� .1; ��p� .01; ��p� .000.
110 J. A. Piazza
[5] [6] [7] [8] [9] [10]
Count
1
Zero-
infl
2
Count
1
Zero-
infl
2
Count
1
Zero-
infl
2
Count

1
Zero-
infl
2
Count
1
Zero-
infl
2
Count
1
Zero-
infl
2
–.001
(.075)
.154
(.133)
.091�
(.055)
.299��
(.113)
.129�
(.052)

.124
(.105)
.120��
(.016)
–.049�
(.030)
.024
(.025)
–.006
(.045)
.089��
(.024)
–.125��
(.045)
.023��
(.007)
–.018
(.013)
.028��
(.007)
–.010
(.012)
.026��
(.007)

–.021�
(.012)
.027��
(.008)
–.010
(.014)
.018�
(.009)
–.041��
(.016)
.034��
(.007)
–.041��
(.012)
–.004��
(.001)
.006�
(.002)
–.005��
(.001)
.006�
(.002)
–.007��
(.001)

.006�
(.003)
–.001
(.001)
.004
(.003)
–.004��
(.001)
.005��
(.002)
–.003�
(.001)
.004�
(.002)
1.514��
(.328)
–1.983��
(.584)
1.539��
(.330)
�2.057��
(.589)
1.944��
(.335)

–1.839��
(.601)
1.137��
(.406)
–.513
(.732)
1.852��
(.308)
�2.411��
(.502)
1.582��
(.328)
–2.004��
(.594)
1.129
(2.439)
1.291
(4.400)
1.562
(2.475)
–2.848
(5.349)
–7.925��
(2.920)

–7.190
(7.234)
2.741
(2.632)
–7.557
(12.180)
3.653�
(2.158)
7.172�
(3.395)
1.523
(2.481)
1.597
(4.408)
.032��
(.006)
–.016
(.010)
.030��
(.007)
–.021�
(.010)
.035��
(.007)

–.014
(.010)
.028��
(.007)
.002
(.012)
.039��
(.006)
–.022�
(.009)
.028��
(.007)
–.013
(.010)
.445��
(.048)
–.227��
(.077)
.429��
(.049)
–.223��
(.080)
.518��
(.051)

–.150�
(.082)
.495��
(.056)
–.108
(.105)
.475��
(.044)
–.248��
(.063)
.397��
(.050)
–.159�
(.081)
–.102��
(.037)
–.027
(.053)
–.092�
(.038)
–.029
(.054)
–.117��
(.037)

–.042
(.054)
-.208��
(.041)
–.052
(.066)
–.125��
(.033)
–.028
(.045)
–.076�
(.038)
–.013
(.054)
.230
(.243)
.484
(.522)
.233
(.244)
.399
(.543)
.161
(.249)

.425
(.562)
.537�
(.274)
.858
(.693)
–.010
(.204)
.318
(.368)
.296
(.242)
.526
(.546)
.938��
(.091)
�1.414��
(.263)
.945��
(.089)
�1.454��
(.265)
.963��
(.089)

�1.490��
(.272)
.943��
(.100)
�1.727��
(.434)
.864��
(.080)
�1.148��
(.189)
.768��
(.099)
�1.176��
(.273)
.016��
(.001)
�1.009��
(.160)
.016��
(.001)
�1.036��
(.171)
.016��
(.001)

�1.068��
(.180)
.015��
(.001)
�1.051��
(.211)
.018��
(.001)
�1.371��
(.198)
.015��
(.001)
�1.030��
(.176)
–.909�
(.538)
3.250��
(.927)
–1.023�
(.532)
3.372��
(.924)
–1.349��
(.524)

3.193��
(.915)
–.109
(.577)
1.691
(1.105)
–1.366��
(.533)
4.244��
(.870)
–1.309�
(.539)
3.404��
(.935)
3,279 3,247 3,326 2,578 4,767 3,245
1,331 1,318 1,308 1,050 1,657 1,326
1,948 1,929 2,018 1,528 3,110 1,919
1064.72�� 1056.82�� 1094.29�� 818.98��
1295.29�� 1072.58��
9.98�� 9.92�� 9.82�� 7.94�� 12.60�� 9.82��
estimations. All predictors lagged one period.
111

Results
Table 2 presents the results of the estimations regressing the
individual measures
of repression to terrorist attacks. Because the individual
components are correlates
of one another, they are run in separate models to avoid
problems of
multicollinearity.56
Model 1 is a simple baseline model that only includes the
covariates. Here we
can see that regime type, measured using the Polity score, is a
positive and significant
predictor of counts of terrorist attacks and is a negative
predictor of the likelihood a
country will experience no terrorism. This finding is consistent
with the mainstay of
research showing that democracies, measured as an overall
regime type, experience
higher rates of terrorism.57 The essence of this finding—for the
count model—is
reproduced across all of the models in Table 2. It is therefore
interesting that in
the remaining models, some measures of repression, which
operationalize regime
behavior rather than regime type, are found to be significant
even when holding
regime type constant.
The first hypothesis, which expects forms of repression that
raise costs for ter-
rorist activity and=or worsen the strategic environment for
would-be terrorists to
reduce terrorist attacks, is tested using the measures of
restriction of movement,

association, press censorship, and physical integrity rights
abuse (Models 2, 3, 9,
and 10). However, the results in Table 2 do not yield support. In
Models 2, 3, and
9 the repression indicator is not found to be significant for
either the count or the
zero-inflated logit. The coefficient for the count model for
physical integrity rights
abuse in Model 10 is significant but positive for the count
model, contra expecta-
tions, while the coefficient for the zero-inflated logit is
significant and negative. (A
similar pattern is evident for the other indicators used to test the
first hypothesis:
coefficients for the count models are positive, rather than
negative, but do not meet
standard levels of statistical significance.)
The second hypothesis, which anticipates that elements of
repression associated
with closure of nonviolent opportunities for political dissent
boost terrorism, is
tested in Models 4, 5, 6, and 9. This hypothesis is partly
supported by the results.
As hypothesized, restriction of electoral self-determination
(Model 4) and labor
repression (Model 6) are significant and positive predictors of
counts of terrorist
attacks—though electoral self-determination is not found to
reduce the likelihood
that a country experiences zero attacks and labor repression is
found to boost both
high counts of terrorism and the probability a country
experiences zero attacks, sug-
gesting a more complex relationship between this manifestation
of repression and

terrorism.
58 However, restriction of free speech (Model 5) and press
censorship
(Model 9) are not found to be significant.
The third hypothesis, in which forms of repression that provoke
or exacerbate
public grievances against the state are expected to increase
terrorist activity in coun-
tries, is most consistently supported by the results. All three
specific repression indi-
cators associated with this hypothesis—religious repression
(Model 7), minority
discrimination (Model 8), and abuse of physical integrity rights
of citizens (Model
10)—are found to be significant predictors of counts of terrorist
attacks in countries.
Moreover, for minority discrimination and physical integrity
abuse, the zero-inflated
logit coefficient is also significant and signed in the proper
direction, suggesting that
countries characterized by low levels of these two forms of
repression are more likely
to experience no terrorism at all.
112 J. A. Piazza
In all 10 of the regression estimation models, these results are
found to be robust
to the inclusion of some highly significant controls.59 Across
all models, regime type,
regime durability, level of human=economic development,
income inequality mea-

sured using the Gini coefficient, national population, the civil
war indicator, and
counts of previous terrorism are significant predictors of
terrorism in the expected
direction. Country surface area is also significant in all models,
but in the opposite
direction expected: negative. Only the national capabilities
index (CINC) and the
dummy variable for country participation in an international
war are not consist-
ently significant across models. Inclusion of these control
indicators, along with
the calculation of country-clustered robust standard errors, help
to allay concerns
of omitted variable biases in the estimations.
Substantive Impact of Forms of Repression on Terrorism
To assess the substantive effects of the various types of
repression examined in the
analysis, I calculated marginal effects with all covariates set
constant at their means.
The results of these for the individual and aggregate measures
of repression are
graphed in Figure 1.
In the figure, the mean substantive effect on the dependent
variable—in this
case, counts of terrorism—is graphed along with upper and
lower 95% confidence
intervals. Figure 1 reveals that of the forms of repression
examined, restriction of
electoral self-determination results in the highest amount of
subsequent terrorism
(.95 attacks). On average, for each one-point (out of a 3-point
scale) increase in

repression of electoral self-determination, countries are found
to experience 23.3%
more domestic terrorist attacks. Countries featuring repression
of labor rights and
religious freedom experience on average between .53 and .42
more attacks than
Figure 1. Marginal effects of individual types of repression on
domestic terrorist attacks.
countries without such repression. Increasing by one point
(again, out of a 3-point
scale) labor or religious repression boosts domestic terrorist
attacks by 9.5 and
13.9% respectively. Repression of minority rights and physical
integrity rights abuses
bear a similar substantive effect: countries featuring these types
of repression experi-
ence, on average, .41 more attacks than countries that do not. A
one-point increase
(out of an 8-point scale) in minority discrimination increases
terrorism by 12.4% and
by 10.1% for physical integrity rights abuse. The other forms of
repression are not
significant.
Conclusion
The study produces several key conclusions. First, the study
finds that repression
overall is a stimulant, rather than a suppressor, of domestic
terrorism within

countries: none of the specific types of repression are found to
reduce terrorism. This
finding, while consistent with some studies of individual
predictors of terrorism like
human rights abuses,59 largely contradicts the mainstream
theoretical expectation in
the field of terrorism studies and in the policy community that
repression is an effec-
tive safeguard against or panacea for terrorism.60 Illiberal
states that repress their
populations do not inoculate themselves from terrorism via
repression, and liberal
states should not expect greater protection from terrorism by
augmenting the rights
of their citizens.
Second, in disaggregating repression into specific forms, the
study finds that
some manifestations of repression actually increase a country’s
vulnerability to
attacks. This finding appears to be the product of two processes
and a handful of
specific types of repression. When repression road-blocks
nonviolent alternatives
to participation—most notably when it obstructs citizens’ rights
to participate in
elections and when it deters expressions of labor rights—
domestic terrorism
increases. Indeed, electoral self-determination is found to be the
most substantive
precipitant of terrorism in the analysis, prompting almost
double the amount of ter-
rorism than the other predictors. Discrimination against
minorities and physical
repression are found to increase domestic terrorism by
prompting popular grievances

and alienating citizens from the government—a finding that is
consistent with pre-
vious empirical research. However, religious repression is also
found to precipitate
terrorism by increasing grievance and alienation, and is found
to be a slightly more
substantive predictor than minority or physical repression.
These findings help to
clarify the causal relationship between repression and
terrorism—showing it to be
conditional on the type of repression—and underscore the
importance of disaggrega-
tion when contemplating the relationship between regime type
and terrorism.
Notes
1. Ana Bela Santos Bravo and Carlos Manuel Mendes Dias,
‘‘An Empirical Analysis of
Terrorism: Deprivation, Islamism and Geopolitical Factors,’’
Defence and Peace Economics
17, no. 4 (2006): 329–341; Stephen B. Blomberg and B. Peter
Rosendorff, ‘‘A Gravity Model
of Globalization, Democracy and Transnational Terrorism,’’ in
G. D. Hess, ed., Guns and But-
ter (Cambridge: MIT Press, 2007), 25–156; Alex Braithwaite
and Quan Li, ‘‘Transnational
Terrorism Hot Spots: Identification and Impact Evaluation,’’
Conflict Management and Peace
Science 24, no. 4 (2007): 281–296; Axel Dreher and Justina A.
V. Fischer, ‘‘Government
Decentralization as a Disincentive for Transnational Terror? An
Empirical Analysis,’’ Inter-
national Economic Review 51, no. 4 (2010): 981–1002;
Konstantinos Drakos and Andreas

114 J. A. Piazza
Gofas, ‘‘In Search of the Average Transnational Terrorist
Attack Venue,’’ Defence and Peace
Economics 17, no. 2 (2006): 73–93; William Lee Eubank and
Leonard Weinberg, ‘‘Does
Democracy Encourage Terrorism?’’ Terrorism and Political
Violence 6, no. 4 (Winter 1994):
417–443; William Lee Eubank and Leonard Weinberg,
‘‘Terrorism and Democracy: What
Recent Events Disclose,’’ Terrorism and Political Violence 10,
no. 1 (1998): 108–118; William
Lee Eubank and Leonard Weinberg, ‘‘Terrorism and
Democracy: Perpetrators and Victims,’’
Terrorism and Political Violence 13, no. 1 (Spring 2001): 155–
164; Kate Ivanova and Todd
Sandler, ‘‘CBRN Incidents: Political Regimes, Perpetrators and
Targets,’’ Terrorism and Polit-
ical Violence 18, no. 3 (2006): 423–448; Quan Li and Drew
Schaub, ‘‘Economic Globalization
and Transnational Terrorism: A Pooled Time-Series Analysis,’’
Journal of Conflict Resolution
48, no. 2 (2004): 230–258; James A. Piazza, ‘‘Do Democracy
and Free Markets Protect Us
from Terrorism?’’ International Politics 45 (2008): 72–91;
Burcu Savun and Brian J. Phillips,
‘‘Democracy, Foreign Policy and Terrorism,’’ Journal of
Conflict Resolution 53, no. 6
(2009): 878–904; Sarah Jackson Wade and Dan Reiter, ‘‘Does
Democracy Matter?’’ Journal
of Conflict Resolution 51, no. 2 (2007): 329–348.
2. Alex Schmid, ‘‘Terrorism and Democracy,’’ Terrorism and
Political Violence 4, no. 4

(Winter 1992): 14–25.
3. Alan Dershowitz, ‘‘Is an Outright Ban the Best Way to
Eliminate or Constrain
Torture?’’ in Stuart Gottlieb, ed., Debating Terrorism and
Counterterrorism: Conflicting Per-
spectives on Causes, Contexts and Responses (Washington, DC:
Congressional Quarterly Press,
2009), 320–335; Axel Dreher, Martin Gassebner, and Lars H. R.
Siemers, ‘‘Does Terror
Threaten Human Rights?: Evidence from Panel Data,’’ CESIFO
Working Paper No. 1935
(2007),
http://www.econstor.eu/bitstream/10419/25980/1/538079215.PD
F; Connor Gearty,
‘‘Terrorism and Human Rights,’’ Government and Opposition
42, no. 3 (2007): 340–362; Paul
Hoffman, ‘‘Human Rights and Terrorism,’’ Human Rights
Quarterly 26, no. 4 (2004):
932–955; John Yoo, ‘‘Counterterrorism and the Constitution:
Does Providing Security
Require a Trade-Off with Civil Liberties?’’ in Stuart Gottlieb,
ed., Debating Terrorism and
Counterterrorism: Conflicting Perspectives on Causes, Contexts
and Responses (Washington,
DC: Congressional Quarterly Press, 2009), 339–352.
4. Joe Eyerman, ‘‘Terrorism and Democratic States: Soft
Targets or Accessible
Systems,’’ International Interactions 24, no. 2 (1998): 151–170.
5. Quan Li, ‘‘Does Democracy Produce or Reduce Transnational
Terrorist Incidents?’’
Journal of Conflict Resolution 49, no. 2 (2005): 278–297.
6. James A. Piazza, ‘‘Regime Age and Terrorism: Are New

Democracies Prone to
Terrorism?’’ International Interactions 36, no. 2 (2013): 246–
263.
7. Deniz Aksoy and David Carter, ‘‘Electoral Institutions and
the Emergence of
Terrorist Groups,’’ British Journal of Political Science 44, no. 1
(2014): 181–204.
8. Matthew Wilson and James A. Piazza, ‘‘Autocracies and
Terrorism: Conditioning
Effects of Authoritarian Regime Type on Terrorist Attacks,’’
American Journal of Political
Science 57, no. 4 (2013): 941–955.
9. Courtenay Conrad, Justin Conrad, and Joseph Young,
‘‘Tyrants and Terrorism: Why
Some Autocrats are Terrorized While Others Are Not,’’
International Studies Quarterly 58,
no. 3 (2014): 539–549.
10. Deniz Aksoy, David Carter, and Joseph Wright, ‘‘Terrorism
in Dictatorships,’’
Journal of Politics 74, no. 3 (2012): 810–826.
11. Andreas E. Feldmann and Maiju Perälä, ‘‘Reassessing the
Causes of Nongovernmen-
tal Terrorism in Latin America,’’ Latin American Politics and
Society 46 (2004): 101–132;
James A. Piazza, ‘‘Types of Minority Discrimination and
Terrorism,’’ Conflict Management
and Peace Science 29 (2012): 521–546; James A. Piazza,
‘‘Poverty, Minority Economic Dis-
crimination and Terrorism,’’ Journal of Peace Research 48, no.
3 (2011): 339–353; James I.
Walsh and James A. Piazza, ‘‘Why Respecting Physical

Integrity Rights Reduces Terrorism,’’
Comparative Political Studies 43, no. 4 (2010): 551–577.
12. Christian Davenport, ‘‘State Repression and the Tyrannical
Peace,’’ Journal of Peace
Research 44, no. 4 (2007): 485–504; Hanne Fjelde, ‘‘Generals,
Dictators, and Kings: Authori-
tarian Regimes and Civil Conflict, 1973–2004,’’ Conflict
Management and Peace Science 27,
no. 3 (2010): 195–218; Barbara Geddes, Paradigms and
Sandcastles: Theory Building and
Research Design in Comparative Politics (Ann Arbor:
University of Michigan Press, 2003);
Jennifer Gandhi, Political Institutions under Dictatorship (New
York: Cambridge University
http://www.econstor.eu/bitstream/10419/25980/1/538079215.PD
F;
Press, 2008); Kristian S. Gleditsch and Michael D. Ward,
‘‘Double Take: A Reexamination of
Democracy and Autocracy in Modern Polities,’’ Journal of
Conflict Resolution 41, no. 3
(1997): 361–383.
13. Schmid, ‘‘Terrorism and Democracy’’ (see note 2 above).
14. Brigitte Nacos, Mass-Mediated Terrorism: The Central Role
of the Media in Terrorism
and Counterterrorism (Lanham, MD: Rowman and Littlefield,
2007); Robert Pape, ‘‘The
Strategic Logic of Suicide Terrorism,’’ American Political
Science Review 97, no. 3 (August

2003): 343–361.
15. Eyerman, ‘‘Terrorism and Democratic States’’ (see note 4
above).
16. Martha Crenshaw, ‘‘The Causes of Terrorism,’’
Comparative Politics 13 (1981):
379–399.
17. James DeNardo, Power in Numbers: The Political Strategy
of Protest and Rebellion
(Princeton, NJ: Princeton University Press, 1985).
18. Li, ‘‘Does Democracy Produce or Reduce Transnational
Terrorist Incidents?’’ (see
note 5 above).
19. Aksoy and Carter, ‘‘Electoral Institutions and the
Emergence of Terrorist Groups’’
(see note 7 above).
20. Aksoy et al., ‘‘Terrorism in Dictatorships’’ (see note 10
above).
21. Bravo and Dias, ‘‘An Empirical Analysis of Terrorism’’
(see note 1 above).
22. Wilson and Piazza, ‘‘Autocracies and Terrorism’’ (see note
8 above).
23. A case example helps to explain this. Domestic political
repression and media censor-
ship in Brazil during the 1964–1985 military dictatorship is a
commonly cited motive for the
1969 kidnapping of U.S. Ambassador Charles Burk Elbrick by
the Left-Wing MR-8 (Revol-
utionary Movement 8 October). MR-8 hoped to circumvent
government restrictions on media
and political dissent by kidnapping a prominent diplomat.

above).
(see note 1 above).
26. Aksoy et al., ‘‘Terrorism in Dictatorships’’ (see note 10
above).
27. Wilson and Piazza, ‘‘Autocracies and Terrorism’’ (see note
8 above).
28. Kalevi J. Holsti, ‘‘Political Causes of Humanitarian
Emergencies,’’ in Wayne
Nafziger, Frances Stewart, and Raimo Vayrynen, eds., War,
Hunger and Displacement: The
Origins of Humanitarian Emergencies (Oxford: Oxford
University Press, 2000), 239–281;
Andreas Wimmer, ‘‘Who Owns the State? Understanding Ethnic
Conflict in Post-Colonial
Societies,’’ Nations and Nationalism 3 (1997): 631–666.
29. Stathis Kalyvas, ‘‘The Paradox of Terrorism in Civil War,’’
The Journal of Ethics 8,
no. 1 (2004): 97–138.
30. Martha Finnemore and Kathryn Sikkink, ‘‘International
Norm Dynamics and
Political Change,’’ International Organization 52 (1998): 887–
917.
31. Ted Robert Gurr, Why Men Rebel (Princeton, NJ: Princeton
University Press,
1970); Ahmed S. Hashim, Insurgency and Counterinsurgency in
Iraq (Ithaca, NY: Cornell
University Press, 2006); Ted Robert Gurr, ‘‘Why Minorities
Rebel: A Global Analysis of
Communal Rebellion and Conflict since 1945,’’ International

Political Science Review 14
(1993): 161–201.
32. Crenshaw, ‘‘The Causes of Terrorism’’ (see note 16 above).
33. Jeffery Ian Ross, ‘‘Structural Causes of Oppositional
Political Terrorism: A Causal
Model,’’ Journal of Peace Research 30 (1993): 317–329.
34. Piazza, ‘‘Types of Minority Discrimination and Terrorism’’
(see note 11 above);
Piazza, ‘‘Poverty, Minority Economic Discrimination and
Terrorism’’ (see note 11 above).
35. Max Abrahms, ‘‘Why Democracies Make Superior
Counterterrorists,’’ Security Stu-
dies 16, no. 2 (2007): 223–253; Hashim, Insurgency and
Counterinsurgency in Iraq (see note 31
above); Anthony James Joes, Resisting Rebellion: The History
and Politics of Counterinsur-
gency (Lexington: University of Kentucky Press, 2004); Gil
Merom, How Democracies Lose
Small Wars (Cambridge: Cambridge University Press, 2003);
Edward Rice, Wars of the Third
Kind: Conflict in Underdeveloped Countries (Berkeley, CA:
University of California Press,
1988).
36. Walsh and Piazza, ‘‘Why Respecting Physical Integrity
Rights Reduces Terrorism’’
(see note 11 above).
(see note 1 above).
116 J. A. Piazza

39. David L. Cingranelli and David L. Richards, CIRI Human
Rights Data Project
(2010), http://ciri.binghamton.edu/index.asp.
40. Freedom House, Freedom of the Press Data (2012),
http://www.freedomhouse.org/
report-types/freedom-press
41. Minorities and Risk Project, ‘‘Minorities at Risk Dataset’’
(College Park, MD: Center
for International Development and Conflict Management, 2009),
http://www.cidcm.
umd.edu/mar
42. Walter Enders, Todd Sandler, and Khusrav Gaibulloev,
‘‘Domestic Versus Transna-
tional Terrorism: Data, Decomposition and Dynamics,’’ Journal
of Peace Research 48, no. 3
(2011): 319–337.
43. Furthermore, domestic terrorism is a more frequent,
widespread, and deadly=damag-
ing phenomenon than transnational terrorism. (See Ignacio
Sanchez-Cuenca and Luis de la
Calle, ‘‘Domestic Terrorism: The Hidden Side of Political
Violence,’’ Annual Review of Polit-
ical Science 12 [2009]: 31–49; Enders et al., ‘‘Domestic Versus
Transnational Terrorism’’ [see
note 42 above]). Enders et al. provide a thorough discussion of

the operational difference
between domestic and transnational terrorism.
44. The zero-inflated technique facilitates the separate
investigation of predictors of
counts of terrorist attacks and the likelihood that a country will
experience zero terrorist
attacks. In theory, these can bear different relationships. Patrick
T. Brandt, John T. Williams,
Benjamin O. Fordham, and Brian Pollins, ‘‘Dynamic Models for
Persistent Event Count Time
Series,’’ American Journal of Political Science 44, no. 4 (2000):
823–843; Adrian Colin
Cameron and P. K. Trivedi, Regression Analysis of Count Data
(Cambridge: Cambridge
University Press, 1998); Gary King, ‘‘Statistical Models for
Political Science Event Counts:
Bias in Conventional Procedures and Evidence for the
Exponential Poisson Regression
Model,’’ American Journal of Political Science 32, no. 3
(1988): 838–863.
45. The results of the Vuong tests are reported in the main
results for all models. W. H.
Greene, ‘‘Accounting for Excess Zeros and Sample Selection in
Poisson and Negative
Binomial Regression Models,’’ Working Paper, Stern School of
Business, New York Univer-
sity (1994), EC-94-10; J. S. Long, Regression Models for
Categorical and Limited Dependent
Variables (Thousand Oaks, CA: Sage, 1997); Q. Vuong,
‘‘Likelihood Ratio Tests for Model
Selection and Non-Nested Hypotheses,’’ Econometrica 57
(1989): 307–333.
46. See Martin Gassebner and Simon Luechinger, ‘‘Lock, Stock,

and Barrel: A Compre-
hensive Assessment of the Determinants of Terror,’’ Public
Choice 149, nos. 3–4 (2011):
235–261.
47. Piazza, ‘‘Poverty, Minority Economic Discrimination and
Terrorism’’ (see note 11
above).
48. Though I expect HDI to be a positive predictor of terrorism,
I do note the body of
complicated empirical findings regarding poverty and terrorism.
For example, Braithwaite
and Li, ‘‘Transnational Terrorism Hotspots’’ (see note 1 above)
and Li, ‘‘Does Democracy
Produce or Reduce Transnational Terrorist Incidents?’’ (see
note 5 above) find poverty to
boost terrorism in countries, while Abadie, Blomberg and Hess,
and Enders, Hoover and
Sandler find a more complex and nonlinear relationship between
poverty and terrorism:
Alberto Abadie, ‘‘Poverty, Political Freedom, and the Roots of
Terrorism,’’ American Econ-
omic Review 96, no. 2 (2006): 50–56; S. Brock Blomberg and
Greogory Hess, ‘‘From (No) But-
ter to Guns? Understanding the Economic Role in Transnational
Terrorism,’’ in Keefer and
Loayza, eds., Terrorism, Economic Development, and Political
Openness (Cambridge, MA:
Cambridge University Press, 2008), 83–115; Walter Enders,
Gary A. Hoover, and Todd Sand-
ler, ‘‘The Changing Nonlinear Relationship Between Poverty
and Terrorism’’ Journal of
Conflict Resolution (Forthcoming, 2015).
doi:10.1177=0022002714535252.

above).
note 5 above).
51. Wade and Reiter, ‘‘Does Democracy Matter?’’ (see note 1
above); Eyerman, ‘‘Terror-
ism and Democratic States’’ (see note 4 above).
note 5 above); Michael G. Findley and Joseph K. Young,
‘‘Terrorism and Civil War: A Spatial
http://ciri.binghamton.edu/index.asp
http://www.freedomhouse.org/report-types/freedom-press
http://www.freedomhouse.org/report-types/freedom-press
http://www.cidcm.umd.edu/mar
http://www.cidcm.umd.edu/mar
and Temporal Approach to a Conceptual Problem,’’
Perspectives on Politics 10, no. 2 (2012):
285–305.
above).
54. This is accomplished by inserting a lagged measure of the
dependent variable in on
the right-hand side in all estimations. As a check of robustness,
duplicate models are also

run with this lagged dependent variable removed. These produce
the same results as those por-
trayed in the main analysis.
55. Walter Enders, Todd Sandler, and Khusrav Gaibulloev,
‘‘Domestic Versus Transna-
tional Terrorism: Data, Decomposition and Dynamics,’’ Journal
of Peace Research 48, no. 3
(2011): 319–337.
56. All are significantly correlated with one another at the p�
.000 level. Variance
inflation factor diagnostics are not necessarily suggestive of
strong multicollinearity (mean
VIF¼2.23). However, the condition number, calculated on
eigenvalues extracted from the
variables in the model, registers at 55.5, suggesting some
concern that collinearity problems
are affecting significance levels and signs of coefficients. D. A.
Belsley, E. Kuh, and R. E.
Welsch, Regression Diagnostics: Identifying Influential Data
and Sources of Collinearity
(New York, NY: John Wiley, 1980).
57. e.g., Eubank and Weinberg, ‘‘Does Democracy Encourage
Terrorism?’’ (see note 1
above).
58. Countries characterized by labor repression are more likely
to experience either high
levels of terrorism or they are likely to experience none at all.
This peculiar finding underscores
the value of using the zero-inflated technique. A standard
negative binomial regression analy-
sis reveals a non-significant negative relationship between labor
repression and domestic ter-

rorism. It is likely that two different theoretical processes
predict the likelihood that repression
of labor rights will prompt a country to experience no terrorism
versus a high level of terror-
ism, and that the effect of these processes is washed in an
estimation where zero values are
pooled with counts of attacks, thereby masking a significant
relationship between labor
repression and terrorism.
59. When a control for the Muslim population of a country is
included in the estimations,
the core results remain the same. When a dichotomous indicator
for Afghanistan, Iraq, and
Pakistan is included—three countries that experience high
levels of terrorism in the later per-
iod of the data—the core results remain the same with two
exceptions: religious repression
becomes borderline significant and labor repression is not found
to be significant in the count
model only.
61. Dershowitz, ‘‘Is an Outright Ban the Best Way to Eliminate
or Constrain Torture?’’
(see note 3 above); Yoo, ‘‘Counterterrorism and the
Consitution’’ (see note 3 above).
118 J. A. Piazza
Repression as a Suppressor and Stimulant of Terrorism: Three
Theoretical StoriesRepression and Raised Costs of
TerrorismRepression and Closed Avenues for DissentRepression
and Elevation of Group

GrievancesHypothesesAnalysisControlsResultsSubstantive
Impact of Forms of Repression on TerrorismConclusionNotes
Journal of Criminal Justice 47 (2016) 12–20
Contents lists available at ScienceDirect
Journal of Criminal Justice
Sensitivity to the Ferguson Effect: The role of managerial
organizational justice
Justin Nix a,⁎, Scott E. Wolfe b
a University of Louisville, 2301 South 3rd Street, Louisville,
KY 40292, United States
b University of South Carolina, 1305 Greene Street, Columbia,
SC 29208, United States
⁎ Corresponding author.
E-mail address: [email protected] (J. Nix).
http://dx.doi.org/10.1016/j.jcrimjus.2016.06.002
0047-2352/© 2016 Elsevier Ltd. All rights reserved.
a b s t r a c t
a r t i c l e i n f o
Article history:
Received 25 May 2016
Received in revised form 27 June 2016
Accepted 28 June 2016
Available online 6 July 2016
Purpose: We argue that the police have been adversely impacted
by Ferguson-related negative publicity in ways
beyond the supposed increase in crime (e.g., reduced motivation
and increased perception of danger). Further,
we suggest that organizational justice is a key factor that
influences officers' sensitivity to such Ferguson Effects.

Methods: We used a sample of 510 sheriff's deputies surveyed 6
months after the incident in Ferguson. We ex-
plored whether organizational justice is associated with
deputies' sensitivity to several manifestations of the
Ferguson Effect using OLS and ordered logistic regression
models.
Results: The results demonstrated that deputies who believed
their supervisors were more organizationally fair
were less likely to feel unmotivated, perceive more danger,
believe their colleagues have been negatively impact-
ed, or feel that US citizens and local residents have become
more cynical toward the police in the post-Ferguson
era.
Conclusions: Police supervisors who use organizational justice
as a guiding managerial philosophy are more likely
to shield their officers from the negative work-related outcomes
that can follow recent Ferguson-type publicity.
Supervisors should be fair, objective, honest, and respectful
when dealing with their subordinates in order to
communicate that the agency has their back even when it may
appear the community does not.
© 2016 Elsevier Ltd. All rights reserved.
Keywords:
Policing
Police management
Organizational justice
Ferguson Effect
1. Organizational justice and sensitivity to the Ferguson Effect
Over the last eighteen months, there has been much debate
about
the so-called “Ferguson Effect” on US police. This idea holds
that in re-
sponse to heightened scrutiny of the police following the fatal
shooting

of unarmed Michael Brown in Ferguson, Missouri in August
2014, offi-
cers are less motivated to aggressively perform their duties and
are
pulling back from proactive strategies. Proponents suggest that
this
“de-policing” will result in increased crime rates throughout the
US.
The most robust empirical assessment of this argument to date
recently
revealed that the Ferguson Effect has not caused increased
crime across
the US (Pyrooz, Decker, Wolfe, & Shjarback, 2016; but see also
Rosenfeld, 2016). While this evidence is good news and puts to
rest
any worries of a nationwide crime wave (see Mac Donald,
2015),
there may in fact be other ways in which the Ferguson Effect
manifests
itself. For instance, research has shown that negative publicity
sur-
rounding the police in the aftermath of Ferguson was associated
with
lower levels of officer self-legitimacy (Nix & Wolfe, 2015) and
reduced
willingness of officers to engage in community partnerships
(Wolfe &
Nix, 2016a). These are important findings because extant
research has
demonstrated that officers with greater self-legitimacy are more
committed to using procedural justice with citizens (Bradford &
Quinton, 2014) and less reliant on physical force to gain
compliance
(Tankebe & Meško, 2015), while community partnerships are an
essen-
tial aspect of community and problem-oriented policing (Braga,

Kennedy, Waring, & Piehl, 2001; Gill, Weisburd, Telep, Vitter,
&
Bennett, 2014). Thus, while systematic crime rate increases do
not
seem to be a direct consequence of the Ferguson Effect, there is
reason
to believe that police officers have been adversely impacted by
the
Ferguson controversy (and related incidents across the US),
which in
turn has implications for crime. In this way, sensitivity to the
Ferguson
Effect can be viewed as a negative work-related outcome for
officers,
their supervisors and agencies, and the communities they serve.
The problem, however, is that we know very little about what is
as-
sociated with officers' sensitivity to such Ferguson Effects. In
other
words, what is it that makes a police officer more or less likely
to feel af-
fected by negative publicity and public discontent stemming
from
Ferguson? This is an important policy question for police
agencies and
command staff. What can supervisors do to help prevent their
officers
from being adversely impacted by negative publicity stemming
from
high-profile incidents like that in Ferguson? Organizational
justice the-
ory offers a sound framework for such an understanding
(Cohen-Charash & Spector, 2001; Sheppard, Lewicki, &
Minton, 1992).
Within the business management literature, studies have shown

that
greater perceived supervisor organizational justice is associated
with
http://crossmark.crossref.org/dialog/?doi=10.1016/j.jcrimjus.20
16.06.002&domain=pdf
mailto:[email protected]
http://www.sciencedirect.com/science/journal/00472352
13J. Nix, S.E. Wolfe / Journal of Criminal Justice 47 (2016) 12–
20
beneficial work-related outcomes such as increased productivity
and
greater organizational commitment among employees (Colquitt,
Conlon, Wesson, Porter, & Ng, 2001). And although relatively
few stud-
ies have applied the organizational justice framework to the
study of
police behavior, the available evidence suggests that officers
who per-
ceive their supervisors as being fair are more likely to identify
with
their organization, comply with procedures, and hold more
favorable
attitudes toward community policing, procedural justice, and the
public
more generally (Bradford, Quinton, Myhill, & Porter, 2014;
Myhill &
Bradford, 2013; Tankebe, 2014). On the other hand, officers
who believe
their supervisors are unfair express less trust in their agency
(Wolfe &
Nix, 2016b) and are more likely to engage in misconduct (Wolfe

&
Piquero, 2011). It is with these results in mind that we argue
organiza-
tional justice may also be associated with less sensitivity to
negative
publicity stemming from Ferguson-related public discontent.
Officers
who feel fairly and respectfully treated by their supervisors may
be par-
tially shielded from the effects of negative press surrounding
their occu-
pation. This is particularly important in agencies across the US
that may
not have experienced a high-profile police shooting but are
neverthe-
less dealing with the fallout of such events in other
jurisdictions. Such
organizational justice likely communicates to officers that they
can
trust their agency and supervisors and that they will be there to
support
them in the face of public scrutiny.
Accordingly, the present study considered whether perceived
orga-
nizational justice was associated with several different
indicators or
manifestations of the Ferguson Effect. We accomplished this
using a sur-
vey of sheriff's deputies (N = 510) employed by an agency in a
south-
eastern US metropolis. Multivariate regression equations were
estimated to determine the extent to which organizational
justice was
associated with sensitivity to the Ferguson Effect and to rule
out the

possible confounding influence of other individual traits (e.g.,
self-legit-
imacy). Our findings provide valuable insight for police
executives who
wish to protect their officers from the public outrage
surrounding their
profession in the post-Ferguson era of policing. In this way we
are not
interested in finding ways for officers and their agencies to skirt
ac-
countability for wrong-doing. Rather, the overarching goal of
this
study was to provide empirical evidence concerning the type of
police
supervisor actions that can help ensure officers do not become
less mo-
tivated, withdraw from their duties, or become less effective
cops be-
cause of the threat of media scrutiny and cell phone video
recording.
The implications of this study are important from a police
policy stand-
point but also because internal fairness within a police agency
may ulti-
mately impact public safety by creating better street cops.
2. The Ferguson Effect
Dating back to the summer of 2014, there have been several
highly
publicized fatal encounters between white police officers and
unarmed
black citizens. The first occurred in Staten Island, NY, when
Eric Garner
died after being placed in a choke hold by NYPD officers. A
bystander

captured the incident on video – which included Garner saying
multiple
times “I can't breathe” – and it ultimately went viral on the
internet.
Shortly thereafter, in Ferguson, MO, unarmed Michael Brown
was shot
and killed by Officer Darren Wilson. This encounter was not
captured
on video, but several witnesses claimed that Brown had his arms
raised
over his head as if to be surrendering when he was shot.
Although the
officer's use of force was later ruled justified by the US
Department of
Justice (i.e., evidence suggested that Brown attempted to grab
the
officer's gun), the incident sparked civil unrest that lasted
several
weeks in Ferguson and captured extraordinary media attention.
Eight months later, in North Charleston, SC, cellphone video
emerged of Walter Scott being shot five times in the back as he
was flee-
ing Officer Michael Slager, who has since been indicted for
murder and
is awaiting trial. Just one week after Scott's death, Freddie Gray
went
into a coma while being transported by a Baltimore Police van
for pos-
session of an illegal switchblade. The media suggested Gray
(who died
from his injuries one week later) had been the victim of a
“rough
ride,” and six officers were ultimately indicted for various
charges in-
cluding false imprisonment (the knife turned out to be a pocket

knife)
and manslaughter.1 Days after Gray's funeral, televised protests
in
downtown Baltimore turned violent: rocks were thrown, fires
were
started, patrol cars were destroyed, and many people (including
police
officers) sustained injuries. The rioting eventually forced the
governor
of Maryland to declare a state of emergency and call in the
National
Guard.
Though allegations of excessive use of force against unarmed
black
citizens are nothing new (e.g., Rodney King in Los Angeles),
these and
related events have resulted in unprecedented levels of police
scrutiny
in recent months (Weitzer, 2015). This is due in large part to
the advent
of social media and the ease with which citizens can record
police be-
havior on cell phones and upload to the Internet for millions to
view.
Such continuous negative publicity surrounding the police at a
national
level has led some to argue that the police are withdrawing from
their
duties in order to avoid being the next viral video on YouTube
(Martinez, 2015; Sutton, 2015) – an argument that has become
known as the “Ferguson Effect.”2 One month after the
Baltimore riots,
the Wall Street Journal published an op-ed by Heather Mac
Donald
(2015), in which she argued that crime increases being

experienced in
several major US cities were precursors to a nationwide crime
wave
that is the direct result of the Ferguson Effect and de-policing.
Top law
enforcement officials such as St. Louis Chief Sam Dotson (who
coined
the term “Ferguson Effect”), FBI Director James Comey and
DEA Chief
Chuck Rosenberg, city mayors such as Rahm Emmanuel, and
others
have all echoed concerns over de-policing stemming from the
Ferguson
Effect.
2.1. The evidence concerning the Ferguson Effect
Until recently, the Ferguson Effect debate has been “long on
anec-
dotes and speculation and short on data” (Pyrooz et al., 2016:3).
For ex-
ample, the FBI Director warned of the Ferguson Effect and
President
Obama argued it may not exist, but both suggested we need data
to an-
swer such questions. To determine whether Ferguson was
associated
with changes in crime rates at the national level, Pyrooz and his
co-au-
thors analyzed monthly UCR Part I offenses in 81 large US
cities
12 months before and 12 months after the death of Michael
Brown in
Ferguson. They found no evidence of a post-Ferguson change in
overall,
violent, or property crime trends – although disaggregated

analyses
suggested that robbery rates were on the rise in the post-
Ferguson
era. Importantly, they did reveal that a handful of cities—those
with
higher than average crime rates, larger African-American
populations,
and greater police per capita—experienced increases in violent
crime
starting at about the same time as the Ferguson incident.
Substantively,
however, the magnitude of such crime rate changes was quite
small. For
example, in the “Ferguson Effect cities” it would take nearly
two years to
witness a one-unit increase in homicides, on average. A
Ferguson Effect?
Probably – but certainly nothing to sound alarm bells over.3
What Pyrooz and colleagues' analyses could not speak to,
however,
was whether Ferguson and related events have resulted in de-
policing.
In a recent report for the 21st Century Cities Initiative at Johns
Hopkins
University, Morgan and Pally (2016) explored this possibility
in Baltimore by examining trends in both crime and arrest data
from
2010 to 2015, which captures the deaths of both Michael Brown
and
Freddie Gray. With respect to crime, the authors found that
shootings,
homicides, robberies, carjackings, and automobile thefts all
increased
in the three months following Gray's death. Yet despite these
crime in-

creases, the arrest count over the same period declined by 30%
(in fact,
arrests had been declining during the 8 months prior to Gray's
arrest,
which is perhaps attributable to the events surrounding Brown's
death in Ferguson). Thus, the authors found that negative
publicity sur-
rounding Gray's death in Baltimore was associated with both
increases
in crime and a slowdown in police activity. Together, these
studies
14 J. Nix, S.E. Wolfe / Journal of Criminal Justice 47 (2016)
12–20
suggest that there is no Ferguson Effect on national crime rates;
howev-
er, negative publicity stemming from events like Ferguson and
Balti-
more do appear to have an effect on police behaviors.
Importantly,
such an effect seems to occur regardless of whether a city has
experi-
enced a high-profile incident of its own (e.g., Baltimore's de-
policing
after Brown's death, but before Gray's death).
Equally important is the possibility that, in response to both
negative
media attention and public discontent, the police have begun to
ques-
tion the confidence they have in their own moral authority, or
self-legit-
imacy (see Bottoms & Tankebe, 2012). Indeed, Nix and Wolfe
(2015)

demonstrated that reduced motivation due to negative publicity
in the
months following Ferguson was associated with lower levels of
self-le-
gitimacy among officers in their sample. This is especially
troubling
given that higher levels of self-legitimacy have been linked to
greater
organizational commitment and less dependence on physical
force to
gain compliance (Tankebe & Meško, 2015), as well as greater
commit-
ment to using procedural fairness (Bradford & Quinton, 2014).
Similarly, Wolfe and Nix (2016a) found that officers who felt
less
motivated as a result of negative publicity surrounding law
enforcement
indicated less willingness to engage in community partnerships
– a key
component of policing in the community-problem solving era.
Impor-
tantly, however, the study also revealed that officers' lack of
willingness
to work with community members was more a result of
perceived su-
pervisor unfairness and lack of self-legitimacy. Finally, some
commenta-
tors and law enforcement officials have proclaimed that
policing has
become more dangerous in the wake of Ferguson due to officers
being
more hesitant to use force when the situation calls for it
(Canterbury,
2016; Reese, 2014; Safir, 2015). Some have even suggested that
the

number of police officers being assaulted and killed in the line
of duty
has increased sharply (Hattem, 2015), though empirical
evidence sug-
gests otherwise (Maguire, Nix, & Campbell, 2016).
Anecdotes and opinions concerning the Ferguson Effect abound
and
many cops argue that it is real. The problem with most media
attention
concerning the Ferguson Effect is that it is treated often as a
singular
phenomenon. The reality is that there may be many Ferguson
Effects.
While research suggests that a Ferguson Effect on crime rates
appears
to be confined to select cities in the US, there are many other
conse-
quences experienced by officers that have resulted from
negative pub-
licity. In this way, empirical evidence confirms much of the
conjecture
and anecdotes. Some cops are less motivated and confident,
view the
job as more dangerous, are arresting fewer people for minor
offenses,
and are more hesitant to engage with community members in the
post-Ferguson era. Again, it is important to emphasize that
social
media contagion has allowed Ferguson-type incidents to be
experi-
enced in agencies that have not experienced their own high-
profile po-
lice shooting (see Pyrooz et al., 2016). Ultimately, social media
has
created a situation where citizens and officers alike can reap the

nega-
tive effects of such incidents regardless of geographical
proximity. Offi-
cers need to be held accountable for wrongdoing but this
evidence
suggests that a sizeable portion of police officers are feeling the
ill effects
of intense public scrutiny. These are important observations not
only for
police agencies but the communities they serve. Ultimately,
officers im-
pacted in this manner are less effective than they should be.
This has di-
rect implications for the safety of citizens and the wellbeing of
communities. Unfortunately, we know very little about what
factors
are associated with officers' sensitivity to Ferguson-related
negative
publicity. Organizational justice theory offers one possibility
for us to
begin to establish an evidence-based understanding of the
phenomenon.
3. Organizational justice
Organizational justice theory has a long history in the business
man-
agement literature (see, e.g., Lind & Tyler, 1988). In fact,
several meta-
analyses have demonstrated strong empirical support for the
conclu-
sion that employees are more likely to engage in a wide-range
of
beneficial work-related behaviors when they perceive their
organiza-
tion as fair (Cohen-Charash & Spector, 2001; Colquitt et al.,

2001).
There are three primary components to organizational justice,
the first
of which is distributive fairness. Employees base their
evaluations of su-
pervisors partially on the extent to which they perceive
organizational
outcomes, such as salary and promotion decisions, as being
distributed
evenhandedly across the organization (i.e., such decisions are
not based
on individual characteristics or “who you know”). The second
compo-
nent, interactional justice, concerns the degree to which
employees
feel they are treated with respect and politeness by supervisors.
The
third, and most important, element of organizational justice is
proce-
dural fairness. Over and above outcome-based equity,
employees look
for supervisory decisions and organizational processes to be
handled
in procedurally just manners—decisions are clearly explained,
unbiased,
and allow for employee input.
Given the overlap between the management of cooperate busi-
nesses and police organizations, a wave of organizational
justice re-
search in policing contexts has occurred in the past few years.
Wolfe
and Piquero (2011), for example, showed that officers were less
likely
to engage in misconduct when they viewed their agency and
supervi-

sors as organizationally fair. Other research has echoed this
finding
and revealed further beneficial outcomes that stem from
organizational
justice. Officers are more likely to identify with their agency
and its
goals, hold more favorable views of community policing (and
the public
more broadly), use procedural justice, and have higher levels of
self-le-
gitimacy when they perceive their supervisors as
organizationally fair
(Bradford & Quinton, 2014; Bradford, Quinton, Myhill, &
Porter, 2014;
Myhill & Bradford, 2013; Tankebe, 2014; Tankebe & Meško,
2015;
Tyler, Callahan, & Frost, 2007). Relatedly, but using slightly
different ter-
minology, recent studies have underscored the importance of
“internal
procedural justice” within police departments (Trinkner, Tyler,
& Goff,
2016; Van Craen, 2016). The President's Task Force on 21st
Century
Policing (2015) even included internal procedural justice as a
corner-
stone of building trust within the community—trust must start
from
the inside before being sustained in communities. Taken
together, the
literature demonstrates that officers who feel their supervisors
are pro-
cedurally fair, distribute outcomes based on objective criteria,
and treat
subordinates with respect, engage in more organizational
citizenship

behaviors and harbor positive attitudes that are beneficial to
both the
agencies they work for and the communities they serve.
With such results in mind, there are several reasons why we
would
expect organizational justice to be associated with less
sensitivity to the
Ferguson Effect. First, it is important to emphasize that we view
sensi-
tivity to the Ferguson Effect as a negative work-related outcome
given
the many potential negative consequences of such an
orientation. If of-
ficers feel less motivated or believe citizens have worse
opinions of the
police in the wake of Ferguson, for example, they may be less
likely to
engage in successful crime reduction strategies such as using
procedural
justice, community-oriented policing, or order-maintenance
policing.
Empirical evidence supports this conclusion (Morgan & Pally,
2016;
Wolfe & Nix, 2016a). On the other hand, officers may be
protected
from such negative outcomes when they are treated in a fair
manner
by their supervisors. Organizational justice communicates to
individual
officers that their supervisors and the broader agency have their
back—they are there to support them.4 Furthermore, being
treated fairly
and respectfully by supervisors lets officers know that they have
a voice
in their agency and they are a part of the department, not simply

a sub-
ordinate employee. Most importantly, supervisors who use
organiza-
tional fairness are indicating to officers that “we are in this
together”
regarding public scrutiny and Ferguson-related negative media
atten-
tion. This sends an important psychological message to officers
that if
something does go wrong it will be dealt with fairly.
It is important to determine whether organizational justice is
related
to officers' sensitivity to the Ferguson Effect because of
relatively easy-
to-implement policy implications that would follow.
Organizational
fairness can be used as a management philosophy by ensuring
that
15J. Nix, S.E. Wolfe / Journal of Criminal Justice 47 (2016) 12–
20
supervisors treat officers in a procedurally fair, unbiased, and
respectful
manner, and by offering them a voice in decisions. In turn, this
strategy
can help stave off any negative psychological effects of media
and public
scrutiny. This is important in itself but using organizationally
fair super-
vision techniques also has a number of other benefits that come
with it
such as creating officers who are more committed to and
trusting of

their agency, more willing to work with the community and use
proce-
dural justice, and less likely to engage in counterproductive
work be-
haviors (e.g., misconduct). Organizational justice is also likely
to help
lead to needed reforms in agencies with strained police-
community re-
lations. In short, the organizational justice return on investment
is great.
4. The current study
Accordingly, the present study explored whether officers'
percep-
tions of organizational fairness within their agency was
associated
with their sensitivity to the Ferguson Effect. We examined this
question
with a survey of sheriff's deputies that was conducted about six
months
after Michael Brown was killed in Ferguson. This was a time
period
when the “Ferguson Effect” was receiving a great deal of
attention on so-
cial and conventional media sites and when high ranking
officials were
warning of the ill-effects of the phenomenon (see, e.g.,
Anderson, 2014;
Frizell, 2014; Matt, 2014; Reese, 2014). We use a variety of
measures to
explore officers' attitudes concerning various possible
manifestations of
the Ferguson Effect. The purpose of the present study was to
provide a
theoretically sophisticated understanding of the correlates of

sensitivity
to the Ferguson Effect in order to provide evidence-based police
policy
recommendations. The overarching goal was to further
demonstrate
the utility of organizational fairness within police agencies.
5. Methods
5.1. Data
Shortly after the beginning of 2015, we surveyed 510 full-time,
sworn sheriff's deputies employed by an agency in a
southeastern US
metropolis (response rate = 85%).5 The survey was
administered online
at a password-protected website and participation was
encouraged by
ensuring anonymity and securing the endorsement of the
agency's
Deputy Advisory Council – a group of deputies who represent
the inter-
est of their colleagues and is very respected throughout the
agency. As is
typical of survey research, some respondents returned
incomplete sur-
veys, which resulted in a small amount of missing data. We
employed
multiple imputation using chained equations (MICE; 10
imputations)
to handle missing data, which is available in Stata 14 (Andridge
&
Little, 2010; Fuller & Kim, 2005).
5.2. Dependent variables

We measured sensitivity to the Ferguson Effect with five
separate
dependent variables meant to capture various consequences
attribut-
able to the Ferguson controversy. Specifically, we considered
whether
the respondent felt s/he has been impacted, his/her colleagues
have
been affected, and the public has been affected by the Ferguson
contro-
versy, respectively, in the wake of Michael Brown's death and
subse-
quent related events in the ensuing months.
5.2.1. Ferguson Effect on self
We presented respondents with eight statements regarding the
ex-
tent to which negative publicity had impacted them in the 6
months
leading up to the survey (the survey was administered
approximately
6 months after Brown's death in Ferguson). For example,
respondents
were asked to indicate their level agreement (1 = strongly
disagree,
2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree) that
over the
past 6 months, negative publicity surrounding law enforcement
had
“made it more dangerous to be a law enforcement officer,”
“made it
less enjoyable to have a career in law enforcement,” and “made
it
more difficult for you to be motivated at work.” A complete list
of the

items used to measure the effect of negative publicity on
respondents
is available in Appendix A. Principal components analysis
(PCA) with
varimax rotation demonstrated that the eight items loaded onto
two
distinct components – one pertaining to less motivation (λ =
4.18, load-
ings N0.66) and the other to increased danger on the job (λ =
1.06, load-
ings N0.60). Each component demonstrated adequate internal
consistency (motivation α = 0.87, danger α = 0.71) and,
therefore,
were combined into separate additive scales. Less motivation
ranges
from 5 to 25, with higher scores indicating the respondent felt
less mo-
tivated to do his/her job as a result of negative publicity over
the prior
6 months. Increased danger ranges from 3 to 15, with higher
scores
reflecting a belief on the part of the respondent that law
enforcement
had become more dangerous as a result of negative publicity
following
Ferguson and related events. Descriptive statistics for all
variables used
in the analyses are presented in Table 1.
5.2.2. Ferguson Effect on colleagues
It is possible that regardless of whether officers believed
negative
publicity stemming from the Ferguson controversy had affected
them,
they might believe that it had influenced other police officers,

including
their colleagues. This is an important consideration given that
police of-
ficers routinely rely on their colleagues for backup. For
example, officers
may hesitate to stop suspicious persons if they feel their
colleagues are
reluctant to use force when it may be necessary. To capture this
senti-
ment, we asked respondents to indicate their agreement (1 =
strongly
disagree to 5 = strongly agree) with statements regarding
whether neg-
ative publicity surrounding law enforcement in the previous 6
months
had: (1) made it more difficult for coworkers to do their job, (2)
made
it more difficult for coworkers to be motivated at work, (3)
caused co-
workers to be less proactive on the job than they were in the
past, and
(4) caused coworkers to be more apprehensive about using force
even
though it may be necessary. PCA suggested the four items
loaded onto
a single component (λ = 2.67, loadings N0.76) and Cronbach's
alpha in-
dicated strong internal consistency (α = 0.83). Accordingly, we
com-
bined the items into an additive scale ranging from 4 to 20 with
higher scores reflecting a belief that negative publicity
surrounding
law enforcement had negatively affected colleagues.
5.2.3. Ferguson Effect on citizens' views
It is also possible that, in response to the Ferguson-related

contro-
versy, officers have come to believe that citizens' attitudes
toward the
police have worsened (see Culhane, Boman, & Schweitzer,
2016). If so,
this could have important ramifications for the police. For
example, it
may lead to further immersion into the “us versus them” nature
of the
police subculture (Chan, 1996; Neiderhoffer, 1967;
Waddington,
1999), which could result in less willingness to work with the
commu-
nity to solve problems (Braga et al., 2001). To measure the
extent to
which our sample felt this way about US citizens, respondents
were
asked to indicate their level of agreement (1 = strongly disagree
to
5 = strongly agree) with the following statement: “In general,
US citi-
zens' views of the police have gotten worse in the last 6
months.” Sim-
ilarly, we asked respondents how much they agreed that “Over
the past
6 months, Marie County (pseudonym) residents' perceptions of
law en-
forcement have gotten worse.” This item was used as a fifth
dependent
variable, Local citizens, in order to consider the possibility that
respon-
dents felt local citizens' views differed from those of US
citizens more
broadly.

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