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The effect of trust in government on
rallies ’round the flag
E S E A R C H
Journal of Peace Research
49(5) 631–645
ª The Author(s) 2012
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DOI: 10.1177/0022343312440808
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J Tyson Chatagnier
Department of Political Science, University of Rochester
Abstract
Previous research has shown that foreign policy crises can cause a ‘rally ’round the flag’ effect, boosting citizens’
approval of their leaders. While scholars agree on the effect’s existence, its magnitude and nature are less readily
apparent. This article considers two factors that have been neglected in previous studies: the context in which a conflict occurs and the public’s level of trust in government. The theory presented here suggests that trust is not only an
effect of a rally, but mediates the magnitude of the rally. It also proposes that the nature of the rally will be unaffected
by whether the state is provoked by its opponent prior to crisis initiation. The resulting hypotheses are tested using
aggregate US public opinion data around international crises, as well as individual-level data from the 1990–92
ANES panel regarding the Persian Gulf War. The analysis indicates that trust in government has a major influence
on the size of a rally effect, especially at the individual level. However, trust matters more for those in the opposition
than for those who have supported the government in the past. These results suggest implications for understanding
public attitudes toward foreign policy and for the diversionary theory of war.
Keywords
divisionary war, public opinion, rally, trust
Introduction
‘Do you approve or disapprove of the way George W.
Bush is handling his job as president?’ When asked this
question by Gallup pollsters in mid-August of 2001,
57% of Americans responded that they approved of the
job that President Bush was doing. A month later, 90%
of those polled responded favorably to the same question. What caused such a major shift in the way that
Americans saw President Bush? In the time between the
two surveys, the United States suffered the most devastating terrorist attack in its history, causing billions of
dollars of property damage and leaving thousands dead.
In response, Americans rallied around their leaders,
offering support where before there had been opposition,
and calling for unity where there had been division.
Though extreme, the shifts in opinion following the
11 September attacks were unique only in magnitude
and not in type. Political scientists have long been aware
of the existence of a ‘rally ’round the flag’ effect that
boosts leaders’ approval when crises loom (e.g. Waltz,
1967; Mueller, 1970; Lee, 1977). When confronted
by a common enemy, citizens will circle the wagons, providing additional support to the government, in order to
fend off the threat.
If politicians recognize the rally effect, then under
adverse domestic conditions it might be exploited for
short-term gain. This proposition – that leaders can use
wars to distract the public from unfavorable domestic
situations – underlies the diversionary war hypothesis,
proposed by numerous international relations theorists
(e.g. Richards et al., 1993; Downs & Rocke, 1994; Hess
& Orphanides, 2001). If leaders are willing and able to
invoke the rally effect, they can generate approval gains
for themselves, which they may be able to turn into policy gains.
Corresponding author:
[email protected]
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This article puts aside leaders’ motivations and deals
specifically with their ability to make use of this effect.
In particular, I look at the relationship between rallies
and political trust, positing that citizens’ trust in elected
officials affects leaders’ responses to crises. In order for
leaders to manipulate public opinion for their own benefit, the public must be manipulable. This evokes an
interesting possibility: if trustworthy leaders are more
likely to enjoy high public approval ratings (which is
plausible), then the leaders who are most able to manipulate the public in this manner are those who are least in
need.
To analyze the nature of the rally effect and its relationship to political trust, I first examine a series of militarized interstate disputes (MIDs) involving the USA
and the changes in presidential approval surrounding
these events. Next, I assess the phenomenon using
individual-level survey data collected by the American
National Election Study (ANES; Miller et al., 1999) that
are meant to gauge public opinion with respect to the
first Gulf War. The analysis shows that changes in presidential approval following a crisis are dependent upon
pre-crisis political trust. These findings suggest an explanation for the disconnect between the intuitive appeal of
diversionary war theory and political scientists’ inability
to find empirical support.
The rally effect
The rally ’round the flag hypothesis states that in times of
international crisis, citizens rally to their leaders, offering
greater levels of support and approval. Only dramatic
international crises can produce the significant increases
in national cohesion and public support for the president
because only events that confront the nation as a whole
meet the necessary conditions to strengthen in-group
identity and bring together disparate sectors of the public
(Mueller, 1970). Initially identified in international relations by Waltz (1967) and formally incorporated into
models of presidential approval by Mueller, this phenomenon is now a well-known empirical regularity.
Research from the period immediately following the
formal statement of the rally effect supported this hypothesis, finding that crises meeting Mueller’s requirements
tend to produce significant increases in presidential popularity (Lee, 1977; MacKuen, 1983), but also that the benefits accruing to leaders in times of crisis are fleeting
(Cotton, 1986; Ostrom & Job, 1986). More recent
research, however, has been less supportive of the existence of a meaningful rally effect. While several studies
reaffirm the earlier findings (e.g. Brody, 1992; Lai &
Reiter, 2005), others dispute the potency of the rally,
arguing that the magnitude of the change is insignificant
(DeRouen, 2000; Baker & Oneal, 2001). This calls into
question not only the nature but the very existence of the
rally.
A possible explanation for these divergent findings is
that there exists an additional set of factors driving the
likelihood or size of the rally. Uncovering these conditions
can explain both the expected magnitude of a rally following a crisis and the inconsistent findings across studies. To
this end, researchers have sought to determine the factors
underlying the rally effect. James & Rioux (1998) find
that, in the Cold War context, the rally effect generally
occurs when a crisis involves the Soviet Union and disappears for conflicts short of war when the USSR is not
involved. Baker & Oneal (2001) report that the use of
force has an insignificant effect on the size of a rally, while
the factors that most affect public response are mediarelated. Chapman & Reiter (2004) find that UN Security
Council approval significantly increases the size of a rally,
but approval from other bodies has no effect. Finally,
some studies suggest that rallies occur only among certain
groups, such as those already predisposed to support the
president (Edwards & Swenson, 1997), or those who are
most ambivalent and susceptible to new information
(Baum, 2002).
None of these studies has considered the role of trust
in government as a determinant of rallies. When levels of
political trust rise or fall, the expected size of the rally
may also change. Publics that are more suspicious of government might be less willing to rally to their leaders in
times of crisis. The rationale behind this proposal can be
found in diversionary war theory, a companion literature
to the rally effect and the logical next step.
The existence of a rally effect potentially creates
perverse incentives for leaders. If the rally phenomenon holds, a president in need of a short-term
approval boost could solve the problem by initiating
or encouraging the onset of an international crisis.
This is the essence of the diversionary theory of war:
foreign conflict allows a leader to expand or retain his
or her power when threatened domestically (Richards
et al., 1993; Downs & Rocke, 1994; Hess & Orphanides, 2001).
Diversionary theory holds that, in the face of an external threat, group members will respond with increased
cohesion and concordance (Simmel, 1898). Given some
minimal existing threshold of internal cohesion and
group identity, an external conflict can pull a group back
from the brink of fragmentation or dissolution (Coser,
1956; Simmel, 1956). In the realm of international
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633
politics, external threat is represented by interstate war,
allowing ‘a state ridden with inner antagonisms to overcome these antagonisms’ (Simmel, 1956: 93). By
choosing to go to war when faced with domestic opposition, leaders shift the focus to a new enemy, giving
them the ability to hold on to or expand their power
(Haas & Whiting, 1956; Wright, 1942). The rally
effect works in precisely this manner, stirring individuals who were previously in opposition to draw together
in support of their leaders against the external threat.
In addition to the literature that provides a theoretical
basis for diversionary incentives in international politics
(e.g. Richards et al., 1993; Downs & Rocke, 1994;
Tarar, 2006), recent studies also claim empirical support.
US presidents have fallen under particular empirical
scrutiny, due to the disproportionate amount of data
on US politics. Recent work suggests that presidents
tend to have a greater proclivity to use force when facing difficult economic situations (Ostrom & Job,
1986; James & Oneal, 1991), in times of domestic
unrest and falling popularity (DeRouen, 1995; Sobek,
2007), or when elections draw near (Stoll, 1984). Others, however, argue that the empirical case is weak, citing flaws even in contemporary research on
diversionary war (Levy, 1989; Meernik & Waterman,
1996; Meernik, 2000).
These findings suggest that the rally effect may be a
useful tool for leaders. The specter of an external enemy
provides the public with a target against whom to direct
anger that might otherwise be reserved for the government. However, if the public realizes the leader’s goals
and acts strategically, the incentive to divert disappears.
While there is evidence that the public generally looks unfavorably upon crisis initiation by leaders (Benson, 1982), it
is less clear that Americans have the necessary awareness to
counter leaders’ diversionary incentives (Converse, 1975;
Neuman, 1986; Delli Carpini & Keeter, 1996).
Mueller (1970) argues that because international
crises are such poignant and potentially deadly events,
they are likely to attract the attention of even the least
engaged Americans. This article builds upon that thesis,
arguing that as cynicism increases, the public will pay
significantly more attention to the actions taken by government. Concerns about possible governmental exploitation
should make citizens more diligent, observing the actions
of potentially predatory leadership, in order to punish or
deter offenders. The additional scrutiny leads to less willingness on the part of the citizenry to bear unnecessary
costs. Thus, higher levels of cynicism should translate into
smaller rallies. The public’s faith in government can be captured directly by measures of political trust.
The role of trust in government
Americans possess a variety of individual beliefs about
what it means for a government to ‘do the right thing’.
The degree of congruence between these expectations
and what citizens believe that the government is actually
doing can be conceptualized as political trust (Hetherington, 1998, 2005). As Uslaner (2002: 44–47) points
out, trust in government is a type of ‘strategic trust’,
which is particularistic and based upon observed demonstrations of trustworthiness. Unlike moral trust, strategic
trust depends not upon a general trust in people, but
rather upon beliefs about whether an individual (or institution) can be trusted to do a particular thing. Strategic
trust is mutable and contingent (Dasgupta, 1988; Uslaner, 2008). Whereas moral trust is generational, strategic
trust changes as relevant institutions demonstrate
(un)trustworthiness. This definition of trust is particularly useful for this analysis as it taps underlying affect
toward government and public cynicism (Miller, 1974).
Political trust has been viewed by scholars as important and desirable in its own right. As such, it has generally been treated as a dependent variable (e.g. Miller,
1974; Citrin, 1974; Keele, 2007). Recent studies, however, have examined how trust affects policy and the
effectiveness of policymakers. Hetherington (1998:
803) finds that political trust leads to ‘warmer feelings’
toward government and ‘provides leaders more leeway
to govern effectively’ (see also Hetherington, 2005).
Rudolph & Evans (2005) concur, reporting that trust
affects policy latitude on a wider variety of issues than
initially believed. As political trust increases, the leader
can advance an agenda with less resistance. If leaders’
domestic goals can be frustrated by low levels of political
trust, their foreign policy agenda may suffer as well.
The literature traditionally distinguishes between
trust and approval. Political trust measures the degree
to which citizens believe that government actions will
lead to good outcomes. Individuals with less trust in government expect less successful public policy, making
them less likely to support it. Although these individuals
may support certain ‘policy goals, they do not support
the policies themselves because they do not believe that
the government is capable of bringing about desired outcomes’ (Hetherington, 2005). Thus, low levels of trust
in government can paralyze the policy process, as politicians will be unable to obtain the support and resources
necessary without resorting to coercion (Chanley,
Rudolph & Rahn, 2000; Keele, 2007). To the extent
that trust is a prospective evaluation of the government,
approval can be thought of as its retrospective
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634
counterpart. Some scholars have noted a relationship
between the two concepts, and that during periods of
low public trust, approval ratings are, on average, significantly lower (Brody, 1992; Hetherington, 1998). This
may arise because the lack of trust prevents leaders from
acting, leading the public to judge them harshly for a lack
of policy success. Although this relationship between
trust and approval is conceivable, the two remain conceptually distinct, and it is not impossible for a leader
to enjoy high approval ratings during a period of low
trust. Indeed, Hetherington (2005) notes that President
Clinton – who maintained relatively high levels of
approval, especially toward the end of his presidency –
held office during a period in which trust in government
was especially low within the USA.
The lack of interest in the effects of political trust on
foreign policy is puzzling given the importance of even
routine decisions concerning interactions with other
countries. If trust affects foreign policy in the same way
that it affects domestic policy, then when political trust is
low, foreign policy decisions should simultaneously face
greater scrutiny and less support. Hence, it is easy to connect political trust to the rally effect and diversionary war
more generally. Coser (1956) claims that some minimal
threshold of internal cohesion is necessary for a diversion
to be effective: if a group is too fragmented, an external
enemy can cause it to shatter beyond repair. As Uslaner
(2002) points out, (democratic) governments cannot
function well without sufficient trust. Thus, political
trust taps cynicism and affects leaders’ abilities to implement policy. This renders it an excellent proxy for cohesion. Diversionary tactics under conditions of low trust
may lead to more intense focus upon domestic problems
and governmental flaws.
This argument spawns two major hypotheses about
the effects of trust on foreign policy. Across multiple
events, low levels of trust should decrease the size and
magnitude of a rally. When trust is low, citizens are more
likely to detect diversionary foreign policy, or to see the
specter of diversion where none exists.
Hypothesis 1: The aggregate level of pre-crisis trust in
government will be positively related to the size of the
change in aggregate presidential approval following a
crisis.
Across individual opinions for a single event, individuals whose approval levels change the most should be
those with the most extreme levels of trust. Thus, individuals whose trust is high should participate in the rally,
while those whose trust is low should see diversionary
motives even when crisis decisions are driven purely by
national security. This means that, regardless of the circumstances, individuals with relatively low levels of trust
in government should be particularly unlikely to rally.
Hypothesis 2: An individual’s level of trust before a crisis
will be positively related to the size of the post-crisis
change in presidential approval for that individual.
A potential counter-argument is that the effect of trust
in government may be moderated by provocation.
Although citizens may be more likely to see policy as
diversionary when trust is low, if there is clear provocation, even skeptical individuals may rally behind the
leader. To assess the robustness of the trust effect, I test
a third hypothesis, related to provocation.
Hypothesis 3: Pre-crisis trust will not affect the size of the
change in presidential approval following a crisis that
results from provocation.
While the theory predicts that Hypotheses 1 and 2
will hold, Hypothesis 3 is primarily a robustness check.
Theoretically, trust should matter even under provocation. An interaction effect significantly different from
zero would limit the scope of the theory. Unfortunately,
Hypothesis 3 can only be tested across events (i.e. with
macro-level data). As such, while Hypotheses 1 and 3 are
both tested in the first analysis, only Hypothesis 2 is
tested in the second. Notably, the crisis in the microlevel section is one in which the USA was provoked.
Because Iraq attacked a US ally, even Americans who
mistrusted President Bush might have viewed the war
as justified, causing them to rally despite their lack of
trust. Therefore, even if Hypothesis 3 is correct, the
micro-level analysis will be biased against Hypothesis 2.
Data and methods: Aggregate level
In order to test both sets of hypotheses, I conduct the
analysis in two parts. The first examines the two
macro-level hypotheses, following the examples of Oneal
& Bryan (1995) and Chapman & Reiter (2004) in its
implementation. Most data for this portion come from
the replication data provided by Chapman & Reiter.
Their data cover 229 crises involving the USA between
1933 and 2001.1
1
The crises are drawn from the MID dataset (Ghosn, Palmer &
Bremer, 2004), which comes from the Correlates of War project.
They cover all instances in this time period during which a threat,
display, or use of force occurred involving the USA.
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635
The dependent variable is the change in aggregate
presidential approval from the most recent Gallup poll
taken prior to the crisis to the earliest Gallup poll conducted afterward. The mean rally for the entire set is
approximately 0.4 percentage points. Because the trust
question was not frequently asked by pollsters, many
of the observations in the Chapman & Reiter dataset
cannot be included here. Of those that are, the mean
rally is a substantially higher 1.6. The largest rally is 33
points, following the 11 September attacks and subsequent invasion of Afghanistan. This summary statistic
suggests that a rally effect does exist, and that leaders
receive some (relatively minor) political benefit from
crises.
The key independent variable is political trust prior to
the crisis event.2 This is taken from various opinion polls
measuring political trust.3 Where possible, the polls used
are nationally representative samples published by CBS/
New York Times or ABC/Washington Post. In the few
cases where such polls are unavailable, other sources are
used.4 Polls are only included when the wording and
choices are directly comparable. All polls included in the
data offer those interviewed the exact same responses to
the question about political trust. Aggregate trust is calculated by summing the percentages of those surveyed
who said that they trusted government to do what was
right ‘all of the time’ or ‘most of the time’. On average,
this is fairly low, with a mean of 33.1%. No more than
half of those surveyed ever expressed a willingness to
trust government most or all of the time.
Because trust questions appear on surveys less frequently than do questions about approval, these data are
less complete than the approval data. Trust questions
generally were not asked within weeks of a crisis event.
A poll is included in the dataset only if the question was
asked within a reasonable amount of time prior to the
crisis. Generally this is one to three months, though it
2
One potential concern is that trust and approval are endogenous.
While this may be true, it does not present a problem for this
analysis, which considers the effect of trust at time t on the change
in approval between times t and t þ 1. Endogeneity would only be
a concern if current trust was a function of future approval. Such a
relationship is all but impossible, suggesting the potential problem
of contemporaneous endogeneity should not be a factor in this
analysis.
3
Data for all polls come from the Roper Center’s iPoll Databank,
available at: http://www.ropercenter.uconn.edu/data_access/ipoll/
ipoll.html.
4
Remaining polls were published primarily by CNN, Los Angeles
Times or Gallup. Others came from Market Strategies, Americans
Discuss Social Security, and Pew.
may be as high as six. Furthermore, the question was not
asked consistently until 1977. Thus, observations prior
to this year are not included in the analysis. After removing the observations for which trust data are missing,
there are 78 events occurring between 1977 and 2001.
Given the potentially long periods between conflicts and
measures of trust in these data, there may be suspicions
about how accurately the trust variable actually captures
pre-crisis trust. The optimal solution would be to find
reliable measures of trust that were measured shortly
before the crisis occurred. However, because such data
are not available, I have verified robustness using Keele’s
(2007) quarterly trust data as an alternative specification.5 The results were substantively unchanged.
Provocation is a dummy variable indicating whether
the USA, an ally, or a friendly state was attacked or
threatened. In either instance, the president has a clear
case for war that can be presented to the American people. Crises in which the USA was the clear initiator or
there was no clear threat are cases in which the motivation for war is less obvious. Under these circumstances,
diversionary motives can be inferred more easily. Of the
78 cases analyzed here, the USA was provoked in 47 of
them. These include incidents in which there was an
attack against the USA or a friendly state, as well as those
in which another state made a direct threat against the
USA or an ally. The MID data include categories that
code specifically for these types of incidents, and I
employ their coding here.
The remaining variables come from the research conducted by Baker & Oneal (2001) and Chapman &
Reiter (2004). Baker & Oneal argue that the size of a
rally is largely driven by spin. They find that media coverage, bipartisan support, and White House statements
are all related to the appearance of a post-crisis rally.6
Chapman & Reiter, meanwhile, find that Security
Council authorization has a significant impact on the
size of a rally, but that there is no effect from other organizations, including the General Assembly. All of these
variables are included here. Both works also employ several controls. Factors that might drive presidential
approval independent of crisis onset include economic
conditions, months until the next election, pre-crisis
presidential approval, whether the USA had revisionist
goals (i.e. whether it hoped to gain from the conflict), the
5
I thank Luke Keele for kindly making his data available to me.
Given the importance of bipartisan support, it may be that divided
government would be a relevant explanatory variable. I thank an
anonymous reviewer for suggesting this. Subsequent analyses
indicate, however, that divided government does not affect the rally.
6
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journal of PEACE RESEARCH 49(5)
636
severity of the crisis (the number of actors and great powers involved and salience of the issue), whether the opponent was a major power, the number of US allies in the
conflict, and whether the conflict is classified as a war
(requiring at least 1,000 battle deaths).7
Analysis
In keeping with the methodology employed by previous
researchers, the analysis uses ordinary least squares (OLS)
regression with bootstrap standard errors. The variables
of interest are trust and the interaction between trust and
provocation. Notably, provocation is highly correlated
with the interaction term (r ¼ 0:92), raising severe
multicollinearity issues. However, as it is generally necessary to include all constituent terms when modeling
interaction effects (Brambor, Clark & Golder, 2006), I
estimate two separate ‘full’ models. The first includes
only provocation, while the second also contains the
interaction between trust and provocation.
Table I displays the results from several models of
determinants of rally size. To show the substantial implications of data loss, I replicate Chapman & Reiter’s
model in columns 1 and 2. The first model exactly replicates their primary model with war as a dummy variable.
This includes all observations in the original dataset. The
second column presents the same model using the data
employed throughout the rest of the analysis. The differences between the two models are quite stark. Though
no major variables change direction, the magnitudes of
many coefficients change significantly. Additionally, the
standard errors increase substantially in most cases. As a
result, several variables that show significant explanatory
power in Model 1 become insignificant in Model 2.
There are two possible reasons for the drastic changes
between the two models. The most likely explanation is
simply that while both models estimate 15 parameters,
Model 2 has fewer than half the observations of Model
1. With fewer data points, the estimates will be less precise. Alternatively, there might have been a significant
change in the way the public views war since the inauguration of the Carter administration. It is possible that US
experiences with events like Vietnam and Watergate
have fundamentally altered the way that Americans
respond to international crises and presidential uses of
force. Unfortunately, it is not presently possible to
7
Although the MID data do not classify Kosovo as a war, Chapman
& Reiter (2004) argue that there were likely more than 1,000 battle
deaths and code it as a war in their analysis. The war dummy that
includes Kosovo is used here.
determine with certainty which explanation accounts for
the change. Thus, neither possibility can be discounted.
Column 3 presents the results from the regression of
rally size on the general presidential popularity controls,
theoretically important independent variables, and trust
in government. The analysis lends some initial support
to Hypothesis 1. The coefficient on trust is positive and
significant at the p < :10 level. This indicates that, holding all else constant, an increase in aggregate political
trust should cause presidential approval following a crisis
to grow at least marginally. A J test for non-nested model
comparison (Davidson & MacKinnon, 1981) indicates
that explanatory power is coming from both Models 2
and 3. That is, the control variables that Chapman &
Reiter include explain something not present in Model
3, while the trust and provocation variables explain
something not found in Model 2. Thus, I include all
variables in the final two models.
Columns 4 and 5 include the relevant crisis-level control variables from the Chapman & Reiter analysis, as
well as trust and provocation.8 Interestingly, there are
few changes when these factors are included. Only one
variable, prior popularity, gains or loses statistical significance consistently in the new models; however, the
magnitude of the coefficient increases only slightly, indicating little substantive change even here. Trust in government tells the same story in Model 4 that it tells in
Model 3 – additional trust increases the size of the rally
effect – though its effect is reduced slightly.
Model 5, which includes the interaction between trust
and provocation, reveals a larger coefficient, but a lack of
significance for the trust variable. As expected, the interaction effect is also negative, but non-significant. By
themselves, the estimates in the model indicate a larger
expected rally when there is no provocation, but a
slightly smaller one when the USA is provoked. However, owing to the relatively small number of observations and the multicollinearity problem, there is not
sufficient precision to ensure that any of these estimates –
including the marginal effect under provocation
(s:e: ¼ 4:02) – is different from zero. Model comparison
suggests that including the interaction term does not
improve the model and that the slightly more parsimonious Model 4 is superior (F ¼ 0:15). This indicates
that there is some evidence that pre-crisis trust affects
rally size (per Hypothesis 1), independent of provocation
8
Ongoing war is omitted because it was invariant following the
Vietnam War.
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637
Table I. Aggregate-level determinants of rally size
Model 1
Model 2
Model 3
Model 4
Model 5
(Chapman & Reiter, 2004) (Reduced obs.) (Major variables) (No interaction) (Full model)
Prior popularity
Business confidence
Months before election
Bipartisan support
Administration statement
New York Times coverage
Security Council authorization
US revisionist
Major power opponent
Number of allies
Non-Security Council action
Regional organization action
Crisis severity
War
0.1111***
(0.0471)
0.0279*
(0.0166)
0.0126
(0.0266)
1.619*
(0.858)
1.688***
(0.6008)
0.4243
(0.4443)
4.809
(4.287)
1.440**
(0.6655)
1.085*
(0.6033)
0.1347
(0.2191)
0.7074
(1.085)
0.7540
(2.984)
0.7402
(0.5694)
11.63
(8.484)
0.0980
(0.0704)
0.0063
(0.0229)
0.0158
(0.0383)
2.959*
(1.568)
0.6846
(0.8703)
0.3071
(0.6609)
4.416
(5.528)
1.036
(1.057)
1.802*
(1.054)
0.1528
(0.3924)
2.599
(2.835)
0.3146
(11.444)
0.1119
(1.072)
17.05
(10.873)
Trust
Provoked
0.0961
(0.0956)
0.0091
(0.0236)
0.0126
(0.0462)
4.808***
(1.87)
0.5311
(1.137)
0.2156
(0.6836)
11.58*
(5.932)
0.1326*
(0.0820)
1.296
(1.044)
0.1356*
(0.0796)
0.0046
(0.0231)
0.0027
(0.0416)
3.420**
(1.690)
0.3430
(1.100)
0.1279
(0.7322)
6.071
(5.288)
0.6128
(1.107)
2.022*
(1.140)
0.1665
(0.3765)
2.287
(2.711)
1.009
(10.534)
0.6209
(1.111)
16.35
(10.111)
0.1181*
(0.0701)
1.335
(1.163)
2.632
(2.741)
0.32
78
4.909*
(2.975)
0.46
78
Trust Provoked
Constant
Adjusted R 2
N
2.126
(1.526)
0.29
198
6.152*
(3.139)
0.44
78
0.1383*
(0.0804)
0.0042
(0.0232)
0.0015
(0.0426)
3.370**
(1.656)
0.3532
(1.124)
0.0679
(0.7506)
5.706
(5.499)
0.5822
(1.129)
2.051*
(1.159)
0.1487
(0.3931)
2.336
(2.758)
1.460
(10.894)
0.5679
(1.146)
16.39
(10.314)
0.1463
(0.1034)
0.1995
(4.135)
0.0468
(0.1199)
4.037
(3.395)
0.45
78
Bootstrap standard errors in parentheses. Two-tailed tests: *p < :10; **p < :05; ***p < :01.
(contra Hypothesis 3). Based on the results in Model 4,
trust appears to mediate the size of a rally.
Though the effect is somewhat anemic, trust in government maintains its level of significance across multiple model specifications. Given the major swings in
coefficient sizes for some of the variables when moving
from Model 1 to Model 2, it is possible that the findings
might be strengthened with more data. The estimates
here provide tepid support for the hypothesis that trust
affects rally size, though the extent appears to be quite
minor. In particular, from the results in Model 4, an
increase in trust of one standard deviation (slightly under
10 points) leads to a rally approximately 1 percentage
point larger. Initially, this appears so small as to be irrelevant. However, the mean rally size in these data is
slightly over 1.5 points, meaning that a standard deviation shift in trust increases the rally size by 67%, from
the mean. From this perspective, trust has a major
impact on the extent to which Americans rally in the
event of a crisis.
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journal of PEACE RESEARCH 49(5)
638
This analysis indicates that trust has some effect on
presidential approval in the wake of a crisis, though the
extent of its impact remains somewhat uncertain. To
gain a clearer understanding of the mechanisms that may
link trust to presidential approval, it is necessary to move
away from aggregate-level data and to examine individual
responses. This provides a more nuanced view of the role
of trust in rallies ’round the flag.
Data and methods: Individual level
The micro-level analysis consists of individual-level survey data from the 1990–92 ANES panel (Miller et al.,
1999). This particular analysis uses only the 1990 and
1991 waves, which were intended to measure support for
President Bush vis-á-vis the Persian Gulf War. The first
wave was initiated at the end of 1990, after the initial
commitment of troops to the Gulf, but before the beginning of actual hostilities. The second wave took place in
the summer of 1991, following the conclusion of fighting and the withdrawal of Iraqi troops from Kuwait.
Given that the 1990 wave includes questions on trust
in government, the survey fits the purpose of this study
perfectly.9
The dependent variable is again rally size, but this
time at the individual level. This is a measure of the difference in an individual’s evaluation of President Bush in
the 1991 wave and his or her evaluation in the 1990
wave. While operationalization of approval is simple in
the aggregate case, it is trickier at the individual level.
Therefore, I employ two different measures of a respondent’s approval of President Bush. One is a four-point
ordinal scale, ranging from ‘strongly approve’ to ‘strongly
disapprove’. The size of the rally for an individual here
can range from 3 to þ3. The other measure uses a feeling thermometer, in which individuals rate their feelings
of ‘warmth’ toward the president on a scale of 0 to 100.
The size of the rally on the feeling thermometer theoretically ranges from 100 to þ100. This operationalization more closely resembles the dependent variable in the
aggregate analysis.
The independent variable of interest is trust in 1990.
As with approval, this is ordinal. To respond to the question of how often they can trust the government,
9
Unfortunately, this is the only such study. While the ANES has
released a three-wave panel that covers the time period during which
the 2003 Iraq War took place, the timing of the waves renders it significantly less useful: the 2004 interviews were administered more
than a year and a half after the invasion. Any rally effect would likely
have dissipated by this time.
individuals are given three options (all, most, or some
of the time). A significant number of respondents
(around 2%) eschewed the given alternatives and opted
instead to volunteer that the government could never
be trusted. These individuals are kept in the sample and
coded 0, as their voluntary responses convey useful information. Overall trust was relatively low, with most individuals responding that the government could only be
trusted some of the time.
Summary statistics for the ANES data are comparable to the aggregate-level data, though individuals surveyed were slightly more trusting, and the average
change in approval was smaller. The survey also indicates that the average level of trust in government
increased following the Gulf War. This is unsurprising
and is consistent with previous literature on the subject
(e.g. Parker, 1995). However, the degree to which trust
increases is minor, relative to the change in approval.
While the mean level of approval increases by 0.43, the
increase in mean level of trust is just over one-third
that. Although a ‘trust rally’ may have occurred, it was
relatively small. More importantly, the presence of a
post-conflict increase in trust should not negate the
importance of prewar trust on the size of the change
in approval. If conflict increases trust in government,
it may affect the expected rally size for a subsequent
conflict; however, there is no reason to believe it will
be relevant to the expected rally for the current conflict.
Nonetheless, to ensure that rally size is not driven by
changes in trust, rather than pre-crisis trust alone, I
control for the difference in an individual’s level of trust
across the two waves.
Since the analysis looks only at data for a single crisis
event, it is not possible to examine the effects of the USA
being provoked. However, this was a conflict in which a
friendly state was invaded, leading the USA to experience
some degree of provocation.10 Hypothesis 3 (which was
unsupported above) suggests that trust may have a
smaller effect upon a rally in this case than it would elsewhere. Therefore, this is not a ‘most-likely-case’ scenario;
if anything, the deck is stacked against finding any effects
for trust.
In addition to the trust variable, I include controls
drawn from the ANES survey. Voting for Bush and
approval in 1990 are peculiar to this analysis. The former
is included because high levels of approval leave little
room for a rally, while the latter is included because supporters may be more likely than opponents to rally to the
10
The earlier provocation variable was coded 1 for this conflict.
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Chatagnier
639
president (Edwards & Swenson, 1997). Given that some
time passed between the end of hostilities and the second
wave of the survey, factors other than the war – economic performance, in particular – may also have been
relevant to respondents. The summer of 1991 brought
the recession that would contribute to Bush’s defeat the
following year. To account for economic effects, I
include a measure of the respondent’s assessment of his
or her family’s financial situation in 1991 relative to
1990. The remaining control variables are primarily
demographic in nature. These variables include age, race,
gender, education level, household income, church
attendance, ideological self-placement, and partisanship.
Finally, I create an interaction between trust and voting
for Bush, hypothesizing that trust may affect supporters
and non-supporters differently.
Analysis
In conducting the analysis for the feeling thermometer
variable, I again use OLS with bootstrap standard errors.
In the case of the ordinal rally variable, the appropriateness of OLS is less clear. As approval is measured on a
three-point scale, the difference takes seven possible values. Because it is unclear whether the number of categories renders the variable sufficiently continuous, I
present results from both OLS and ordered probit specifications. Finally, although these are panel data, they can
appropriately be treated as cross-sectional, as the unit of
analysis is the individual, rather than the individualwave. The panel aspect is used only to obtain information
about opinion change following the war, and observations
are not pooled across time.
The models in Table II strongly support Hypothesis
2. Individuals who express greater trust in government
are more likely to rally following a crisis. The effect of
trust is much more robust at the individual level than
in the aggregate. In each case, trust positively and significantly affects the expected size of the rally. Other variables also generally behave as expected, and Bush
voters appear to be the most likely to adjust their opinion
of the president upward after the war. Although financial
status affects approval, the estimated effect is fairly small,
and trust remains significant. Thus, it seems unlikely
that the economy was driving the change in respondents’
opinions of Bush.
Column 1 presents the results from the regression of
feeling thermometer ratings upon the explanatory variables. Changes in trust in government and approval do
appear to be related, as those individuals who became
more trusting following the war also had higher
opinions of Bush. However, this does not undercut the
impact of initial trust. Indeed, trust is both statistically
and substantively significant. The coefficient indicates
that an increase from one trust category to the next
increases an individual’s post-crisis feelings for Bush
by nearly five points. Incidentally, a five-point shift was
the median rally (as measured by the feelings thermometer) in these data. Moreover, the effect of a onecategory difference in trust is almost as large as a fivecategory difference in partisanship. Ceteris paribus, an
individual who moved from trusting the government
‘some of the time’ to ‘most of the time’ would be
expected, following the war, to increase his or her
approval of President Bush by almost the same amount
as an individual who moved from being a strong Democrat to a moderate Republican.
The results in Column 1 strongly support the hypothesis that trust mediates rally effects. However, feeling
thermometer ratings are not the same as approval ratings.
Columns 2 and 3 present the results from using the
ordinal-valued approval measure to tap into the rally
effect more directly. The results are virtually indistinguishable from the first model. With respect to trust,
they are largely the same as those in Model 1, indicating
that the effect of trust is not sensitive to specification of
the rally. Initially, the relatively small coefficient on trust
in Model 2 suggests that the effect of trust is minor.
However, as the mean change in approval under this specification is slightly over 0.4, a one-category shift in trust
would account for more than half of that. The effect of
trust on rally size, relative to other important variables
(in particular, partisanship and vote choice), is effectively
the same in both models.
Although the OLS results are easier to interpret, the
results from the ordered probit in Column 3 may provide a more appropriate specification. Because the interpretation of these coefficients is not straightforward, I
present predicted probabilities with other variables set
to their medians. Figure 1 illustrates the predicted probabilities of membership in each of the rally categories,
across levels of trust. Importantly, each of the seven
graphs is scaled differently. While this means trends may
appear exaggerated, it is useful in that it demonstrates the
nominal direction in which trust moves individuals in
each category. Hypothesis 2 has implications for the
direction of effect in each of these cases: greater trust
should increase the likelihood of rallying and decrease
the likelihood of being in a non-rally category. Scaling
the graphs in the manner of Figure 1 provides insight
into whether the directional effect operates as
hypothesized.
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journal of PEACE RESEARCH 49(5)
640
Table II. Individual-level determinants of rally size
Prior approval
Age
White
Male
Education
Household income
Religious
Voted for Bush
Ideology
Party ID
Family finances
Change in trust
Trust
Model 1
(Feeling thermometer)
Model 2
(Approval: OLS)
0.5267***
(0.0470)
0.0866*
(0.0472)
5.62**
(2.320)
1.907
(1.351)
0.9006**
(0.4500)
0.2153
(0.1612)
1.368***
(0.5045)
2.837*
(1.714)
0.7901
(0.6626)
1.081**
(0.4413)
0.8649
(0.6427)
4.809***
(1.265)
4.9877***
(1.585)
0.6293***
(0.0406)
0.0046**
(0.0020)
0.1035
(0.1194)
0.0612
(0.0634)
0.0905***
(0.0205)
0.0127*
(0.0065)
0.0287
(0.0229)
0.1710**
(0.0818)
0.0809***
(0.0315)
0.0669***
(0.0187)
0.0528*
(0.0308)
0.2208***
(0.0592)
0.2774***
(0.0716)
Model 3
(Approval: Ordered probit)
0.9382***
(0.0691)
0.0068**
(0.0031)
0.184
(0.1733)
0.1017
(0.0981)
0.1334***
(0.0323)
0.0192*
(0.0102)
0.0495
(0.0352)
0.2437**
(0.1239)
0.0991**
(0.0482)
0.1087***
(0.0286)
0.098**
(0.0459)
0.388***
(0.0935)
0.2584***
(0.1092)
Bush Trust
Constant
Log-likelihood
Adjusted R 2
N
18.87***
(5.483)
0.26
619
Model 4
(Approval: Ordered probit)
0.9400***
(0.0689)
0.0067**
(0.0031)
0.1650
(0.1737)
0.1129
(0.0975)
0.1322***
(0.0321)
0.0183*
(0.0101)
0.0486
(0.0352)
0.6881**
(0.2736)
0.1007**
(0.0476)
0.1067***
(0.0286)
0.0999**
(0.0476)
0.3163***
(0.0935)
0.5552***
(0.1527)
0.3404*
(0.1862)
0.4784**
(0.2261)
0.38
587
613.26
611.68
587
587
Bootstrap standard errors in parentheses. Two-tailed tests: *p < :10; **p < :05; ***p < :01.
Figure 1 bears out the predictions of Hypothesis 2.
Higher levels of trust increase the probability of being
in any of the positive categories and decrease the probability of being in the zero or negative categories. Essentially, the higher the level of trust, the more likely the
individual is to rally. Furthermore, while the largest absolute changes are in the þ1 and þ0 categories (increasing
from 0.13 to 0.42 and decreasing from 0.70 to 0.46,
respectively), the relative changes in other categories are
substantial. In the 3 category, for example, a full shift
in trust reduces the probability of membership by
approximately 0.003. However, given the generally small
probability of being in this category, this is a reduction of
more than 98%. Similarly, in the þ3 category, a full shift
in trust only increases probability of membership by
about 0.018, but this represents more than a thirtyfold
increase.
To understand the effects of trust more fully, it is
instructive to compare it with other variables. The most
obvious choices are political: voting for Bush in 1988
and partisanship. To do this, I calculate the predicted
probability that an individual belongs to each category
across all values of the relevant variable, holding all others
at their medians. Figure 2 compares the effects of these
three variables for a full shift (from minimal to maximal
value) in each.
As is apparent from Figure 2, trust has an important
impact on rally size. In nearly every category, the trust
effect is noticeably larger than either competitor. This
is especially true for changes between 1 and þ2, where
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Chatagnier
641
Rally size of −2
Rally size of 0
2.0
3.0
4.0
1.0
2.0
3.0
4.0
0.6
0.4
1.0
2.0
3.0
4.0
Level of Trust
Level of Trust
Level of Trust
Rally size of + 1
Rally size of + 2
Rally size of + 3
1.0
2.0
3.0
4.0
Level of Trust
0.03
0.02
Bootstrap
95% Conf.
Interval
0.01
Predicted Probability
0.10
0.05
Predicted Probability
0.3
0.2
Predicted
Probability
0.00
0.00
0.1
Predicted Probability
0.4
0.04
0.15
0.5
0.5
Predicted Probability
0.15
0.10
0.00
0.00
0.000
1.0
0.05
0.03
0.04
Predicted Probability
0.05
0.7
0.20
0.06
Rally size of −1
0.01
0.02
Predicted Probability
0.008
0.004
Predicted Probability
0.012
Rally size of −3
1.0
2.0
3.0
4.0
1.0
Level of Trust
2.0
3.0
4.0
1.0
Level of Trust
2.0
3.0
4.0
Level of Trust
Figure 1. Predicted probabilities of rally size
it dwarfs both other variables. Overall, the comparisons
in Figure 2 provide strong support for the effect of trust
on rally size.
Returning to Table II, the final model in Column 4
includes an interaction between 1988 vote choice and
trust in government. Because previous research (e.g.
Edwards & Swenson, 1997) has indicated that a president’s supporters are the most likely to rally, trust in government may be irrelevant to them. Supporters may
always be willing to rally, finding some justification for
a conflict in any circumstance. By interacting trust and
vote choice, Model 4 investigates this proposition. The
results from the model are mildly supportive of the
hypothesis.11 Recomputing the marginal effects and
standard errors to account for the interaction term (see
Mallick, 2009), the results indicate that, for an individual with sample median characteristics, the interaction
moderates the effect of trust somewhat. While increasing
trust generally increases the individual’s willingness to
rally, this effect is occasionally dampened by having
11
A likelihood ratio test reveals that inclusion of the interaction term
results in a marginal improvement over Model 3 (p 0:076).
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journal of PEACE RESEARCH 49(5)
0.4
0.0
0.2
Non−Bush Voters
Bush Voters
−0.2
−0.1
0.0
0.1
0.2
Change in Predicted Probability
Trust Shift from Never to Always
Party ID Shift from Strong Democrat to Strong Republican
Vote Shift from Not Bush to Bush
−3
−2
−1
+0
+1
+2
+3
−0.4
−0.3
−0.2
Change in Predicted Probability
0.3
0.4
642
−3
−2
−1
+0
+1
+2
+3
Change in Approval
Change in Approval
Figure 2. Predicted change in rally size
Figure 3. Predicted effects of a full trust shift
voted for Bush.12 The general effect is illustrated by
Figure 3, which shows, for the median respondent, the
change in the predicted probability of being in a particular rally category, after going from never to always trusting the government. In each case, the shift in trust makes
an individual more likely to be in one of the rally categories, and less likely to be in the zero or negative categories. However, the size of the change in probability
for Bush voters in each category is relatively small, while
the change for non-Bush voters increases dramatically.
The likelihood of a one-category rally increases for a
non-Bush voter by approximately 0.37. The size of the
increase for a Bush voter is less than half that.
Supporters of the president (those who voted for him
in 1988) are marginally more likely to rally. Although
more trusting supporters are more likely to participate
in larger rallies, the difference is small. On the other
hand, trust has an enormous impact on nonsupporters, whose behavior following a crisis seems to
be driven in large part by trust in government. Nonsupporters who express high levels of trust are far more
likely to participate in larger rallies than those who
express low levels of trust. Indeed, the Gulf War had the
greatest effect on presidential approval for trusting individuals who voted against Bush in 1988.
It is possible that this phenomenon is an artifact of the
question wording. Supporters of Bush were not
substantially more likely to express trust in government
(the correlation between voting for Bush and trusting
government is r < 0:06), and it is possible that these
individuals make a distinction between ‘the government’
and President Bush himself (this is especially likely
among conservatives, who tend to be suspicious of government generally, but are more apt to support Bush). As
such, the level of confidence that these individuals have
in the president may be greater than the level of political
trust that they express. However, this fits well with the
theory presented earlier. It is expected that opponents
of the president would allow their cynicism to lead them
to the worst case scenario, whether it was warranted or
not. Presidential supporters, on the other hand, might
try to find justifications for an action, even when none
exists. In either case, the differential effect of trust on rallies relative to presidential support is interesting and
comports with intuition.
12
The effect is significant at the p < 0:05 level in two cases, both of
which involve low-trust Bush voters and a one-category decrease in
approval. In both of these instances, the marginal effect of the interaction is positive, while trust is negative.
Conclusion
The analyses above indicate that trust in government
plays a large role in determining the occurrence and size
of rallies ’round the flag. Macro-level results across 78
foreign policy crises involving the United States provide
tentative evidence that rallies are larger when individuals
express greater trust in government. At the individual
level, the effects are even more pronounced. Analysis of
individual opinions following the Gulf War indicates
that more trusting individuals are more likely to improve
their opinion of the president following a foreign policy
crisis. This result holds even though the USA was
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643
provoked by an attack on a friendly state. The impact of
trust depends partially upon the individual’s support for
the incumbent. Those who have voted for the president in
the past will tend to rally in times of crisis, regardless of
their general level of trust in the government. The propensity of an individual who did not vote for the president to
rally is significantly mediated by that individual’s level of
trust in government. More trusting non-supporters are
more likely to rally than are cynical non-supporters.
The significant relationship between trust and rallying
means that declining levels of political trust may be a
welcome change. If suspicious citizens are less likely
to rally, they will be more difficult to manipulate. Citizens with low levels of political trust can potentially
foil leaders’ diversionary plans. Ironically, to the extent
that trust and approval are related, leaders who are
most in need of a temporary boost in approval are precisely those who can expect the least positive change
from initiating a foreign policy crisis. Diversionary war
is most effective for those who have the least need to
divert.
It may be that this somewhat counter-intuitive relationship is the reason for the lack of clear empirical support
for diversionary theory. Previous theories have assumed
that the effect of a diversionary war was relatively constant
across time and leaders, and that it was essentially positive.
However, if the effects of diversionary war are contextually
dependent, the incentives may not be as clear as theorists
have implied. The analysis here suggests that leaders in
need of diversions may not have any incentive to divert
because they know that such a policy would be ineffective
at best. This is a powerful result that may explain the curiously divergent findings within the diversionary literature
and should be incorporated into the theoretical literature.
Unfortunately, this analysis was confined to the
United States. To some extent, these results may be geographically limited. However, given the nature of the
findings, this is more revealing than it initially appears.
The president of the United States has considerable latitude in the use of force, especially relative to other heads
of state.13 As such, the USA is an excellent candidate for
the use of diversionary war. That it is difficult for an US
president to divert tells us much about the likelihood of
diversions elsewhere. This leaves room for future
research on countries other than the USA, providing variation on the executive latitude dimension. In countries
in which interbranch consent is necessary for the use of
13
I thank an audience member at a conference presentation for
pointing this out.
force, agreement may serve as a signal to the voters,
diminishing the importance of trust, though diversion
would remain difficult.
Future research into diversionary theory and the rally
phenomenon should incorporate the idea of political
trust, opening new avenues of inquiry. An especially
interesting example is the potentially endogenous relationship between trust and rallies. If, as the results here
indicate and as some scholars (namely, Hetherington
& Nelson, 2003) claim, rallies boost both approval and
trust in government, and if trust is necessary to secure
large rallies, it may be the case that a president has incentives to initiate one crisis immediately following another.
Further research might determine the dynamic relationship between rallies, trust, and approval. In particular, at
what point might citizens catch on to diversions?
In order to understand more clearly how domestic
and international politics interact, students of international relations must take public opinion seriously and
treat voters as strategic actors. The analysis presented
here demonstrates that some voters seem to be aware that
leaders have diversionary incentives. Developing a clear
understanding of international politics necessitates a
more nuanced understanding of domestic politics.
Building strong international relations theory requires
that scholars incorporate the important insights that have
come from public opinion research.
Replication data
The data and R code for the analyses in this article can be
found at http://www.prio.no/jpr/datasets.
Acknowledgements
Previous versions of this article were presented at the
University of Rochester American Politics Working
Group and the 2010 Annual Meeting of the Midwest
Political Science Association. I am grateful for comments
from the participants, as well as Hein Goemans, Peter
Haschke, Gary Hollibaugh, Dick Niemi, Jonathan
Olmsted, Lynda Powell, and several anonymous
reviewers. All remaining errors are my own.
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JOHN TYSON CHATAGNIER, b. 1982, MA in Political
Science (University of Rochester, 2010); PhD Candidate in
Political Science at the University of Rochester (2007–);
current research interest: international conflict with thirdparty observation.
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