The Effect of Competition on Terrorist Group Operations
Stephen Nemeth
Department of Political Science
244 Waters Hall
Kansas State University
Manhattan, KS 66506
snemeth@k-state.edu
Abstract: Scholars have long accepted the contention that competition amongst terrorist
organizations raises the level of violence used by the competitors (Crenshaw, 1981, 1985,
Oots, 1989; Bloom, 2004, 2005; Chenoweth, 2010). This paper discusses this claim and
advances another – that competition amongst terrorist organizations creates incentives to
use less violence. Using insights from the organizational ecology literature - namely that
competition occurs within “species” – I create a variable that assesses intra-species
competition. I test both claims using a dataset of domestic terrorism created from the
Global Terrorism Dataset for the years 1970-1997. I find support for the hypothesis that
competition leads to more terrorism, validating the claims of outbidding theorists.
Furthermore, ideologies have differential effects on whether outbidding occurs, with
nationalist and religious terrorist groups responding to competition with more terrorism
and left-wing organizations responding with less.
The idea that competition amongst terrorist organizations results in a number of
negative outcomes, such as suicide terrorism, civilian targeting, and extreme violence has
become a powerful and persuasive idea in the terrorism literature (Crenshaw, 1981, 1985;
Oots, 1989; Bloom, 2005; Chenoweth, 2010). Organizations, vying for the attention of
recruits or for the support of wavering adherents, use escalating levels of violence, or
“outbidding” as a means to demonstrate their commitment and capability (Bloom, 2005).
This violence can also be turned against competing organizations, rendering the states
most likely to be fertile grounds for terrorism the most dangerous for terrorist
organizations (Oots, 1989). The outcome of this process is likely to have an indelible
mark on affected states; competition acts to legitimize more violence, encourage violence
against civilians and, in some cases, to encourage the use of suicide terror (Bloom, 2005).
Intuitively, this perspective has great appeal. Organizations that can demonstrate
their ability through continued and notable violence are advantaged in both recruitment
and group maintenance (Crenshaw, 1985; Post et al., 2003). Recruits are drawn to the
organizations which have the most selective incentives to offer, with the opportunity to
participate in violent activity forming a primary motivation (Crenshaw, 1985). Group
cohesion and retention is increased because violence and the number of operations
performed help “build morale within the membership through the experience of
cooperative operations” (Waugh, 1983: 9). Violence is currency in this perspective –
groups that are the most adept in its use ensure their survival, develop into capable
adversaries of the state, and become increasingly able to achieve their political goals.
At the same time, the argument is one of nuance. For Bloom (2005), the type of
violence characterized by outbidding only flourishes and resonates in particular situations.
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Organizations that engage in suicide terrorism, or excessive levels of violence, in the
incorrect environment fail to win public support and potentially endanger the
organization. The terrorism literature is replete with accounts of groups miscalculating
the amount of violence a populace was willing to accept (see Ross and Gurr, 1989;
Cronin, 2006). In such cases, violence has played a negative role in the development of
the organization, leading to less recruiting success, reduced public support, and the
decline, if not the dissolution, of the group.
This paper seeks to address why competition leads to more terrorism in some
cases and less in others. Like Bloom (2005), I forward that two factors - government
policy and social acceptability – determine whether outbidding actually occurs. In areas
where those factors are present competition leads to outbidding. Areas with competition
that are absent those factors will not demonstrate outbidding behavior. In fact,
competition in such states may actually lead to less terrorism. This insight distinguishes
Bloom’s (2005) discussion of outbidding from earlier ones (Crenshaw, 1981, 1985; Oots,
1989). I test this contention using cross-national domestic terrorism data from the Global
Terrorism Dataset (GTD) for the years 1970-1997.
Second, I test these claims using an improved operational definition of
competition. Building upon the organizational ecology literature, I develop a measure of
competition that is “species” specific (Lowery and Gray, 1995). This means that
competition is restricted to groups of a similar type; in this case, competition is restricted
to groups that share a similar ideology. This lets us avoid treating two very different
concepts the same way: the absolute number of terrorist organizations and the density of
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the organizational environment. By constructing an indicator using the latter, we achieve
a closer association between measure and reality (Post et al., 2003)
The paper is composed as follows: In the next section, I discuss the various ways
that competition may affect terrorist organizations. I highlight Bloom’s (2005) theory of
outbidding and the factors that make it possible. I follow with a discussion of the
relationship between competition and terrorism when those factors are not present and
how, in those circumstances, competition may reduce terrorism. The section ends with
the discussion of the hypotheses that stem from the theory. In the third section, I discuss
the data and coding rules. I emphasize the organizational ecology literature to create a
measure of terrorist organizational competition independent of the total number of
terrorist organizations that reside within a state. The fourth section presents empirical
tests of the hypothesis. The fifth section concludes.
THE FACETS OF COMPETITION
While outbidding has become the dominant perspective relating competition to
terrorism, the possibility exists that competition can also have a negative, rather than a
positive effect. One of the most prominent of these alternatives is that of backlash –
groups select a target or engage in violence that reduces the support of previously
sympathetic population, thus reducing the flow of resources and the ability of the
organization to carry out attacks (Ross and Gurr, 1989; Cronin, 2006). At the same time,
competition may also lead to a reduction in violence if it leads to cooperation between
two terrorist organizations or if it acts to reduce the capacity of the competitors. These
alternatives stand in contrast to the outbidding perspective, yet neither these alternatives
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nor the outbidding perspective have been subject to quantitative analyses (although see
Chenoweth, 2010). Before these perspectives are tested, I discuss them in detail below.
Outbidding
The outbidding perspective arises from the realization that dual pressures exist
within all terrorist organizations. Terrorist leaders, “must cope with a constant tension
between their desires to preserve the organization and the membership’s desire for action”
(Crenshaw, 1985: 476). Early theories of outbidding posited that competition solely
affected these two factors (Crenshaw, 1985; Oots, 1989). Later theories, notably that of
Bloom (2004, 2005), sees competition leading to outbidding when external conditions –
the acceptability of violence and government policy - are favorable.
The first theory of outbidding sees competition contributing to the collective
radicalization of the terrorist organization (Crenshaw, 1985). Groups facing competition
from a more extreme competitor typically radicalize and engage in more violence to
prevent the defection of members to the competitor organization.i The adoption of
terrorism by the Official IRA in response to the same decision by the Provisional IRA is
indicative of this type of outbidding logic (Crenshaw, 1985; Moloney, 2010). In the
Palestinian areas, the adoption of suicide terror by secular groups after its use by
fundamentalist organizations may be another example.ii
Secondly, Crenshaw (1985) suggests that outbidding may occur when competition,
and the threat of member exit, leads members to fight harder to validate their investment
in joining the organization. The decision to join a terrorist group entails a sacrifice and a
distinct change in lifestyle; Wolf (1978: 176) depicts the life of a terrorist as one
“characterized by the lack of comfort, the absence of expendable income, and the denial
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of leisure activity and personal privacy”. As a result, the high personal cost endured by
members makes activity their only sustenance and identity. Increased action therefore, is
a logical result of individuals seeking to ensure their choices to engage in terrorism are
justified (Kellen, 1979; Crenshaw, 1985).
The failure of the Israeli-Palestinian peace process in the late 1990s and the
subsequent rise in suicide terrorism provided the main impetus for the most recent
incarnation of the outbidding theory (Bloom, 2005). The increase of the use of suicide
terror, and the support groups received for their actions soon created an environment
where all groups had to engage in spectacular acts of violence.iii The logic of this theory
is simple and persuasive - “if multiple insurgent groups are competing for public support,
bombings will intensify in scope and number as they become both the litmus test of
militancy and the way to mobilize greater numbers of people within their community”
(Bloom, 2005: 78).iv This is known to be effective; Jerrold Post and his research team
found that nearly 60 percent of members in secular groups and 43 percent of religious
group members admitted to joining the most active terrorist organization in their
community (2003: 173).
This theory does differ from its predecessors. For Bloom (2005), outbidding
requires that the environment be able to support a group’s decision to engage in extreme
violence. In the case of the Israeli-Palestinian crisis, outbidding was successful because
the ongoing conflict, the collapse of the peace process, and the ineffectiveness of the
Palestinian Authority created an atmosphere of hopelessness that both spurred the
creation of terrorist organizations and legitimated terrorism, particularly suicide terrorism.
The newfound acceptability of this tactic became the mark by which all organizations
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were judged, setting off the cycle of outbidding. Support for suicide terrorism increased
quickly after these occurrences, reaching upwards of 85 percent in October 2001 from
lows of 24 and 33 percent during the period from 1997 to 1999 (Bloom, 2005: 193).
In Sri Lanka, another of Bloom’s (2005) case studies, outbidding arose for largely
the same reasons. The Tamil history with the Sri Lankan government had been marked
by political futility and communal violence at the hands of the majority Sinhalese. As a
result, Tamil quality of life had changed little since Sri Lankan independence. This status
quo led to the acceptance of terrorism as a political tactic and, moreover, to the creation
of a number of Tamil separatist groups, one of which was the Liberation Tigers of Tamil
Eelam (LTTE). As a result, the violence that resulted was similar in origin to the
Palestinian territories – groups competed with one another for support within an
atmosphere that accepted this kind of violence.
Unlike the Palestinian case, the acceptability of terrorism began to wane in Sri
Lanka. The LTTE had used violence to great effect; it struck at the Sinhalese, moderate
Tamils, and its competitors to become the predominant organization pressing for Tamil
separatism. By 2001, the long-running conflict between it and the Sri Lankan
government has sapped the will of the organization’s supporters, driving it to negotiations
with the government. By the time of Bloom’s analysis, Tamil hopefulness for peace and
the end of competition between the various Tamil organizations had largely ruled out the
use of suicide terrorism as a tactic.
This perspective has led to some quantitative work – most notably that of
Chenoweth (2010). In this work, she argues that intergroup competition explains why
democracies experience more terrorist activity than non-democracies. She finds support
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that transnational terrorist incidents and domestic terrorist organizations are more likely
to originate in competitive polities. While her analysis does provide some validation of
Bloom (2005), it is not a test of terrorist competition per se. Instead, competition
between terrorist organizations is subsumed into a larger measure of political competition.
States may, in fact, have high levels of terrorist competition while having little political
competition. Competition is also assumed to occur across the terrorist group system.
The assumption here is that resources and recruits are indifferent about which
organization they are directed to as long as they are directed to the most active one. I
discuss the potential drawbacks to this approach, particularly in the context of the
organizational ecology literature, in the methods section.
Competition and Moderation
While Bloom’s (2005) theory provides an excellent explanation of terrorist
competition and its outcomes in those areas which include both components, it is
important to consider what the effect of competition may be when either of those two
conditions is absent. First, competition may raise the cost of action; civilians see
outbidding as escalating savagery rather than meaningful attempts for political change,
driving civilians away and increasing the risk of backlash (Ross and Gurr, 1989). Second
and relatedly, this cycle of violence may serve as an implicit government counterterror
policy. Internecine struggles amongst terrorist organizations may drain groups of
resources and recruits, decreasing the efforts needed by incumbent governments for
counterterrorism. These considerations may lead to the observation that competition may
lead to less, rather than more, violence.
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The possibility of backlash is a major risk of outbidding in an incorrect
environment. Groups have frequently miscalculated the effects of their violence and
triggered this response. Cronin (2006) points out the Popular Front for the Liberation of
Palestine – General Command (PFLP-GC) and ETA as two groups amongst many that
have engendered condemnation for their actions. In the context of outbidding, the
Omagh bombing in August 1998 can be seen as a major contemporary instance of
backlash occurring from competition –between the Real Irish Republican Army, the
perpetrators, and the Provisional Irish Republican Army (Dingley, 2001). The deaths of
29 civilians from the attack, precisely during the Northern Ireland peace process, led to a
denunciation of the perpetrators from every political party in Northern Ireland, Ireland,
and Great Britain. Moreover, group support from individuals within the United States
waned and support for the then-recently signed Good Friday agreement increased
(Dingley, 2001).
Lastly, competition and outbidding may be damaging because it works to
inadvertently advance the state’s agenda rather than the terrorists’ goals. In Sri Lanka
and Turkey, the government either funded a favored terrorist organization or turned a
blind eye to intergroup violence in the hopes that the organizations would eliminate, or
greatly weaken, each other (Bloom, 2005). The extent to which groups may be
concerned with this problem is unknown. However, the decision of the PKK and Turkish
Hezbollah to abandon intergroup conflict in favor of jointly fighting the government may
indicate that groups have some realization of the dangers of conflict with one another
(Bloom, 2005).
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These concerns all contribute to a number of mechanisms which may lead to
competition causing less violence. Groups may first simply try to avoid backlash by
changing the nature and number of their attacks. This is especially evident if we consider
the level of public support as relatively fixed; each increase of an additional organization
reduces each group’s potential allocation of support. Given the assumption that using
outbidding violence results in a net gain of organizational support for the organization,
the use of this strategy in competitive situations ultimately results in each group gaining a
pool of supporters that does not compensate for the loss of members. Instead, this should
lead to the formation of coalitions - a rare occurrence (Crenshaw, 1985; Oots, 1989) - or
the moderation of violence.
An additional explanation for why competition may lead to less violence may lie
in the work of Lewis Coser (1956). He argued that external conflict can result in
cohesion within groups or the creation of coalitions, or at least elements of cooperation,
amongst different groups. In terms of this analysis, the increased attention brought to
groups by competition can lead to elements of coordination, or even cooperation,
between the competitors. Bloom (2005) noted that both the Kurdish Workers’ Party
(PKK) and Turkish Hezbollah, when confronted with government attention, abandoned
outbidding to adopt a campaign of violence directed against the Turkish government.
Brym and Araj (2008: 493-495) note that Israeli action had even pushed both Hamas and
Fatah into situations of tactical cooperation. In both cases, the number of terrorist events
perpetrated by these groups was lower after coordination than they were prior.v
The two perspectives regarding terrorist group competition provide contrasting
hypotheses about their effect on group operations. They are presented as follows:
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Hypothesis 1: Groups in competitive and favorable environments will commit more
terrorist acts than groups in non-competitive and non-favorable environments.
Hypothesis 2: Groups in competitive and favorable environments will commit less
terrorist acts than groups in non-competitive and non-favorable environments.
DATA AND METHODS
In order to analyze the relationships discussed here, I use the Global Terrorism
Dataset (GTD) from the National Consortium for the Study of Terrorism and Responses
to Terrorism (START) at the University of Maryland. The dataset includes 81,800 acts
of domestic and international terrorism occurring in 180 states spanning the years 19702007.vi
The GTD provides a remarkably flexible platform for two reasons. The first is
that its definition of terrorism is quite broad, referring to terrorism as “the threatened or
actual use of illegal force and violence to attain a political, economic, religious, or social
goal through fear, coercion, or intimidation” (LaFree and Dugan, 2007: ii). The
definition, absent references to targets and referring to a variety of goals and mechanisms,
allows researchers to create their own definitions and circumvents the contentious issue
of having to use an established definition of terrorism (Schmid and Jongman, 1988;
Hoffman, 1998; Silke 2004). Second, the GTD contains a wide variety of perpetrators of
terrorist violence. Well-defined organizations such as Hamas, Al-Qaeda, and the
Tupamaros are included along with actors such as political parties, student protesters, and
rebels. This also provides flexibility by allowing researchers to focus on interests ranging
from crime to social movements.
Since the analyses regard the effects of competition on group behavior, I use the
group-state/year as the unit of analysis. This distinction, rather than group-year, accounts
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for the behavior of the same group in different states, such as Karen National Union in
Myanmar versus its branch in Thailand. The repressive environment in Myanmar is
likely to exert a different effect on group behavior than the somewhat more permissive
environment in Thailand.
Second, this also accounts for differing levels of competition within the same
state. A state may have a competitive atmosphere regarding left-wing groups, but a
relatively monopolistic environment regarding groups on the right. Accounting for
competition as a state-wide phenomenon is likely to eclipse the effect of the substantial
range of terrorist ideologies that are contained within a state. This distinction and
ideological competition are discussed in more detail below.
I also restrict my analyses to cases of domestic terrorism. This is important not
only because domestic terror is more prevalent than international terrorism (Rosendorff
and Sandler, 2005), but because analyses that focus solely on international terrorism or
combine the two may lead to incorrect conclusions because they will be biased towards
large states and certain highly capable groups (Abadie, 2006).
In terms of competition, international and domestic groups are likely to face
different pressures. Groups operating domestically have to rely on resources within the
country – meaning that their practices are likely to be heavily driven by their public
support. This means that factors such as competition, as well as the acceptability of
violence and government policy, are likely to show a direct impact on the amount of
terrorism a group perpetrates. An international group, on the other hand, does not face
the same pressure. Instead, the international group can circumvent factors at the target
state and go back to its home base to get the needed resources. Competition, then, should
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have very little to do with international group behavior; in fact, Siqueira and Sandler
(2006) state that groups with outside sponsors, particularly international groups, are
likely to face little restraints on the type of violence they use.
I create this distinguishing coding rule by noting the attack location and
perpetrating group in the GTD. This is then compared to the available group record in
the START Center’s Terrorist Organizational Profiles (TOPS) database.vii If the location
of the attack in the GTD coincides with a known operating area for the terrorist
organization in the TOPs data, the event is marked as domestic terror.viii The process of
distinguishing international from domestic terror is illustrated in Figure 1.
[Figure 1 Here]
The final dataset contains 31,364 acts of domestic terror perpetrated by 459
terrorist organizations.ix This number is comprised of 429 individual groups plus 30
“franchises”. These attacks are then aggregated by group-state/year to create a dataset of
2,131 group-state/years with terrorist attacks. Using the start and end-dates of terrorist
activity from the TOPS database, I fill in all non-terror years (years the group was active
but not engaged in terrorist attacks) with zeros. The final dataset that results includes
8,217 group-state/years.
Dependent Variable
The dependent variable used in this analysis is a yearly count of the number of
domestic terror attacks committed by each individual terrorist organization. Attacks are
included in the dataset if they are intentional, involve a use of violence or a threatened
use of violence, and the actors are sub-national (START, 2009: 4-5). Attacks must also
fulfill two of three additional criteria for inclusion: the act must be directed towards a
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political, economic, religious, or social goal, there must be evidence of an intent to coerce,
and the action must be outside of the realm of legitimate military activities (START,
2009: 4-5). Lastly, to reduce bias that may result from overemphasizing capable
organizations, I follow Maoz (2007) and include failed acts of terrorism.
Independent Variable
To assess the effects of group competition, I use the inverse of the HerfindahlHirschman Index (HHI) as my main independent variable (Herfindahl, 1950; Hirschman,
1945). The HHI was originally conceived as a way to assess the concentration of firms in
a marketplace. Used in this capacity, it has since its inception become a central
component in economic analyses; both the Justice Department and the Federal Reserve
use it to evaluate the market impact of potential mergers (Hannan, 1997; Rhodes, 1993).
One of the advantages of this measure, as opposed to other means of determining
competition, is that it provides a measure that is invariant to the number of competitors.
For example, there may be several firms in a market that create a particular good, yet the
market share of one may create an environment where little competition actually exists.
Similarly, the presence of several terrorist groups may not indicate a truly competitive
environment, especially if one is clearly more capable and more noteworthy than the rest.
The ability of the HHI to account for this potential asymmetry is widely touted as one of
the strengths of the measure (Calkins, 1983).
The HHI is calculated as:
𝑁
∑ 𝑆𝑖2
𝑖=1
Where 𝑆𝑖 is the market share of firm i and N is the number of firms in the market.
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To determine the number of firms in the market, I adopt the concept of “competitive
exclusion” from the organizational ecology literature (Lowery and Gray, 1995). This
states that competition is a function of the resources that one draws from: groups will
only compete with other groups that draw on the same resource (Lowery and Gray, 1995).
For Lowery and Gray’s (1995), this meant competition amongst interest groups occur
within similar advocacy markets. Farm advocacy groups are distinct from business
groups and, as such, are only likely to face competition from other farm groups. As a
result, their analysis focuses on “species-guilds” – “sets of organizations representing
related interests” (1995: 9).
I conceptualize the same for terrorist organizations: each state has a certain
number of ideological “markets” in which recruits and resources are sought and
competition is bounded. Communist terrorist organization should face competition from
groups with similar ideological goals, not dissimilar ones. Secessionists have their needs
best served from a nationalist, rather than a religious, organization. Post et al. (2003: 173)
notes terrorist recruitment occurring within these lines: “individuals from strictly
religious Islamic backgrounds were more likely to join Islamist groups, while those who
did not have a religious background might join either a secular or religious group.”
Using this insight, I use the RAND Corporation’s End of Terror dataset (Jones
and Libicki, 2008) to classify each state as having four potential ideological “markets” nationalist, religious, left-wing, and right-wing. To determine the number of “firms” in
each of these “markets”, I sum for each state/year the number of other groups that exist
within each of the four ideological categories. Market share is then determined by the
percent of attacks committed per state/year by each group within each market. This best
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corresponds to the insight that members stay in and recruits join the most active
organizations (Crenshaw, 1985; Oots, 1989; Post et al., 2003).
These two values are used to calculate the HHI for each ideological category for
every state-year. The use of the inverse of the HHI follows Taagepara and Shugart (1989)
and allows for a more readily interpretable variable – scores near 1 indicate a condition of
monopoly while higher scores indicate competitive environments.x If the outbidding
argument is correct, high values of this variable will be associated with more total attacks.
If the moderation perspective is correct, low values will be associated with more attacks.
[Figure 2 Here]
Figure 2 plots the average level of organizational competition for the ten states
with the highest number of domestic terrorist attacks.xi Bars of one unit length indicate a
condition of monopoly while longer bars indicate progressively more competitive
environments. The colors indicate terrorist ideology as determined by the RAND End of
Terror Dataset (Jones and Libicki, 2008). The results from the chart appear to accord
with our understanding of terrorism. Colombia appears to offer an extremely competitive
environment for left-wing groups while France and the UK offer competitive arenas for
nationalist terror organizations. It is also interesting to note that high number of
uncontested categories; most of the top victimized states are characterized by relatively
monopolistic ideological categories. This finding, with the three caveats mentioned
above, contrasts with Bloom’s (2005) outbidding theory.
The three exceptions accord well with our understanding of terrorism in those
states. The high score for left-wing groups in Colombia indicate an environment where
the success of organizations such as the Revolutionary Armed Forces of Colombia
15
(FARC) and the National Liberation Army (ELN) gave rise to smaller organizations such
as the Guevarista Revolutionary Army and the Popular Liberation Army. In France and
the UK, the high level of competition occurs due to groups engaged in struggles for
Basque, Corsican, and Northern Ireland separatism.
Figure 3 plots the average level of competition by regime type over the time
period of the GTD dataset. These are calculated from the Polity IV dataset using the
Polity2 measure (Marshall et al., 2009).xii States with Polity2 scores at 6 and above are
coded as democratic and those below 6 are coded as autocratic. Figure 4 plots
competition by regime type using a trichotomous classification between autocracy,
anocracy, and democracy. The coding rule for democracy and autocracy remain the same.
The middle categorization, anocracy, is coded by Polity2 scores ranging from -5 and 5.
[Figures 3 and 4 Here]
Results indicate that democratic states are more competitive than their autocratic
counterparts (t=3.92, p<.01) and, using the trichotomous classification of regime type,
more competitive than either autocracies or anocracies (F=9.00, p<.01). While the
underrepresentation of terrorist groups in autocracies is a problem for analysis (Drakos
and Gofas, 2006), the difference in the number of groups between the regime types
provides support for Eubank and Weinberg’s (1994, 1998) findings that democracies are
more likely to harbor terrorist groups than autocracies. Further, this echoes Chenoweth’s
(2010) research linking the emergence of terrorist organizations in democracies to high
levels of intergroup competition.
Because outbidding theory is a contextual one – depending on the “domestic
politics of the minority group and the state counter-terror strategies and responses to
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insurgent violence” (Bloom 2005: 79) – I include a variable assessing the “environment”
that each state provides a terrorist organization. This variable is drawn from Mullins and
Young (forthcoming), who argue that states and societies that legitimize and rationalize
the use of violence may be more likely to be a victim of terrorism. This occurs as a result
of a spillover process – groups model and adopt the state’s use of violence to its own
interactions with others.
This measure is drawn from four distinct indicators – two which capture state
violence against its people, a third that measures citizen violence, and a final measure of
state involvement in war. The first measures whether or not a state used capital
punishment in a given year while the second captures the state’s use of extrajudicial
killings through the Political Terror Scale (Gibney and Dalton, 1996). The third
component assesses citizen violence by using the number of homicides per 100,000
people as drawn from the World Health Organization. The final element simply
measures state participation in an interstate or intrastate war as measured by the
Correlates of War project. Because the four components were found to load on a single
factor - this analysis, like the later analyses in Mullins and Young (forthcoming), will use
a single variable – culture of violence – to conduct the analyses. The temporal range of
this variable reduces the subsequent analyses to the 1970-1997 period.
To best assess this relationship, I create an interaction term between the
concentration score and the culture of violence variable. While some information can be
gained from the coefficients on interaction terms, I follow Brambor et al.’s (2006)
suggestion to visually analyze interaction terms. To do this, I use Boehmke’s (2006)
Grinter data utility.xiii
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Control Variables
I consider a number of control variables that may have an impact on group
activity. I first consider the state’s ability to exert control over its population and territory.
A weak central authority creates gaps in state control that allow insurgency to flourish
and allows groups to divert resources from organizational security to the conduct of
international terror (Takeyh and Gvosdev, 2002; Lai, 2007). For domestic terrorist
organizations, a weak central government should operate in both of these ways; groups
can operate unencumbered by state repression and they can dedicate more of their
resources to attacks within the state.
I assess state control by using a variable indicating a state’s relative political
capacity (RPC) (Arbetman and Johnson, 2008). This variable was originally used in
Organski and Kugler (1980) to measure the ability of states to wage war independent of
the absolute size of their resource base. At the domestic level, similar measures of
resource extraction have been associated with a decrease in internal violence (Benson and
Kugler, 1998). This variable is roughly calculated as the ratio of the total value of actual
state extractions relative to the potential value of all state extractions (Arbetman and
Johnson, 2008).xiv I anticipate that increased state control will be associated with fewer
attacks.
A second control variable I include is the state’s regime type. The impact of
regime type has been thoroughly debated in previous research, resulting in three schools
of thought. The first argues that the liberal characteristics of democracies, such as respect
for civil liberties, freedom of the press, and rights of due process reduce operational costs
for terrorist groups and allow them to recruit new members and plan attacks with minimal
18
interference from the government (Crenshaw, 1981; Hamilton and Hamilton, 1983;
Schmid, 1992). A second argues that democracies face reduced risks from terrorism
because there are many ways, such as voting, demonstrations, or the formation of
political parties to effect change without the need for violence (Eubank and Weinberg,
1994; Eyerman, 1998). Lastly, the third argues that the components of democracy have
differential effects on terrorism; characteristics like political efficacy and electoral
participation help to reduce terrorism while constraints of executive power increase the
probability of terrorism (Li, 2005). For this, I use regime type data from POLITY IV.xv
I divide this score into three parts and exclude autocracy as the baseline category.
A number of other control variables are used in this analysis. Civil war should
have a positive effect on all three of our dependent variables. Governments engaged in
civil wars should be less able to maintain control over their territory, reducing their
ability to combat terrorism and allowing for groups to devote more resources towards
terrorist violence. At the level of the populace, civil war can sway unaligned moderates
to support terrorist organizations increasing their vitality and longevity (Kalyvas, 2004).
Data for this comes from the UCDP/PRIO Armed Conflict Dataset (Gleditsch et al.,
2001).xvi
Larger populations are also likely to have an effect on terrorist group operations.
Large populations provide organizations with a larger base to recruit from, a broader pool
to draw resources from, and a more difficult environment for a state to monitor. All of
these characteristics should contribute to more active organizations. The values for the
population variable are taken from Gleditsch (2002). This variable is logged to reflect
the decreasing benefit to terrorist groups given larger populations.
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Lastly, I account for economic development as a final control variable. While
economic discontent has been linked to a variety of political outcomes, research on the
role of economics on terrorism has found little support for a direct effect (Krueger and
Maleckova, 2003; Abadie, 2006; Piazza, 2006). Rather, support and recruitment for
terrorism seem to occur more often amongst the educated and employed than the poor
(Krueger and Maleckova, 2003; Bueno de Mesquita, 2005). At the same time, wealthier
states that are able to provide adequate social welfare policies are less likely to have
popular support for terrorism and to experience terrorism on their soil (Burgoon, 2006).
This is unclear at the level of the group; organizations in low-wealth countries may
produce less terrorism because it is difficult to assemble enough recruits who meet a
group’s qualifications. As the wealth of a state increases, groups may produce more
terrorism. At the highest levels of state wealth, the production of terrorism may taper off
as qualified recruits exist but support for terrorism is low. I account for this by including
the logged term of per capita GDP. Data for this variable comes from Gleditsch (2002).
Because the hypotheses relate to terrorist group activity, as measured by number
of attacks, I use an event count model. Poisson models are not appropriate in this case, as
they assume that the data are independent and homogenous; it is likely that targeting is
not independent as groups that have gained experience with it are more likely to use it in
the future (Jackson et al., 2005). Instead, given that the number of total attacks is
dependent and is over-dispersed, I employ a negative binomial model (Long, 1997;
Cameron and Trivedi, 1998). I lagged the independent variables to account for
endogeneity. Lastly, I also include robust standard errors clustered by group to address
any potential problems with heteroskedasticity and serial correlation (Greene, 2002).
20
RESULTS
[Table 1 Here]
Table 1 presents the results from our test of competition and terrorist activity.
The first model indicates that competition amongst terrorist organizations within their
respective ideological niches has a negative and statistically significant effect on the
number of terrorist attacks that occur on a yearly basis. The substantive effects confirm
this relationship; a one standard deviation increase (.960) in competition yields a nearly
50% decrease in the number of terrorist attacks.xvii Given that the average number of
terrorist attacks in the data is 7.94, groups in environments with competition scores one
standard deviation above the mean (1.69) – an environment with one additional group –
will perpetrate four fewer attacks than it would in a less competitive environment.
Unlike Bloom (2005), this initial finding seems to suggest that moderation, rather than
outbidding, may be the way that terrorist organizations respond to competition.
The controls generally perform as expected. A state’s orientation towards
violence is statistically significant and associated with a greater number of terror attacks,
echoing Mullins and Young (forthcoming). The effect of democracy is also positive and
strongly significant. This may indicate that domestic terror is strongly influenced by the
democratic process – issues of representation or legislation may provoke groups to
violence. At the same time, this may also reflect the deep divisions in reporting terrorist
acts between democracies and autocracies (Drakos and Gofas, 2006). GDP per capita is
also shown to be positive and significant. This suggests that groups will be more active
in areas where they can get the best recruits. As expected, relative political capacity is
21
negative and significant, indicating that states with greater control over their territories
experience less terrorism. This supports research by Fearon and Laitin (2003) and Piazza
(2008) who find that higher levels of state capacity are related to decreased levels of both
insurgency and terrorism, respectively. Lastly, civil war is significant and in the
anticipated direction. This result indicates that, like Kalyvas (2004), we can see domestic
terrorism as a tactic used by combatants within civil war. This may also occur because
civil conflict allows terrorist groups room to operate with less threat of government
repression.
Contrary to our expectations, larger populations are associated with groups
committing less terrorist acts. In fact, population increases of one standard deviation
result in a 45% reduction in group attacks. This result is puzzling; populations accord
larger bases for recruitment, greater target selection, a larger audience to intimidate, and
greater monitoring difficulties for the government. One potential explanation for the
result is that it may be a methodological artifact – population may affect groups of
different ideologies in different ways. I conduct analyses disaggregating group type and
discuss this point in detail below.
The second model in Table 1 incorporates the interaction between group
concentration and a state’s acceptance of violence. The interaction effect is positive but
not statistically significant. When analyzed visually using the grinter utility (Boehmke,
2006), as shown in Figure 5, a different interpretation emerges. Here, the effect of
competition on the number of attacks has a slight positive effect as the state the terrorist
group resides in becomes more tolerant of violence - a similar, albeit weaker, finding to
that of Bloom (2005). The controls provide comparable results to that of the first model.
22
Table 2 disaggregates the analyses into the four ideological categories used by the
Jones and Libicki (2008) data. This may help to address the weak findings presented
above. It also helps to clarify whether the effect of outbidding is different across
ideological types – an element that is not directly addressed by Bloom (2005). One may
anticipate that groups with a religious ideology may be more likely to engage in
outbidding regardless of the acceptability of violence because their spiritual mandate
trumps any desire to gain widespread public support (Juergensmayer, 2003). Nationalist
groups, on the other hand, may be sensitive to outbidding since excessive violence may
negatively affect public support, making the attainment of their goals more difficult
(Sanchez-Cuenca and de la Calle, 2009).
The results indicate that the effects of many of the variables are conditional on
group ideology. This is first echoed in the results for competition; 3 out of the 4 models
demonstrate that competition in the ideological environment leads to fewer attacks. The
lack of a finding in the fourth case - right wing groups may indicate that these types of
groups are less sensitive to issues of citizen perception given that they are, in many
instances, an arm of state policy and a recipient of state support.
The conditional effects are made more evident by visually analyzing the
interaction terms in Figure 6. Here, for religious and nationalist terrorist organizations,
the marginal effect of competition on domestic terror attacks is shown to increase as the
acceptability of violence increases.xviii In other words, religious organizations and their
nationalist counterparts respond to competition using outbidding across most states. Leftwing groups do not appear to engage in outbidding. Rather, for those instances where
the interaction is significant, competition leads to moderation for left-wing organizations.
23
The interaction for right-wing organizations is not significant, thus I make no claims
about the relationship.
The control variables also indicate that ideology has a considerable effect on their
direction and significance. The state’s culture of violence has a differential effect across
the ideologies; religious groups are less likely to perpetrate attacks in more violenceacceptant states while both left and right-wing groups are more likely to. For anocracies,
nationalist groups increase their attacks, while left and right-wing groups curtail their
activities. In addition, nationalist and left-wing groups are also active in democracies,
although the results for left-wing organizations fall outside traditional significance levels.
Per capita GDP only has an effect for nationalist groups; nationalist terrorist
organizations such as MEND (Movement for the Emancipation of the Niger Delta) and
GAM (Free Aceh Movement) have used arguments based on the wealth of the central
government to justify their secessionism (Ross, 2004). Relative political capacity
decreases the number of nationalist and left-wing attacks while increasing the number of
right-wing attacks. Given that this measures a government’s ability, a positive
relationship here may denote the inclination of some governments to use right-wing
groups as a coercive element of their policy (Mason and Krane, 1989). The civil war
variable is positive and significant for religious and nationalist groups. This may indicate
that these groups have larger goals, such as regime change, than groups of other
ideologies and that a condition of warfare may be the best context to pursue these goals ().
Lastly, population is only significant for left-wing organizations.
CONCLUSION
24
While theories of outbidding have been central to explanations of terrorist actions
for many years, few attempts have been made to subject the theories to empirical testing.
This analysis, focusing on group level data, finds a positive relationship between
competition and increases in terrorist violence, conditional on a state’s acceptance of
violence. As such, this finding is consistent with those of Bloom (2005). These results
become more pronounced when the analysis takes group’s ideologies into account.
Religious terrorist groups show the greatest proclivity to outbid followed by nationalist
organizations. The positive finding for religious organizations affirms Juergensmeyer’s
(2003: 221) observation that “there is no need…to contend with society’s laws and
limitations when one is obeying a higher power”. Left-wing organizations respond by
reducing their violence – precisely responding to society’s limitations.
In addition, this analysis utilized the organizational ecology literature to better
operationalize the concept of competition. Previous discussions of outbidding and
competition treated competition as boundless – resources and recruits ran towards the
most capable organization. Similarly, recruits were drawn to any group, regardless of
their ideology or history. Interviews and assessments of terrorist operatives have shown
that this is not the case, recruits and resources are very specific about their destination
(Post et al., 2002). As such, terrorist organizations can be theorized to operate via the
“competitive exclusion” principle – competition only occurs between organizations of a
similar type. This then allows us to create measures that take this type of sectoral
competition into account.
This research also points to the value of considering using the group as the unit of
analysis. Work by Asal and Rethemeyer (2008) demonstrate this utility, showing that
25
some organizational attributes have important impacts on organizational lethality while
others do not. Here, this choice shows various levels of competition, and thus very
disparate levels of violence, can exist within a state. Aggregating the data to use larger
units of analysis, like the state, threatens to obscure this valuable heterogeneity. Such a
focus, and the utilization of concepts from different fields, may provide more clarity to
this complex and menacing phenomena.
26
Figure 1: Coding Rule & Screening Mechanism
Step 1. According to TOPs, the
FMLN was known to operate
solely in El Salvador.
Step 2. These states are not defined as regular
operating areas for the FMLN and, thus, are
not considered domestic.
Selected FMLN Attacks 1980-1983
Case
Group
Date
State
1
Farabundo Marti National Liberation Front
(FMLN)
1/14/1980
El Salvador
2
FMLN
1/24/1980
El Salvador
3
FMLN
2/14/1980
Guatemala
4
FMLN
9/15/1980
El Salvador
5
FMLN
2/4/1981
El Salvador
6
FMLN
11/12/1981
El Salvador
7
FMLN
4/26/1982
El Salvador
8
FMLN
10/18/1982
El Salvador
9
FMLN
2/3/1983
El Salvador
10
FMLN
8/18/1983
United States
Step 3. As a result, Cases 3 and 10 are not
coded as cases of domestic terrorism.
27
Religious
Left-Wing
K
U
ke
y
Tu
r
iL
an
ka
Sr
Sp
ai
n
pi
ne
s
Ph
ilip
Pe
ru
nc
e
Fr
a
Sa
lv
ad
or
El
ol
om
bi
a
C
C
hi
le
0
.5
1
1.5
2
2.5
Figure 2: Average Level of Concentration for Top Ten Target States of Domestic Terrorism (1970-1997)
Nationalist
Right-Wing
28
1.2
1.4
1.6
1.8
2
2.2
Figure 3: Average Level of Terrorist Organization Concentration (Autocracies and Democracies) (1970-1997)
1970
1980
1990
2000
Year
Democracy
Autocracy
29
1
1.5
2
2.5
3
Figure 4: Average Level of Terrorist Organization Concentration (Autocracies, Democracies, and Anocracies) (1970-1997)
1970
1980
1990
2000
Year
Democracy
Autocracy
Anocracy
30
.3
.2
.1
0
-1.5
-1
-.5
Kernel Density Estimate of lagfactor
0
.4
Figure 5: Effect of Competition Conditioned on Acceptability of Violence
-1
0
1
2
Acceptability of Violence
3
31
Figure 6: Effect of Competition Conditioned on Acceptability of Violence by Group Type
32
Table 1: The Effect of Competition on Domestic Terrorist Attacks
Model 1
%Δ
Model 2
%Δ
Competition
-.714***
(.122)
-49.6
-.770***
(.166)
-52.3
Culture of Violence
.752***
(.151)
124.2
.656**
(.294)
102.1
Concentration * Culture
.055
(.103)
Anocracy
.019
(.391)
Democracy
1.25***
(.419)
Logged GDP per capita
.000***
(.000)
145.4
.000***
(.000)
148.8
RPC
-.506*
(.261)
-23.6
-.503*
(.261)
-23.5
Civil War
.750**
(.310)
111.8
.764**
(.310)
114.7
-.379***
(.113)
-45.3
-.383***
(.113)
-45.7
Logged Total Population
Constant
N
Log Likelihood
Wald χ2
-.002
(.385)
247.9
1.23***
(.422)
-4.63
(1.29)
-4.74
(1.31)
3111
-5900.73
95.38***
3111
-5900.12
121.11***
240.7
Note: Robust Standard Errors clustered on group in parentheses. * significant at 0.10, ** significant at 0.05,
*** significant at 0.01 (two tailed). All independent variables lagged at t-1. Percentage change calculated
as change in 1 standard deviation for continuous variables and unit change for dichotomous variables.
33
Competition
Table 2: The Effect of Competition on Total Terrorist Attacks by Ideology
%Δ
%Δ
%Δ
Religious
Nationalist
Left Wing
Right Wing
-1.69***
-76.4
-.824***
-60.5
-.526**
-32.0
-.321
(.608)
(.164)
(.241)
(.330)
Culture of
Violence
-2.03***
(.633)
-86.7
.215
(.306)
.911***
(.336)
Con * Culture
.994***
(.367)
591.8
.110
(.092)
-.063
(.137)
Anocracy
-.284
(.662)
2.00***
(.374)
637.1
-.840**
(.403)
-56.8
-2.92***
(.562)
Democracy
-.018
(.673)
1.84***
(.330)
529.4
.949*
(.542)
158.4
.288
(.709)
Logged GDP
per capita
-.000
(.000)
.000***
(.000)
294.3
.000
(.000)
RPC
-.226
(.979)
-.847**
(.351)
-39.5
-.857**
(.387)
Civil War
1.62**
(.801)
.742**
(.290)
109.9
.658
(.474)
Logged Total
Population
-.374
(.266)
.161
(.111)
-.647***
(.218)
Constant
6.78
(2.57)
-1.91
(1.41)
8.28
(2.21)
403.4
177.2
%Δ
1.27**
(.616)
283.2
-.527
(.458)
-94.6
-.000
(.000)
-29.8
.495**
(.228)
28.5
.903
(.583)
-60.5
-.264
(.385)
2.67
(3.37)
N
422
1371
1149
169
-498.77
-2328.64
-2621.95
-209.31
25.46***
114.81***
107.10***
453.13***
Note: Robust Standard Errors clustered on state in parentheses. * significant at 0.10, ** significant at 0.05, ***
significant at 0.01 (two tailed). All independent variables (other than ideology) lagged at t-1. Percentage change
calculated as change in 1 standard deviation for continuous variables and unit change for dichotomous variables.
Log Likelihood
Wald χ2
34
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38
i
This can also occur as a response to competition within the organization. Moderates may radicalize to
prevent radical members from defecting to form a competing organization.
ii
An example of the consequences of ignoring radicalization is the fracturing of the Popular Front for the
Liberation of Palestine in the early 1980s when it refused to consider participating in acts of violence such
as hijacking or guerrilla warfare (Crenshaw, 1985: 85).
iii
See Brym and Araj (2008) for a reexamination of Bloom’s (2005) data and a critique of the outbidding
hypothesis.
iv
It took fourteen months for suicide terrorism to spread from fundamentalist organizations like Palestinian
Islamic Jihad (PIJ) and Hamas to secular organizations like the Al-Aqsa Martyr’s Brigade and the Popular
Front for the Liberation of Palestine (PFLP) (Brym and Araj, 2008).
v
Using the online component of the GTD (www.start.umd.edu/gtd/), I gathered the total number of events
for the two terrorist organizations. I compared the total number of attacks for each group to the number of
terrorist attacks that occurred during each occasion of “cooperation/coordination.” The PKK participated
in 994 total incidents in Turkey, 367 of which occurred after the “cooperation/coordination” phase began in
1993. Turkish Hezbollah participated in 4 incidents, all of which occurred after 1993. Altogether, 371
attacks out of 998 (37%) occurred during the cooperative phase. For Hamas and Fatah the
“cooperation/coordination” phase is the duration of the Second Intifada (2000-2006). Hamas perpetrated
287 total attacks, 150 of which occurred during the Intifada. Fatah engaged in 52 total attacks, 10 of which
occurred during the Intifada. In this case, 160 out of 339 (47%) attacks occurred during the Intifada.
vi
During the transfer of the files from their original owner to START, the files for 1993 were lost.
Analyses using this data are all missing in this time period.
vii
TOPs is located at http://www.start.umd.edu/start/data/tops/.
viii
This also holds for terrorist organizations operating in more than one country given that the additional
countries are recognized by the data.
ix
Out of the total number of cases - 81,800 – 32,112 were excluded because they were listed as “unknown”
or “other”. From the remainder, 11,882 cases were dropped because they included unorganized collectives
such as “a deranged patient”, “student protestors”, or “pirates” as well as groups that are not accounted for
in TOPs. A further 2,155 were dropped – 836 because they were doubtful instances of terrorism and 1,319
were dropped because they represented excluded target types. In all, this results in 35,651 total cases;
31,364 domestic and 4,287 international.
x
This measure is called the “effective number of political parties” and provides an indication of “the
number of hypothetical equal-sized parties that would have the same effect on fractionalization of the party
system as have the actual parties of varying sizes” (Taagepara and Shugart, 1989: 79).
xi
Scores for all the states (N = 82) in the analysis are available upon request.
xii
I use the Polity2 measure from the dataset; this provides a twenty point scale created by subtracting the
Autocracy score from the Democracy score while accounting for the effects of transitions, interregnums,
and interruptions. “Transitions” (-88) are interpolated across the span of the transition. “Interregnums” (77) are given a neutral score of 0 and “interruptions” (-66) are coded as missing (Marshall et al., 2009).
xiii
Grinter works by plotting the marginal effect of the primary independent variable on the conditional
variable while holding others constant.
xiv
For a more detailed discussion of the construction of the variable, refer to Arbetman and Johnson (2008).
xv
Once again, I use the Polity2 variable. Substitution with the original Polity variable does not appreciably
change the results.
xvi
This dataset defines armed conflict as, “a contested incompatibility that concerns government and/or
territory where the use of armed force between two parties, of which at least one is the government of a
state, results in at least 25 battle-related deaths” (UCDP/PRIO Armed Conflict Dataset, 2009: 1). Four
types of conflict are coded in the data: extrasystemic, interstate, internal conflict, and internationalized
internal conflict. For the purposes of this study, I restricted the analysis to the last two forms of conflict.
xvii
Substantive effects were calculated using the listcoef function in STATA (Long and Freese, 2005)
xviii
In the case of religious organizations, this effect is significant only when the upper and lower bounds of
the confidence interval exclude zero.
39