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ON ETHNIC CONFLICT AND THE ORIGINS

OF TRANSNATIONAL TERRORISM

Atin Basuchoudharya& William F. Shughart II

b

aDepartment of Economics and Business, Scott Shipp Hall ,

Virginia Military Institute , Lexington, VA, USAbDepartment of Economics , University of Mississippi , PO Box

1848, University, MS, 386771848, USA

Published online: 19 Apr 2010.

To cite this article:Atin Basuchoudhary & William F. Shughart II (2010) ON ETHNIC CONFLICT AND

THE ORIGINS OF TRANSNATIONAL TERRORISM, Defence and Peace Economics, 21:1, 65-87, DOI:

10.1080/10242690902868343

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Defence and Peace Economics, 2010

Vol. 21(1), February, pp. 6587

ISSN 1024-2694 print: ISSN 1476-8267 online 2010 Taylor & FrancisDOI: 10.1080/10242690902868343

ON ETHNIC CONFLICT AND THE ORIGINS OF

TRANSNATIONAL TERRORISM

ATIN BASUCHOUDHARYa,AND WILLIAM F. SHUGHART IIb

aDepartment of Economics and Business, Scott Shipp Hall, Virginia Military Institute, Lexington, VA,USA; bDepartment of Economics, University of Mississippi, PO Box 1848, University, MS 38677-1848,

USA

TaylorandFrancisGDPE_A_387006.sgm

(Received in final form 27 October 2008)

10.1080/10242690902868343DefenceandPeaceEconomics1024-2694 (print)/1476-8267 (online)OriginalArticle2010Taylor&[email protected]

Using the ITERATE dataset, we explore the origins of transnational terrorist activity, from 1982 through 1997, in 118countries. We model terrorism, not as a function of a nations ethnic, religious or linguistic fractionalization, but asan independent measure of perceived ethnic tensions. When we control for institutional quality, evidence that politicalrights and civil liberties mitigate the terrorism-producing effects of ethnic tensions exists only since 1990. Economicfreedoms, on the other hand, robustly reduce the number of terrorist attacks originating in ethnically tense societies.

Keywords: Ethnic tensions; Transnational terrorism; Political rights; Economic rights; Cold War

JEL Codes:D74

The advantages of possessing the control of the powers of the government, and thereby of its honors and emol-uments, are, of themselves, exclusive of all other considerations, ample to divide a community into two greathostile parties. (John C. Calhoun)1

1. INTRODUCTION

Man is a social animal as well as a political one. From Paleolithic times to the present day,

the survival of the species has hinged on the evolution of cooperative interaction amongst

rationally self-interested individuals and, not surprisingly, the strongest of mankinds

interpersonal bonds are nurtured by ties of blood. Kinship fosters trust, loyalty and adherence

to other behavioral norms that help control free-riding (Gifford, 2004). Amartya Sen (2006)

emphasizes that while identification with a particular group can facilitate within-group

cooperation (see also, for example, Putnam, 2000), excessive identification can also lead

to inter-group conflict. Thus, while groups promote the creation of social capital that

allows their members to coexist peacefully, trading networks to emerge, and public goods to

be produced, the asymmetrical relationships between insiders and outsiders can lead to

Corresponding author. Department of Economics and Business, Scott Shipp Hall, Virginia Military Institute,Lexington, VA 24450, USA. E-mail: [email protected]

1

Quoted in Hardin (1999: 276).


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66 A. BASUCHOUDHARY AND W.F. SHUGHART II

polarization and violent confrontation. Such inter-group tensions may find expression in

transnational terrorist activity.

Indeed, some recent literature exploring the causes and consequences of terrorism finds that

the probability of a country being victimized by terrorist groups is related positively to

measures of the target countrys ethnic, linguistic and religious fractionalization (e.g., Kurrild-

Klitgaard, et al., 2006). Ethnically polarized countries are more likely to be plagued by civilwar and other domestic violence (Montalvo and Reynal-Queral, 2005). A survey of the histor-

ical record suggests that the three terrorist waves that have swept the globe over the past

century terrorism in the service of national liberation, of left-wing causes and of anti-western

Islamic fundamentalism can be traced to the ethnic frictions created by the scramble for

Africa that preceded the First World War (Parkenham, 1991) and to the arbitrary national

boundaries subsequently drawn at the Paris Peace Conference that carved up the Ottoman and

Hapsburg Empires into British and French colonial spheres of influence. The unleashing of

ethnic and religious separatism in the Middle East and Central Asia in the wake of the colonial

powers withdrawal from the scene and the more recent collapse of the Soviet Union are

central to the understanding of modern terrorist activity.2

This paper looks directly at the relationship between ethnic tensions in a country and the

probability of a terrorist act originating from that country. This is very different from prior

work in understanding the causes of terrorism, which, as we shall see, asks whether ethnic

diversity is a determinant of the nations targeted by terrorist attacks. We ask instead whether

the level of ethnic tensions helps explain terrorisms countries of origin. The paper also sheds

new light on the conjecture that the end of the Cold War was a watershed event for transna-

tional terrorism.

Our empirical analysis uses information on transnational terrorist activity in 118 countries

from 1982 through 1997, taken from the ITERATE dataset (Mickolous, et al., 2003). We thus

adopt the definition of terrorism advanced by Enders and Sandler (2006: 3), namely, that it is

the premeditated use or threat to use violence by individuals or sub-national groups in orderto obtain a political or social objective through the intimidation of a large audience beyond that

of the immediate victims.3

We find that terrorism is more likely to emerge in countries where ethnic tensions are

perceived to be high. When we control for institutions, there is little evidence that political and

civil rights freedom of expression, of assembly, of the press, democratic elections, and so on

are by themselves sufficient to overcome the terrorism-producing effects of ethnic tensions.

Economic freedoms, on the other hand, do seem to reduce the probability of terrorist attacks

originating in ethnically tense countries, especially so since the fall of the Berlin Wall in 1989.

Our results suggest that property rights are more important than civil rights in explaining

terrorisms countries of origin: transnational terrorism tends to find more fertile ground wherethe economic liberties of the people are limited than where it is their political liberties that are

limited. In other words, it may be incorrect to think of terrorism as being rooted in ethnic

differences. The empirical evidence reported herein thus supports Erik Gartzkes (2007)

2 See Shughart (2006), Fearon (2006: 856) and, for an in-depth treatment of the exceptional mismatch betweenethnic identities and political structures in certain parts of the world, Ferguson (2006). In contrast to Shughart(2006), Horowitz ([1985] 2000: 7576) claims that, in Africa at least, the boundary-drawing process frequently tookethnic interests into account, and boundaries often were redrawn later by colonial powers in response to ethnicdemands. He goes on to argue, however, that the colonies were artificial, not because their boundaries were indif-ferent to their ethnic composition, but because they were, on the average, many times larger than the political

systems they displaced or encapsulated, thus greatly expanding the range of ethnic group interactions (and points ofpotential friction), most notably in the case of national elections: many groups encountered each other for the firsttime during colonial rule (Horowitz [1985] 2000; 98).

3 Terrorism is theater, according to Brian Jenkins (quoted in Coll, 2004: 139). Alternative definitions aresupplied by, for example, the US Department of State (1997).


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TRANSNATIONAL TERRORISM 67

contention that there is a causal link between liberal economic processes and peace between

nations, but that liberal politics is only correlated with peace. Terrorism arises less from a

clash of civilizations or clash of cultures (Huntington, 1996; Fisk, 2005) than it does from

the absence of market-friendly institutions.

The paper is organized as follows. Section 2 reviews prior work on ethnicity and civil

conflict. We describe our dataset and estimation methodology in Section 3. In Section 4, wepresent and discuss our results. Section 5 concludes.

2. VOLKSTUMSKAMPF4

Control of the state, control of astate, and exemption from control by others are among the main goals of ethnicconflict. (Horowitz [1985] 2000: 5; emphasis in original)

Ethnicity supplies a natural basis for group formation (Landa, 1994). Larger than a family,

but affiliation with which nevertheless is reckoned primarily by a descent rule, members

of theprototypicalethnic group share a common language, religion, customs, sense of home-land, and relatively dense social networks (Fearon, 2006: 852853; emphasis in original).5

Shared behavioral norms and repeated interaction support the development of stable goods

and credit markets. The ability to recognize and remember individuals, to reward good

behavior and to punish bad, promotes reputation building, which lowers transaction costs.

Moreover, the imperatives of evolutionary biology survival and reproduction make it ratio-

nal for individuals to value the wellbeing of even remote kinsfolk over the genetically distinct

members of unrelated groups: under the right conditions, the selfish gene also can be altruistic

(Dawkins, 1989).6

By definition, within-group cooperation yields benefits in excess of costs, which are then

shared according to some rule (Olson, 1965).

7

In interacting with other groups, however, thegame frequently is zero-sum one groups gains are secured at other groups expense. This is

especially true when it comes to capturing control of the institutions of government, which are

important sources of patronage and other artificially created scarcity rents. In other words,

successful alignment of self-interest and group interest weakens incentives to cooperate with

other groups, which may come to be seen, not as potential trading partners, but as adversaries.

Conflict is often unavoidable because the group that seizes power distributes the rents among

its own members and rarely compensates the losers (Hardin, 1995). The failure of power-

sharing arrangements in such settings is likely to breed Volkstumskampf(Arce and Sandler,

2003).

The organization of groups along ethnic lines thus generates both benefits and costs.

Scholars have devoted considerable attention recently to studying the possible links between

4 A euphemistic neologism for ethnic conflict delighted in by the Nazis and more effective in maintainingcontrol of a heterogeneous state than overt propaganda, according to philologist Victor Klemperer (Ferguson, 2006:455).

5 Ethnicity is connected to birth and blood, but not absolutely so (Horowitz [1985] 2000: 5152). Cautioningagainst the acceptance of the figment of the pigment, Horowitz argues in favor of an inclusive conception ofethnicity that embraces differences identified by color, language, religion, or some other attribute of common origin.Indeed, it is not the attribute that makes the group, but the group and group differences that make the attributeimportant (Horowitz [1985] 2000: 46, 50).

6 The right conditions follow from Hamiltons Rule [which] states that, other things equal, evolutionary selec-

tion will lead a Donor organism D to aid a recipient organism R if the cost-benefit ratio CD/bRis less than their relat-edness rDR, where cost CDand benefit bRare measured in increments to the fitness (i.e., reproductive survival)

of Donor and Recipient, respectively (Hirshleifer, 2001: 21; emphasis in original).7 Among the most important needs met by ethnicity is the need for emotional support and reciprocal help, and

for mediation and dispute resolution (Horowitz [1985] 2000: 81).


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ethnic heterogeneity and ethnic violence, both within countries and across them. In what

follows, we summarize work on two important questions raised in the existing literature. One

asks whether civil war, terrorism and other forms of lethal conflict are more likely to emerge

in ethnically tense nation-states; the other asks whether institutions (of governance, primarily)

can blunt the ethnic cleavages that otherwise would turn violent. We then discuss the connec-

tions between domestic ethnic tensions and transnational terrorism.

2.1. Ethnic Heterogeneity and Violence

The question whether ethnic diversityper seis salient in explaining the emergence of violent

conflict is still open to debate. Easterly (2000), for example, has suggested that ethnic fraction-

alization is an important driver of recurrent bloodshed on the African continent. Cashdan

(2001), in contrast, does not find any consistent empirical support for the hypothesis that

ethnocentrism breeds xenophobia.

Collier (2000) finds a more nuanced relationship between ethnic heterogeneity and civil

unrest. His work suggests that very ethnically diverse countries tend to have lower levels ofconflict than those where one ethnic group dominates other minorities.8As Horowitz ([1985]

2000: 39) puts it, a profusion of dispersed groups usually creates such great ethnic heteroge-

neity at the center that when the center intervenes it may do so as a neutral arbiter. On the

other hand, in those states where a few groups are so large that their interactions are a constant

theme of politics at the center[,] the claims of one group tend to be made at the expense of

another: mutually exclusive demands characterize political debate (Horowitz, [1485] 2000).

Indeed, Esteban and Ray (1994) conclude that ethnic polarization is greatest when a society is

divided into two groups of similar size.

More recently, Kurrild-Klitgaard et al. (2006) report a weak, but nevertheless positive

relationship between terrorist activity and the ethnic, linguistic, and religious fractionaliza-tion of countries on the receiving end of terrorist attacks. It is certainly true that emphasizing

differences and fabricating ethnic tensions cultivates the grievances of groups perceiving

themselves to be disadvantaged under the status quo.9Glaeser (2005), for example, presents

a model where politicians foment hatred of other ethnic groups to foster solidarity and orga-

nize mass action, including violence, to advance their own agendas. As a matter of fact, by

posing a credible threat to the existing governments monopoly power over determination

of the distribution of rents (Kirk, 1983), domestic violence directed at other ethnic groups

can be a strategic choice for capturing power.10Because bloodlines and long-term friend-

ships limit the possibility of infiltration (Enders and Sandler, 2006: 88), ethnic groups that

pursue their goals through violent means also have more effective defenses against the

states countermeasures.

8 Specifically, in societies where one ethnic group comprises 4590% of the population there is a 28% chance ofcivil conflict. However, when ethnic groups are more evenly distributed the probability of conflict falls to 3%. Itturns out, though, that Africa contains many of the worlds most ethnically diverse nation-states Uganda tops thelist; Kenya ranks third (Alesina et al., 2003). Fearon (2006: 854) likewise notes that Sub-Saharan Africa stands outas the only region in which fewer than half the countries have an ethnic majority group. These observations tend toundermine the argument that violence is more likely where one ethnic group is dominant. On the other hand, Collierand Hoeffler (2004) report evidence suggesting that civil war is more likely to erupt in such countries.

9 Hirshleifers (2001: 45) paradox of power implies that in any conflict over resources disadvantaged groups will

fight harder than better-endowed groups, whose members have more to lose and, hence, more to gain from coopera-tion with the other side.

10 Others have drawn an analogy between terrorism and hate crimes since the definition of such crimes includesattacks by one religious or ethnic group on another religious or ethnic groups (see, for example, Hamm, 1998;Kressel, 1996).


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2.2. Institutions

To what extent can institutions dampen inter-group tensions and lower the violence-producing

potential of ethnic Balkanization? Numerous studies report that healthier domestic economic

performance higher per capita incomes and faster rates of economic growth lowers the risk

of ethnic violence (see, for example, Green et al., 1998; Jefferson and Pryor, 1999; Krueger

and Pischke, 1997). However, Krueger and Maleckova (2003) observe that the main lesson ofthis literature may be that institutional factors such as disintegration of the rule of law

resulting from governmental sanctioning of violence against minorities or a more general

breakdown of the social order might be instrumental in explaining ethnic violence. In fact,

Krueger and Maleckovas (2003) work on the relationships between education, poverty and

terrorism finds that while the population shares of various religious groups matter in explain-

ing terrorism, the absence of civil liberties seems to matter more.

Easterly (2000) suggests that good institutions can mitigate the adverse effects of ethnic

rivalry. He has argued that countries with strong institutions have tended to avoid the negative

social and economic consequences of ethnic fractionalization. However, while contending that

it is institutional quality that determines the level of violence in a country as well as itseconomic wellbeing, Easterly does not distinguish between different types of institutions,

political versus economic.

Wilkinson (1986: 39) argues that there is little moral justification for violence as a means

of expressing political demands in a liberal democracy where the civil rights of minorities are

protected and the personal safety of members of minority groups is not in question. According

to him, history is on the side of James Madison (Wilkinson, 1986: 25) and, hence, conflict

between an aggrieved minority and a tyrannical majority is less likely in a liberal democracy

even if such a state is ethnically fragmented. Horowitz ([1985] 2000), on the other hand, is less

sanguine, observing that democratic elections in heterogeneous societies are frequently

nothing more than ethnic censuses. He attaches greater importance to the careful design ofpolitical institutions that take account of the particular circumstances of time and place,

including the relative numbers, relative incomes and geographic distributions of a nations

various ethnic groups. One size does not fit all. Federalism, regional autonomy, and devolving

political power away from the center can reduce conflict in some cases, but contribute to the

emergence of secession movements and civil war in others.

Frey and Luechinger (2003) propose that policies increasing the opportunity cost of terror-

ists are more effective in curbing terrorism than is increasing the material cost of terrorism

through deterrence alone.11Faria and Arce (2005) elaborate on this theme by providing a theo-

retical model where both deterrence and an increase in the opportunity cost of terrorism reduce

the popular support that is essential for recruiting potential terrorists. Collier and Hoeffler

(2004: 569) suggest that rebellion is more likely when the income foregone by rebels is low.12

In point of fact, they find that civil war is less likely if preceded by high rates of income

growth.

Important questions thus remain unanswered. Even if ethnic tensions might be a flashpoint,

and civil liberties, including a free press, the right of people peaceably to assemble and to

voice their opinions, possibly reduce the risk of civil conflict (Wilkinson, 1986; Krueger and

11 Frey and Luechinger (2003: 247) offer three specific strategies: visits to other countries, principal witnessprogrammes, and formal contact, discussion processes and access to normal political participation. Anderton andCarter (2005) present a more rigorous analysis of the tradeoffs that emphasizes the importance of underlying cross-

price elasticities, expenditure shares and income elasticities in evaluating the effectiveness of Frey and Luechingersbenevolence strategy versus a deterrence strategy.

12 Anecdotally, Collier and Hoeffler (2004) point out that during the Russian civil war the desertion rates for bothcontending armies (the Reds and the Whites) were about ten times higher during the summer than in winter theincome foregone by the peasant rebels was much higher when fields needed to be plowed and harvests gathered.


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Maleckova, 2003), the potential mitigating effects of economic liberties have not yet been

explored as thoroughly. Do institutions that allow people freedom to pursue opportunities for

improving their standards of living reduce the risk of terrorism?

2.3. From Ethnic Tensions to Transnational TerrorismEthnic divisions can trigger civil unrest, violent conflict, including full-blown civil war, and

terrorist attacks targeting out-group members or public officials that are purely local in nature,

originating and ending in the same country. Indeed, domestic terrorism outpaces transnational

terrorism worldwide by a factor of nine (Enders and Sandler, 2006: 22). There are, however,

a number of reasons why bloodthirsty ethnic tensions in one country frequently are elevated

to the international arena.

One strategy for responding to the threat of terrorism is what Lee (1988) calls the paid-

rider option. In exercising that option, a nation offers sanctuary to a foreign terrorist group

in return for assurances that the group will refrain from striking targets in its safe haven. East

Germany provided such refuge to the Red Army Faction (Baader-Meinhof Gang) and toother perpetrators of left-wing terror during the 1960s (Shughart, 2006). Lee (1988: 24) cites

Frances harboring of both Arab and Basque terrorists as well as Cypriot and Italian accom-

modation of Palestinian terrorist groups as additional cases in point.13Failed states, such as

Palestine itself, Lebanon, Afghanistan and Pakistan likewise have served as launching pads

for transnational terror.

Many transnational terrorist events are in fact rooted in ethnic conflicts in other lands.

Attacks by Algerian terrorists on Metropolitan France supply one graphic example (Horne,

[1977] 2006). September 11, 2001, also exemplifies this, as do the Madrid train bombings on

March 11, 2004, and the July 2005 terrorist attack on Londons Underground.14American

interests overwhelmingly are the targets of recent terrorist incidents. More than half of theinternational terrorist attacks in 1982, for instance, were directed against US citizens or

property on foreign soil. Those incidents occurred in 78 different countries, and 45 percent of

them took place in Western Europe (Wilkinson, 1986: 105106). Terrorists are rational

actors. They respond to counterterrorism measures that harden targets at home by redeploy-

ing their resources to strike at softer targets abroad, a strategy that undermines unilateral

responses to the terrorist threat (Sandler, 2005).

Ethnic conflicts often spill over the artificial national borders that are the legacies of colo-

nialism and post-world war political realignment (Ferguson, 2006; Shughart, 2006). For

example, the PKK, a terrorist organization with the goal of creating an independent Kurdistan

from territory located in Turkey, Iraq and Iran, has been accused by Turkey of operating out

of the northern Iraqi homeland of ethnic Kurds. More to the point, our interest is in explaining

the origins of terrorism, whether the terrorists strike at home or abroad. It is already well

13 John le Carr (2008: 5657) supplies a fictional account of the paid-rider option circa 9/11:Okay, [Hamburg] harbored a few Islamist terrorists, and a trio of them had gone off and blown up the TwinTowers and the Pentagon. So what? It was what theyd come here to do, and theyd done it. Problemsolved. Theyd struck at the heart of the Great Satan, and theyd killed themselves in the process. We weretheir lauchpadfor Christs sake, not their target! Why should weworry? So we lit candles for the poorAmericans. And weprayedfor the poor Americans. And we showed them a lot offree solidarity. Andwhen the Iraq War came along, and we good Germans stayed aloof from it, that made us even more

immune. Madrid happened. Okay. London happened. Okay. But no Berlin, no Munich, no Hamburg. Wewere too immune for anyof it. (Emphasis in original)

14 As one of many other examples, Sikh militants based in the Canadian province of British Columbia blew up anIndian airliner on June 23, 1985, in an effort to pressure the Indian government into ceding them an independentstate carved out of India.


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established that liberal states are uniquely vulnerable as targets of terrorist attacks (Wilkinson,

1986).

3. DATA AND METHODOLOGY

Theory suggests that competition for access to economic resources or political power may

trigger conflicts between different ethnic groups as they jockey for position. Most of the

existing empirical research on the relationships between ethnicity and terrorist violence

across countries tends to focus on the numbers or population proportions of ethnic groups in

a country. It is possible that scholars have failed to find an unambiguous link between ethnic

diversity and terrorism because they have not looked in the right place. Our analysis suggests

that economic institutions (or the lack thereof) are better predictors of terrorism than ethnic

tensions. In other words, models that link terrorism to ethnic fractionalization are likely

misspecified.

In what follows, we present the results of estimating panel data models that test hypotheses

relating to the interactions between ethnic tensions, civil liberties, political freedoms, and

economic institutions as determinants of transnational terrorisms countries of origin. We also

test whether these interactions differ before and after the end of the Cold War. Our dataset

comprises annual observations on 118 countries between 1982 and 1997.

We use the ITERATE (International Terrorism: Attributes of Terrorist Events) dataset

(Mickolous et al., 2003) as our source of information on terrorist incidents. The dataset is

constructed by collating information about terrorist attacks from the print media, including the

Associated Press, United Press International, Reuters, the Foreign Broadcast Information

Service and major US newspapers. One limitation of ITERATE is that it focuses on transna-

tional terrorist events, i.e., terrorist events that have consequences for more than one country.

As described in Enders and Sandler (2006: 5366), there are several problems with the datasetbeyond its lack of coverage of domestic terrorist incidents. One such problem is the difficulty

of distinguishing some terrorist acts from more ordinary criminal activity, and because terror-

ist groups sometimes do not claim responsibility for their actions, another is the problem of

attribution. Some acts of terrorism may escape notice because they are not deemed newswor-

thy. ITERATE remains to our knowledge, however, the most comprehensive dataset of its

type. Krueger and Maleckova (2003: 138), for instance, report a strong correlation between

the number of terrorist events recorded in ITERATE and an index of terrorist events derived

from US. State Department data (0.9 if India, an outlier, is dropped from the sample and 0.57

otherwise).

In any case, information from ITERATE is coded in our dependent variable, TOTALATTACKS, which tracks the annual number of transnational terrorist incidents, classified

according to the nationality of the person or group responsible for each of them. Thus, if

Albanian terrorists committed an act of transnational terror in 1983, we count the incident as

originating in Albania in 1983. If more than one nationality is represented in a terror group,

the relevant nationality is coded as that of the groups largest subset of members.

As mentioned earlier, most empirical approaches to ethnicity (see, for example, Easterly

and Levine, 1997; Krueger and Maleckova, 2003; Kurrild-Klitgaard, et al., 2006) rely on some

HerfindahlHirschman-type index of ethnic, linguistic or religious fractionalization. A nation

is more heterogeneous on such measures the larger is the number of different groups it

contains and, hence, the less likely it is that any two people belong to the same group.But the definition of what constitutes an ethnic group is problematic. Alesina et al.(2003),

for example, observe that some indices are based entirely on linguistic differences while others

are based on religious differences. To complicate matters, group identification itself may be


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fluid over both time and space.15Attempts at objective identification and coding of ethnic

groups thus introduce an element of arbitrariness. Moreover, indices of fractionalization

constructed using measures of ethnicity, language or religion lead to substantially different

results when they are entered in regressions to explain growth and government quality

(Alesina et al. 2003: 157).

Botswana supplies an apt example (Fearon, 2003: 198). That country, whose economy hasperformed reasonably well in recent years,16 has one large ethnic group the Tswana.

However, the Tswana comprise eight tribal subgroups, each of which wields considerable

political and social influence. Should one code Botswana as being ethnically homogeneous or

heterogeneous?17If Botswana is coded as ethnically homogeneous then the contention that

ethnic homogeneity enhances a countys economic performance gains support. On the other

hand, if Botswana is coded as ethnically heterogeneous, the link between ethnic homogeneity

and economic performance is weakened.

Although it, too, is based on arbitrary definitions of ethnicity, the concept of ethnic polar-

ization stands on a theoretically stronger footing than measures of ethnic, linguistic or reli-

gious fractionalization (Esteban and Ray, 1994; Montalvo and Reynal-Querol, 2005). An

ethnic polarization index is constructed by summing the (absolute values) of the distances with

respect to a set of distinguishing attributes between groups of relatively uniform size, inter-

nally homogeneous with respect to the attributes, but differing significantly on the same

attributes from other groups. The index takes a maximum at 0.5. Ethnic polarization thus is

greatest when a society is divided into two groups of equal size. So, too, is ethnic conflict

(Esteban and Ray, 1999), a result consistent with Horowitzs ([1985] 2000) claim that disputes

are more likely when an ethnic majority faces a large ethnic minority. Thus, one expects, and

finds, that ethnic polarization is a much better predictor of conflict than ethnic fractionaliza-

tion (Montalvo and Reynal-Querol, 2005).

Rather than constructing indexes of ethnic fractionalization or ethnic polarization, we rely

on the IRIS-3 file proprietary to Political Risk Services, Inc. (PRS) and published in itsInter-national Country Risk Guide(Political Risk Services, Inc. 19821997) for information on

the level of perceivedEthnic Tensionswithin a country. Based on the responses to a series of

questions framed so as to ensure consistency, the ICRGs editors rank countries every year on

a scale ranging from 0 to 6, where higher values indicate lower ethnic tensions. The ICRGs

dataset is relied on by business for risk assessment and has been used in academic research as

well (for a detailed survey and comparison with other risk indices, see Hothi and McAleer,

2004). Relative to alternative datasets it has the advantage of including a large number of

countries over a relatively long time span (Seldadyo, et al., 2007).

Keefer and Knack (2002) suggest that the PRS data capture the essence of ethnic polarization

while avoiding many of the measurement problems associated with standard population-basedmeasures of ethnic fractionalization and ethnic polarization. They in fact regress the PRSs

15 Part of the problem confronting scholars is that ethnic and linguistic fractionalization data typically are gath-ered from census returns, which are subject both to manipulation since there is an element of self-definition inethnic affiliation, and to tampering by groups that stand to gain either by inflating their own numbers or deflatingthose of others. In consequence, disputes over census results in ethnically divided societies are common (Horowitz[1985] 2000: 195). Fearon (2003: 198) nevertheless suggests using survey-based methods for obtaining informationon ethnic identities, cautioning, however, that responses may vary depending on external factors. During episodes ofpoor economic performance, for example, hitherto unimportant ethnic divisions may become relevant; the samerespondents may report less ethnic distinctiveness when the economy is doing well.

16

According to the World Banks WDI database, Botswanas GDP grew by 8.2% in 2000, and by 6.2% in 2006.17 Alesina et al.(2003) provide some additional examples of these problems. An index based on language wouldnot capture any polarization between blacks and whites in the United States. An index based on a static definition ofethnicity would not capture the five different groups into which the Oromo of Ethiopia have split as a result of exog-amy and migration.


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estimates of perceived ethnic tensions on a representative index of ethnic fractionalization

(taken from Sullivan, 1991), namely, the percentage of the population belonging to a countrys

largest ethnic group. The regression results suggest that ethnic tensions are high when a coun-

trys largest ethnic group represents about 37% of the population (Keefer and Knack, 2002:

135), but tend to fall if the largest ethnic group constitutes a larger or smaller percentage of the

population. Keefer and Knack therefore conclude that the PRS groups summary assessmentof perceived ethnic tensions is consistent with Esteban and Rays (1994) definition of ethnic

polarization.18

The IRIS-3 dataset also contains information on economic freedom specifically we use its

risk of expropriation (EXPROPRIATION) and risk of repudiation of contract by govern-

ments (REPUDIATION) indices. Both of these indices range from 0 to 10, with higher scores

indicative of greater economic freedom. According to the IRIS-3 datasets documentation, the

risk of expropriation index tracks the risk of outright confiscation and forced nationaliza-

tion of private property. Lower ratings suggest a greater likelihood of expropriation. The risk

of repudiation of contracts by government index addresses the possibility that foreign busi-

nesses, contractors, and consultants face the risk of a modification in a contract taking the form

of a repudiation, postponement, or scaling down as a result of an income drop, budget

cutbacks, indigenization pressure, a change in government, or a change in government

economic and social priorities. Lower scores imply that contract repudiation is more likely.

We create an overall index ofECONOMIC FREEDOMby averaging these two indices. We

note here that this variable captures the security of property rights rather than their allocation.

For example, Sweden and Singapore rank closely on our index of economic freedom. Keefer

and Knack (2002) observe that the governments share in spending is higher in Sweden than

in Singapore, suggesting a greater redistribution of property rights in the former country.

Keefer and Knack (2002) report a correlation coefficient of 0.90 between the ICRG property

rights index (from which we extract two components, EXPROPRIATION and REPUDIA-

TION) and another property rights index constructed from data produced by BusinessEnvironment Risk Intelligence.19

We obtain information on POLITICAL RIGHTS and CIVIL LIBERTIES from Freedom

House (19821997). These indices range in value from 1 to 7. Lower numbers indicate coun-

tries with more civil liberties and political rights. The political rights index ranks countries by

electoral process (three indicators), political pluralism and participation (four), and

functioning of government (three). The civil liberties index ranks countries on the basis of

freedom of expression and belief (four indicators), associational and organizational rights

(three), rule of law (four), and personal autonomy and individual rights (four). We create

an additional variable, POLITICAL FREEDOM, by taking the simple average of POLITICAL

RIGHTSand CIVIL LIBERTIES.We obtain the observations on GDP PER CAPITAand its annual rate of growth (GROWTH

RATE) from the World Development Indicators (WDI) database of the World Bank (1982

1997). The variables track the levels and rates of growth in per capita GDP for each country,

where GDP PER CAPTIAis measured in constant 2000 US dollars and GROWTH RATEis

the percentage change in it.ETHNIC TENSIONS, POLITICAL RIGHTS, CIVIL LIBERTIES,

ECONOMIC FREEDOM, GDP PER CAPITA and GROWTH RATE all are measured

18 Further support for Keefer and Knacks (2002) conclusion is provided by Collier and Hoeffler (2004: 581), whofind that fractionalization affects the likelihood of ethnic conflict nonlinearly: the potential for conflict at first

increases with ethnic fractionalization, but then falls as fractionalization continues to rise.19 The additive index used by Keefer and Knack (2002) includes, in addition to EXPROPRIATIONandREPUDI-ATION, the ICRGs ratings for corruption, bureaucratic quality and rule of law. Keefer and Knack report thatthese three other components are highly correlated with one another, with correlation coefficients ranging from 0.66to 0.88. They find the index itself to be highly reliable, producing a Cronbachs alpha of 0.94.


11/24


according to the country of origin of the group responsible for each terrorist incident. This

methodology allows us to investigate whether the politico-economic characteristics of a nation

may drive citizens of that nation to transnational terrorism.

We recognize that theETHNIC TENENSIONSvariable is proprietary to the PRS group and

is constructed from subjective assessments of the level of ethnic tensions in each of the countries

included in the PRSs database. Thus, one might expect an increase in terrorist activity origi-nating from a country to have an impact on perceptions of that countrys ethnic tensions. To

deal with the possibility of reverse causation running from terrorist violence to perceived ethnic

tensions, we enterETHNIC TENSIONSwith a one-year lag. The negative impacts of ethnic

fractionalization on growth (see, for example, Easterly and Levine, 1997; Easterly, 2000) and

of ethnic polarization on growth (Keefer and Knack, 2002; Basuchoudhary et al., 2007) are

well-established. Thus, last years ethnic tensions may reduce this years GDP by affecting last

years growth rate. We lag the GDP PER CAPITAvariable to avoid this complication as well.20

In fact, we enter all of our explanatory variables with a one-year lag. Lagging of course reduces

degrees of freedom, but can be justified by recognizing that it takes time to plan and execute

a terrorist attack.21

We estimate fixed-effects, negative-binomial regression models on our panel dataset. We

use this approach primarily because most countries in our sample do not export terrorism

and, hence, there are many observations for which TOTAL ATTACKS = 0. Furthermore,

preliminary tests suggested over-dispersion of the data, leading us to reject the alternative

Poisson model. There is considerable debate over the appropriateness of fixed versus random

effects for nonlinear panel data models (Cameron and Trivedi, 2005). Our dataset consists of

most countries in the world. It would be hard to argue that the individual country effects are

random, thereby making the choice of fixed effects easier. We nevertheless report some

selected results from random effects regressions (see Table XIII(a) below) in order to show

that the estimates are not sensitive to the choice of panel data estimating technique.

The treatment of time in mixed panel data and count models is problematic. Figure 1 plotsthe cross-sectional means of our key explanatory variables over time. ETHNIC TENSIONS,

EXPROPRIATION and REPUDIATION exhibit upward trends beginning in 1990, which

corresponds to the ending of the Cold War, while the other variables do not. We enter all right-

hand side variables with a one-year lag and estimate separate regressions for pre- and post-

1990 subsamples of our dataset as ways of controlling for time-wise effects.FIGURE1 Countrymeansforvariablesplottedwithrespecttotime.

In fact, the plots of cross-sectional means shown in Figure 1 might leave us open to the crit-

icism that there is too little variation in some of our explanatory variables. However, the results

of ANOVAs carried out in Tables I through V suggest that our dataset exhibits within-country

variation. Notice that the MSEs for all the variables reported are positive numbers. Since the

MSE for any variable estimates the variance within each treatment or category weightedacross treatments, an MSE other than zero suggests within-treatment variance. The actual

numbers reported are small but recall that the indices we use vary only between 0 and 6 for

ETHNIC TENSIONSandECONOMIC FREEDOMand between and 1 and 7 for POLITICAL

FREEDOM. Of course, the F-statistics reveal significant between-country variation for all of

the explanatory variables. The simple average of the within-country variances for each vari-

able reported in Table VI also suggest the existence of within-country (over time) variation.

20 GDP PER CAPITAandETHNIC TENSIONSare uncorrelated contemporaneously, although as expected fromstudies such as that of Easterly (2000), last periods ETHNIC TENSIONSis highly correlated with current GDP PER

CAPITA.21 Terrorist acts in the current year are even less likely to influence ethnic tensions and property rights two yearsearlier. We therefore ran all variants of the regressions reported below entering two lags of the explanatory variablesrather than one and found that the results were unchanged. Given that our estimates seem to be robust to lag struc-ture, we formally report those obtained with the right-hand side variables lagged one period.


12/24


FIGURE 1 Country means for variables plotted with respect to time.

TABLE I ANOVA: CIVIL LIBERTIES, categorized by country

Source of Variation Df SSE MSE

Between 118 5509.904 46.694

Within 1739 1223.57 0.7

Total 1857 6733.475 3.63

F-Statistic: 66.364***Notes: Asterisks denote significance at the 1% (***), 5% (**), and 10% (*) levels.

TABLE II ANOVA: POLITICAL RIGHTS, categorized by country


Between 118 7209.573 61.09

Within 1739 1740.98 1.001

Total 1857 8950.55 4.82

F-Statistic: 61.03***Notes: See Table I.


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4. RESULTS

Our results suggest that heightened ethnic tensions in a country generally increase the number

of transnational terrorist attacks by citizens of that country. Poorer countries also spawn more

terrorists. On the other hand, greater economic freedom reduces the odds that terrorism willarise from either of those causes. In sharp contrast to the studies of Krueger and Maleckova

(2003) and Li (2005), we find, over the full 19821997 sample, that an absence of political

rights and civil liberties in a country has no impact on the number of terrorist attacks

TABLE III ANOVA:EXPROPRIATION, categorized by country


Between 118 4529.57 38.38

Within 1625 4100.91 2.52

Total 1743 8630.48 4.95


TABLE V ANOVA:ETHNIC TENSIONS, categorized by country


Between 118 3215.372 27.2489

Within 1663 1116.92 0.67

Total 1781 4332.29 2.43

F-Statistic: 40.57***Notes: See Table I

TABLE IV ANOVA:REPUDIATION, categorized by country


Between 118 5535.242 46.9

Within 1625 3318.25 2.04

Total 1743 8848.49 2.04


TABLE VI Standard Deviations within and between Countries

Variable

ETHNIC TENSIONS Overall 1.560

Between 1.330

Within 0.792

POLITICAL FREEDOM Overall 2.009

Between 1.830

Within 0.828

ECONOMIC FREEDOM Overall 2.166

Between 1.692

Within 1.389


14/24


perpetrated by citizens of that country. We do find, however, that liberal political institutions

have become more important in reducing the number of terrorist attacks originating from a

country since the end of the Cold War. This post-Cold War effect holds for ethnic tensions as

well unless mitigated by economic opportunity.

Tables VII through X present different views of our raw data. Summary statistics for all

variables are reported in Table XI. Figure 2 plots average ethnic tensions, by country, over the16 years of our data and relates it to the number of terrorist attacks from each country. Tables

XII though XIV report our estimated models.

TABLE VII Number of Transnational Terrorist Attacks and Average Ethnic Tensions, by Country, 19821997

Country Code Country Number Total Attacks Average Ethnic Tension

Sudan SDN 163 34 0.48

Sri Lanka LKA 112 31 0.96

Congo, Dem. Rep. ZAR 203 0 0.99

Israel ISR 93 17 1.52

India IND 88 49 1.53

Guyana GUY 80 1 1.81

Lebanon LBN 107 250 1.81

Guatemala GTM 78 39 1.86

Pakistan PAK 146 28 2.01

Angola AGO 4 39 2.04

South Africa ZAF 202 0 2.08

Peru PER 148 157 2.14

Kenya KEN 99 1 2.18

Malaysia MYS 135 1 2.28

Madagascar MDG 121 0 2.29

Togo TGO 180 0 2.31

Turkey TUR 188 130 2.33

Uganda UGA 190 11 2.45

Russian Federation RUS 160 32 2.47

Indonesia IDN 86 6 2.48

United Arab Emirates ARE 7 0 2.52

Cameroon CMR 40 0 2.54

Trinidad and Tobago TTO 186 1 2.55

Papua New Guinea PNG 151 4 2.67

Philippines PHL 149 161 2.74

Suriname SUR 172 5 2.80

Nigeria NGA 139 4 2.83

Ethiopia ETH 61 34 2.84

Zimbabwe ZWE 205 8 2.84

Tanzania TZA 189 1 2.92

Bangladesh BGD 19 2 2.93

Guinea GIN 71 2 2.94

Bolivia BOL 27 13 2.94

Guinea-Bissau GNB 73 0 3.00

Kuwait KWT 105 6 3.01

Iran, Islamic Republic IRN 90 266 3.13

Bahrain BHR 21 9 3.14

Niger NER 138 6 3.18

Mozambique MOZ 131 55 3.34Cote dlvoire CIV 39 0 3.38

Congo, Republic COG 41 1 3.38


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TABLE VII (Continued)


Senegal SEN 164 0 3.52

Malawi MWI 134 1 3.53

Haiti HTI 84 15 3.56

Sierra Leone SLE 167 11 3.56

Gabon GAB 67 4 3.61

Zambia ZMB 204 0 3.64

Saudi Arabia SAU 162 13 3.67

Mali MLI 126 2 3.67

Canada CAN 34 5 3.69

Belgium BEL 16 0 3.70

Ghana GHA 70 0 3.76

Morocco MAR 118 0 3.79

Algeria DZA 55 63 3.81

Albania ALB 5 6 3.82

Namibia NAM 136 1 3.84

Dominican Republic DOM 54 4 3.84

Ecuador ECU 56 9 3.84

Spain ESP 59 152 3.85

Gambia, The GMB 72 0 3.86

Botswana BWA 32 0 3.87

Romania ROM 159 4 3.90

Bulgaria BGR 20 1 3.94

Jordan JOR 96 29 3.94

Burkina Faso BFA 18 2 4.00

Brunei BRN 30 0 4.00

China CHN 38 0 4.09Egypt, Arab Republic EGY 57 75 4.13

Thailand THA 181 8 4.16

Oman OMN 145 0 4.27

Yemen, Republic YEM 200 0 4.30

Bahamas, The BHS 22 0 4.31

Malta MLT 127 0 4.32

Libya LBY 109 51 4.38

Mongolia MNG 129 0 4.38

Jamaica JAM 95 0 4.51

Nicaragua NIC 140 16 4.54

Qatar QAT 158 0 4.59Vietnam VNM 197 1 4.66

Syrian Arab Republic SYR 178 0 4.68

France FRA 64 49 4.69

United Kingdom GBR 68 6 4.76

Ireland IRL 89 1 4.86

Slovak Republic SVK 173 1 4.96

Honduras HND 82 33 5.00

Hungary HUN 85 0 5.00

Mexico MEX 123 5 5.00

Panama PAN 147 16 5.00

Paraguay PRY 156 0 5.00Luxembourg LUX 115 17 5.01

Tunisia TUN 187 6 5.01

Brazil BRA 28 5 5.03


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FIGURE2 Averageethnictensionsandtotaltransnationalterroristattacksby country,19821997.

Notice that in Figure 2 the spikes in terrorist activity tend to be clustered around numbers

indicating lower levels of ethnic tensions. This suggests an inverse relation between the two.

However, a closer look at the data, say in Table VII, shows that the Democratic Republic of

the Congo a hotbed of ethnic tensions has no reported transnational terrorist incidents. On

the other hand, ethnic-tension-free Greece had 110 transnational terrorist events between

1982 and 1997. This first pass at the numbers suggests that a correlation between ethnic

tensions and terrorism is plausible but that it may be confounded by other factors. This is

what we set out to explore. Notice further, in Table X, that there is a marked drop in the yearly

average count of terrorist attacks between the subsamples of our data that coincide with the

Cold War and after. This supports the conjecture that the end of the Cold War was some kind

TABLE VII (Continued)


Venezuela, RB VEN 196 7 5.06

United States USA 193 45 5.12

New Zealand NZL 144 0 5.22

Singapore SGP 165 2 5.23

Cuba CUB 46 19 5.27

Australia AUS 12 3 5.30

Poland POL 152 6 5.32

Portugal PRT 155 39 5.34

El Salvador SLV 168 68 5.36

Italy ITA 94 33 5.38

Chile CHL 37 57 5.39

Korea, Rep. KOR 104 0 5.48

Colombia COL 42 215 5.71

Austria AUT 13 5 5.71

Switzerland CHE 35 3 5.74

Norway NOR 142 1 5.86

Sweden SWE 175 5 5.86

Czech Republic CZE 49 0 5.90

Argentina ARG 8 18 5.91

Costa Rica CRI 45 6 6.00

Denmark DNK 53 3 6.00

Finland FIN 62 0 6.00

Greece GRC 75 110 6.00

Iceland ISL 92 1 6.00

Japan JPN 97 40 6.00

Netherlands NLD 141 5 6.00

Uruguay URV 192 0 6.00

Table VIII Frequency Distribution of Countries by Average Ethnic Tensions

Number of Countries Average Ethnic Tensions (19821997)

3 01

5 12

25 23

31 34

20 45

35 56


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of a watershed event for terrorism. In any event, there is a natural break in our dataset that isworthy of further investigation.

In model 1 of Table XII we find that low levels of ethnic tensions and high levels of

income significantly reduce the numbers of terrorist attacks originating in a country. This

result holds over the full sample period, 19821997. Surprisingly, and in sharp contrast to

the work of Krueger and Maleckova (2003), the one-period lags of POLITICAL RIGHTS

and CIVIL LIBERTIEShave no explanatory power (see models 2 and 3 in Table XII). Our

estimates are, however, consistent with Montalvo and Reynal-Querols (2005) finding that

the level of democracy is not significantly related to the incidence of civil wars. It is worth

noting that the failure to reproduce Krueger and Maleckovas (2003) results might stem

from the fact that our dataset covers a longer time period than the six years of data (19972002) included in theirs, suggesting that Krueger and Maleckovas finding that political

rights and civil liberties reduce terrorism cannot be generalized. This in turn may reflect a

wider point made in the Krueger and Maleckova paper that institutions are what really

TABLE XI Summary Statistics

Variable Obs Mean Std. Dev Min Max

GDP PER CAPITA 2630 5103.455 7459.11 56.52 39368.63

ETHNIC TENSIONS 1782 3.91 1.56 0 6

POLITICAL FREEDOM 1858 3.82 2.01 1 7

ECONOMIC FREEDOM 1744 6.85 2.17 1.5 10

Table IX Number of Transnational Terrorist Acts by Major World Region, 19821997

World Region Terrorist Acts

North America 50

Central America and Caribbean 158

South America 551

Eastern Europe 12

Middle East and North Africa 852

Sub-Saharan Africa 280

Asia 360

Oceania 8

Western Europe 436

Table X Number of Transnational Terrorist Attacks Before and After the Cold War

Year Total Attacks Year Total Attacks

1982 186 1990 190

1983 198 1991 211

1984 230 1992 109

1985 259 1993 98

1986 237 1994 141

1987 254 1995 125

1988 169 1996 91

1989 146 1997 63

Cold War Average 209.9 Post-Cold War Average 128.5


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matter. However, as we show below, these institutions are likely to be economic rather than

political.

When we change the specification of models 1 through 3 in Table XII by adding our index

ofECONOMIC FREEDOMto models 4 and 6 in Table XIII, we find thatETHNIC TENSIONS

loses its significance. POLITICAL FREEDOM(the simple average of POLITICAL RIGHTS

and CIVIL LIBERTIES) is insignificant in these new specifications, but institutions that

enhance economic freedom in a country evidently mitigate the effect of ethnic tensions on the

number of terrorist acts originating from that country. As defined previously, ECONOMIC

FREEDOMmeasures both the risk of outright governmental confiscation of property as well

as the risk that private contracts can be altered by events beyond the control of individuals, butwithin the control of governments. It measures the degree of economic opportunity available

to individuals and the results therefore suggest that terrorism is less likely to originate in

countries where people have greater freedom to improve their lots in life. Sri Lankan nationals,

FIGURE 2 Average ethnic tensions and total transnational terrorist attacks by country, 19821997.

TABLE XII Do Ethnic Tensions Explain Terrorism?

DEPENDENT VARIABLE: TOTAL ATTACKS MODEL 1 MODEL 2 MODEL 3

ETHNIC TENSIONS(1) 0.0816**

(0.04)

0.0770*

(0.04)

0.0771*

(0.04)POLITICAL RIGHTS(1) 0.024

(0.04)0.015(0.05)

CIVIL LIBERTIES(1) 0.016(0.07)

GDP PER CAPITA(1) 0.000027***(0.0000102)

0.0000242**(0.00001)

0.0000235**(0.0000112)

Log Likelihood 1392.34 1392.123 1392.0945

Wald Statistic 16.29*** 16.8*** 16.86***

Notes: Standard errors in parentheses; asterisks denote significance at the 1% (***), 5%(**), and 10%(*) levels. We do not report theconstant term.


19/24


for example, are more likely to resort to terrorist acts stemming from ethnic tensions than are

Canadians.22

In this context, we note that GDP PER CAPITAis robustly insignificant in explaining the

number of terrorist attacks when economic institutions are taken into account. This result is

consistent with Lerners (1958) seminal work on the Middle East and other later studies (see,

for example, Angrist 1995) suggesting that it is the lack of economic opportunity and not over-

all poverty that leads to extremism. Interestingly enough, Krueger and Maleckova (2003)

make a point that is similar in spirit if not substance. Observing that poor countries typically

also have less-than-stellar democratic credentials, they argue that poverty explains terrorism

22 The case of Canadas home-grown jihadis is well-known. On June 23, 2006, 18 mostly Muslim Canadian menwere arrested in a Toronto suburb on charges of plotting to bomb the Canadian Parliament and storm the offices ofthe Canadian Broadcasting Corporation.

TABLE XIII(a) Do Economic Institutions Matter? (Random Effects)

DEPENDENT VARIABLE: TOTAL ATTACKS MODEL 6.1 MODEL 7.1 MODEL 8.1

ETHNIC TENSIONS(1) 0.0263(0.03)

0.0471(0.04)

0.0422(0.04)

GDP PER CAPITA(1) 2.44e06(0.00001)

POLITICAL FREEDOM(1) 0.0015

(0.03)

0.0144

(0.034)

0.0140

(0.035)ECONOMIC FREEDOM(1) 0.0594**

(0.02)0.0635***

(0.02)0.0621***

(0.025)

Log(GDP PER CAPITA) 0.04(0.06)

0.0375(0.05)

GROWTH RATE 0.0025(0.006)

Log Likelihood 1187.35 1178.69 1173.08

Wald Statistic 12.62*** 14.75*** 14.10***

Notes: See Table XII.

TABLE XIII Do Economic Institutions Matter? (Fixed Effects)

DEPENDENT VARIABLE:TOTAL ATTACKS MODEL 4 MODEL 5 MODEL 6 MODEL 7 MODEL 8


0.7709**(0.040)

0.0169(0.045)

0.0443(0.044)

0.0398(0.045)

GDP PER CAPITA(

1)

0.0000181(0.0000122)

0.0000235**(0.0000112)

0.0000182

(0.0000121)

POLITICAL FREEDOM(1) 0.0307(0.044)

0.0227(0.045)

0.0091(0.041)

0.0093(0.04)

ECONOMIC FREEDOM(1) 0.098***(0.03)

0.098***(0.03)

0.059**(0.03)

0.0575**(0.03)

Log(GDP PER CAPITA) 0.0632(0.089)

0.0654(0.08)

GROWTH RATE 0.0024(0.006)

Log Likelihood 1341.20 1392.09 1341.20 895.1 890.44

Wald Statistic 30.64*** 16.86*** 30.62*** 15.34*** 15.01***



20/24


only when one does not control for political rights and civil liberties. According to them, civil

liberties override GDPs explanatory power when both variables are included. The results of

estimating models 4 through 6 in Table XIII suggest that the connection between a countrys

wealth or lack thereof and its likelihood of spawning terrorism is picking up the effects of

the absence of economic liberties rather than of political freedoms.

Consistent with the initial findings reported in Table XII, holding free elections and having

a functioning government does not have any effect on the likelihood of terrorist attacks origi-

nating from a country. In addition, terrorist attacks are as likely to be launched when the citi-

zens of a country can assemble freely, express their views freely, are subject to the rule of law,

and not subject to random arrests as when such rights are restrained. This result may be driven

by the very high correlation (r2>0.90) between POLITICAL RIGHTSand CIVIL LIBERTIES.

In order to explore this possibility further, POLITICAL FREEDOM, again lagged one year, isentered in model specifications 5 and 6 in Table XIII. The results are consistent with our

earlier conclusion that illiberal political institutions do not explain terrorist events, at least in

our dataset.

Our analyses also suggest that it would be incorrect to conclude that POLITICAL

FREEDOMis tracking the variation inECONOMIC FREEDOM, or vice versa. POLITICAL

FREEDOMdoes not explain terrorism either when it enters withECONOMIC FREEDOMor

without. This finding shows transnational terrorism to be a phenomenon with economic rather

than political roots. Policies aimed at reducing the threat of terrorism that elevate political

considerations over economic considerations may therefore be ineffective. Moreover, in

models 1, 2, and 3 (see Table XII) and 5 (see Table XIII), ethnic tensions in a country continueto explain the number of terrorist attacks originating from that country, even after controlling

for political rights. Political solutions to terrorism arising from ethnic tensions therefore may

be unworkable since the root cause of terrorism seems to lie in poor economic institutions. The

empirical evidence thus is consistent with the hypothesis that ethnic conflict is driven by

competition for economic resources, and that conflict may spill over to terrorism in the

absence of institutional mechanisms that promote the economic opportunities of individuals.23

In other words, the public perception that ethnicity (along with political institutions and wealth

levels) matters in promoting terrorism is probably incorrect. Ethnic tensions are more an

23 This argument is not sensitive to the choice of panel estimation techniques. A random-effects approach onModel 6 (see Model 6.1 in Table XIII(a)) shows that ECONOMIC FREEDOMis the only explanatory variable witha statistically significant impact on TOTAL ATTACKS.

TABLE XIV Institutions During and After the Cold War

DEPENDENT VARIABLE: TOTAL ATTACKSMODEL 9(PRE-1990)

MODEL 10(PRE-1990)

MODEL 11(POST-1989)

MODEL 12(POST-1989)


0.045(0.07)

0.1116*(0.06)

0.034(0.07)

GDP PER CAPITA(

1)

0.0000127(0.0000165)

0.0000006

(0.0000198)

0.000005(0.000023)

0.00000005(0.000023)

POLITICAL FREEDOM(1) 0.013(0.06)

0.02(0.067)

0.162**(0.08)

0.17**(0.082)

ECONOMIC FREEDOM(1) 0.11164**(0.055)

0.09*(0.05)

Log Likelihood 610.8 568.79 562.173 560.619

Wald Statistic 0.62 6.16 12.88*** 16.14***



21/24


expression of underlying problems with economic institutions rather than a proximate cause

of terrorist attacks.

Krueger and Laitin (2008: 168, Table 5.6) extend the arguments in Krueger and Maleckova

(2003) by running negative binomial regressions for the period 19972002. Rather than focus-

ing on ethnic tensions directly, however, they proxy religious fractionalization by entering the

proportions of Hindus, Muslims, and Buddhists in a country to explain the number of interna-tional terrorist events originating there. Furthermore, they enter the log of population, log of

GDP per capita, and GDP growth as controls in their regression equation. They conclude that

a countrys population shares of three non-Christian religions have no impact on terrorist

activity originating from that country. This is consistent with our position that a population

divided along ethnic lines does not necessarily lead to more terrorism. However, Krueger and

Laitins finding that terrorism is more likely to originate in countries lacking civil liberties

seems to be caused by an omitted variable.

We run a version of Krueger and Laitins regression, controlling for the log of GDP per

capita and per capita growth rates as they do (we implicitly control for population by including

the per capita terms), but also entering our other explanatory variables. These results are

reported in models 7 and 8 in Table XIII (and models 7.1 and 8.1 in Table XIII(a) for the

random effects approach). Our results underlining the importance of economic institutions

hold up in this alternative specification.

Models 9 through 12 in Table XIV suggest that the factors explaining terrorism in the bipo-

lar world of the Cold War era differed considerably from those at work in a unipolar post-Cold

War World. We take the fall of the Berlin Wall in 1989 as the watershed event marking the

formal end of the standoff between the United States and the Soviet Union. We break our

sample into two periods: information for all countries until the beginning of 1990 is relevant

to the Cold War period and information for all countries from 1990 to 1997 is relevant to the

post-Cold War period.

We find thatECONOMIC FREEDOMis a negative and significant determinant of terroristactivity originating in a country throughout our sample. In the post-Cold War period, however,

bothECONOMIC FREEDOMand POLITICAL FREEDOMenter significantly in explaining

the number of terrorist attacks originating from a country. POLITICAL FREEDOM is not

significant during the Cold War, while ECONOMIC FREEDOM is. Indeed, ECONOMIC

FREEDOMis the only variable that enters significantly in our Cold War subsample. These

findings suggest, first, that the ethnic-tensions-mitigating effects of liberal economic institu-

tions continue to be robust in the post-Cold War period. That result in fact also holds before

1989, a time when ethnic tensions presumably were kept in check by Cold War priorities,

including the heavy Soviet hand in Central Asia. Second, the results suggest that, consistent

with our findings for the full sample, political rights and civil liberties are not significant inexplaining transnational terrorism prior to the end of the Cold War. They become so after-

wards, though. Indeed, it may be this post-Cold War effect that prompted Krueger and

Maleckova (2003) to emphasize the importance of liberal political institutions in lessening

ethnic violence.

Comparing and contrasting the estimated coefficients onETHNIC TENSIONSin models 11

and 12 with theECONOMIC FREEDOMvariable in model 12 nevertheless shows that ethnic

tensions continue to create terrorist trouble even after controlling for political rights. However,

liberal economic institutions that lower the risks of property being confiscated and of contracts

being repudiated still reduce significantly the number of terrorist attacks originating from a

country. Thus, although having few political rights and civil liberties may foster terrorism inan ethnically polarized society, the threat that polarization will lead to violence can be lessened

by economic opportunity. Thus, no attempt at reducing ethnic tensions that finds expression

in terrorist violence can be successful if it ignores the importance of economic institutions.


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5. SUMMARY AND CONCLUSIONS

The role of ethnic identity in fomenting violence between groups has been the subject of

vigorous academic debate; the importance of the possible connections between ethnicity and

a particular form of violence transnational terrorism hardly requires emphasis. Exploiting

a panel dataset comprising 118 countries over 16 years (19821997), we explore alternativeexplanations for terrorisms countries of origin. This is a departure from much of the existing

literature, which focuses on the targets of transnational terrorism. Our empirical analysis

also differs from prior work in the area insofar as it employs a direct measure of ethnic

tensions rather than relying on measures of ethnic diversity or of linguistic or religious frac-

tionalization based on the population shares of such groups. Last, in addition to asking

whether the terrorism-producing effects of ethnic tensions can be mitigated by good politi-

cal institutions, as some scholars recently have begun arguing, we put economic institutions

to the test.

Our key findings are, first, that terrorism is more likely to originate in ethnically tense

nation-states. Second, the connection between ethnic tension and terrorism persists even after

controlling for political rights and civil liberties. Liberal political institutions indeed are asso-

ciated with fewer transnational terrorist acts in the period after the Cold War. But this result is

not robust prior to 1990. New rounds of terrorist violence seem to have been unleashed in

countries where the heavy hand of Soviet control was not quickly displaced by freer institu-

tions of governance. Third, and what is most important, we find that economic freedoms lessen

the tendency for ethnic tensions to spawn transnational terrorism over the entire sample, both

before and after the fall of the Berlin Wall. In other words, the proximate cause of terrorist

attacks is a lack of good economic institutions rather than ethnic differences.

In sum, institutions that promote economic liberty are more effective in reducing terrorist

violence in ethnically tense societies than purely political institutions that protect individual

rights. Multiethnic societies carved from the carcasses of the Ottoman and Hapsburg Empiresby Britain and France at the end of First World War or cobbled together out of the debris left

by the Soviet Unions collapse are not doomed to endless cycles of ethnic tension and

violence. The clash of civilizations and cultures rooted in ethnic identity is not inevitable. Our

evidence suggests that stemming the tide of ethnic conflict in the 21st century is more a matter

of property rights than of political rights. We do not say that democracy and civil liberties do

not matter. In fact, we emphasized their importance in the post-Cold War era above. However,

the first-best policy option for breaking the link between ethnic tensions and terrorist violence

lies in liberal economic institutions. Diverse peoples secure in their property rights, free to

start businesses and to pursue other economic opportunities are more likely to coexist peace-

fully than are groups engaged in playing zero-sum games.

ACKNOWLEDGMENT

The authors benefitted from the comments and suggestions of our discussant, Lisa Chauvet,

and other participants at a session of the First World Congress of the Public Choice Societies

in Amsterdam, including Art Carden, Roger Congleton, Bernie Grofman and Erich Weede.

Scott Beaulier, who discussed our paper at the 2007 meetings of the Public Choice Society,

added considerable value to the paper, as did audience members Todd Nesbit, Russ Sobel and

Sasha Tomic. The thoughtful written comments of Dann Arce, John Warner and the journalstwo anonymous referees were especially helpful in sharpening our arguments and analysis. As

is customary, though, the authors accept full responsibility for any remaining errors of

omission or commission.


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