Determinants of Third Parties’ Intervention and Alignment Choices in Ongoing Conflicts, 1946–2001

Determinants of Third Parties’ Interventionand Alignment Choices in Ongoing

Conflicts, 1946–2001

Renato Corbetta

University of Alabama at Birmingham

The decision to intervene in ongoing conflicts is one of the most diffi-cult foreign policy choices states often face. Yet, studies of third parties’joining behavior have been rare and limited in several respects. First,they have explored only a subset of all interventions—military interven-tions. Second, they have concentrated on security-based determinants ofintervention—power and alliance considerations—while underplayingother possible motivations behind the decision to intervene. Third, theyhave explored intervention and alignment choices as separate issues.This paper proposes a model of joining behavior that includes bothsecurity considerations and homophilous network ties as determinantsof third parties’ intervention and alignment choices. The model is testedon military and nonmilitary interventions data from Corbetta and Dixon(2005) for the 1946–2001 period. The results from a boolean logit esti-mation indicate that (1) the intervention decision is the result of bothsecurity-driven, pragmatic considerations and homophily between join-ers and disputants; and (2) opposition to a party in a conflict is asimportant as a third party’s social proximity to the side being supported.

When in April 1982 Argentine troops occupied the Falkland Islands, whichBritain had controlled since the 1830s, US President Ronald Reagan found him-self in an uneasy position (Weisburd 1997). At the height of the Cold War, thePresident could not afford to let a severe conflict between two countries tradition-ally close to the United States develop in the United States’ own backyard.Attempting to preserve friendship and alliance ties in South America and Europe,Reagan first pursued a diplomatic solution. However, Great Britain and Argentinasternly rejected all of the United States’ mediation efforts. By the end of April,British warships were en route toward the Falklands, and a military confrontationseemed inevitable. President Reagan faced a tough decision. Could the UnitedStates afford to remain neutral in such a conflict? And if it chose to intervene,with which side in the conflict was the United States to align? Ultimately, Presi-dent Reagan leaned toward Great Britain. On April 30, 1982, the United Statesceased any mediation effort, imposed economic sanctions on Argentina, andbegan providing material support for the British. British troops landed on May21, 1982, and they recaptured the islands in slightly more than three weeks withlimited casualties. The US support for Great Britain continued until Argentinetroops officially surrendered on June 14, 1982 (Weisburd 1997:53–54).

Author’s note: The author thanks Bill Dixon, Gary Goertz, Brad Jones, Charles Boehmer, Andrew Long, ResatBayer, Bear Braumoeller, Riccardo Prina, and two anonymous reviewers for their helpful comments.

� 2010 International Studies Association

Foreign Policy Analysis (2010) 6, 61–85

Latin American and European decision makers found themselves in a similarposition. Like the United States, some European and Latin American states alsohad incentives to side with either the United Kingdom or Argentina. Somemembers of the (then) European Community states chose to throw their weightbehind Great Britain and imposed economic sanctions on Argentina. Some LatinAmerican countries, instead, showed greater sympathy for the invasion andofficially expressed support for Argentina, although none of them backed uptheir expressions of solidarity with actions.

What factors led President Reagan to favor Great Britain over Argentina?What accounts for the difference in behavior exhibited by the United States,the EC states, and some Latin American countries? Why did some stateschoose to intervene in the first place, and how did they choose which side totake? Questions related to third-party states’ choices during ongoing conflictsare relevant to international politics theory and foreign policy practice. Yet,the issue of third states’ intervention and alignment choices has remainedunder-explored in International Relations. Most theories look at joining behav-ior simply as a byproduct of power considerations or alignment choices madebefore a conflict. Furthermore, the few existing studies on the subject analyzeintervention and alignment decisions as independent, separate outcomes.Focusing exclusively on military interventions, they neglect the full range ofoptions available to third-party states.

This paper attempts to fill some of the gaps in this research area by offering amodel of third-party interventions that simultaneously accounts for third-partystates’ decision to join in an ongoing conflict and their alignment choices.Beginning with the well-known opportunity and willingness framework (Most andStarr 1989), it proposes that third parties’ decisions are a function of their abilityto intervene in an ongoing conflict, their pragmatic interests in the conflict, andtheir homophily toward the disputants. Hypotheses derived from the model aretested empirically with data on military and nonmilitary interventions in inter-state disputes for the 1946–2001 period.

Existing Research on Joining Behavior

International relations scholars have rarely addressed joining behavior as a directobject of study. Rather, they have often approached it indirectly in the contextof research on conflict initiation. Two streams of theory in particular have dealtwith this topic—rational choice theory and realism. Rational choice models ofconflict initiation suggest that states choose their opponents carefully and rarelystart hostilities against another state if their chances of winning a one-on-oneconflict are low (Bueno de Mesquita 1980, 1981). However, states operate in anuncertain international environment, and one such source of uncertainty comesfrom the behavior of third-party states. Conflict initiators try to minimize the pos-sibility that third states will join in on the side of their opponent. Bueno deMesquita (1981), Reed (2000), Werner (2000a) and others show that in factconflict initiators effectively select themselves into conflicts that tend to remainone-on-one affairs. Expectations about third parties’ intervention behavior shapecrisis bargaining dynamics and the subsequent behavior of a conflict’s originators(Smith 1995, 1996). Werner (2000a) shows that conflict originators adjust theirdemands in order to prevent interventions by third states. Nonetheless, approxi-mately 16 percent of all interstate disputes between 1816 and 2001 have experi-enced military third-party intervention.1

1About 362 out of 2323 disputes, according to Militarized Interstate Disputes data (Ghosn, Palmer, and Bremer2004). For a definition of Militarized Interstate Disputes, see Jones, Bremer, and Singer (1996), Ghosn et al.(2004).

62 Intervention in Ongoing Conflicts

Concern with third parties’ is inherent to realist scholarship because of itsemphasis on balancing dynamics. Realists have often raised contradictoryhypotheses about balance-of-power before and during a conflict (Waltz 1979;Morgenthau 1985), balance of threat (Walt 1987), or bandwagoning (Schweller1994). According to realist approaches, states form pre-war alliances to countermore powerful and more threatening adversaries. When stronger and ⁄ or morethreatening powers attack weaker states, third parties are expected to enter anongoing conflict on the weaker side in order to preserve the balance of power.Some revisionist states and some weaker states, however, may enter as third par-ties on the stronger side when ‘‘spoils of conquest’’ are available or when theirparticipation may appease a stronger, threatening partner (Schweller 1994).Empirical evidence about third parties’ balancing or bandwagoning tendencies ismixed (Altfeld and Bueno de Mesquita 1979; Werner and Lemke 1997; Gartzkeand Gleditsch 2003).

Scholars of conflict processes have empirically tested realist claims about pre-conflict alignment tendencies and actual joining behavior during conflict. Tworesearch programs have been particularly involved: studies on the reliability ofalliances and studies on the spatial diffusion of conflict. Debates about the reli-ability of alliance agreements (Smith 1996; Leeds, McLaughlin Mitchell, andLong 2000; Leeds 2003a,b, 2005; Gartzke and Gleditsch 2004) and the mecha-nisms of conflict diffusion in space (Most and Starr 1980, 1989; Houweling andSiccama 1985; Most, Starr, and Siverson 1989; Kadera 1998; Gleditsch 2002a;Hammarstrom and Heldt 2002; Starr 2005) have shown that both preconflictcommitments and spatial factors can motivate the decision to join. Overall, ‘‘alli-ances increase the probability of third-party intervention in wars’’ (Smith1996:33). The specific commitments written into alliance treaties matter a greatdeal in determining their reliability (Leeds et al. 2000). Expectations about thereliability of alliance ties affect the likelihood that allies will resist aggression,thereby influencing the chances of third-party intervention (Smith 1995, 1996).Studies on the spatial diffusion of conflict, instead, have highlighted how geo-graphical proximity increases the opportunity for a third party to becomeinvolved in an ongoing conflict. The highest likelihood of intervention occurs incases of direct geographical contiguity to a conflict.

A vast body of scholarship on deterrence has addressed, somewhat indirectly,the topic of joining behavior as an expression of (general or immediate)extended deterrence (see, for instance, Huth and Russett 1984; Huth 1988a,b).From this perspective, credible third-party threats are essential to successfuldeterrence, while intervention results from failed deterrence efforts. Analystspursuing a bargaining approach to conflict have built on these foundations toexplore the strategic selection biases behind intervention in conflict (see, forexample, Smith 1996; Fearon 2002). However, scholars of crisis bargaining havefocused more on the failures and successes of deterrence than on the empiricalanalysis of whether third parties do actually intervene after deterrence breaksdown. As Quackenbush (2006) argues, deterrence studies have also tended tofocus on the deterrence game between a third-party ‘‘defender’’ and a conflictinitiator ‘‘target,’’ while excluding from the picture the ‘‘protege.’’ In addition,they have overlooked the issue of the origins of third parties’ preferences foreither disputant by restricting their focus to the presence or absence of allianceties.

Few studies have explored joining behavior as their primary research question.These studies cover a variety of conflicts, from crises to full scale wars, and sharetwo major findings. First, third parties’ material capabilities almost invariablypredict intervention. Second, various ties between joiners and disputants play acrucial role in shaping the decision to intervene. Such ties can be formallyexpressed by alliance agreements, or they can be simply pragmatic—as expressed

63Renato Corbetta

by similarities in foreign policy agendas. In a seminal study on the topic,Yamamoto and Bremer (1980) find that major power states have a remarkablepropensity to drag one another into ongoing wars. Altfeld and Bueno de Mesqui-ta (1979) offer a formal model of the decision to intervene in ongoing wars andprovided empirical support for the hypothesis that joiners follow balance-of-power considerations. Kim (1991) largely confirms Altfeld and Bueno de Mes-quita’s (1979) findings, while Huth (1998) highlights the greater propensity ofmajor power states to become involved in conflicts other than wars—specifically,crises – while following balance-of-power considerations. Probably because theirdefinitions are somewhat different from traditional definitions of balancing andbandwagoning, Gartzke and Gleditsch (2003) find evidence of both types ofbehavior in third parties’ interventions in interstate disputes.

A few works on joining behavior stand out in that they bring into the picturesfactors other than capabilities and alliances. Werner and Lemke (1997), in par-ticular, explore the effects of regime and economic similarities on third-partystates’ decision to align themselves with ‘‘side B’’ or ‘‘side A’’ in militarizedinterstate disputes.2 They find that states sharing the same type of regime anddomestic economic structures are likely to end up on the same side in a conflict.Although their findings are stronger for democratic regimes, they also uncoverevidence of a similar mechanism at work for autocracies, especially during thenineteenth century. In a similar vein, Enterline (1999) shows that the timing ofthird parties’ interventions in conflict also appears to be affected, althoughweakly, by similarities in political institutions. Reiter and Stam (2002) andGartzke and Gleditsch (2003), however, find no support for the proposition thatdemocracies are more likely to support other democracies in ongoing conflicts.Finally, Kaw (1990) incorporates ideological similarity between major powers andfactions in an ongoing conflict into a formal expected-utility model of joiningbehavior. She finds evidence that a third party is more likely to support a factionin a conflict with which it shares ideological similarity.3

Some Limitations in the Existing Analyses of Joining Behavior

The few studies that directly tackle the issue of joining behavior face additionalchallenges with regard to research design and empirical tests. These analyses are,in fact, restricted to subsets of conflicts (Altfeld and Bueno de Mesquita 1979), sub-sets of states (Kim 1991; Huth 1998), and subsets of intervention techniques—thatis, military techniques. Such restrictions may produce biased and ⁄ or nongeneraliz-able results.

Three issues in particular emerge from prior research: the use of truncatedsamples resulting from limited measurement of the dependent variable; the useof samples censored on one or more explanatory variables; and incorrect modelspecification for dealing with the previous limitations.4 In the case of joiningbehavior, the models and data used in most studies consider only militarizedinterventions—often in conflicts of the highest magnitude, such as wars. Yet, justas the boundaries between crises, disputes, and wars are not always clear, thethreshold between military intervention and nonintervention is not as sharp ascommonly operationalized. Rather, we can think of intervention as a continuousvariable ranging from indifference to the conflict and abstention to full-scale mil-itary involvement. Corbetta and Dixon (2005), for instance, identify a series of

2For the differentiation of dispute originators into side A and side B, see Jones et al. (1996), Ghosn and Palmer(2003), Ghosn et al. (2004).

3It must be pointed out that Kaw (1990) mostly focuses on the Soviet Union and looks at both intra and inter-state conflicts.

4The problems emerging from such sources of bias have been treated extensively in King, Keohane, and Verba(1994) and more recently in Signorino (2002, 2003).


joining techniques of increasing intensity ranging from verbal statements by athird party state’s public officials to full military involvement. When only extremevalues of all of the possible realizations of the dependent variable are used,researchers are in effect dealing with a truncated sample. If conflicts of lowerintensity are not considered, and if nonmilitary interventions are treated asnonevents, conclusions about joining behavior may not be generalizable.

This is also a problem of sample selection on some value of the dependentvariable—a procedure that can generate biased conclusions (King et al. 1994).5

The process that systematically produces such observations must be taken intoconsideration in order to avoid bias (Signorino 2002:97). But even proponentsof strategic approaches are vulnerable to this risk. By focusing exclusively onthreatened or realized uses of force, while discounting other actions as inconse-quential ‘‘cheap talk,’’ they may still overestimate the deterrent effect of mili-tarily powerful third parties, or underestimate third parties’ willingness to carryout their commitments when deterrence fails.

Because of their emphasis on the use of force, scholars of joining behaviorhave often chosen to narrow the sample of third parties to those states that actu-ally have the means to intervene militarily in ongoing conflicts. Previous researchhas employed status, capabilities, alliances, and geographical location to definethe politically relevant states who can select themselves into the subsample ofactual violent (military) interveners.6 But if only military realizations of thedependent variable are considered, the observed Y can result from some empiri-cally unaccounted process that makes states with high value on some X morelikely to intervene. Choosing samples of joiners based on attributes thatare assumed to increase a third party’s opportunity to join creates threats to theexternal validity of the conclusions. It also reduces their generalizability beyondthe sample (Signorino 1999:96). Extending the conclusions about major powerstates’ tendency to intervene in conflicts to all states in the international systemmay then be misleading.

Finally, while we focus on the factors that make some third parties more proneto intervene militarily, it may likely happen that some third parties with few capa-bilities, no alliances, or great distances away from the disputants will end up inthe sample of interveners due to some other unaccounted characteristic. This isthe source of the well-known sample selection bias, which is likely to lead tobiased inference—a problem that must be accounted for explicitly (Heckman1979; Dubin and Rivers 1990; Sartori 2003). Scholars of joining behavior in thepast have privileged empirical models—such as logistic or probit regres-sions—which do not adequately address this issue. Thus, the following sectionsaim at reducing the aforementioned sources of bias. First, a theoretical model ofthird parties’ preference formation that predicts both intervention and the inten-sity of such intervention on the basis of both security and homophily factors isproposed. Then the paper attempts to translate the theoretical model into anempirical approach that can handle sample selection biases.

The Opportunity and Willingness to Intervene

The opportunity and willingness approach to foreign policy behavior (Most andStarr 1980, 1989; Most et al. 1989; Siverson and Starr 1990; Starr 2005) has beenused before to tackle the question of intervention (see Werner and Lemke1997), and it provides a valuable framework for reducing the aforementionedthreats of bias and nongeneralizability. This framework suggests that not allpotential joiners have the same ability to enter a conflict militarily, and their

5See also Signorino’s (2002) discussion on this point.6See, for example, Yamamoto and Bremer (1980) and Huth (1998).

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alignment decisions are likely to depend on their ability and willingness to inter-vene. This view originates from Sprout and Sprout’s (1969) ideas concerningenvironmental possibilism, environmental probabilism, and cognitive behavior-ism. It stresses the interaction between entity, environment, and entity-environ-ment (Siverson and Starr 1990; Starr 2005:48). The opportunity and willingnessmodel combines micro and macro-levels of analysis by looking at joining behav-ior as a function of: (1) a third party’s characteristics; (2) the external environ-ment; (3) the characteristics of a dispute; and (4) characteristics of thedisputants (Enterline 1999).

Opportunity refers to the ‘‘possibilities that are available to any entity withinany environment, representing the total set of environmental constraints andpossibilities’’ (Siverson and Starr 1990:48). It is useful to think about opportunityin terms of Kadera’s (1998:368) notions of transmission mechanisms, transmis-sion barriers and constraints. Transmission mechanisms are factors facilitatinginteraction among states, while transmission barriers operate in the opposite wayby reducing the likelihood of occurrence of some international phenomenon orbehavior. Finally, constraints are limitations to specific courses of action resultingfrom the interaction of state-level attributes with environmental factors. Thus,opportunity refers to circumstantial factors that make it easier (or more difficult)for an external actor to enter an ongoing conflict. Although there is truth to thenotion that willingness creates opportunity, with regard to joining behavior it isdifficult to think of a third party intervening in an ongoing conflict without theopportunity to do so. A minimum level of opportunity must be present for ajoiner to become involved in an ongoing conflict. It is then possible to hypothe-size that, willingness factors being equal, third parties with greater opportunity for inter-vention will be more likely to enter ongoing conflicts.

However, opportunity by itself is a necessary, but not sufficient determinant ofintervention; some degree of willingness must also be present. Willingness refersto the motivational factors that may influence a state’s interest toward a particu-lar dispute. In the words of Siverson and Starr (1990:49), ‘‘willingness is relatedto a decision maker’s calculations of advantage and disadvantage, costs and bene-fits, considered on both conscious and unconscious levels. It is through willing-ness that decision makers recognize opportunities and then translate thoseopportunities into alternatives that are weighed in some manner.’’ To a largeextent, willingness corresponds to Sprout and Sprout’s (1969) idea of cognitivebehaviorism. Understanding how willingness contributes to turning opportunityinto realized action involves understanding the cognition process through whichpreferences are formed. With regard to joining behavior, willingness is equatedto a third party’s preference for either state involved in a conflict. It implies boththe identification of a preference for a specific outcome of a dispute and theprocess of evaluating whether a direct intervention of some type may bring aboutthe desired outcome. As such, the notion of willingness covers different ways ofidentifying state preferences and interests, along with different models for weigh-ing alternative courses of action.

Research on joining behavior has privileged those determinants of joiners’preferences that express a third party’s security-based interest for one side in aconflict. Models of joining behavior that stress pragmatic interests are steeped inexpected utility theory. Rational decision-making theory predicts that third par-ties will intervene in an ongoing conflict when their expected utility toward thevictory of a specific disputant is sufficiently high. Generally speaking, ‘‘a nation’sutility for another nation is a direct, positive function of the degree to whichthey share a common policy perspective’’ (Bueno de Mesquita 1981:29). Stateswith similar foreign policy perspectives are more likely to cooperate and lesslikely to present a security threat to one another. In a conflict, the more similarthe third party is to either combatant in terms of foreign policy interests, the


greater the value the third party places on that state’s victory. As a result, it ispossible to expect that: opportunity factors being equal, the likelihood of interventionand its the intensity should increase with the utility between a third party and either origi-nator of the conflict. A potential joiner is expected to remain indifferent to bothoriginators of the conflict if it shares no foreign policy goals with either, or if itis equidistant from both (Altfeld and Bueno de Mesquita 1979; Bueno deMesquita 1981, 1989).

However, third-party states’ preferences need not be shaped exclusively bypragmatic concerns. A state’s political affinity for another state can emerge fromsimilarities in ideological, institutional, or cultural characteristics (Nincic andRussett 1979). Starting from the voluminous body of research on the democraticpeace, there is evidence that states with similar norms of behavior and institu-tions are more likely to develop cooperative, peaceful relations with eachanother (Maoz and Russett 1993; Bueno de Mesquita, Morrow, Siverson, andSmith 1999; Werner 2000b; Peceny, Beer, and Sanchez-Terry 2002). Instead,states who differ markedly different with regard to cultural, religious, or in moregeneral terms, civilization traits, are said to be more likely to fight with oneanother (Huntington 1993, 1996).

What is sometimes absent from conflict studies that stress similarity in crucialattributes is a theoretical rationale that can explain why such similarities mayproduce the observed behavior. Such a theoretical foundation is, instead, presentin sociological theories of group formation, group mobility, and social groupnetworks. The notion of homophily underscores this approach to the study ofgroup dynamics. This concept is defined as ‘‘the tendency of people in friend-ship pairs to be similar’’ (McPherson and Smith-Lovin 1987:370). Within this frame-work, a social structure is conceived as a multidimensional space—also known as‘‘social space’’ or ‘‘Blau space’’ (Popielarz and McPherson 1995:699)—of differentsocial positions among which a population is distributed (Blau 1977:4). Individu-als’ salient sociodemographic characteristics define the axes of the social space.These key characteristics are know as parameters, which can be nominal orgraduated. Nominal parameters are basic categorical distinctions betweenindividuals, such as sex, religion, and race. Two actors share the same attribute,or they do not. Graduated parameters are continuous dimensions implyingdifferent rank-ordering among individuals. Education and wealth, for example,are graduated parameters (Blau 1977:7).7

The key notion of homophily theory is that ‘‘social associations are more pre-valent among persons in proximate social positions than between those in dis-tant social positions’’ (Blau 1977:36). With regard to nominal parameters,individuals are either within a group or outside of it. For graduated parameters,instead, proximity and distance are a matter of degree. On this basis, it isexpected that, for any individual, associations within a group are more frequentthan associations outside it. Moreover, the frequency of associations declines asdistance along graduated parameters increases (Blau 1977:36). In other words,‘‘the probability of a tie between two individuals decreases with social dissimilar-ity’’ (Popielarz and McPherson 1995:701). Quite simply, actors with similar traitsare more likely to share a similar worldview. Such similar perspective reduces themotives for conflict and increases the benefits two actors derive from their inter-actions. In addition to the frequency of dyadic associations, the intensity of suchassociations decreases with social dissimilarity. Similar individuals within the samesocial group experience centripetal forces, while people at the margins of a

7Although they divide the social space with regard to group membership and distance between social actors,nominal and graduate parameters are individual attributes and not social positions per se. Rather, socialpositions—and the behavior resulting from two actors being socially close––result from sharing similar individualattributes.

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group are subject to centrifugal forces (McPherson, Popielarz, and Drobnic1992; Popielarz and McPherson 1995).

Within the context of homophily theory, it has been argued that dyadic associ-ations are the outcome of interaction opportunities that emerge from social‘‘foci’’ around which social activities are organized (Feld 1982). Yet, the bulk ofempirical evidence offers support for a voluntaristic view of homophilous tieswithin a group. Within fairly heterogeneous groups, the formation of dyadicassociations between members is more accurately predicted by shared character-istics, or parameters, than by simple interaction opportunities (McPherson andSmith-Lovin 1987). While some basic opportunity for interaction must be pres-ent, similarity in key social characteristics appears to affect the willingness ofindividuals to create and preserve dyadic ties.

Sociologists have long been using notions such as homophily, social position,social distance between actors, and social networks in order to conduct cross-national analyses (see, for instance, Snyder and Kick 1979). The study of interna-tional politics has also started to see fruitful applications of this framework ofanalysis (Hafner-Burton and Montgomery 2006, 2008; Maoz 2006; Maoz, Terris,Kuperman, and Talmud 2006, 2007; Dorussen and Ward 2008). The concept ofhomophily has been used to study conflict between aggregate social actors suchas ethnic groups (see Centola, Carlos Gonzales-Avella, Eguiliuz, and San Miguel2007). In addition, from the notion of security communities to the democraticpeace, many theories of international conflict reflect, at least indirectly, Blau’sview that dyadic conflictual relationships are more likely to emerge across groupsseparated according to key nominal parameters and, within groups, betweenindividuals who are distant according to graduated parameters. For instance, notonly are democratic states less likely to fight one another, but they also appearmore likely to ally with one another than states with dissimilar regime type(Siverson and Emmons 1991; Lai and Reiter 2000). Thus, by equating regimetype, cultural similarities, and other salient characteristics of states to Blau’s nom-inal parameters, homophily theory raises an interesting general hypothesis aboutjoining behavior: opportunity factors being equal, the likelihood of intervention and theintensity of said intervention should increase with the homophily between a third party andeither originator of the conflict.8

To summarize, opportunity and willingness shape the decision to intervene inongoing conflicts. When we consider forms of intervention beyond military inter-ventions, many states are potential third parties to a conflict. For any given con-flict, however, only few states have both the opportunity and the willingness tointervene and take sides. Opportunity largely depends on environmental andstate-level factors. Given that a third party has the potential to intervene, the like-lihood of the intervention will depend on its willingness to align itself with eitherdisputant. Willingness itself can be modeled either as a function of a joiners’security interests or as a function of homophilous traits between a joiner and adisputant, or even as a function of both. This dynamic is analogous to a generalmodel of apparently sequential, yet almost simultaneous choice.

Research Design

Modeling the correlation between actual intervention and alignment is crucialfor improving our understanding of joining behavior. Most existing studies on

8It is important to point out that, while sociological theories of group membership and interaction expect coop-eration and the benefits of cooperation to increase with homophily, it cannot be ruled out that, in internationalrelations, homophily may generate competition (see Hafner-Burton, Khaler, and Montgomery 2009). If that is thecase, similarity in key parameters shall reduce, rather than increase the likelihood of intervention. The empiricalmodel described in the following section puts these competing propositions to a test.


this topic have coded the occurrence of intervention as a dichotomous depen-dent variable and have relied on logit or probit estimation. Other authors,instead, have resorted to multinomial or ordered probit and logit models in theattempt to jointly predict intervention and alignment choices (Altfeld and Buenode Mesquita 1979; Gartzke and Gleditsch 2003). However, these approachesimpose strong assumptions that are regularly violated in the estimation phase.9

Selection models or models of simultaneous, interdependent choice—such asbivariate probit—are better suited for estimation purposes. Although they arenot without limitations (see Sartori 2003), these models are increasingly popularin international relations research. Various authors have employed them in orderto account for selection dynamics across different conflict stages (Reed 2000;Lemke and Reed 2001; Clark and Reed 2003).10 However, such approaches mayfail to represent fully the theoretical model proposed earlier because of theirpropensity to treat opportunity and willingness as sufficient conditions for inter-vention, rather than necessary and sufficient conditions. A better approach isoffered by boolean logit ⁄ probit. Braumoeller (2003) has developed thistechnique with the objective of providing more thorough empirical tests for the-oretical models of multiple, conjunctural causation. Theoretical explanationsinvolving complex causation are widespread in political science. Yet, at theempirical level, scholars often fail to pay adequate attention to relationshipamong the multiple causal paths implicit in their models. Because theoreticalmodels based on opportunity and willingness often fall within the broad familyof the models of complex, conjunctural causality mentioned by Braumoeller(2003), a boolean logit ⁄ probit approach is appropriate for the present analysis.Furthermore, boolean logit ⁄ probit is essentially analogous to bivariate probitwith partial observability (Braumoeller 2003:218). Thus, it can handle simulta-neously the multiple causal paths of the present opportunity–willingnessapproach to joining behavior and the concerns with sample selection raisedearlier.

Intervention in an ongoing militarized dispute on the side of a combatant isthe dichotomous dependent variable of interest. In order to facilitate compari-son of results with previous research, this analysis follows Werner and Lemke(1997) in distinguishing dispute originators as side A and side B. The dependentvariable is coded dichotomously, with one representing a third party’s decisionto align with side B in a dispute, and 0 representing the decision to align withside A. However, unlike previous studies of joining behavior, both militarizedand nonmilitarized interventions are considered, first together, then separately.The data that allow for this coding come from Corbetta and Dixon (2005) andare described more fully below.11

The ideal research design to study joining behavior would account for allpotential interveners and all actual states involved at any stage during a conflict.Coalitions in an ongoing conflict expand and shrink as third parties enter orleave at different stages (Gartzke and Gleditsch 2003). Originators adjust theirbehavior as joiners come and go. Third parties take into consideration not only

9Models with ordered dependent variables estimate an increasing level of willingness to join either side in con-flict with nonintervention as the base category. In these models, the nonintervention category is either empty—ifone samples only actual interveners—or disproportionately larger than other categories—if all potential thirdparties are considered. Conditional and multinomial logit approaches, instead, have been used to estimate the like-lihood that a third party will abstain or join with either side as if the outcomes were independent of one another.Because these options are not independent, these models are likely to violate the assumption of Independence ofIrrelevant Alternatives (IIA) (see Greene 2003).

10 With regard to joining behavior, the only attempted application is found in Smith (1996).11 According to the description of the data set on third-party intervention used for the analysis, the denomina-

tion side A or side B has no intrinsic meaning. Side A simply identifies the disputant with the smaller Correlates ofWar country code (see Corbetta and Dixon 2005).

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the attributes of the original disputants, but also those of other joiners who havealready intervened or may intervene in the future. A research design of this typewould have an ever-shifting unit of analysis, and it would require the collectionof information on the covariates of interest at each stage of the conflict. In mostcases, such information is simply not available.12

Given said obstacles, in studies of joining behavior the unit of analysis is givenby a dyad of conflict originators and a third party (see, for example, Werner andLemke 1997). This approach somewhat oversimplifies complex conflict dynamicsand joining decision, especially in cases of multilateral disputes and repeatedinterventions. However, this limitation need not be too damning. Most interstatedisputes, in fact, begin as two-state affairs, and they experience intervention byno more than one third party (Jones et al. 1996). In addition, concerns withoversimplification depend of the quality of the data. Existing studies on joiningbehavior employ data that provide limited information about third parties’actions.13

More specific information on joiners’ actions is found in Corbetta and Dixon’s(2005) data on third-party interventions. The data track military and low-inten-sity, nonmilitary (economic and diplomatic) interventions over the course of adyad’s conflictual history for the 1946–2001 period.14 In Corbetta and Dixon’s(2005) data set, military interventions range from the offer and provision ofmilitary assistance to actual fighting by a third party on the side of one of thecombatants. Nonmilitary interventions, instead, include: statements of support oropposition toward one side in the conflict; appeals ⁄ demands for cease-fire ortroop withdrawal; promises of economic assistance; promises of military assis-tance; direct diplomatic assistance; diplomatic sanctions; offer and provision ofeconomic assistance; economic sanctions.15

The data on third-party interventions from Corbetta and Dixon (2005) wereintegrated with dyadic MID data (Maoz 2005) to produce a data structure inwhich each observational unit represents a decision by a potential joiner to enterthe conflict and align itself with either disputant during each year of a dispute.With the exception of micro-states, all members of the international system areconsidered as potential third parties during each dispute-year. The inclusion of(almost) all states as potential third parties is crucial because, when nonmilitaryinterventions are considered, even small, remote states may face a nonzeroopportunity to intervene. In addition, the selection dynamic of the joining pro-cess must be modeled explicitly—that is, not by artificially reducing the sampleon the basis of a priori assumptions about political relevance. However, this pro-duces a data matrix with 312,948 observations and a disproportionately smallnumber of interventions. There are, in fact, 1413 interventions, 891 of which arein support of side B in the dispute. Thus, in order to facilitate the estimation of

12 Although conflict phases can be measured in days or months, the majority of indicators in internationalconflict are recorded on a yearly basis. Often information is not present even for such large time intervals. Trans-forming a conflict into minuscule phases—or even recasting the issue of joining behavior into a continuous timeframework—may force researchers to assume that many important variables do not change over time, thereby nulli-fying many of the benefits implicit in this approach.

13 The widely used Militarized Interstate Dispute data, in particular, tell us which side of a dispute a third partyjoins. But, in cases of sequential joining or multiparty disputes, Militarized Interstate Disputes (MID) data do nottell us against which state(s) a third party is acting. A joiner is assumed to be fighting against all states on the oppo-site side, but this seldom occurs. Most often, joiners in multilateral disputes act against one or few specific states inthe opposite coalition. Similarly, joiners do not systematically support all states on the side they have joined.

14 Corbetta and Dixon’s (2005) data record specific third party’s actions against a specific target state. Thismakes the separation of multilateral conflicts into a series of ‘‘third party state-dispute originators’ dyad’’ unitsmore manageable, and it allows one to account for multiple interventions by the same third party during the sameconflict.

15 With regard to military interventions, Corbetta and Dixon’s (2005) data overlap with MID when a thirdparty’s action passes the ‘‘threat of military force’’ threshold.


the boolean model proposed earlier a sample of 63,456 observations was ran-domly selected from the original data set. All of the occurrences of interventionswere included in the sample. Before proceeding with the model estimation, carewas taken to verify that the sample was indeed representative of the larger dataset with regard to the independent variables of interest.

Identifying Opportunity and Willingness

Opportunity and willingness have been discussed so far in general terms as latentvariables. However, in order to test a unified model of joining behavior, theircomponents must be identified. Opportunity is defined by the environmentaland circumstantial elements that shape the possibilistic and probabilistic natureof an intervention decision. Sprout and Sprout (1969:53) and Most and Starr(1989:31) cite actors’ capabilities as one of the crucial connections betweenopportunity and possibilism. Regardless of type, a social actor’s ability to under-take an action depends on its resources. Economic and military power influencesa state’s ability to conduct an activist foreign policy, and it facilitates joining in alarge number of conflicts. A state’s material capabilities, then, are expected toinfluence positively the likelihood of its intervention in an ongoing dispute. TheCorrelates of War project provides the operationalization of material capabilitiesthrough its Composite Index of National Capabilities (CINC). This index repre-sents a combination of a state’s military, industrial, and demographic assets(Singer, Bremer, and Stuckey 1972).

In addition to capabilities, the physical environment in which an actor oper-ates largely influences the set of opportunities it faces. The geographical locationof events and spatial dimension of international politics are contextual variablesto which conflict scholars have paid great attention (Starr 2005). Overall, spatialproximity affects the opportunity structure within which a state operates (Mostand Starr 1980). We know that proximate states are more likely to have unre-solved issues, to go to war with one another, and to become involved in eachother’s affairs (Starr 2005). Conversely, states are not likely to be touched by geo-graphically distant conflicts. Thus, while geographical proximity to either dispu-tant increases the likelihood of intervention, distance from the disputants isexpected to have the opposite effect. In addition, because of geographical dis-tance, third-party states may face asymmetric opportunities to join with eitherside in the conflict. Here, geographical distance is expressed as the logged dis-tance in miles between a third party and side A, and between a third party andside B in the dispute.16

The identification of capabilities and distance as determinants of opportunityis analogous to what we find in Clark and Regan (2003). However, third-partyintervention occurs in the midst of an ongoing conflict that has peculiar charac-teristics. Other conflict-specific factors may shape third-party states’ opportunityto intervene. For example, acts of aggression that are reciprocated by the statebeing attacked tend to increase a conflict’s duration, thus opening up opportuni-ties for third parties to join (Jones et al. 1996). A similar logic applies to conflictsthat experience high level of hostility and conflicts involving major power states.Such disputes have politico-strategic repercussions that ripple across the interna-tional system, affecting potential third parties (Yamamoto and Bremer 1980).Unfortunately, most characteristics of interstate disputes are recorded at the endof a conflict. It is often impossible to determine whether conflict-specific factorsare the result, rather than the cause, of intervention. Consequently, it is impor-tant to proceed with caution before including a conflict’s peculiar characteristicsas indicators of opportunity.

16 Distance data were obtained from the EUGene software application (Bennett and Stam 2000).

71Renato Corbetta

With regard to willingness, as seen in Clark and Regan (2003) and Maoz et al.(2006), pragmatic interest and homophily capture the most recurrent and perva-sive stimuli of foreign policy action specifically directed toward or againstanother state. Most and Starr (1989) make explicit reference to expected utilityanalysis as an approach to capturing willingness in the study of foreign policybehavior. The expected utility approach to third parties’ preference formationhypothesizes that the likelihood of intervention on one side in a conflict willincrease as third parties move away from an indifference threshold, and as theirexpected utility toward a certain outcome and the victory of one side (or thedefeat of the other side) increases. Altfeld and Bueno de Mesquita (1979) andBueno de Mesquita (1989), for instance, offer a model of intervention based onthe relative magnitude of a third party’s utilities for either state involved in thewar. Their model assumes that war is relevant to all states, but only somedecision makers find a conflict sufficiently relevant to justify taking militaryaction (Altfeld and Bueno de Mesquita 1979: 88). Altfeld and Bueno de Mesqui-ta (1979:97) identify two types of utilities that determine whether a conflict issufficiently relevant to a potential third party. One is the utility from a specificoutcome of a conflict; the other is the utility from strategy that a third partyderives from ‘‘participating in the war effort on the preferred side’’ (Altfeld andBueno de Mesquita 1979:97). This type of utility expresses ‘‘the strategicimportance that the third nation C attaches to each of the original belligerents’’(Altfeld and Bueno de Mesquita 1979:97).

According to expected utility models, common foreign policy agendas are thekey determinant of strategic proximity between a third party and a disputant. AsAltfeld and Bueno de Mesquita (1979:91) suggest, it is possible to think of simi-larity in ‘‘alliance portfolio’’ as an indicator of a state’s utility for a certain out-come—that is, how much a state values having a certain combatant to win. Thepresent analysis employs Signorino and Ritter (1999)’s S measure of similaritybetween two countries’ alliance portfolios. Altfeld and Bueno de Mesquita(1979:98) see the presence of an alliance pact—defense pacts or ententes, in par-ticular—between a potential third party and either disputant as reflectingexpected utility from strategy. This is defined as a the value a joiner places onfighting on the same side with one disputant. Alliance Treaty Obligations andProvisions (ATOP) data are employed here to generate two alliance vari-ables—one for a third party and Side A, one for the third party and SideB—coded as 1 if a potential joiner and a dispute originator share a defenseagreement or an entente, 0 otherwise (Leeds et al. 2000; Leeds, Ritter,McLaughlin Mitchell, and Long 2002).17

Most and Starr (1989:31) and Clark and Regan (2003) argue that capabilitiesaffect not only a state’s opportunity but also its willingness to transform thoseopportunities into realized foreign policy actions. Realist theory has also consid-ered capabilities as the most important determinant of a third party’s alignmentchoices. With regard to willingness, the disputants’ capabilities matter just asmuch as a potential third party’s capabilities. Following realism’s classic idea ofbalancing, it is possible to hypothesize that a joiner will be more likely to alignwith one side in a dispute as that side’s capabilities decrease and the opposingside’s capabilities increase. Following Werner and Lemke (1997:534), the capabil-ities component of willingness is measured as the CINC scores of each side ofthe dispute.

In addition to capabilities and alliances, a state’s pragmatic interests includeeconomic interests. Economic ties between a disputant and a potential joinermay influence a joiner’s decision to enter the conflict and take sides. The

17 ATOP data are preferred because they allow one to identify those alliances containing specific provisions forthird-party intervention.


expectation is that the stronger the trade ties between a third party and a stateinvolved in a dispute, the greater the likelihood that the joiner will take sideswith its trading partner. Gleditsch’s Expanded Trade and GDP data provideinformation about trade flows between states for (almost) the entire time periodunder examination and allow one to derive the trade dependence betweenpotential third parties and disputants (Gleditsch 2002b). The logged proportionof a third party’s GDP derived from trade with the disputants is used to producetwo measures of economic connectedness, one between a joiner and disputant Aand one between a joiner and disputant B.18

The homophily-based perspective on foreign policy decision making suggests,instead, that a third party’s willingness to act may result from cultural, normative,ideological, or institutional proximity. Because of the pervasiveness of the demo-cratic peace proposition, the first dimension of homophily to be considered issimilarity in regime type. Democracies not only avoid conflicts with other democ-racies, but they also seem to have an implicit interest in the preservation and dif-fusion of democracy internationally. Studies on the systemic evolution ofdemocracy support the proposition that the growth in number and ‘‘maturity’’of democratic states is, in many ways, a self-supporting mechanism that simplifiesthe foreign policy outlook of democratic states themselves (see, for instance,Cederman 2001a,b). Werner and Lemke (1997) present evidence that states shar-ing the same regime type tend to align with one another in interstate disputes;they also suggest that this tendency also applies to authoritarian states. Followingtheir study, this variable is measured as the difference between two countries’Polity IV’s democracy-autocracy score, often referred to as DEM-AUT score(Marshall and Jaggers 2002). Difference in regime type can range from 20—thelargest possible difference—to 0—perfect equality. Thus, the greater the similar-ity in regime type between a joiner and a disputant in a conflict—that is, thesmaller the difference in their Polity scores—the greater the third party’s willing-ness to side with that disputant.

Beyond institutional homophily, Centola et al. (2007) suggest that social actorswho share similar linguistic, cultural, and ethnic traits can perceive greater affin-ity for one another than states who do not. The stable partnership between theUnited States, the United Kingdom, and Australia, for instance, has ledthese states to be on the same side in many conflicts, from the Korean War tothe recent war with Iraq. Although they share alliances and common foreignpolicy interest, the bond between these states extends well beyond their securitygoals. Their special relationship has often set them apart from other members ofthe same alliances who may have similar foreign policy. This suggests that thegreater the similarity in cultural traits between a potential third party and a dis-putant in a conflict, the greater the likelihood that third party’s will intervene insupport of the most culturally similar state. Of course, culture is a multi-dimen-sional concept that cannot be easily measured. Henderson and Tucker (2001),however, have developed an indicator of states’ civilization that approximates thenotion of a country’s cultural identity.19 Their proxy indicator was used to createa dummy variable coded 1 if a potential third party and a dispute originatorshared the same civilization, 0 otherwise.

Arguably, one can think of other measures which can express third parties’opportunity and willingness to intervene, and any researcher is bound to havepersonal preferences about additional candidates for inclusion. The indicators

18 Because trade data are missing for 1946, 1947, and 2001, many observations are bound to be lost during theanalysis.

19 Originally designed to test empirically Huntington’s (1993, 1996) clash of civilizations thesis, this indicatoridentifies 10 different civilization categories: Sinic, Japanese, Hindu, Islamic, Orthodox, Western, Latin American,African, Buddhist, and ‘‘Other.’’

73Renato Corbetta

proposed above, however, offer several advantages in that (1) they have beenfound to capture opportunity and willingness quite effectively in prior research;(2) they have proven to be consistent estimators across uncountable studies; and(3) they allow one to preserve some parsimony within a computationally inten-sive model such as the one estimated in the following section.

Analysis and Findings

The objective of this analysis is to capture the interconnectedness of the differ-ent dimensions of joining behavior, while avoiding sample selection biases andartificial censoring of the dependent variable found in previous studies. Theboolean approach allows one to capture complex decision dynamics of joiningbehavior while minimizing the pitfalls of prior research. Table 1 reports the esti-mates for a series of boolean logit models. Again, intervention on the side of

TABLE 1. Boolean Logit Estimates of Effects of Opportunity and Willingness on Third Parties’Decision to Intervene and Take Sides in Ongoing Disputes, 1946–2001

All interventions Military Nonmilitary

Path 1 (opportunity)Joiner’s capabilities 29.230*** 20.378*** 27.745***

(1.50) (2.68) (1.68)Log distance from A 0.088 0.371** 0.023

(0.09) (0.17) (0.01)Log distance from B )0.687*** ).736*** )0.568***

(0.07) (0.15) (0.08)Constant )1.403* )0.783 1.025

(0.74) (1.30) (0.95)Path 2 (willingness)

Capabilities A 8.191*** )5.665** 9.800***(1.49) (2.31) (1.56)

Capabilities B )19.269*** )4.547 )27.490***(3.43) (4.04) (4.64)

Affinity with A )4.798*** )0.078 )5.142***(0.57) (0.80) (0.65)

Affinity with B 4.179*** )1.412* 5.325***(0.59) (0.78) (0.66)

Alliance with A 0.181 )1.889*** 1.012***(0.26) (0.53) (0.29)

Alliance with B 0.588** 2.212*** )0.157(0.23) (0.43) (0.27)

Trade dependence with A 0.022* 0.014 0.033**(0.01) (0.02) (0.01)

Trade dependence with B 0.03** 0.054*** 0.021*(0.01) (0.02) (0.01)

Regime similarity to A 0.055*** 0.056*** 0.048***(0.01) (0.01) (0.01)

Regime similarity to B )0.004 )0.031* 0.002(0.01) (0.01) (0.01)

Civilization sim. to A 0.669** 0.693* 0.316(0.23) (0.33) (0.26)

Civilization sim. to B 1.023*** 0.962** 0.845***(0.22) (0.31) (0.24)

Constant )3.144*** )2.675*** )4.255***(0.39) (0.56) (0.48)

Log likelihood )2035.602 )769.004 )1536.992N 45,010 45,010 45,010

***significant at p < .001; **significant at p < .01; *significant at p < .05


combatant B is the dependent variable of interest. In Table 1, the model in thefirst column includes both military and nonmilitary interventions. The models inthe second and third columns, instead, respectively consider military and non-military interventions. For each model, two intercepts are shown as the booleanlogit ⁄ probit routine estimate an intercept for each causal path (see Braumoeller2003). Standard errors are reported in parentheses.20

Three general findings emerge from Table 1. First, it appears that the inclu-sion of nonmilitary interventions makes a considerable difference, as the effectof some of the determinants of joining behavior changes remarkably when wemove from military to nondiplomatic interventions. Second, pragmatic, security-based determinants of intervention and alignment do not entirely explain thirdparties’ choices. Homophily parameters, and in particular regime similarity, con-tribute to our understanding of joining behavior. While the two approaches tothird parties’ willingness—pragmatic ⁄ strategic and homophily-based—are oftenpresented as being antithetical to one another or mutually exclusive, it appearsthat they complemented each other quite effectively. Finally, from these results,it appears that enmity toward one side in a conflict matters just as much as close-ness toward the other side in shaping third parties’ choices. Prior models of join-ing behavior have largely focused on friendship ties between joiners and one ofthe combatant. The present results indicate that intervention is largely motivatedby antagonism toward the less politically proximate disputant. Third parties mayreluctantly support states from which they are quite different if victory by theopposite side is an even less desirable outcome.

The results show that both capabilities and distance shape a third party’sopportunity to intervene in the expected direction. Joiner’s capabilities arealways positively and significantly related to the likelihood of both military andnonmilitary intervention. Distance from the side being supported—side B in thiscase—consistently reduces the chance of intervention. In addition, when militaryinterventions are considered, distance from the enemy matters considerably. Themore distant a third party is from A, the more likely it is to support B. Thisreflects third-party states’ tendencies to come to military aid of states within theirgeopolitical neighborhood against ‘‘outsiders.’’ It further reflects third partiesgreater inclination to intervene in support of B when they feel less vulnerable tothe risk of A’s retaliation.

Concerning third parties’ willingness, the analysis confirms previous findingsthat third parties prefer to balance power rather than bandwagon (Altfeld andBueno de Mesquita 1979; Werner and Lemke 1997). The negative and signifi-cant sign of the coefficient for the capabilities on Side B variable in Table 1 sup-ports the expectation that the more powerful B is, the less likely a third partywill be to take sides with it. However, balance of power behavior breaks downexactly when one would expect to observe it more strongly—that is, with regardto military interventions. Overall, third-party states appear willing to talk tough,but they shy away from supporting their friends militarily the stronger theiropponent gets—side A, in this case. A similar dynamic applies to strategic affinityas measured by the S score. The closer its foreign policy outlook is to B’soutlook, the more likely a third party is to support B. This tendency is reinforcedby foreign policy dissimilarity with the enemy A. However, similarity in foreignpolicy does not have much of an effect on the likelihood that third parties willsupport their friends militarily.

The presence of formal agreement is also a powerful incentive for states tointervene on the side of an alliance partner, as found in prior research (Altfeldand Bueno de Mesquita 1979; Kim 1991; Smith 1996; Werner and Lemke 1997).

20 The models were estimated using the boolean routine with logit link in the ‘‘Boolean’’ R package(Braumoeller 2003).

75Renato Corbetta

This lends support to research indicating alliances indeed are more reliable thanpreviously thought (Leeds et al. 2000, 2002). Because the impact of alliance tiesis more marked with regard to military interventions, the results further corrobo-rate Leeds et al.’s (2000) notion that alliances involve highly specific commit-ments. Third parties are unconstrained by alliance ties with regard tononmilitary forms of intervention, but they ultimately follow prior formal com-mitments in their choice to intervene with military force. Finally, trade depen-dence has a clear impact on intervention and alignment choices, but it does nothelp us predict the direction of that choice. Joiners seem to be ready tosomehow intervene in and manage disputes between trade partners. However,because both coefficients concerning trade are positive and significant, it isdifficult to say whether the intervention will be on the side of the strongertrading partner.21

As a determinant of joining behavior, homophily highlights the effects ofantagonism and dissimilarity on third parties’ foreign policy choices. Becauseregime (dis)similarity is measured as a difference in Polity’s democracy-autocracyscores, the positive coefficients of the difference between a third party and Aindicate greater likelihood that a joiner will intervene in support of B. The nega-tive coefficients of the difference in regime with B indicate that the more dissim-ilar a third party and B are, the less likely a third party is to support B. Thus,evidence suggests that joiners tend to intervene against states that have differentdomestic systems more than they wish to support states with similar political insti-tutions. Remarkably, the effects of regime (dis)similarity are more evident incases of military intervention than in the less demanding cases of nonmilitaryintervention. Homophily in cultural traits fails to predict the specific direction ofthird parties’ intervention and alignment choices. Just like in instances of con-flicts between trading partners, it is plausible that third parties try to interveneand manage conflicts among civilization ‘‘brethrens’’ without developing specificpatterns of alignment choices.22

To provide a more substantive view of these results, Figure 1 shows lowesscurves of the predicted probabilities of intervention across values of selectedcontinuous independent variables. Each plot presents probability curves for allinterventions, military interventions, and nonmilitary interventions. Becauseintervention in ongoing conflicts is a rare event, and because of the fine-grainednature of some of these covariates, a one-unit change in an independentvariables does not translate into dramatic changes in predicted probabilities.However, the plots graphically display: (1) growing probability in intervention insupport of B as similarity between a third party and B grows; (2) growing proba-bility in intervention in support of B as dissimilarity between a third party and Agrows; and (3) differences in joining behavior when military and nonmilitaryinterventions are viewed separately.

Although homophily-based determinants of willingness perform according toexpectations, it is possible that the impact of regime (dis)similarity is beingunderestimated. In fact, differences in Polity regime scores may not vary linearlyacross the range of the variable. Specifically, the literature on the democratic(and ‘‘dictatorial’’) peace suggests that the effects of regime similarity on

21 There is controversy in regard to correct way to measure trade dependence (see Barbieri and Peters 2003;Gartzke and Li 2003; Oneal 2003). However, the present results do not change regardless of whether one uses tradeproportion of GDP, logged trade proportion of GDP, or simply trade volume within a third party-disputant dyad.

22 Because of the controversial nature of measure of cultural similarity based on Huntington (1993, 1996) work,the analysis was replicated employing a dichotomous measure of similarity derived from Ellingsen’s (2000) data onethnic, linguistic, and religious similarity. A third-party state and a disputant were classified as culturally similar ifthey main groups within the respective territories shared the same language, religion, or ethnic origin. The resultsfrom the model changed little statistically and substantively. Furthermore, because Ellingsen’s (2000) data stop at1994, employing this alternative classification caused the additional loss of a large number of observations.


conflict initiation are stronger at high and low values of the democracy-autocracyscore. Because of the learning processes associated with the consolidation ofregimes, mature democracies and autocracies are more likely to take sides with sim-ilar states than with less established combatants. In order to explore this possibility,regime similarity was re-operationalized as a dummy variable coded 1 if a thirdparty and a combatant were mature democracies or autocracies, 0 otherwise.23

Tables 2 and 3 report the results of boolean logit models with dichotomousmeasurements of regime similarity. Again, all interventions, military interven-tions, and nonmilitary interventions are considered in turn. Standard errors arereported in parentheses.

The results from Tables 2 and 3 indicate that the homophily effects of regimesimilarity are more pronounced at high and low values of the Polity index.Mature democracies and autocracies tend to recognize one another as being sim-ilar and side with one another in ongoing disputes. Mature joiners perceivestates who have not clearly embraced a democratic or autocratic identity as politi-cally distant or simply different. The literature on democratization and conflictsuggests that less established regimes are more susceptible to sudden domesticchanges and produce less consistent policies (see, for instance, Mansfield and

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FIG 1. Lowess Curves of Preditced Probability of Intervention across Values of Selected IndependentVariables

23 Mature regimes were identified as having a Polity score greater than 6 for democracies and smaller than )6for autocracies.

77Renato Corbetta

Snyder 1995). Leaders in mature democracies or mature autocracies displaygreater unwillingness to support nations with whom they agree only partially, orwho are more at risk of sudden political and ideological changes. Theoretically,this turn in the findings is consistent with Blau’s (1977) idea that stronger hom-ophily ties develop between individuals who are most similar and with much ofthe literature on the democratic peace.

Two more results are worth noting from Tables 2 and 3. First, the effects ofregime ties are, to some extent, different for mature democracies and matureautocracies. Mature autocratic joiners appear more motivated by a direct tie withthe side being supported—side B, as usual. Conversely, mature democratic join-ers operate somewhat more cautiously, looking at both the presence of a tie withside B and the absence of regime similarity with A. Overall, even after reopera-tionalizing regime similarity, evidence remains of the importance of enmitytoward one side in a conflict vis-a-vis friendship toward the other side. Second,

TABLE 2. Boolean Logit Estimates of Effects of Mature Democratic Ties on Third Parties’ Decision toIntervene and Take Sides in Ongoing Disputes, 1946–2001



(1.33) (1.47) (1.71)Log distance from A )0.081 0.056 )0.195*

(0.08) (0.17) (0.10)Log distance from B )0.731*** )0.951*** )0.645***

(0.06) (0.17) (0.07)Constant 3.111*** 3.685*** 3.436***


Capabilities A 7.536*** )1.314 9.377***(1.40) (1.81) (1.41)

Capabilities B )19.906*** )4.815 )28.292***(3.36) (3.51) (4.55)

Affinity with A )5.865*** )1.059* )5.576***(0.53) (0.62) (0.55)

Affinity with B 4.381*** )0.779 4.711***(0.54) (0.61) (0.56)

Alliance with A 0.358 )1.184*** 0.659**(0.23) (0.36) (0.24)

Alliance with B 0.559** 1.581*** 0.439*(0.22) (0.25) (0.23)

Trade dependence with A 0.024* )0.001 0.033**(0.01) (0.01) (0.01)

Trade dependence with B 0.036** 0.036** 0.023*(0.01) (0.01) (0.01)

Joiner-A mature dem. )0.927*** )0.757*** )0.853***(0.19) (0.25) (0.21)

Joiner-B mature dem. 0.451*** 0.564** 0.257(0.16) (0.20) (0.18)

Civilization sim. to A 0.517** 0.360 0.374*(0.23) (0.25) (0.20)

Civilization sim. to B 0.774*** 0.628** 0.400*(0.19) (0.25) (0.21)

Constant )1.892*** )2.275*** )2.83***(0.29) (0.38) (0.34)

Log likelihood )2525.952 )891.223 )1972.215N 57,973 57,973 57,972



quite surprisingly, after controlling for mature democratic and autocratic ties,the impact of balance of power considerations on joining behavior in cases ofmilitary interventions seems to disappear. This finding goes counter to priorresearch and against the expectation that power calculations would matter mostwhen the costs of intervention rise. As it was pointed out earlier, it is quite possi-ble that previous scholarship has been so focused on power and security-baseddeterminants of joining behavior that it has failed to account for the role ofhomophilous ties. However, it is also likely that, because of the selection dynam-ics that dominate the decision to join, only the most powerful states have suffi-cient capabilities to intervene militarily when their (extended) deterrent effortshave failed. Because such powerful joiners are likely to be considerably strongerthan either side in the dispute, their alignment decisions are ultimately shapedby homophily considerations. This is a dynamic that the model proposed hereeasily accounts for, but that may have escaped prior models of joining behavior.

TABLE 3. Boolean Logit Estimates of Effects of Mature Autocratic Ties on Third Parties’ Decision toIntervene and Take Sides in Ongoing Disputes, 1946–2001



(1.41) (3.26) (1.55)Log distance from A )0.172* 0.051 )0.242**

(0.08) (0.17) (0.10)Log distance from B )0.713*** )0.825*** )0.613***

(0.06) (0.16) (0.07)Constant 3.767*** 2.569*** 3.639***


Capabilities A 7.209*** )3.952* 8.296***(1.34) (1.96) (1.37)

Capabilities B )19.991*** )6.485 )27.739***(3.28) (3.57) (4.17)

Affinity with A )5.529*** )1.567*** )5.708***(0.51) (0.63) (0.57)

Affinity with B 3.595*** )0.242 4.676***(0.51) (0.63) (0.58)

Alliance with A 0.243 )1.327*** 0.979***(0.23) (0.39) (0.24)

Alliance with B 0.606** 1.619*** 0.020(0.22) (0.27) (0.23)

Trade dependence with A 0.026** 0.004 0.041**(0.01) (0.01) (0.01)

Trade dependence with B 0.041** 0.041** 0.033*(0.01) (0.01) (0.01)

Joiner-A mature Aut. )0.395* 0.013 )0.211(0.18) (0.25) (0.20)

Joiner-B mature Aut. 1.208*** 0.373* 0.942***(0.18) (0.23) (0.18)

Civilization sim. to A 0.332* 0.371 0.132(0.18) (0.27) (0.21)

Civilization sim. to B 0.852*** 0.667** 0.569**(0.19) (0.27) (0.20)

Constant )1.898*** )2.299*** )3.181***(0.28) (0.38) (0.34)

Log likelihood )2525.335 )897.844 )1979.784N 57,973 57,973 57,972


79Renato Corbetta

Discussion and Conclusion

Although it is a relatively rare foreign policy decision, intervention in ongoingconflicts has an obvious substantive impact on the prospects of conflict manage-ment and on the chances that a conflict will expand further. Studies of joiningbehavior that attempt to understand this phenomenon by focusing first on third-party states’ preference formation have faced limitations that could lead toincomplete and potentially biased conclusions. These limitations involve a ten-dency to study intervention and alignment choices as separate, independentaspects of joining behavior. In addition, due to data availability, existing studiesonly investigate militarized interventions, while overlooking a very large share ofstates’ joining activities—nonmilitary activities. This paper attempts to addressboth shortcomings by proposing a model of joining behavior based on theopportunity and willingness theoretical framework. The idea of dependencebetween opportunity and willingness, intervention and alignment is inherent tothis approach. Finally, most studies of joining behavior have been steeped in thebelief that third parties’ preferences are dictated by pragmatic, security-basedconsiderations. This paper, instead, reaches into the territory of network theoryby proposing that homophilous ties with the disputants also shape joiners’ pref-erences.

In substantive terms, this analysis indicates that the decision to intervene inongoing conflicts is shaped by both opportunity and willingness, and it is a func-tion of both pragmatic, security-based considerations and homophilous ties. Ingeneral, balance-of-power calculations, similarity in foreign policy preferences,and regime ties with a disputant influence a third party’s decision to intervenein support of that state. However, the present analysis reveals that: (1) differ-ences exist between militarized and nonmilitarized joining behavior, and (2)opposition against one side in a conflict matters as much as friendship with thestate being supported. In fact, balance-of-power calculations and affinity of for-eign policy preferences lead third-party states to talk tough or engage in postur-ing—that is, to intervene nonmilitarily in a dispute. Yet, the existence of a directalliance and the presence of homophilous regime ties matter most when a thirdparty chooses to intervene militarily or escalate an existing nonmilitary involve-ment. This finding reinforces existing research connecting the specificity andreliability of alliances (Leeds et al. 2000, 2002), and it highlights the fruitfulnessof the application of the social network framework to the study on states’ interac-tions.

The notion that a third party’s enmity toward one side in a conflict matters asmuch as friendship toward the other side is implicit in balance-of-power dynam-ics, but it has been somewhat overlooked in regard to other determinants ofjoiners’ preferences. The findings concerning the relative role of similarity anddissimilarity conform to Blau’s expectations about interaction between unitswithin and across social networks and with recent applications of network analy-sis to the study of international conflict (Maoz 2006; Maoz et al. 2006, 2007;Centola et al. 2007). These results further underscore the notion that, beyondthe determinants of third parties’ preference formation, the dynamics leading tointervention are also strategic in nature. For our understanding of joining behav-ior, models that focus on the interactions in crisis bargaining between joinersand ‘‘aggressors’’ in ongoing conflicts (Smith 1996; Werner 2000a) represent anecessary complement to studies that attempt to understand third parties’ moti-vations to defend a ‘‘target.’’

Overall, the policy and theoretical implications of these findings are not trivial.These results—in particular, the emphasis on the dissimilarity between joinersand the targets of intervention—shed light on the considerable variation inthird-party foreign policy choices observed in situations such as the 2003 United


States–Iraq war. Although many democratic states and many European allies hador felt a great degree of affinity to the United States—especially in the aftermathof the September 11, 2001, attacks—they showed reluctance to join the Bushadministration in its dispute against Iraq, before and after the actual fightingtook place. The United States inability to capitalize on the strength of its posi-tion in order to draw many (powerful) joiners to its side was likely due to thefact that potential third parties did not perceive the Hussein regime as suffi-ciently threatening, and they maintained various ties with Iraq. Although manypotential joiners saw themselves as close to the United States, they lacked a suffi-cient degree of opposition against Iraq to justify their intervention. Returning tothe example of the Falkland Islands conflict used in the introduction, part ofPresident Reagan’s indecisiveness about becoming involved can be explained byhis reluctance to oppose Argentina rather than by his unwillingness to supportGreat Britain.

Challenging theoretical implications follow from this. For instance, mostresearch on conflict expansion has focused on the ties between potential thirdparties and the side in a conflict that is being joined. The reliability of allianceties has been a major issue of contention in the literature. As the present findingssuggest, questions about the reliability of alliance ties and their impact on warenlargement and escalation ought to be investigated with reference to the degreeof opposition between an ally and the enemy against whom one is fighting. Simi-larly, studies that focus on the decision to intervene as a function of strategic cri-sis bargaining may benefit by considering the degree of opposition between athird party and the aggressor state and the role that homophilous ties play in theformation of third parties’ preferences. In fact, strategic approaches are optimallysuited to capture the complexity of the three-way bargaining dynamics of multi-party crises. However, they often tend to discount the importance of third parties’motives or narrowly define them in terms of concerns with audience costs and ⁄ orcapabilities. These findings suggest that the credibility of commitments and thewillingness to carry them out may depend on additional factors.

Nonetheless, while it focuses on the sources of joiners’ preferences, integra-tion of this model with strategic approaches is a goal of future research. Suchintegration should be accompanied by further development of data sources. Atthis stage, most real-world conflict data do not allow a thorough empirical explo-ration of the strategic interactions between third parties and disputants, sincethey fail to record the disputants’ responses to the third parties’ actions, espe-cially when such actions are nonmilitary and occur before an interventionbecomes militarized.24 Finally, this research addresses some concerns with biasesof previous models of joining behavior by including both military and nonmili-tary interventions in ongoing disputes. However, it does not exhaust the topic,and the treatment of nonmilitary interventions remains rather coarse. As statedearlier, nonmilitary interventions involve a variety of foreign policy actions,ranging from diplomatic signals to the use of sanctions. Such policies are notperfectly substitutable. They involve different degrees of opportunity and willing-ness. They can be applied more or less effectively in a variety of settings—forexample, pre-crisis negotiation, crisis bargaining, or ongoing conflict manage-ment. A more fine-grained analysis of the universe of nonmilitary interventions ishighly desirable and will be addressed in future work.

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Documents

Determinants of Third Parties’ Intervention and Alignment Choices in Ongoing Conflicts, 1946–2001