audience costs and interstate crises: an empirical assessment of fearon's model of dispute...

Audience Costs and Interstate Crises:An Empirical Assessment of Fearon’s

Model of Dispute Outcomes

PETER J. PARTELL

Binghamton University

AND

GLENN PALMER

Texas A&M University

In a recent article, James Fearon advances an innovative approach to thestudy of interstate crises. He adds to the traditional view (that crisisoutcomes are influenced by the balance of capability and the balance ofresolve) the notion that domestic political audiences exert a strong influ-ence over which state in a crisis is likely to achieve a successful outcome.His game-theoretic analysis yields a number of interesting hypotheses,which are tested in this study using data on militarized disputes, thestructure of polities, and national capability. In general the results stronglysupport Fearon’s model, though we find that relative national capabilitiesdo tend to affect the outcomes of crises. This study highlights the impor-tance of combining formal models of political events with large-N empiri-cal tests.

Traditional notions of interstate bargaining suggest that crisis outcomes are afunction of the relative military might of the participants and the willingness of eachside to use force in order to demonstrate a higher degree of commitment to theissue at stake than the opponent (Snyder and Diesing, 1977; Maoz, 1983; Leng,1993). The escalation of crises, according to this view, occurs as each side attemptsto show its opponent that the costs of further conflict over the issue at stake will belarger than that opponent wants to bear. The outcomes of crises should be thateither one side backs down, because it is less resolved than its opponent, or neitherside backs down and the two sides go to war. The words often used to summarizethis perspective on bargaining is that international crises are “competitions in risktaking” (Schelling, 1960; Kahn, 1965).

In a recent article, James Fearon (1994) offers a fresh perspective on interstatecrisis bargaining. Drawing on Thomas Schelling’s (1960) work on credible commit-ment, he argues that the escalation and outcomes of interstate disputes are in large

International Studies Quarterly (1999) 43, 389–405

©1999 International Studies Association.Published by Blackwell Publishers, 350 Main Street, Malden, MA 02148, USA, and 108 Cowley Road, Oxford OX4 1JF, UK.

Authors’ note: An earlier version of this article was presented at the 1997 Annual Meeting of the Midwest PoliticalScience Association. We are grateful to James Fearon, Stuart Bremer, Joe Eyerman, Robert Hart, Tamar London, andPhilip Schafer for the comments and help on earlier drafts of this article. The article also benefited from the constructivesuggestions of the reviewers and editors of this journal. We wish to thank the National Science Foundation, whosefinancial assistance through grant SBR-9507909 facilitated this research. We alone are responsible for any errors in thiswork.

part a function of the relative degree to which the opponents are subject to domesticaudience costs. According to Fearon, leaders who rely on domestic audiences to stayin power enjoy a relative bargaining advantage in international crises because theiractions are, inherently, highly credible. This credibility exists because a leader whorelies on a domestic audience to stay in power may be thrown out of office shouldthat audience perceive the leader as failing in the foreign-policy arena. When sucha leader makes a public show of force, such as in an interstate crisis or dispute, heropponent realizes it would be very costly for her to back down, or reverse course, asthis would most likely be viewed as a foreign-policy failure by the leader’s domesticaudience. In this fashion, a leader’s actions during a crisis act as “costly signals” ofcommitment, since they show that the leader is willing to risk the costs associatedwith foreign-policy failure in order to achieve a favorable settlement on the particu-lar issue(s) at stake in the crisis.

Fearon’s model has yet to be subjected to thorough empirical testing,1 and giventhe potential importance of Fearon’s model to our understanding of interstatebargaining, crisis escalation, and perhaps by extension, the democratic peace, it isessential that Fearon’s hypotheses face empirical validation. Fearon’s model allowsfor hypotheses about the process by which states select themselves into crises, aboutthe number of escalatory steps to be expected in a crisis, and about the likelyoutcomes of crises. In this article we test the hypotheses from Fearon’s model thatpertain to crisis outcomes. But before moving to these empirical tests, we first willbriefly outline Fearon’s model and explain four hypotheses it yields which we willbe testing.

Fearon’s Model of Domestic Audience Costs

A central component of Fearon’s (1994) model is the idea that international crisesare public affairs played out in front of domestic and international audiences. Thecosts imposed upon leaders from domestic audiences are fairly immediate. Leadersare thus concerned about their performance in crises and wish to avoid foreign-policy failures that can motivate domestic opposition. On the other hand, costsimposed by international audiences take longer to realize. These costs result in theleader’s loss of reputation over time, as foreign-policy failures accumulate. Becauseof the relative time that it takes for these two types of audience costs to take effect,Fearon argues that leaders are more concerned with domestic audience costs thanthey are with international ones. Fearon points out that, ironically, leaders’ concernfor their reputations internationally—a long-standing tenet within the realistschool—may actually result from leaders’ fears of domestic opposition rather thana fear of being perceived as exploitable or weak by other leaders.

A second critical idea in the model is that in states with strong domestic audiencesleaders are agents who conduct foreign policy on behalf of principals (1994:581).In democratic systems, the principals are the voters. In many dictatorships, theprincipals are the high-ranking generals in the military. However, in states withoutstrong domestic audiences, this agent–principal relationship does not exist because

1 Eyerman and Hart (1996) test a portion of Fearon’s model. There are, however, three potential problems withtheir analysis. First, they use various measures of democracy as their indicators of audience costs. As Fearon points out,though, nondemocratic leaders can face strong domestic audience costs as well. A measure of audience costs that isindependent of democracy is required to test the model adequately. Second, they test the hypotheses dyadically bylooking at the crisis behavior of states within jointly democratic crises. Fearon’s hypothesis is monadic. The audience-costhypothesis should apply to all high-audience-cost states, regardless of their opponents’ domestic political structure.Finally, the authors test only one hypothesis of the many that come out of Fearon’s model. This study will use multiplemeasures of audience costs to test four of the central hypotheses that flow from Fearon’s model at the monadic ratherthan dyadic level of analysis.

390 Audience Costs

the leaders have placed themselves into office rather than having been placed thereby others.

This agent–principal relationship is important because it allows states to commu-nicate their resolve to one another. Schelling (1960) uses the example of a workertrying to negotiate a pay raise with her boss. If the worker demands a one dollarraise, the boss has no reason to believe that the worker will not accept a counterofferof fifty cents; but if the worker hires an agent who will lose his job if he accepts anyoffer less than one dollar on behalf of the worker, the one dollar demand becomesmore credible. By committing to a particular issue publicly, for example, bythreatening to use military force in pursuit of a goal, international leaders commu-nicate to their opponents that they are committed enough to risk the costs associatedwith a perceived foreign-policy failure back home. Thus, the risk of incurringdomestic audience costs helps a leader to better communicate his or her commit-ment to issues under international contention. According to this logic, leaders whoface higher audience costs can more credibly signal resolve than leaders who facesmaller, or no audience costs.

Fearon builds these notions of audience costs into a game-theoretic model ofinternational crisis. In the model, crises occur in continuous time, meaning that foreach segment of time before the crisis ends, each state in the crisis can choose to“attack,” “escalate,” or “quit.” Payoffs are determined by the issue in dispute (theprize), each side’s value for war, and the extent of domestic audience costs(1994:582). The state that is the first to back down suffers its respective audiencecosts (which increase over the course of the unresolved dispute) while its opponentreceives the prize. Crises are modeled as “political attrition contests” in the sensethat costs accumulate with each segment of time in which the dispute is not resolved.Comparative statistics offer specific hypotheses about interstate crisis behavior andthe democratic peace phenomenon.

Hypotheses from the Model

Fearon’s model leads to hypotheses about domestic political structure and intra-dispute behavior, as well as other hypotheses about the roles of relative capabilitiesand relative interests. These hypotheses are very clearly stated (Fearon,1994:585–86). The first hypothesis that flows from the model is that states that arebetter able to generate audience costs are less likely to back down in disputesthan states less able to generate audience costs. According to the logic of themodel, audience costs have great signaling value. As Fearon states, “While [ahigh-audience-cost] state may be reluctant to escalate a dispute . . . if it does choose todo so this is a relatively informative and credible signal of willingness to fight overthe issue” (1994:585). In such instances, the opponent will be more likely to backdown recognizing the constrained state’s resolve.

The second hypothesis from the model is that high-audience-cost states will besignificantly less likely to initiate limited probes in foreign policy. By “limitedprobes” Fearon is referring to instances in which a state challenges another state inan attempt to assess the latter’s resolve on a particular issue. These challenges are“limited” in the sense that should the challenged state show a willingness to resistthe challenger, the challenger will either “back off or moderate” its demands(1994:591). States with strong domestic audiences should be very deliberate in thedisputes they choose to initiate because of the high costs for backing down.Consequently, when leaders who face high audience costs do decide to run the riskof incurring the costs associated with initiating a public dispute, it is very unlikelythey will back down in the face of resistance. If such a leader were going to backdown in the face of resistance, she would have rather not initiated than incur thecosts of backing down.

PETER J. PARTELL AND GLENN PALMER 391

A third hypothesis is that in disputes in which both sides decide to escalate, theobservable balance of capabilities should be unrelated to which side backs down.This is so because states “select themselves” into serious crises on the basis of thebalance of capabilities. Once a state decides to escalate, it no longer considers thebalance of capabilities when making decisions about intra-dispute behavior. Accord-ing to Fearon’s model, the outcome of disputes in which both sides signal awillingness to escalate is solely a function of the relative audience costs of theparticipants.

The final hypothesis that we subject to empirical testing is that leaders who facehigh audience costs will pursue more escalatory strategies of crisis managementwhen they face low-audience-cost states than when they face other high-audience-cost states. In Fearon’s model, when two opponents have the same audience-costrates, the risk of war proves to be independent of the audience-cost rate (1994: 586).As audience-cost rates diverge, however, the lower audience-cost state has anincreasing incentive to back down while the high-audience-cost state has an increas-ing incentive to escalate. Generally, Fearon states, the risk of war is increased inthese situations: “The net effect [of a divergence in audience costs] on the risk ofwar may be positive or negative, but it is positive for a broad range of parametervalues” (1994:586). This result may suggest an explanation for the empirical findingthat wars have occurred between democratic and nondemocratic states but notbetween democratic states, if it is the case that democracies face higher audiencecosts than nondemocracies.

Data and Measurement

We use the Correlates of War Project’s Militarized Interstate Dispute, 1816–1992(MID) data set to test Fearon’s model of interstate crises. The MID data set is wellsuited for this task. To be included in the MID set, one state (as defined by Smalland Singer [1982]) must threaten, display, or use military force against anotherstate. The action must be explicit and state-sanctioned, that is, a product orconsequence of governmental decision-making (Gochman and Maoz, 1984:194–95;see also Jones, Bremer, and Singer, 1996). In addition, actions taken in MIDs arerequired to be “overt”—no covert activities are included. An important element ofFearon’s model is that the costly signals that states send to each other must be visibleto the leaders’ respective domestic audiences. The requirement that actions codedin the MID set must be overt ensures that MIDs are publicly viewed contests betweenstates and therefore the type of costly signaling that Fearon discusses should takeplace in the events recorded in the MID set.

The MID set contains both bilateral and multilateral disputes. Multilateraldisputes are those that contain multiple interstate actors on either one or both sidesof the dispute. These are troublesome given the hypotheses to be tested since it isdifficult to characterize the leadership structure of a group or coalition of countries.For example, how should the Allied powers during the Second World War be codedwhen both high- and low-audience-cost states fought alongside one another? Dixon(1994) chose to use the political structure of the strongest state on each side of aconflict as the indicator of that side’s decision-making structure, but it is not alwaysclear that the strongest party directs the behavior of its coalition partners duringdisputes. In such instances, it is conceivable that the dispute side would be consid-ered high-audience-cost, while the actions observed were taken by one of thecoalition members facing low audience costs. To avoid such possible difficulties, wesimply exclude all multilateral disputes and examine only the 1,705 bilateralconflicts in the MID set, though missing data for some of the indicators lower thisnumber of cases.

392 Audience Costs

One striking feature of the MID data set is the infrequency with which we observestates backing down in militarized disputes: in only 123 of the 1,463 bilateral MIDsin our sample does one side back down. To truly digest the infrequency of thisphenomenon consider that in the MID set as a whole (2,034 cases), a dispute is morelikely to result in interstate war (using the 1,000 battle death criterion) than it is toend with the initiating side backing down (81 MIDs end in war and 58 MIDs endwith a yield by side A). Even though it is more likely for one disputant to back down(making no distinction between initiator and target) than it is for the dispute toescalate to war, one might conclude from these frequencies that Fearon’s model, inmaking predictions about which side in a dispute is likely to back down, empiricallypertains to a fairly rare phenomenon.

Alternatively, an objection might be raised about drawing this conclusion basedsolely on the MID data set. Perhaps the unique coding rules of the MID data set areresponsible for the large number of “ties,” which we define as neither side backingdown, using the MID outcome categories “compromise” (82 cases) and “stalemate”(1,024 cases). While Fearon’s model tells us which state should be expected to makea larger concession in those crises that end in compromise, the MID data set doesnot carry such information. If it did, the number of disputes that fall into our “tie”category would be reduced, and the number of cases that Fearon’s model might beable to explain would be slightly larger.2 As for the stalemates, Fearon excludesthese outcomes from his game structure, so that all crises end either in war or withone side backing down. We suspect, but do not know, that many of the MIDs thatare coded as stalemates are not resolved and thus the participants fight over thesame issues in subsequent disputes. Since the MID set does not allow for thegrouping of multiple disputes over the same issue into a single prolonged conflict,we are left with a large and possibly inflated number of stalemates.

A final and related possible objection requires exploration. It may be that theMID data set is less willing to label dispute outcomes as yields for one side or theother than would many analysts. In that case, the MID data set may operateaccording to excessively strict or even arbitrary coding rules that make it inappro-priate for analyzing the determinants of the crisis outcomes.3 There is no objectivemanner to determine whether there are “too many” stalemates in the MID data set,but we can address the question of whether the MID data set is stricter than othersources in assigning a “yield” to its cases. To determine this, we investigated howfour sources coded the crises analyzed in Lebow, 1981. The summary of thecomparison is shown in Table 1. As the table illustrates, the outcomes as coded bythe MID data set are in agreement with the large majority of other outcomes,sometimes surprisingly so. Both Lebow (1981) and Leng (1993) are in agreementwith the MID data set in all but one overlapping case, that of the Berlin Blockade.It is worth noting that Snyder and Diesing (1977) are apparently more hesitant toascribe “yields” to a crisis, disagreeing with Lebow (1981), Leng (1993), and theMID data set on the coding of Munich and the Cuban Missile Crisis. It would seemthat the MID data set is about as likely to code a given crisis as ending in a “yield”

2 If this were the case, then the limited number of “yields” would imply that use of the MID data comprises a relativelyeasy test for Fearon’s model, since those “yields” would almost certainly be the unambiguous ones. Other outcomes thatmight be “weak yields” or “compromises,” and that might be more difficult to predict are categorized as “stalemates.”We are grateful to one of the reviewers for this point.

3 A “yield” in a MID is “defined by the coerced submission by one state to the demands made by another state butshort of any clear alteration of the status quo directly attributable to the threat, display or use of military force. . . . [A]yield can be identified whenever one state capitulates by offering concessions which appease the demands of anotherstate before the militarized forces of either state has secured any substantial tactical gains on the battlefield” (Jones,Bremer, and Singer, 1996:180).


as are other scholars.4 While the MID data set aims to include all instances ofinterstate threat, display, or use of force, analysts who use case studies to test theirhypotheses may sometimes—understandably—select cases on a nonrandom basis.

Finally, Fearon’s model is generally applicable to crises where each side hasinvolved itself sufficiently so as to generate high audience costs if it is able. The MIDdata set does not allow us to determine whether that point was reached in a givendispute. We believe that when the target state in the dispute responds to the initiatorwith its own threat, display, or use of force (i.e., when the dispute is reciprocated),the expectations of Fearon’s model obtain. We also believe, however, that the pointwhere the target has achieved sufficient involvement may occur below the levelwhere the MID data set would record a response. That is, some MIDs that are codedas nonreciprocated may nonetheless have met Fearon’s criterion for high mutualinvolvement. Indeed, there are eleven MIDs in which the target took no action butwhere the initiator is coded as yielding; in those instances, the target was clearlyinvolved even though there is no coded action. For that reason, we conduct ouranalyses separately on all MIDs and on reciprocated MIDs.

Analysis

The first of Fearon’s hypotheses is that in public disputes, the leader facing higheraudience costs should be significantly less likely to back down. To test this hypothesiswe conduct a series of ordinal, or ordered, logit analyses where the dependentvariable is a trichotomous measure of MID outcomes measured from the perspectiveof the MID initiator5 (0 = initiator backed down, 1 = neither side backed down,

TABLE 1. Comparison of the Codings of Crisis Outcomes

CASE MID Lebow Snyder and LengDeising

Fashoda, 1898 Yield by France Yield by France Yield by France Defeat forFrance

Korea, 1903–1904 War War — —Moroccan Crisis, — Compromise Yield by Defeat for1905–1906 Germany GermanyBosnian Annexation, Yield by Yield by Yield by Defeat for1908 Serbia Serbia Serbia SerbiaMoroccan Crisis, 1911 Compromise Compromise Compromise CompromiseJuly, 1914 War War War WarRhineland, 1936 Yield by Yield by Yield by Defeat for

France France France FranceMunich, 1938 Yield by UK, Yield by UK, Compromise Defeat by UK,

France France FranceBerlin, 1948 Stalemate Yield by USSR Yield by USSR Defeat for

USSRKorea, 1950 War War — —Cuban Missile Crisis, Yield by Yield by Compromise Defeat for1962 USSR USSR USSRSino-India, 1962 War War — —Arab-Israeli, 1967 War War — —

Sources: Lebow, 1981; Snyder and Deising, 1977; Leng, 1993.

4 It is worth pointing out that the relative infrequency of back downs is not peculiar to the MID data set. In a similarsample of International Crisis Behavior project crises (not used herein), only 11 percent of the cases involved one sidebacking down as measured by a value of 4 (defeat) on the outcome variable contained in that data set.

5 The initiator is the state that is the first to use at least a threat of force. The target of the MID is the state at whichthe initiator’s militarized action is directed.

394 Audience Costs

2 = target backed down). In the 1,463 disputes that are used in the analyses thatfollow, the target yields in 85, the initiator yields in 38, and neither yields in 1,340.The fact that the middle category is so large does not influence the statistical resultsin any way other than that the models predict that most disputes will end in thatmiddle category.

The issue of how to measure audience costs is slightly involved. In a recent study,Eyerman and Hart (1996) use various measures of democracy (Polity III, Maoz andRussett [1993], Freedom House, and Ray [1993]) to measure audience costs. AsFearon recognizes, democratic states tend to face stronger domestic audiences thanother types of states. However, the use of a state’s democratic status is problematicbecause audience costs can be incurred by undemocratic states as well. Fearon, forexample, points out that the Politburo held the ability to punish Soviet leaders inthe post-Stalin Soviet Union and that Khrushchev may have been removed fromoffice as a result of his handling of the Cuban Missile Crisis. Using democracy as ameasure of audience costs thus runs the risk of including high-audience-cost statesamong the group of states that are supposedly free from such constraints. To trulymeasure audience costs one would need to measure the likelihood that a leader willbe removed from office in the event that she fails in the foreign-policy arena.

Partell (1997b) argued that the amount of institutional constraint faced by anexecutive is a reasonable measure of potential audience costs. While not ideal in thesense that it does not address the likelihood of removal from office or the ability ofthe leader to generate actual audience costs, this measure does tap the extent towhich a leader can institute policy unilaterally. We argue that the more a leader isconstrained in her ability to implement policy on her own, the more reliant she ison others for her position of authority, and thus the more likely it is that she can beremoved from office if she fails to perform her duties to the satisfaction of others inthe political system. This measure avoids the problems incurred by using democraticstatus, and also has a certain degree of face validity—for example, the constraintson Khrushchev are visible using this second measure.

In this article we use both measures based on democratic status and measuresbased on executive constraint to test Fearon’s hypotheses. The domestic politicalvariables used to test hypothesis 1 are taken from the Polity III data set. We use fourdifferent methods of assessing the relative degree to which each dispute participantfaces audience costs. Each method involves the creation of a pair of dummy variables.

The first method compares the initiator’s score on Polity III’s 11-point institu-tionalized democracy index to the target’s score on this index. If the initiator has ahigher score, a dummy variable is coded 1; otherwise, this dummy is coded 0. If thetarget has a higher democracy score, a second dummy variable is coded 1; otherwise,this second dummy is coded 0. The second method we use to assess relative audiencecosts compares the initiator’s score on Polity III’s 7-point measure of executiveconstraints6 to the target’s score on this measure. As with the first measure ofaudience costs, two dummy variables are created. The first is coded 1 when theinitiator’s executive constraint score is higher than the target’s and 0 otherwise; anda second dummy variable is coded 1 if the target’s score is higher than the initiator’sand 0 otherwise.7

6 The Polity II codebook (Gurr, Jaggers, and Moore, 1989:15) describes this indicator as measuring “the extent ofinstitutionalized constraints on the decision-making powers of chief executives, whether individuals or collectivities.Such limitations may be imposed by ‘accountability groups.’ In Western democracies these are usually legislatures. Otherkinds of accountability groups are the ruling party in a one-party state; councils of nobles or powerful advisors inmonarchies; the military in coup-prone polities; and in many states a strong, independent judiciary.” This scale rangesfrom 1 (“Unlimited Authority”) to 7 (“Executive Parity or Subordination”).

7 Gleditsch and Ward (1996) show that the Polity III measure of executive constraints is the most importantcomponent of the Polity III institutionalized democracy score. It is therefore unsurprising that the correlation between


The third and fourth methods used to assess relative audience costs are similarto the first two, but each involves an additional step. Before comparing theparticipants’ scores to each other, we first designate each as either democratic ornot (in the case of the institutionalized democracy index) and as either constrainedor not (in the case of the executive constraints measure). We designate a disputeparticipant as democratic if its institutional democracy score is greater than 5. Astate is coded as highly constrained if its executive constraints score is greater than2.8 Once this is done for both the initiator and target, we compare their designations.Thus, under the third method of assessing relative audience costs we code a dummyvariable 1 when the initiator is democratic and the target is not (this dummy is coded0 otherwise), and a second dummy is coded 1 when the target is democratic whilethe initiator is not (and 0 otherwise). The fourth method utilizes a dummy variablethat is coded 1 when the initiator is constrained while the target is not (and 0otherwise), and a second dummy coded 1 when the target is constrained while theinitiator is not (and 0 otherwise).

While these measures may seem complicated at first, they allow for a nicecomparison of the domestic political structures of dispute combatants. Notice thatunder each of the four methods of assessing relative audience costs, both dummiesin the pair can take on the value of zero. For example, under the first method, thiswill occur when the initiator and target have equal scores on Polity III’s institution-alized democracy index. Under the fourth method, this will occur in disputesbetween two constrained states and in disputes between two nonconstrained states.Because of this coding scheme, the intercepts in the regression models that followrepresent the disputes for which both dummy variables are coded zero—thedisputes between states facing equal levels of audience costs according to therespective measures employed.

Last, we include a variable that measures the relative capabilities of the disputeparticipants. Fearon’s third hypothesis predicts that relative capability should beunrelated to the outcome in disputes where both sides escalate. If that hypothesisis not supported, then analyses of dispute outcomes would be misspecified if theyexcluded relative capability.9 We measure this with the ratio of the initiator’snational capability to the sum of the initiator’s and the target’s capabilities. Theresulting variable takes on values between zero and one, with larger numbersreflecting relatively more powerful initiators. To measure the capabilities of the

these first two measures of executive constraints is high. For both initiators and targets, the correlation between beingmore democratic and more constrained is .74.

8 In the case of the democracy indicator, the results are not sensitive to this cut-off point; raising the cut-point toother levels alters the results of the analysis only very slightly. In the case of the executive constraints measure, increasingthe cut-off point from 2 tends to weaken the results. We believe that we have chosen the most theoretically justifiedcut-off, as the difference between the presence of “slight constraints” (category 3) and no constraints (category 1) islarger and more important theoretically than the difference between, for example, “substantial limitations on executiveauthority” (category 5) and “executive parity” (category 7). On theoretical grounds, we think this is the correct decision.

Second, we view the “executive constraint” variable as capturing a somewhat different notion from the democracymeasure. We chose the executive-constraint cut-off with an eye toward avoiding undesired collinearity between the twovariables. The correlations between our measure of democracy (with a cut-point of greater than 5) and the measure of“constrained” at various cut-points for the latter are:

Constraint cut-off is greater than Tau-b with the measure of democracy1 .4502 .4943 .8084 .8365 .8506 .827

The correlation with democracy gets very high for cut-points greater than 2, and we believe that represents the bestvalue to dichotomize the variable on theoretical and methodological grounds.

9 The results of the analysis done with or without this variable are almost identical.

396 Audience Costs

dispute participants, we use the Correlates of War Project’s data on nationalcapabilities to create the Composite Index of National Capability (CINC) as de-scribed by Singer, Bremer, and Stuckey (1972).

The results using each of these four measures of audience costs are shown inTable 2. All four methods of measuring relative audience costs produce statisticallysignificant regression models as evidenced by the chi-square statistics at the bottomof the table.10 All of the measures of audience costs are in the hypothesized direction,with six of the eight coefficients statistically significant. The results seem to suggestthat the initiator’s ability to incur higher audience costs makes it more likely thatthe target will yield (y = 2) and that an ability to incur greater audience costs on thepart of the target will make it more likely that the initiator will yield (y = 0), as ispredicted by Fearon’s model. The control variable, “Power Ratio,” is statisticallysignificant and positive in all four models: the stronger relative to the target theinitiator is, the more likely the target will yield, other things being equal. (Recallthat Fearon’s model predicts this variable will have no effect on the outcome inreciprocated conflicts—and Table 2 reports analysis of all conflicts.)

The second hypothesis that we test is that states that are better able to generateaudience costs are less likely to attempt “limited probes” in foreign policy. By“limited probe,” Fearon means a situation in which the initiator of a dispute backsoff after meeting resistance from the target state. Further, the third hypothesis statesthat in instances where the target resists the initiator by reciprocating the dispute,the relative capabilities of the adversaries should not affect the outcome. Table 3shows the results of an ordered logit analysis where the dependent variable, as inTable 2, is trichotomous (0 = initiator yielded, 1 = no yield, 2 = target yielded),but the analysis is limited to include only those 694 disputes in which the target tookaction in response to the initiator’s challenge (reciprocated disputes). The inde-pendent variables in the analysis in Table 3 are the same as in the previous table.

Table 3 provides some modest support for hypothesis 2. When executive con-straints are used to designate states as capable or not of generating high audiencecosts (Method 4), there is some evidence that high-audience-cost initiators are lesslikely to yield than other initiators. The results presented in Table 3 also show thatdemocratic initiators are not less likely to back down than nondemocratic initiators.Apparently it is constraints to which the executive is subject specifically, rather thandemocratic characteristics more generally, that affect the state’s ability to incuraudience costs. Executive constraints are a better predictor of who will back downin a dispute than democratic status.

Interestingly, we find that the relative capability of the disputants does not affectthe outcome in any of the four models of reciprocated disputes, just as Fearon’smodel predicts. This is different from our earlier finding from the sample of allbilateral disputes: the stronger the initiator, the more likely the target is to backdown. Given the willingness of the target to reciprocate the dispute, the outcome isindependent of relative capability. Apparently, the demonstration of resolve has theeffect posited by Fearon’s model, and the establishment of greater commitmentthrough the acceptance of higher audience costs affects the dispute outcome.11

Before continuing with the tests of the remaining hypotheses, we need to examinethe results thus far more carefully. It is not sufficient to accept the signs of thecoefficients as tests of Fearon’s hypotheses. Greene (1993), for instance, warns

10 See King, 1989:84, and Aldrich and Nelson, 1986:59, for a discussion of this likelihood ratio test.11 Morgan and Palmer (1997) found that weaker states are more likely to reciprocate a dispute than are stronger

states. In conjunction with the current finding, weaker states that reciprocate apparently succeed in demonstratingresolve and thereby avoid the necessity of yielding. Similarly, Bueno de Mesquita, Morrow, and Zorick (1997) find acurvilinear relationship between relative capabilities and the likelihood of violence, with weaker targets more likely touse violence than targets that are about equal in power to the initiator.


against interpreting the signs of coefficients in ordered logit models withoutexamining the effects that each variable has on the likelihood that each case will fallinto a particular category of the dependent variable.12 In Table 4, we present theconditional probabilities that are predicted by the models in Tables 2 and 3. In eachcase, to obtain the predicted probabilities we held the power ratio of the disputantsconstant at their mean values (.56 for all disputes and .53 for the reciprocateddisputes).

Table 4 shows that in all situations where the target is structurally more able toincur high audience costs than is the initiator (either because it is democratic orbecause its executive is constrained), the probability that the initiator will yield is

12 Greene (1993:673) shows that these categorical probabilities can be derived using the following formulae:Prob(y=0) = Φ(–ß’x)

Prob(y=1) = Φ(µ1 – ß’x) – Φ(–ß’x)

Prob(y=2) = Φ(µ2 – ß’x) – Φ(µ1 – ß’x)

. .

. .

Prob(y=j) = 1 – Φ(µj-1 – ß’x)

where Φ is the probability function (here logit), ß is the estimated coefficient for variable x, and the µ’s are the estimatedthreshold values for each y category. In this case the logit function is utilized so Φ = (eß’x / (1+eß’x)).

TABLE 2. Ordered Logit Regression of MID Outcomes (N = 1463)

METHOD 1 METHOD 2 METHOD 3 METHOD 4Coefficient Coefficient Coefficient Coefficient

Variable (Std. Error) (Std. Error) (Std. Error) (Std. Error)

Constant 3.418*** 3.715*** 3.405*** 3.338***(.324) (.291) (.243) (.253)

Initiator more democratic .540** — — —(.251)

Target more democratic –.668** — — —(.296)

Initiator more constrained — .150 — —(.232)

Target more constrained — –1.021*** — —(.279)

Initiator democratic and target not — — .271 —(.232)

Target democratic and initiator not — — –.702*** —(.275)

Initiator constrained and target not — — — .582***(.218)

Target constrained and initiator not — — — –.741***(.282)

Power ratio .869*** .908*** .894*** .934***(.305) (.303) (.316) (.300)

µ2 6.764*** 6.796*** 6.652*** 6.719***(.218) (.223) (.212) (.219)

LL Full Model –477.86 –476.97 –484.43 –480.30LL Null Model –498.28 –498.28 –498.28 –498.28Chi-squared 40.84 42.62 27.71 35.96Significance .0000 .0000 .0000 .0000

One-tailed significance levels reported (*p < .10; **p < .05; ***p < .01).

398 Audience Costs

higher than that probability for the target. Similarly, in all instances where theinitiator is better suited to impose high audience costs on itself, the probability thatthe target will yield is higher. The probabilities indicate that Method 3 does notperform strongly, particularly when the analysis is confined to reciprocated dis-putes. Method 4, which determines whether the target or the initiator is constrained,performs very well both for reciprocated and for all disputes. As was the case withour initial interpretation of the coefficients, it appears that the constraints placedupon the executive specifically, rather than the democratic structure of the politicalsystem generally, are more likely to affect the state’s ability to incur high audiencecosts. This is consistent with Fearon’s model.

With the large number of stalemates/compromises in the data, we might learnsomething about the importance of audience costs by restricting the analysis to the123 MIDs in which one side yielded. In other words, we exclude all disputes thatfall into the middle category. Table 5 shows the results of such a logit regressionwhere the dependent variable is now a dichotomous indicator of which side in thedispute yielded (1 = target yielded, 0 = initiator yielded). All of the models aresignificant, and all the coefficients are in the anticipated direction (save for that on“Initiator More Constrained”), but only the variables measured by Method 4 havecoefficients that are both statistically significant and in the correct direction. It isinteresting to note that the models that use “democracy” predict slightly less well inthis analysis than the models using “executive constraint.” This is consistent withFearon’s point that while democracies, in general, face higher audience costs than

TABLE 3. Ordered Logit Regression of Reciprocated MID Outcomes (N = 694)



Constant 3.001*** 3.327*** 3.031*** 3.269***(.411) (.358) (.297) (.343)

Initiator more democratic .464 — — —(.420)

Target more democratic –.361 — — —(.417)

Initiator more constrained — .128 — —(.374)

Target more constrained — –.816** — —(.394)

Initiator democratic and target not — — –.007 —(.437)

Target democratic and initiator not — — –.431 —(.364)

Initiator constrained and target not — — — .480*(.356)

Target constrained and initiator not — — — –1.018***(.415)

Power ratio .541 .571 .643 .552(.508) (.515) (.508) (.502)

µ2 6.733*** 6.799*** 6.662*** 6.887***(.309) (.324) (.299) (.339)

LL Full Model –210.46 –208.94 –212.13 –206.74LL Null Model –214.17 –214.17 –214.17 –214.17Chi-squared 7.43 10.46 4.09 14.87Significance .0593 .0150 .2520 .0019



other states, nondemocratic states too can have high audience costs. Also, it issurprising that the political characteristics of the target have a much stronger effecton the outcome than do the characteristics of the initiator.

Finally, note that the power ratio of the two states strongly affects which backsdown—the stronger state is advantaged, other things being equal. Recall that thepower ratio had an effect in determining which side yielded in all disputes, but thatits effect in reciprocated disputes was not statistically significant, as Fearon’s modelpredicts. It appears, then, that relative capability in a dispute helps determine whichside will yield in the early stages of the dispute (i.e., before the dispute becomesreciprocated); and relative capability affects which side will prevail given that oneside or the other yields. As Fearon’s model leads us to expect, however, the relativecapability of the disputants generally does not have an effect in reciprocateddisputes.

The fourth hypothesis we test is that states capable of generating high audiencecosts should tend to pursue more escalatory strategies when they face states less ableto generate audience costs than when they face fellow high-audience-cost-generatingstates. This is the mechanism in the model that Fearon claims can explain whydemocracies do not go to war with each other, but still go to war with nondemocra-cies (if it is true that on average democracies face higher audience costs than otherstates): “democratic leaders have a structural incentive to pursue more escalatory,committing strategies when they face authoritarians than when they face fellowdemocrats” (Fearon, 1994:586).

To test this hypothesis we look at the escalation of disputes through the four stagesof hostility: threat of force, display of force, use of force, and war.13 Specifically, we

TABLE 4. Conditional Probabilities

All ReciprocatedCondition Disputes Disputes

Probability Probability Probability ProbabilityTarget Initiator Target InitiatorYields Yields Yields Yields

METHOD 1Target more democratic .029 .038 .022 .051Equally democratic .054 .020 .031 .036Initiator more democratic .090 .011 .048 .023

METHOD 2Target more constrained .027 .039 .018 .057Equally constrained .071 .014 .040 .026Initiator more constrained .081 .012 .046 .023

METHOD 3Target democratic, initiator not .031 .039 .024 .050Equally democratic .060 .020 .036 .033Initiator democratic, target not .078 .015 .036 .033

METHOD 4Target constrained, initiator not .027 .042 .013 .073Equally constrained .054 .021 .035 .028Initiator constrained, target not .093 .011 .055 .017

13 The definition of “war” is the standard Correlates of War 1,000-battle deaths threshold. For operational definitionsof the other steps, see Jones, Bremer, and Singer, 1996. These steps have been used in previous analyses of the escalation

400 Audience Costs

use three dependent variables: first, we determine whether a dispute (which, bydefinition, entails at least a threat of force) escalates to the display of force; second,we determine whether disputes that have achieved the level of display of forceescalate to the use of force; and, finally, we see whether disputes that have reachedthe level of the use of force escalate to war. In adopting this design, we restrict thecases analyzed in each escalatory stage to those that have achieved the precedingstage. For instance, only disputes that have reached the stage of use of force areanalyzed when we investigate the escalation to war.

We test two models using each of the three dependent variables. Each modelcontains two dummy variables. The first model’s dummy variables measure whetherboth parties to a dispute are democratic or not (1 = yes, 0 = no) and whether thedisputing dyad contains only one democratic state (1 = yes, 0 = no). The secondmodel has two dummies, reflecting whether both parties to a dispute were con-strained (1 = yes, 0 = no), or whether only one state was constrained (1 = yes,0 = no). The likelihood of escalation for the third category of dyads (two nonde-mocracies/two nonconstrained states) is measured by the intercept. Fearon’s modelpredicts that the coefficients on the variables measuring joint democracy and jointexecutive constraints should be negative. The model’s expectations of the coefficients

TABLE 5. Logit Regression of MID Outcomes in Disputes in Which OneSide Yielded (N = 123)



Constant .410 .637 .110 –.133(.658) (.571) (.435) (.480)

Initiator more democratic .186 — — —(.607)

Target more democratic –1.538*** — — —(.633)

Initiator more constrained — –.217 — —(.579)

Target more constrained — –2.071*** — —(.600)

Initiator democratic and target not — — .230 —(.561)

Target democratic and initiator not — — –1.455*** —(.555)

Initiator constrained and target not — — — 1.040**(.566)

Target constrained and initiator not — — — –1.490***(.580)

Power ratio 1.434** 1.601** 1.606*** 1.678***(.680) (.690) (.689) (.675)

LL Full Model –63.74 –61.64 –66.47 –63.08LL Null Model –76.05 –76.05 –76.05 –76.05Chi-squared 24.61 28.80 19.16 25.92Significance .0000 .0000 .0003 .0000Percent correctly predicted 73 77 73 76


of disputes to war. See, for instance, Maoz and Abdolali, 1989, Bueno de Mesquita and Lalman, 1992, Ray, 1995, andSenese, 1996, 1997. A recent work that analyzes MID outcomes is Mousseau, 1998.


on the variables indicating mixed dyads are more ambiguous: generally, mixeddyads should be more likely to escalate than dyads consisting exclusively of low-audi-ence-cost states, though there are some circumstances under which they may be lesslikely to escalate than those dyads (Fearon, 1994:fn. 26). In each model we includethe power ratio of the disputants as a control variable.14

The results of this analysis are presented in Table 6. The table shows the analysisof the two models on each of the three dependent variables capturing the escalationof the disputes. The results give some limited support to this hypothesis. First, thecoefficient on the “Democratic–Democratic” variable is in the anticipated negativedirection and statistically significant in the “Threat-to-Display” model only: jointlydemocratic disputants are less likely to escalate beyond the threat of force, but thereis no statistically significant effect after that stage. Indeed, the coefficient on jointdemocracy on the escalation from the display to the use of force is weakly positive.This is similar to Senese’s (1997) finding that disputes consisting of two democraciesare more likely to escalate to the use of force than are other types of disputes. Second,the variable capturing whether the two states involved in the dispute are eachconstrained performs a little better. Disputes between two states with highly con-strained executives are less likely to escalate through the threat and through thedisplay of force, as Fearon’s model predicts. Neither statistical model, however,explains the escalation from use of force to war. Indeed, even the power ratiovariable is not statistically significant and the equations themselves are not signifi-cant. Overall, the fourth hypothesis has some modest statistical support.

Discussion and Conclusions

In evaluating a theory, it is very helpful to have all the hypotheses either supportedor rejected. Under such conditions, it is easy to make an assessment of the overallusefulness of the theory. Unfortunately, this rarely happens, and the present workis no exception. However, the weight of the evidence found herein seems to be infavor of Fearon’s model of interstate crises. Support is found in one form or anotherfor all of the hypotheses tested. First, states that are structurally better able togenerate high audience costs, either because they are democratic or more particu-larly because they have a politically constrained executive, tend to be more able toprevail in disputes. Second, such states are less likely to back down once theyencounter resistance in a crisis. Third, the relative capability of the crisis participantsdoes not affect the outcome once the dispute is reciprocated, as Fearon’s modelpredicts; however, in all disputes, the weaker state is more likely to yield. Last,disputes between two states that are both able to demonstrate high audience costsare slightly less likely to escalate to the display of force, and disputes between twoconstrained states are less likely to escalate to the use of force.

Some minor questions are raised about the applicability of Fearon’s model toreal-world crises. Foremost is the issue of stalemates. Recall that about 8.5 percentof the MIDs used here end in one side backing down. We argued that this relativelylow figure is primarily due to the large number of cases included in the data set,and not in the coding rules for the outcome. We note that in another widely usedlarge-N sample, the International Crisis Behavior data set (Brecher and Wilkenfeld,1992), about 11 percent of the cases have one side or the other backing down (seefootnote 4). Further investigation must take place to determine the reason the MID

14 Fearon argues that the relative capability of the disputants should have no effect on the outcome when both sidesescalate sufficiently so as to incur some domestic audience costs. If the incursion of those costs is related to the stage ofescalation then relative capability should have less of an effect on the likelihood of further escalation as we move upthrough the escalatory process. This is a strong condition and it is necessary for the expectation. We therefore do notview Fearon’s model as directly implying this diminishing effect of relative capability.

402 Audience Costs

TABLE 6. Democracy, Executive Constraints, and the Escalation of Disputes

Variable Threat → Display Display → Use Use → War

Constant 3.578*** 3.835*** 1.614*** 1.702*** –3.537*** –3.693***(.313) (.488) (.155) (.488) (.435) (.632)

Democratic– –.830** — .244 — –.940 —Democratic (.405) (.280) (1.041)

Democratic– –.262 — –.038 — –.371 —Nondemocratic (.264) (.132) (.391)

Constrained– — –.769** — –.276* — –.340Constrained (.448) (.205) (.623)

Constrained– — –.256 — –.066 — .070Nonconstrained (.458) (.204) (.560)

Power ratio –.680** –.691** –.718*** –.732*** .260 .276(.382) (.386) (.200) (.204) (.593) (.587)

LL Full Model –283.53 –282.62 –746.64 –743.94 –128.66 –128.99

LL Null Model –287.03 –287.03 –753.82 –753.82 –129.59 –129.59

Chi-squared 7.00 8.82 14.37 19.76 1.85 1.19

Significance .072 .032 .002 .000 .604 .754

N 1463 1463 1391 1391 1068 1068


and ICB data sets contain so many stalemates. If these are simply disputes and crisesthat are recurring over the same, unsettled issue, then Fearon’s model need notaccount for them—this is a problem with the way the data were collected. If, on theother hand, these stalemated disputes and crises are unrelated to one another, thenthere is a very large number of events in the world that Fearon’s model currentlysays nothing about. While Fearon’s model may be extended to incorporate stale-mates as an outcome, we are not able now to determine the empirical utility in doingso. That sort of investigation is beyond the scope of the current project; however, itis an important next step.

One of the primary criticisms leveled against formal models of political phenom-ena is that the hypotheses produced are seldom empirically verified. In this piecewe have subjected a portion of a prominent formal model of international politicsto a variety of empirical tests. In sum, the results suggest that audience costs exertinfluence over which side to a dispute will back down, but the connection betweenaudience costs and the democratic peace is not clear.15

Despite the shortcomings of the theory in this regard, in other aspects of disputebehavior, Fearon’s model reveals some interesting dynamics and this is testimonyto the usefulness of formal models of politics. In particular, the hypothesis that states“select” themselves into and out of serious crises based on their assessment of relativecapability shows some support—in disputes in which both sides choose to escalate,which side backs down is independent of which side is stronger. This finding mayhave profound implications for the way in which we think about bargaining ininternational crises and has already been used to test other hypotheses on thedemocratic peace (Siverson, 1996). Selection-effect notions have also been used tointerpret puzzling empirical results pertaining to the intra-dispute behavior of states(Partell, 1997a). For these reasons, formal modeling techniques can be powerfultools in the study of politics, provided they are coupled with rigorous empiricaltesting.

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