diversionary despots? comparing autocracies' propensities to use and to benefit from military...

Diversionary Despots? Comparing Autocracies’Propensities to Use and to Benefit from Military Force

Jeffrey Pickering Kansas State UniversityEmizet F. Kisangani Kansas State University

This article adds to recent research that has begun to systematically analyze the varied conflict propensities of autocracies.Using political incentive theory, we develop hypotheses on the diversionary proclivities of three distinct types of autocraticregimes that contradict conventional wisdom and the findings of recent empirical studies. To provide a full rendering ofautocracies’ diversionary tendencies, we test our hypotheses with Generalized Method of Moments (GMM) models thatcapture reciprocal relationships among external military force and four of its potential domestic causes from 1950 to 2005.Although our results provide only partial support for political incentive theory, they demonstrate the utility of using properlyidentified reciprocal models and of analyzing refined conceptualizations of autocratic regimes. We find that certain types ofautocracies are more prone to use diversionary force and to benefit from it than others.

Until recently, few attempts have been madeto develop systematic knowledge on the con-flict behavior of different types of authoritarian

regimes. As the body of evidence supporting the demo-cratic peace has grown deeper and more nuanced, an-alytic attention has understandably focused on the for-eign policy behavior of democracies. However, even afterthe “Third Wave” of democratization following the endof the Cold War, as many as half of the world’s coun-tries remain undemocratic. The advances that scholarshave made to understand the foreign policy behavior ofdemocracies have thus overlooked what have historicallybeen the bulk of the world’s states holding the vast ma-jority of the world’s population. In this article, we add torecent research that has begun to study the use of militaryforce by different types of autocracies.

The consensus of research to date is that single-partyauthoritarian regimes are less likely to use external mili-tary force than other types of autocratic regimes, of whichthe most common types identified are military regimesand personalist regimes that are dominated by a singlecharismatic individual (Lai and Slater 2006; Peceny, Beer,and Sanchez-Terry 2002). Peceny and Butler even go sofar as to assert that single-party regimes are “the type ofauthoritarian regime with patterns of conflict behavior

Jeffrey Pickering is Professor of Political Science, Kansas State University, 244 Waters Hall, Manhattan, KS 66506 ([email protected]). Emizet F.Kisangani is Professor of Political Science, Kansas State University, 244 Waters Hall, Manhattan, KS 66506 ([email protected]).

A previous version of this article was presented at the 2008 annual meeting of the International Studies Association. We thank JosephAistrup, Andrew Long, three anonymous reviewers, and the editors for helpful comments.

most reminiscent of democracies” (2004, 41). Drawingfrom the insights of Bueno de Mesquita and colleagues’(2003) political incentive theory, we contend that the pre-vailing consensus may have one significant and clearly de-lineable theoretical and empirical limitation. We suspectthat the extant hierarchy that casts single-party regimes asunlikely to use force and other autocracies as highly proneto do so might be reversed when analysis centers on onepotentially prevalent type of external military force: di-versionary force. Diversionary force is external militaryforce used for domestic political reasons, with examplesbeing attempts by the political leadership to shift attentionaway from domestic economic problems or from variousforms of political unrest (James and Rioux 1998; Levy1989).

We put our contention to the empirical test withreciprocal estimates of interstate military force and itspotential domestic causes in a time-series, cross-sectional(TSCS) sample of 140 autocracies from 1950 to 2005. Ourgoal is to develop a more accurate and precise understand-ing of autocratic diversionary behavior. Reciprocal mod-els are well suited for this task because they are method-ologically appropriate for studies of diversion, and theygreatly enhance our ability to comprehend different sets ofactors’ diversionary behavior in large N studies. Their use

American Journal of Political Science, Vol. 54, No. 2, April 2010, Pp. 477–493

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478 JEFFREY PICKERING AND EMIZET F. KISANGANI

has nonetheless been exceedingly rare in the diversionaryliterature to date.

We begin our comparative study of autocratic di-version by discussing the utility of reciprocal analyses ofdiversionary behavior. We then provide a brief review ofthe empirical literature that distinguishes among autoc-racies and their varied propensities to use military force.We turn to political incentive theory to generate our hy-potheses on autocratic force in the third section. Thefourth section outlines political incentive theory’s expec-tations for the reciprocal components of our analysis. Inother words, it presents theory on the impact that ex-ternal military force should have on domestic conditionsacross different autocratic regimes. We present our vari-able measurement and methods in the fifth section, andwe discuss our empirical findings in the sixth section. Weprovide conclusions in the final section of the article.

The Utility of Reciprocal Analyses ofDiversionary Force

Two decades ago, Levy (1989) argued that we must usereciprocal analyses to provide a full rendering of states’diversionary behavior. Few, however, have heeded Levy’scall. To date, only three articles have employed reciprocalestimates of diversionary force and its domestic causes,and each focuses solely on the United States (DeRouen2000; DeRouen and Peake 2002; Wood 2009). This re-luctance to adopt reciprocal methods has, unfortunately,seriously limited the explanatory power of diversionarystudies.

Reciprocal analyses are important because they pro-vide an answer to one of the most vexing criticisms oflarge N research on diversionary force. Detractors havelong held that large N studies can never prove that do-mestic political or economic considerations are foremostin leaders’ minds when they dispatch troops overseas.Leaders may be responding to a range of external stimulithat we cannot fully account for with control variablesin large N studies, and, of course, we will never be ableto read decision makers’ minds (see Hendrickson 2002,31; Levy 1989). If a proportion of the military operationswe presume to be diversionary are actually taken for le-gitimate strategic or geopolitical reasons, our statisticalresults may be both spurious and misleading.

Reciprocal models begin the process of resolving thistheoretical and methodological quandary by determin-ing whether or not the use of interstate military forcegenerates domestic political and economic benefits foractors. If reciprocal estimates show that leaders reap do-

mestic rewards from using military force abroad, theyprovide greater confidence that any statistical correla-tions discovered between domestic explanatory variablesand the dependent variable external military force repre-sent diversionary behavior. If using military force overseascreates or exacerbates domestic problems, doubt is caston the contention that many, if not most, of these mil-itary operations were initiated for diversionary reasons.Decision makers may certainly miscalculate and imple-ment policies that aggravate rather than mollify domesticproblems, but for them to do so consistently with the samepolicy option—interstate military force—across the widerange of countries and the long time spans typical of largeN, cross-national research seems highly improbable. Re-ciprocal models thus not only have commonly acknowl-edged methodological advantages, but they can providewell-defined, concrete advances to theory as well.

Autocratic Regimes and MilitaryForce

We refer to an autocracy as “the rule of a person or agroup of persons who arrogate to themselves and monop-olize power in the state, exercising it without restraint”(Neumann 1957, 161). This definition envisages a num-ber of autocratic subtypes. The most widely used sub-type classification has been advanced by Geddes (1999).Geddes (1999) distinguishes among three types of au-tocratic regimes: single-party regimes, military regimes,and personalist regimes (see also Brooker 2000; Peceny,Beer, and Sanchez-Terry 2002). She defines single-partyregimes as “regimes in which the party has some influenceover policy, controls most access to political power andgovernment jobs, and has functioning local level orga-nizations” (1999, 20). In single-party regimes, the partybasically defines political life in the country by controllingaccess to decision-making authority and providing essen-tial services. Although there are exceptions like Mexico,Senegal, and Taiwan, most single-party states have beensocialist regimes. Military regimes are governed by “an of-ficer or retired officer, with the support of the military es-tablishment and some routine mechanism for high-levelofficers to influence policy choice and appointments”(20). Geddes does not consider states that have experi-enced military rule for fewer than three years to be mili-tary regimes, but rather views these countries to be goingthrough indeterminate periods “. . . of holding customaryrules in temporary abeyance . . . or transition from one setof rules to the next” (18). Finally, personalist regimes arecharacterized by leaders who “have consolidated control

DIVERSIONARY DESPOTS? 479

over policy and recruitment in [their] own hands” (20).These leaders often begin their rule as chief executives inmilitary or single-party regimes, but at some point theysweep challengers within these organizations aside (Ged-des 2006, 138). Of course, not all autocracies fit neatlyinto Geddes’s three-part classification, as she recognizes.She terms regimes with traits from two or more categorieshybrids. Examples include General Zia’s Pakistan that ex-hibited characteristics of both institutionalized militaryrule and personalism and Egypt and Burundi during dif-ferent periods. Hybrids constitute slightly less than 25%of her sample.

Lai and Slater (2006) offer a different classificationscheme for authoritarian governments.1 Their infrastruc-tural power perspective maintains that authoritarian sys-tems should be distinguished by the instruments of powerthat autocrats use to retain office rather than the numberand the professions of the individuals who participate inthe decision-making process. According to Lai and Slater,authoritarian governments ultimately rely on one of twoinstruments of power to rule their societies: the militaryor a single, cohesive political party that penetrates impor-tant segments of society. They consequently code mostof Geddes’s personalist regimes as military regimes, sincemore often than not personalist leaders rely on the repres-sive capacity of the military to remain in office (Lai andSlater 2006, 120, footnote 9). Although Lai and Slater’sinfrastructural power formulation has merit, we useGeddes’s trichotomous framework when crafting our the-ory to provide a more nuanced understanding of auto-cratic diversionary behavior. Geddes’s typology also hasthe advantage of being used in the majority of the stud-ies of comparative autocratic conflict behavior to date,making our findings more broadly comparable to extantresearch.2

Lai and Slater’s (2006) analysis is also the only studyin the comparative autocratic conflict literature groundedin diversionary logic. Lai and Slater maintain that single-party regimes use external military force significantly lessoften than military regimes because they have more sta-

1Danilovic and Clare (2004) use the concepts of vertical and hor-izontal accountability to add a fourth type of authoritarian sys-tem to Geddes’s (1999) classification. While we find merit inDanilovic and Clare’s approach, we employ Geddes’s schema be-cause its prevalence in the literature makes our results directlycomparable to extant research.

2We also ran supplemental analyses on the various hybrid regimesoutlined by Geddes, which account for 23.7% of the total state-years in our sample. We find, as Peceny and Butler (2004) do, thatsubstantively discernable empirical patterns do not emerge whenanalyzing hybrids. Since their ambiguous characteristics also makeit difficult to develop logical hypotheses about their behavior, wedo not present theory or findings on hybrid regimes.

ble governments. Single-party regimes tend to develop anall-encompassing ideology to legitimize their rule, whichrests on public acceptance or at least acquiescence ratherthan brute force. They are typically governed by cohe-sive political elites who operate within broadly acceptedhierarchies. Importantly, the military’s subservient statuswithin the hierarchy is almost always well established.3 Infact, the party is usually intricately connected to nearly allimportant societal organizations in single-party regimes,and it often proves adept at mobilizing the population tofurther the goals of the regime with mass political orga-nizations (see Kasza 1995). This stability and broad legit-imacy has important implications for the foreign policyof single-party regimes. It tends to allow their leaders totake foreign policy decisions on their merits, not becausethey need to win over domestic groups.

In contrast, military regimes “rarely elaborate full-blown regime ideologies to justify long-term authoritar-ian rule . . . [and, as a result] they tend to enjoy less ofa cushion of ideological legitimacy to help them weather. . . tough times” (Lai and Slater 2006, 116–17). The typeof strong-armed rule and repression that military gov-ernments rely on frequently produces brittle regimes.Splintering at the elite level is not uncommon in thesestates, with different sets of military officers attempting towrest power away from competitors (Danopoulos 1988;Wintrobe 1990). According to the infrastructural powerperspective, it is the inherent frailty of military govern-ments that compels the officers in charge to “. . . use for-eign policy to secure loyalty and bolster legitimacy” (Laiand Slater 2006, 117). One way they can do this is bydispatching troops across borders for diversionary pur-poses. Argentina’s occupation of the Falklands/Malvinasislands offers a classic example of a military regime usinginterstate military force for reasons of domestic politicalsurvival (Levy and Vakili 1992).

Although diversionary arguments are not advancedin other empirical studies comparing autocratic regimes’conflict behavior, these studies produce empirical resultsconsistent with Lai and Slater’s outcomes.4 Single-party

3In most socialist single-party regimes, ideological/political officersare assigned to significant military units to ensure fealty to theparty, and promotion is only secured when party mores have beenrespected (see Colton 1979).

4There has been only one other unidirectional cross-national studyof different types of autocracies’ diversionary behavior to date,Pickering and Kisangani (2005). However, in this earlier study, weuse a relatively crude dichotomization of autocracies based uponthe Polity scale rather than the more sophisticated conceptualiza-tions of autocratic regimes that have been common in the compar-ative politics literature and research on autocratic conflict behavior.Our previous results are thus not directly comparable to extant lit-erature on autocratic use of force. Most other empirical studies of


regimes are found to be less prone to use military forcethan other autocratic regime types, particularly personal-ist regimes (Peceny, Beer, and Sanchez-Terry 2002; Pecenyand Beer 2003; Peceny and Butler 2004).5 Political in-centive theory suggests that when it comes to diversion-ary force, the opposite pattern should hold. Single-partyregimes should be more prone to use diversionary forcethan personalist regimes or military regimes, though ex-pectations for the latter are less certain. The followingsection details political incentive theory’s perspective.

Political Incentive Theory andAutocratic Diversion

The benchmark assumption of political incentive theoryis that political leaders want above all else to stay in office(Bueno de Mesquita et al. 2003). They thus continuallystrive to satisfy the domestic constituencies that help tokeep them in power. To facilitate cross-national gener-alization, the political incentive approach separates thesecore domestic constituencies into two groups: selectoratesand winning coalitions. Selectorates are individuals whocan theoretically be part of the leadership selection pro-cess. They are “roughly the citizenry” of a country, all ofwhom stand some chance, albeit sometimes a relativelysmall chance, of influencing the choice of a new leader(Bueno de Mesquita et al. 2003, 40). Winning coalitionsare the subset of the selectorate “who control enough . . .

instruments of power to keep the leader in office” (Buenode Mesquita et al. 2003, 8). The selectorate thus matchesconventional conceptions of a country’s mass populationreasonably well, while winning coalitions are consistentwith common ideas about ruling coalitions and otherelites in society. For reasons of parsimony, we focus onvariations in winning-coalition size when discussing po-litical incentive theory and autocratic diversion.

diversionary force that compare across regime types employ di-chotomous variables separating nondemocracies from democra-cies or three-part classifications that also code mixed regimes. Aseparate handful of studies use continuous measures of regimetype. Oneal and Tir (2006) offer one example of the former ap-proach, while Enterline and Gleditsch (2000) utilize the latter ap-proach. None of these approaches provides the same insight intoautocratic behavior as the more precise and theoretically groundedregime classifications developed by Geddes (1999) and Lai andSlater (2006).

5Although earlier studies do not compare across autocratic regimes,they are also largely consistent with Lai and Slater’s findings. Orenand Hays (1997), for example, find that socialist regimes wereunlikely to fight one another during the Cold War. Weart (1994)finds that established oligarchies, which are conceptually similar tosingle-party regimes, rarely go to war with one another. See Bebler(1987) for an exception.

Political incentive theory postulates that as winningcoalitions grow larger, the delivery of public goods be-comes more important for leaders’ survival in office. As aconsequence, leaders who rely on large winning coalitionsmust perform in office. They must implement successfulpolicies and deliver public goods to members of the win-ning coalition, which often includes large segments of thecountry’s population. The same does not hold for leaderswho preside over small winning coalitions. These actorsoften have little reason to propose policies that deliverpublic goods. They can retain office simply by ensuringthat a steady flow of private goods placates members of thewinning coalition. Leaders who rely on small coalitionscan consequently oversee disastrous policies like sharpeconomic downturns and war defeats without excessivefear of losing office (see Bueno de Mesquita et al. 2003,440). So long as a disproportionate share of the country’swealth is being channeled to elites in the ruling coalition,they will continue to hold power.

Of the three types of autocracies included in Geddes’s(1999) classification, single-party regimes tend to have thelargest winning coalitions (Geddes 2006, 16; Peceny andButler 2004, 574). In these regimes, leaders’ tenure de-pends in one way or another on party members, in partic-ular party elites (Purcell 1973). Personalist regimes shouldhave the smallest winning coalitions, typically a tiny cadreof fiercely loyal cronies. Autocrats in military regimes,who depend to varying degrees on the military highcommand, often have winning coalitions of mixed sizes.Given Geddes’s (1999) categorization scheme, though,they are unlikely to be either as small as those found inpersonalist regimes or as large as in most single-partystates.

If this characterization is correct, one should an-ticipate a much higher quality and quantity of publicgoods provided by single-party regimes than personalistregimes, with the performance of military regimes restingsomewhere in the middle. There is a good deal of evi-dence suggesting that this is the case. Even a casual glanceat the basic public infrastructure such as roads, electric-ity, and transportation systems provided by single-partyregimes in Vietnam, China, Singapore, and PRI Mexicoin comparison to Mobutu’s Zaire, Somoza’s Nicaragua,Niyazov’s Turkmenistan, or Mugabe’s Zimbabwe under-scores the point. It is also not a stretch to claim that, ingeneral, the health care and educational services providedby single-party regimes also tend to be superior to thosefound in personalist regimes (Wintrobe 1990, 866).

Of course, our interest is not in autocracies’ provi-sion of public goods. It is the propensities different typesof autocratic regimes have for using diversionary force.Political incentive theory puts forth a simple calculation


that explains why single-party regimes should have thegreatest proclivity to divert among autocratic regimes.The argument centers on the amount of domestic polit-ical and economic resources leaders have to help themretain office, R, and the amount they routinely need tospend to maintain the support of their winning coalitions,M . The greater the difference between R and M , the easierit is for leaders to weather difficult political or economictimes. Consequently, leaders who operate with only aslight margin of difference between R and M—and thushave relatively few spare domestic resources readily avail-able for political survival—will inevitably look to foreignpolicy for options that might help them maintain powerwhen domestic political or economic challenges arise. Asthe policy availability argument common in diversion-ary literature (Brule 2006; Pickering and Kisangani 2005)contends, diversionary military force may often be one ofthe options they consider.

In political incentive theory, the key considerationdetermining the difference between R and M , (R-M), isthe size of the state’s winning coalition. When the win-ning coalition is relatively large, leaders must spend asignificant proportion of their available resources to re-tain their supporters’ loyalty (Bueno de Mesquita et al.2003, 277–80). The provision of public goods does notcome cheap, and leaders with comparatively large win-ning coalitions must do everything in their power to “de-liver the goods” to the widest possible cross-sections oftheir winning coalitions by implementing successful poli-cies. Leaders with small winning coalitions have a muchsmaller outlay of M , since they only need to line the pock-ets of a small cadre of sycophants.

Following this logic, one can expect personalist lead-ers to accumulate much larger stockpiles of the resourcesnecessary for political survival than leaders in single-partystates. When times turn tough because of economic orpolicy failure, personalist leaders should consequentlyhave greater ability to weather the storm without fearof losing office than their counterparts in single-partyregimes (Bueno de Mesquita et al. 2003, 280). They cantap their presumably massive public and private accountsto increase the flow of private goods to winning-coalitionmembers and to fund increased repression of elite orpublic dissidents.6 Since leaders of single-party states willhave comparatively fewer extra resources (M) for eitherof these survival strategies, buying off cronies or repres-sion, they should be more likely to contemplate the use of

6Because the gap in living standards is so large between those insidetheir small winning coalitions and those outside of it, it will not bedifficult for personalist dictators to find henchmen to crack downon political rivals and protesters (Bueno de Mesquita et al. 2003,343–44).

diversionary force to rally the winning coalition behindthem. This is why Bueno de Mesquita et al. (2003, 219)conclude that “large coalition systems . . . provide incen-tives for leaders to pick on much smaller rival states . . .

[and] to be bullies.”7

Of course, in making comparisons across autocraticregimes, we should not minimize the resources that lead-ers in single-party states have for political survival. Amonga large number of potential examples, Tiananmen Squareshould serve as a cautionary tale for those peddling ideasabout the weakness of single-party regimes. We have nodoubt that the leaderships of single-party governmentswill do everything in their power to hold on to officeduring times of domestic difficulty. They will hide or al-ter economic statistics (Bueno de Mesquita et al. 2003),restrict media freedom, flood the media with misleadingpropaganda (Purcell 1973), and redouble their efforts towin over key elites with private goods. Although we arenot aware of any systematic studies of leadership survivalrates in single-party autocracies during times of domesticdifficulty, we would be surprised if they were low.

Even if this is true, however, we have to remember thatthe contribution of political incentive theory is its abilityto highlight how institutional differences across regimespresent leaders with different sets of policy options. Lead-ers in personalist and single-party regimes may both havea high probability of withstanding domestic challenges totheir leadership, but they may rely on a completely differ-ent array of survival tools. While personalist leaders caneasily crack down on or buy off dissidents, single-partyleaders may have to search for major policy successes toboost their support within their large winning coalitions.A limited, diversionary use of military force abroad mayprovide just such a boost.

Since winning coalitions in military regimes vary insize, the officers leading military governments can be ex-pected to employ blends of the survival tools employed bypersonalist and single-party leaders. Our first hypothesisis thus:

H1. Single-party regimes are more prone to use diver-sionary force than military regimes and especiallypersonalist regimes.

Table 1 summarizes how our first hypothesis based on po-litical incentive theory differs from the expectations of theinfrastructural power approach. Political incentive theoryalso goes beyond extant theory on autocratic diversion in

7Bueno de Mesquita et al. (2003, 236–41, 248–50) devote con-siderable attention to the diversionary proclivities of actors withlarge winning coalitions. Since winning-coalition size varies greatlyacross autocracies, we draw out the implications of their discussionfor autocratic diversionary behavior.


TABLE 1 Theoretical Probabilities ofDiversionary Force in Single-Party,Personalist, and Military Regimes

Infrastructural PoliticalPower Incentive

Perspective Perspective

Single-Party Regimes Low HighPersonalist Regimes High LowMilitary Regimes High Mixed

one additional, empirically testable way. It implies thatdiversionary force will “pay off” for single-party regimesmore often than it does for other autocracies, providinganother layer of explanation of autocratic diversionaryproclivities.

Reciprocal Effects: Does Diversion“Work”?

The political incentive approach implies that positive ornegative feedback loops may emerge when diversionaryforce either helps to ameliorate domestic problems or failsto do so, respectively. Leaders may thus be more prone touse diversionary force if it “worked” for their predeces-sors, allowing them to retain office in bad domestic timesby blunting elite dissent and/or stimulating the economy.The past success of military force may even create an in-grained policy prescription that leaders instinctively turnto when they face domestic dissent.8 Similarly, if diver-sionary force does not work, or even makes the domesticpolitical situation worse, leaders may be hesitant to con-sider this survival tool.

Political incentive theory suggests that leaders insingle-party regimes stand a good chance of achievingthe domestic outcomes they seek from diversion becausethey tend to select the timing and the targets for di-versionary military action carefully (Bueno de Mesquitaet al. 2003, 215–72). Given the large size of their winningcoalitions, single-party leaders must implement policiesthat have a reasonably high probability of success to en-sure that their winning coalitions remain loyal. This willbe especially the case for policy as visible as the use of ex-

8This argument is similar to Most and Starr’s (1980) contentionthat policy success or failure can positively or negatively reinforce,respectively, decision makers’ propensities for choosing similar pol-icy options again. It is also consistent with much research on foreignpolicy learning (see Levy 1994).

ternal military force.9 Single-party leaders know that fewthings will cause support within their winning coalitionsto erode as rapidly as a failed military mission abroad(see Bueno de Mesquita et al. 2003, 273–326). They canthus be expected to be extremely cautious when contem-plating the use of diversionary military force. They canalso be expected to do everything in their power to ensurethat military missions succeed once they are launched. AsBueno de Mesquita et al. observe, “all else being equal,the larger the W i [winning coalition], the harder nationi tries. . .” (2003, 237) to prevail in military operationsabroad.

Since personalist leaders’ political fates are rarely tiedto the outcomes of military missions, they have less incen-tive to be careful when selecting the targets or the timingof their military operations. They also have less reason totry hard to ensure that military missions succeed. Theythus tend to adopt a more risk-acceptant approach tothe use of interstate military force than counterparts insingle-party states.10 High levels of risk acceptance do notnecessarily mean that personalist military ventures willproduce bad outcomes, however. Risky military opera-tions may succeed spectacularly in some instances but failmiserably in others. Such wide variance stands in con-trast to the generally positive outcomes that should begenerated by cautious, determined single-party leaders.11

Military regimes, again, can be expected to havemixed records of producing positive domestic outcomeswhen they use military force abroad because the size oftheir winning coalitions vary. Considering the role thatwinning-coalition size may play in the domestic success orfailure of diversionary operations, our second hypothesisis:

9The diversionary literature often presumes that leaders will seekrelatively weak targets to ensure a rally-inducing “victorious” mis-sion (see Morgan and Bickers 1992). The opponent must not betoo weak, however, or else the public will give little credit to theleader for a successful military mission and little rally effect willaccrue (see Tarar 2006).

10We thank an anonymous reviewer for helping to sharpen thisportion of the argument. A different literature also hypothesizesthat personalist leaders tend to be more risk acceptant than leadersin single-party systems. Research on leader psychology suggeststhat differences in recruitment processes across regimes may allowleaders with substantially different psychological profiles to rise topower. Risk seekers may, for example, be prone to seize power ina personalist regime, while the highly bureaucratized structure ofsingle-party systems rewards risk-averse individuals (Levy 1992,305).

11Personalist dictators’ high propensities for risk may help to ex-plain why personalist regimes have not won a single interstatewar since 1945 (Reiter and Stam 2003). Since full-scale wars areamalgamations of numerous discrete military missions, personal-ist military operations may fail at higher rates than those launchedby other states as well.


H2. Single-party regimes are more likely than militaryregimes and especially personalist regimes to achievepositive domestic outcomes, such as decreased po-litical unrest and improved economic performance,from the use of external military force.

Research Design

The unit of analysis in our TSCS data of 140 autocra-cies from 1950 to 2005 is the state-year. Our reciprocalframework requires that we analyze a number of differentdependent variables that also serve as independent vari-ables in subsequent estimates. Each dependent variablerequires a distinct set of control variables as well.

Dependent and Independent Variables

Foreign Military Force. The International Military Inter-vention (IMI) data collection is used to operationalize for-eign military force. IMI records all verifiable cases whennational “troops or forces . . . move into the territory . . .

of another country” to pursue political, economic, strate-gic, or humanitarian objectives (Kisangani and Pickering2008; Pearson and Baumann 1993, 5). In essence, it cat-alogs episodes when national military personnel are pur-posefully dispatched into other sovereign states, no matterhow large or small the mission. IMI thus considers foreignmilitary intervention to be first and foremost a policy tool,which is the result of a policy decision by national leaders(among others, see Krain 2005). We create the variablemilitary intervention with IMI to enumerate the numberof times that a state unilaterally intervenes abroad in acalendar year.12 Fordham and Sarver (2001), among oth-ers, emphasize the importance of using state-level datasuch as IMI to test state-level theories like diversionarytheory.

Our sample includes 392 military interventionslaunched by autocracies from 1950 to 2005, a numbercomparable to the 417 interventions initiated by democ-racies over that time period. Unlike the data on democ-racies, however, autocratic interventionary behavior isnot skewed to a small number of powerful states. WhileBritain, France, and the United States account for nearly

12Our operational definition helps to eliminate aggregation bias.As Mitchell and Moore (2002, 440) point out, the use of dichoto-mous variables to operationalize interstate force needlessly removes“potentially important information” that may improve our under-standing of the phenomenon.

30% of democratic interventions, no single state is re-sponsible for more than 6% of autocratic interventions.

Domestic Political Unrest . Most past research on pop-ular support and diversionary force focuses on advancedindustrial democracies and uses public opinion pollingdata to operationalize both mass (selectorate) and elite(winning coalition) support for the government. Sinceour study concentrates on autocracies where polls areseldom taken, we use the five forms of overt political dis-satisfaction cataloged by Banks (2007) to operationalizemass and elite unrest. Government crises and purges arecombined to produce our measure of elite unrest . Gen-eral strikes, antigovernment demonstrations, and riotsare combined to create mass unrest .13 The correlation be-tween these two forms of domestic protest is low (.22)and is not statistically significant at the .10 level. We as-sume that since elites in winning coalitions are autocraticleaders’ most important constituency, rising levels of eliteunrest should be more likely to lead to diversionary forcein single-party and perhaps military regimes than risinglevels of mass unrest.

Domestic Economic Performance. Many empiricalstudies of diversion utilize a “misery index” that combinesunemployment and inflation to operationalize domesticeconomic difficulty, while others use economic growthas measured by annual changes in real GDP. Since reli-able unemployment data are not available for most of thestates in our sample, we rely on the other two measures.For economic growth, we use the real annual percentagechange in GDP using data from Heston, Summers, andAten (2006). Inflation is operationally defined as annualchanges in the price index using data from the Interna-tional Monetary Fund (1983, 2006).

13Our operationalization of elite and mass unrest follows Pickeringand Kisangani (2005) and Kisangani and Pickering (2007). ArthurBanks (2007, datafile) defines these events as follows: (1) govern-ment crisis as “any rapidly developing situation that threatens tobring the downfall of the present situation—excluding situationsof revolt aimed at such overthrow”; (2) purges: “any systematicelimination by jailing or execution of political opposition . . .”; (3)general strikes: “any strike of 1,000 or more industrial or serviceworkers. . .that is aimed at national governmental policies or au-thority”; (4) antigovernment demonstrations: “any peaceful pub-lic gathering of at least 100 people for the primary purpose ofdisplaying. . .their opposition to government policies. . .”; and (5)riots: “any violent demonstration or clash of more than 100 citizensinvolving the use of physical force.” Note also that the frequency ofincidents of elite and mass unrest do not vary significantly acrossour regime types. For example, single-party regimes record 345incidents of mass unrest and 298 incidents of elite unrest in oursample, while personalist regimes experience 334 and 273 incidents,respectively.


Control Variables

Military Intervention as the Dependent Variable. Our “Mil-itary Intervention Model” includes three control variablesfound in the literature to be positively correlated with mil-itary intervention: strategic rivalry, subsystem crisis, andbad neighborhood. Each provides a measure of oppor-tunities that arise in the international environment forleaders to use foreign military force. Colaresi, Rasler, andThompson (2007) define strategic rivals as states that aresufficiently threatening competitors to qualify as enemies.Strategic rivalry counts the number of strategic rivalriesa state is involved in during a given year. A prominentalternative to the strategic rivalry collection, the endur-ing rivalry data, was substituted for the Colaresi, Rasler,and Thompson (2007) data in supplemental analyses.14

The outcomes were substantively similar. Subsystem cri-sis counts the total number of crises in an actor’s lo-cal subsystem annually using data from the InternationalCrisis Behavior Project (2008) data collection. Bad neigh-borhood measures a similar but statistically uncorrelatedphenomenon (see Sambanis 2001). It counts the numberof armed conflicts ongoing in neighboring states usingMajor Episodes of Political Violence Project data (2009).

Political Unrest as the Dependent Variable. Our esti-mates of elite and mass unrest include economic growth,inflation, and ethnic fractionalization as control variables.Following extant literature, we expect that economicgrowth will be negatively correlated with political un-rest, while inflation and ethnic fractionalization will bepositively correlated with it (Ellingsen 2000; Przeworskiet al. 2000).15 Ethnic fractionalization data are from anupdate of Fearon and Laitin (2003).

Economic Growth and Inflation as Dependent Vari-ables. Our estimates of economic growth include the mostprominent control variable in the economic literature onthe subject. Investment as a percentage of GDP (a measureof capital) should be positively correlated with economicgrowth (Barro and Sala-I-Martin 1995).16 Data on invest-

14See Colaresi, Rasler, and Thompson (2007) on the conceptual andoperational differences between their strategic rivalry collectionand the enduring rivalry data set.

15Controversy over the extent that ethnic fractionalization is relatedto the outbreak of civil war does not extend to lower-level activitieslike political protests and domestic violence. A positive relationshiphas been found between ethnic fractionalization and these formsof unrest (among others, see Ellingsen 2000).

16In supplemental analyses, we include the natural logarithm of acountry’s total population (a measure of labor taken from the COWdataset) as an additional control variable in our economic growthestimates. We do not present results for this variable because ofspace considerations in Table 3 and because its inclusion does notalter our substantive results.

ment are from Heston, Summers, and Aten (2006). In ourestimate of inflation, economic growth is our lone controlvariable because of the mitigating impact it is presumedto have on prices.

Model Description and a FewMethodological Issues

We use a set of three simultaneous equations to estimatethe reciprocal relationships that exist among diversionaryforce and its domestic consequences. The first is our mil-itary intervention model, in which military interventionis the dependent variable. The second is our political un-rest model. It encompasses estimates for both elite unrestand mass unrest. The third is our economic performancemodel. It again has two sets of estimates, one for eco-nomic growth and another for inflation. The models canbe summarized as follows:

Military Interventionit = �0 + �1Eliteit + �2Massit

+ �3Economic Growthit

+ �4Inflationit

+ �5Military Interventionit−1

+ �jZIit + εit, (1)

Political Unrest it = �0 + �1Political Unrest it−1

+ �2Military Interventionit

+ �iZPit + � it, (2)

Economic Performanceit = �0 + �1Military Interventionit

+ �iZEit + �it, (3)

where ZI, ZP, and ZE are vectors of control variables,while ε, � , and � represent stochastic terms.

This system can be reformulated in matrix format asfollows:

�y + X′� + � = 0, (4)

where y, X, and � are the vectors of endogenous variables,exogenous variables, and parameters to be estimated re-spectively; � is the vector of stochastic error terms withthree components given by

�it = �i + �t + it, (5)

where �i is the country-specific component, �t is the time-specific component, and it is white noise related to bothcountry and time. Moreover, it is normally distributedwith mean zero and a constant variance. In general, �i and�t will be correlated with the regressors in the equation.


Two methodological issues must be addressed be-fore we begin our empirical analysis. The first issue ismulticollinearity, which is of special concern given ouruse of two variables to measure domestic unrest (eliteand mass unrest) and domestic economic performance(economic growth and inflation). Variance inflation fac-tor (VIF) tests were performed to determine if multi-collinearity was a problem in our estimates. No singlemodel had a mean VIF approaching 10, the standardthreshold indicating the presence of multicollinearity. Infact, the largest mean VIF recorded in an estimate was1.11 (in the intervention model estimate of all autocra-cies). Individual explanatory variables also had VIFs wellbelow 2 in all of our models, offering further evidence thatmulticollinearity does not have a pernicious effect on ourestimates.

The second issue concerns the stationarity of ourdependent variables, an important subject in time-seriesmodels. Following Oh (1996), Wu (1996), and others,we use panel-data unit root tests to determine whetherthe variables in our three models are stationary. Sinceour data are unbalanced, the best such test is the IPStest (Im, Pesaran, and Shin 2003).17 Although IPS resultsacross our three autocratic regime types are somewhatmixed, the null hypothesis of unit roots could not berejected for most of our dependent variables at the .05level of significance.18 This suggests that many of ourdependent variables are not stationary and that standardregression estimates using raw or level data may producespurious results. One method is particularly well suitedto overcome this problem in simultaneous models, theGMM.

17Econometricians now agree that once commonly used unit roottests such as the Dickey-Fuller (DF), the augmented Dickey-Fuller(ADF), and the Phillips-Perron (PP) lack power in distinguishingthe unit root null from stationary alternatives. We considered otherwidely used panel data unit root tests such as the Levin and Lin,or LL, and the revised Levin, Lin, and Chu (2002), but they wereless appropriate for unbalanced data than IPS (for a review, seeMaddala and Wu 1999). Note that the IPS test for unit root consistsof a t-test of the coefficient on the lagged level.

18For example, in military regimes, the null hypothesis of the unitroot could not be rejected for our endogenous variables IMI, eliteunrest, and mass unrest at the .05 level of significance, while itcould not be rejected at the .005 level of significance for economicgrowth. For single-party regimes, we could not reject the hypothesisat the .05 level for mass unrest, economic growth, and inflation,but we could reject it for elite unrest. Results are similarly mixed forpersonalist regimes. As a further test, we divided our TSCS data byregion using the five standard regions listed in COW rather than byautocratic regime type. The regional data provide more consistentevidence that our dependent variables are nonstationary.

The GMM Method

We use dynamic panel GMM (see Arellano and Bond1991; Hansen 1982; Ogaki 1993) to exploit the linearmoment restrictions implied when using nonstationarypanel data.19 The advantage of the GMM estimator (�matrix estimator) is that it allows the transformation ofthe variables to achieve orthogonality between the coun-try fixed effects and the regressors. Thus, in the absenceof autocorrelation, the � matrix GMM estimator is effi-cient and consistent (Baltagi 2005). This method requiresthat the variables be measured as deviations from theirperiod means and equations be estimated in differencedform. Equation (4) summarizing our model can thus berewritten:

Γ�y + ΔX′� + Δ� = 0, (6)

where y and X are centered on their period means, andΔ is the difference operator. We use robust estimatorsbecause our dependent variables include both count andinterval data (see note 19). We retain the robust estimatorbecause the first two estimators were inefficient. We relyon the Akaike Information Criterion to determine thenumber of lags in our endogenous variables.

The consistency of our estimation depends on thestochastic properties of the error term given in Equa-tion (5) or �it = �i + �t + it, especially if they are corre-lated with the regressors or if the error terms are seriallycorrelated. If our independent variables (variables on theright hand of our system of equations) are orthogonalto �it, a generalized least-squares estimator will be con-sistent. If, on the other hand, these variables are strictlyexogenous with respect to �t but not to �i, a within-groupestimator (or fixed effects) will be consistent.

Given the nature of our three models, we do notbelieve that orthogonality with it and either weak orstrong exogeneity hold. Besides the endogeneity of ourdependent variables political (i.e., elite and mass) unrest ,

19The notion of a moment is fundamental for describing features ofa population. For example, the population mean or population av-erage, �, is the first moment that measures a central tendency. Thesecond moment is variance. Let yi =1, . . . , N, denote the dependentcount variable military intervention, which is independently Pois-son distributed, with the conditional mean specified as E(yi | xi) =�i = exp(xi

′�) where xi is a k-vector of explanatory variables and �

is a k-vector of parameters. The conditional mean specification ofthis equation defines a regression model yi = �i + ui = exp(xi

′�) +

ui, with E(ui | xi) = 0. The GMM estimator based on this momentcondition only minimizes (y − �)

′XW −1

N X′

(y–�), where WN is aweight matrix. As the minimum of this latest matrix is obtainedat X

′(y − �) = 0, the GMM estimator for � will be the same as

the Poisson maximum-likelihood estimator. GMM’s equivalenceto Poisson explains why GMM is used to analyze count dependentvariables in economic literature (see Windmeijer 2008).


economic growth, and military intervention, the need to in-clude lagged dependent variables in our models ensuresthat the orthogonality condition will not be satisfied evenfor the fixed-effect estimator, whether it is estimated inlevels or in differences. Measuring the variables as devia-tions from their period means and first differencing themremoves �i and �t from the error term. Serial correla-tion is also removed by differencing and by lagging ourendogenous variables.

GMM also has a number of advantages over otherestimators. First, for reciprocal estimates, GMM is a dy-namic, instrumental variable estimator equivalent to anefficient three-stage least squares (3SLQ) estimator (Bal-tagi 2005). Second, one does not have to specify distribu-tional assumptions, such as normal errors, with GMM.GMM thus provides a unifying framework for recip-rocal analyses of most common dependent variables,continuous, dichotomous, or count (see note 19 andWindmeijer 2008). Third, GMM allows researchers tospecify a set of moments that they believe will be robustto any misspecifications of the statistical model (Baltagi2005, 150–61). This is especially beneficial because, asHansen (1982) has shown, all instrumental variable esti-mators with TSCS data can be cast as GMM estimators,no matter whether the models are linear or nonlinear.

To cross-check our results, we estimate single equa-tion estimates of our non-differenced (i.e., level) datameasuring our variables as deviations from their means,a procedure that is equivalent to a GMM model withoutfirst-differencing. By definition, these models suffer fromautocorrelated errors and provide inefficient estimates.They nonetheless produce results that are substantivelythe same as our GMM models, thereby lending greaterconfidence to our outcomes.20 Note also that becausewe first difference variables and include lagged valuesfor some endogenous variables, three years are droppedfrom our sample. We end up with usable observationsfrom 1953 to 2005 for our 140 autocracies.

Statistical Analysis of the Data

Table 2 and subsequent tables show that all the statisticalmodels fit the data well as indicated by highly significantWald � 2s. Table 2 also provides first- and second-order

20The results are largely the same substantively. For example, out-comes for the first model “all autocracies” in Table 2 are as follows:Predicted Military Intervention = .009 − .0894 IMI∗∗ + .0187 EliteUnrest∗ −.003 Mass Unrest − .075 Growth − .000 Inflation + .054Rivalry∗∗∗ + .043 Crises∗∗ + .090 Bad Neighborhood, where ∗∗ =p < .05 and ∗∗∗ = p < .01.

correlations (m1 and m2) suggesting that our estimatesare consistent. Although m1 shows the presence of first-order serial correlation, the test statistic for second-orderserial correlation (m2) based on residuals from the first-differenced equation is not statistically significant. It thusfails to reject the null hypothesis of no second-order au-tocorrelation. As Arellano and Bond (1991) point out,only the presence of second-order serial correlation inthe differenced residuals implies that the estimates areinconsistent; the existence of first-order serial correlationdoes not.21 Sargan tests for overidentifying restrictions,not reported for space constraints, indicate that these re-strictions are correct and that the set of instruments usedto estimate the equation is the correct one.

Table 2 displays the results for the dependent vari-able military intervention (equation 1). The first col-umn provides results for all autocracies included inGeddes’s (1999) collection, both pure forms and hybrids.The outcomes correspond with conventional views of au-tocratic diversion as well as political incentive theory. Au-tocratic leaders, like their democratic counterparts, aremore prone to use force abroad when unrest emergesamong elites than when it surfaces among the masses (seeMorgan and Bickers 1992). Given that elites in winningcoalitions are the single most important constituency sus-taining an autocrat’s rule, this is not surprising. In con-trast, variations in economic growth rates do not seemto influence autocrats’ propensity to use force abroad.Perhaps this is because declining growth rates are not apolitical challenge to many autocrats, who can continueto line the pockets of cronies even as the overall economyslows. However, rising inflation reduces the probabilitythey will dispatch troops overseas. Inflation may thuscause some level of dissent within the elite, particularlyif it constricts their purchasing power. Our control vari-ables show that autocrats tend to respond to the externalstimuli of strategic rivalry and subsystem crises, but livingin a bad neighborhood does not appear to increase theirpropensity to use interstate force.

While our general model of autocracies matches theexpectations of the political incentive approach, our es-timates of specific autocratic types in columns 2, 3, and4 of Table 2 do not. Column 2 indicates that single-partyregimes use diversionary force a short time after eliteunrest begins to rise, while column 3 suggests that con-temporaneous elite unrest compels personalist regimesto use military force. Military regimes seem to dispatch

21The statistic computed from a one-step homoskedastic modelshows that all the instrument sets are uncorrelated with residuals,because the assumptions of the test are unknown under a robustestimator. See Arellano and Bond (1991, 282).


TABLE 2 Dynamic GMM Model of Diversionary Use of Force by Autocracies, 1950–2005

Variables Autocracies (All Types) Single-Party Regimes Personalist Regimes Military Regimes

Constant −.0043 −.0008 −.0042 −.0152∗∗∗

(.0032) (.0022) (.0044) (.0037)Interventiont−1 −.1151∗∗∗ −.0878∗∗∗ −.1149∗∗∗ −.1484∗∗∗

(.0285) (.0279) (.0353) (.0422)Interventiont−2 −.0791∗∗∗ −.0604∗∗∗ −.0949∗∗ −.1279∗∗∗

(.0278) (.0136) (.0379) (.0279)Elite Unrestt .0521∗+ .0448 .0716∗∗ .0273

(.0268) (.0447) (.0335) (.0445)Elite Unrestt−1 .0375∗ .0718∗+ .0148 .0639∗

(.0213) (.0390) (.0197) (.0361)Mass Unrestt −.0072∗∗ −.0045 −.0072∗∗∗ .0094∗

(.0031) (.0028) (.0018) (.0056)Mass Unrestt−1 .0038 .0023 .0009 −.0080

(.0052) (.0034) (.0032) (.0084)Economic Growtht −.0071 −.0393 −.0060 −.1629

(.1506) (.1919) (.1302) (.1894)Economic Growtht−1 .0230 .0444 .0772 .0701

(.1269) (.2053) (.1559) (.2029)Inflationt −.00002∗∗∗ −.00003∗∗∗ −.00002∗∗∗ −.0001

(2.40E-06) (7.99E-06) (1.64E-06) (.0006)Inflationt−1 −.00002∗∗∗ −.00003∗∗∗ −.00002∗∗∗ .0009∗∗∗

(2.36E-06) (4.41E-06) (1.55E-06) (.0002)Strategic Rivalryt .1161∗ .1745∗∗∗ .1798∗∗∗ .1540∗∗∗

(.0676) (.0401) (.0494) (.0394)Subsystem Crisest .0255∗ .0193 .0221 −.0052

(.0148) (.0167) (.0182) (.0254)Bad Neighborhood .0433 .0231 .0235 .0772

(.0374) (.0414) (.0358) (.0535)

Wald � 2 198.53∗∗∗ 1347.23∗∗∗ 624.43∗∗∗ 130.47∗∗∗

m1 −4.54∗∗∗ −3.04∗∗∗ −3.22∗∗∗ −2.93∗∗∗

m2 1.50 −.05 .80 .95N 1444 841 680 506

Note: Robust standard errors are in parentheses below the estimates; ∗, ∗∗, and ∗∗∗ indicate statistical significance at the .10, .05, and .01levels in two-tailed tests; + indicates that this result misses the .05 level of statistical significance by a slight margin.

troops abroad when they encounter elite unrest as well,although this estimate is barely statistically significant atthe .10 level in column 4.22 Military regimes are also theonly government type that seems to divert in responseto economic troubles, in this case rising inflation. Theseoutcomes challenge H1, which presumes that single-partyregimes are more prone to use diversionary force than ei-ther personalist or military regimes. One of the main

22Elite unrest has only one asterisk in column 2 for single-partyregimes as well, but we have more confidence in this result since itmisses the .05 level of significance by a very narrow margin.

benefits of reciprocal estimates, however, is their abilityto shed new light on relationships in subsequent models.We must consequently turn to our reciprocal estimatesbefore rendering a verdict on H1 and political incentivetheory.

Our control variables are consistent across the threeregime types in Table 2. The opportunities to use forceprovided by subsystemic crises and by living in a badneighborhood do not appear to compel the three types ofautocracies examined here to use interstate military force.All three types are, however, highly prone to use militaryforce against strategic rivals.


TABLE 3 Dynamic GMM Model of Political Unrest in Autocracies, 1950–2005

Elite Unrest Mass Unrest

Single-Party Personalist Military Single-Party Personalist Military

Constant −.0088∗∗ −.0105 −.0182∗∗∗ .0203 .0575 .0468

(.0035) (.0064) (.0068) (.0192) (.0432) (.0362)

Elite Unrestt−1 .1471∗∗∗ .1369∗∗ .0799

(.0401) (.0601) (.0784)

Elite Unrestt−2 .0466 .0766 −.0346

(.0321) (.0504) (.0368)

Mass Unrestt−1 .4001∗∗∗ .1442 .1993

(.0391) (.1738) (.1326)

Mass Unrestt−2 .0399∗ .1565∗∗∗ −.0498

(.0205) (.0281) (.0413)

Interventiont .1237 .4077∗ .0482 −.2425 −.6077 .6457∗∗

(.1354) (.2209) (.1636) (.2789) (.4223) (.3068)

Interventiont−1 .0588 .2209∗∗ .1095 .0449 .0935 −.1644

(.0621) (.0904) (.0821) (.1409) (.2651) (.2625)

Economic Growtht −1.2077∗∗∗ −.6574∗ −.8913∗ −1.7618 −2.2265 −2.3078

(.3633) (.3715) (.5214) (1.8946) (1.9803) (1.6582)

Economic Growtht−1 .2557 .8099 .3537 −.5664 .7419 −2.3659

(.6440) (.6146) (.6015) (2.0899) (1.1889) (1.4531)

Inflationt −1.33E-06 .00005∗∗∗ .0038 .0004∗∗∗ .00003 .0003

(.00002) (9.93E-06) (.0027) (.00004) (.00002) (.0045)

Inflationt−1 −.0002∗∗∗ .00005∗∗∗ −.0036 −.0004∗∗∗ .00001 −.0079

(6.39E-06) (7.02E-06) (.0024) (.00004) (.00003) (.0057)

Ethnic −.00002 2.77E-06 −.00002 −.00004 −.00005 −.00007

Fractionalization (.00001) (.00002) (.00002) (.00007) (.0002) (.00008)

Wald � 2 314.84∗∗∗ 743.38∗∗∗ 17.08∗∗ 441.39∗∗∗ 372.62∗∗∗ 18.48∗∗

N 782 676 500 782 674 500

m1 −2.66∗∗∗ −2.55∗∗ −3.30 −1.98∗∗ −2.12∗∗ −2.40∗∗

m2 −.94 −1.56 .75 .28 −1.57 −1.10

Note: Robust standard errors are in parentheses below the estimates; ∗, ∗∗, and ∗∗∗ indicate statistical significance at the .10, .05, and .01levels in two-tailed tests.

Table 3 presents findings for our domestic unrestmodels (equation 2). It thus provides our first empiricalcut at H2, which states that single-party regimes will bemore likely to garner positive domestic outcomes fromthe use of military force abroad than other autocracies.Column 1 in Table 3, however, indicates that external mil-itary intervention generates no positive benefits withinsingle-party leaders’ most important constituency, elitesin their winning coalitions. They nonetheless fare consid-erably better than counterparts in personalist regimes. Ascolumn 2 shows, elite unrest increases significantly bothcontemporaneously and the year after a military inter-vention in personalist regimes. Column 3 indicates thatmilitary intervention has no impact on elite unrest inmilitary regimes.

The negative ramifications that follow personalistuses of force are not unanticipated. They underscore therisk-acceptant behavior political incentive theory ascribes

to personalist leaders. This type of dictator seems to usemilitary force in diversionary situations (Table 2, col-umn 3) despite the fact that it clearly has not “worked”for their predecessors or perhaps even for themselves.In fact, their domestic positions are made significantlyworse by the use of force abroad since it generates sub-stantial unrest within their core constituency. This raisesthe question of whether personalist uses of force can prop-erly be called diversionary. The use of diversionary forceusually implies that a relatively sophisticated political cal-culation has been made to dispatch troops abroad withthe goal of holding on to political power. In autocraticregimes, this means launching military operations withthe hope that they will quell dissent within the autocrat’sruling coalition (see Table 2). Given the results in Table3, it is hard to argue that personalist leaders make suchcalculations when they send troops abroad. If they do,they consistently do so poorly.


TABLE 4 Dynamic GMM Model of Economic Performance in Autocracies, 1950–2005

Economic Growth Inflation

Single-Party Personalist Military Single-Party Personalist Military

Constant −.0006 −.0009 −.0018∗∗ .1929 2.5657 .0575

(.0006) (.0007) (.0008) (.2879) (2.5319) (.1442)

Economic −.2142 −.2039∗∗ −.2608∗∗∗

Growtht−1 (.1628) (.0932) (.0830)

Economic .0809 .0506 −.0015

Growtht−2 (.0557) (.0754) (.1265)

Inflationt−1 .3759∗∗∗ .0561∗∗∗ .4922∗∗∗

(.0040) (.0091) (.1630)

Inflationt−2 .5123∗∗∗ .1436∗∗∗ .0039∗∗

(.0033) (.0040) (.0018)

Interventiont −.0052 .0037 −.0236∗ −39.9913 −142.5768 −2.9249

(.0076) (.0073) (.0123) (41.0376) (132.2174) (2.4711)

Interventiont−1 −.0074 .0023 −.0098 −39.2860 −77.5568 −3.6351

(.0077) (.0070) (.0112) (39.5153) (72.7796) (5.2768)

Elite Unrestt −.0138∗∗∗ −.0050 −.0089∗ −8.5095 49.3263 5.1086

(.0051) (.0036) (.0048) (12.7023) (46.1294) (4.3799)

Elite Unrestt−1 −.0021 −.0033 .0001 −2.3207 41.7509 3.5579

(.0043) (.0024) (.0035) (5.0631) (38.4509) (3.5275)

Mass Unrestt −.0019∗∗∗ −.00238∗∗∗ −.0005 5.4083 1.5065 −.4089

(.0005) (.0006) (.0009) (5.3823) (2.3287) (.6250)

Mass Unrestt−1 −.0011 .0005 −.0005 −.9403 −.2009 .8519

(.0013) (.0009) (.0009) (1.0084) (1.6291) (.6980)

Investmentt−1 .0009 .0027∗∗∗ .0025∗∗

(.0012) (.0011) (.0011)

Growtht−1 −45.8706 −100.1000 −37.3775∗∗

(40.5621) (68.4345) (17.8596)

Wald � 2 67.59∗∗∗ 61.45∗∗∗ 100.96∗∗∗ 9.86E + 06∗∗∗ 1.08E + 06∗∗∗ 53924.57∗∗∗

N 860 753 524 834 705 498

m1 −4.11∗∗∗ −2.55∗∗ −3.43 −1.01 −1.01 −1.31

m2 −.37 .36 −.39 1.00 1.16 −1.12

Note: Robust standard errors are in parentheses below the estimates; ∗, ∗∗, and ∗∗∗ indicate statistical significance at the .10, .05, and .01levels in two-tailed tests.

Table 3 also provides results for mass unrest. Mili-tary intervention does not improve mass support in ei-ther single-party or personalist regimes, and it tends tospark increased mass unrest in military regimes. Again,this result casts some initial doubt on Table 2’s findingthat military regimes use diversionary force. If militaryoperations abroad consistently increase domestic unrestinstead of acting as a salve that helps to heal domes-tic political wounds, it may be necessary to reexamineclaims that these missions were launched for diversionarypurposes.

Control variables largely behave as expected inTable 3. Economic growth suppresses elite unrest whileinflation increases both elite and mass unrest. We pre-sumed that ethnic fractionalization would tend to foster

domestic unrest, but the direction of this estimate is neg-ative in five of six models. It does not, however, reachstatistical significance.

Table 4 presents outcomes for our economic per-formance models (equation 3). Only one independentvariable is statistically significant in the table. Contempo-raneous military intervention has a negative impact oneconomic growth in military regimes, a finding that callsthe correlation between domestic problems and the initi-ation of external intervention by military regimes furtherinto question. Our single control variable in the growthmodel, investment, is positive and statistically significantas expected. In the price model, economic growth is inthe correct direction in two of the three models, and it isstatistically significant in one.


Conclusions

In this article, we analyze the diversionary proclivitiesof leaders in different types of authoritarian regimes.We do so by examining the reciprocal relationshipsthat exist between the external use of force and itsdomestic causes in three distinct types of autocracies.Using the GMM method, we present properly identifiedmodels that reveal some interdependent causal relation-ships among political unrest, economic difficulties, andthe use of military force. Our results suggest that the con-sensus that has emerged in recent comparative studies ofautocratic conflict behavior on the relative peacefulnessof single-party regimes may require modification for the1950–2005 time period (Lai and Slater 2006; Peceny, Beer,and Sanchez-Terry 2002; Peceny and Butler 2004). At thesame time, our findings do not provide unequivocal sup-port for hypotheses generated from political incentivetheory.23

As political incentive theory suggests, leaders insingle-party regimes seem prone to use external mil-itary force when they face the type of domestic po-litical challenge that most threatens their rule, risinglevels of elite unrest. Contrary to political incentive theoryand Hypothesis 1, we also find that personalist and mili-tary regimes use military force overseas when elite unrestincreases. Such results from the unidirectional compo-nents of our analyses are best understood in the con-text of our full reciprocal models, however. Leaders insingle-party regimes do not reap domestic political re-wards in the form of reduced levels of elite unrest whenthey use military force abroad. They nonetheless fare con-siderably better than their counterparts in personalist andmilitary regimes. External military force used by person-alist regimes significantly increases levels of elite unrestin these countries, while military regimes’ military op-erations generate substantial levels of mass unrest anddampen economic growth. These outcomes raise ques-tions about how many of the military missions in oursample of personalist and military regimes truly weremotivated by diversionary goals.

We thus find that a more nuanced understandingof the diversionary proclivities of different autocratic

23Some might argue that the inexact fit between political incen-tive theory and our empirical results is a limitation in our article.We, however, think that the slight disjuncture between our theoryand our findings increases our study’s utility. Our findings demon-strate weaknesses in both of the major theoretical approaches onthe subject while they simultaneously provide insight on ways toimprove the approach with the most explanatory traction. Ourresults consequently provide a solid example of the standard scien-tific interaction between the development of improved empiricaltesting and the refinement of theory.

regimes emerges when reciprocal models are employed.The best evidence of diversionary behavior found in ourreciprocal models is that for single-party regimes, the ac-tors that political incentive theory suggests should havethe greatest penchant for diversion. Political incentive the-ory’s contention that single-party regimes’ diversionaryactivities will tend to pay off domestically requires modifi-cation, however. Perhaps even leaders who rule over largewinning coalitions and hence must perform in office maynot be able to control all of the uncertainties involvedwhen military force is used abroad. Despite their bestefforts, they may not be able to select operations and tar-gets that ensure success and a high probability of accruingdomestic political rewards.

The limits of political incentive theory have to beplaced in the context of the infrastructural power per-spective’s performance. When the more complete infor-mation provided by reciprocal models is examined, theinfrastructural perspective’s contention that personalistand military regimes are the autocratic states most proneto divert rings hollow. Even more importantly, our re-sults challenge the basic premise of the infrastructuralpower approach. The infrastructural approach argues thatpersonalist and military regimes should be analyzed asa single category, since they both tend to rely on thepower of the military to retain office. We find, how-ever, that both the propensity to divert and to benefitdomestically from the use of military force varies sig-nificantly across personalist and military regimes. Theconceptual distinctions that Geddes (1999) and oth-ers make between personalist and military regimes thusappear to have merit when it comes to diversionarybehavior.

While political incentive theory fits our results best,we believe that one relatively straightforward enhance-ment will improve its explanatory power. Geddes (2006),Purcell (1973), and others demonstrate that autocraticgovernments progress through different stages as theirtenure lengthens. Early stages are characterized by jock-eying for power among elites that dream of building theirown personalist regimes. Further volatility may be in-troduced soon afterward if certain elites try to “decom-press” the regime by gradually initiating policies that in-clude broader segments of society (Geddes 2006). Anautocratic regime’s grip on power, and its institutionalcontours, are firmly established only when these phaseshave been successfully navigated. Since these changes haveconsiderable potential to impact a government’s propen-sity to use diversionary force, it seems wise to incorpo-rate the additional theoretical layer of regime age intopolitical incentive theory. This addition should cost lit-tle in terms of parsimony, and it holds the potential


to expand political incentive theory’s explanatory powersignificantly.

Further research on autocratic diversion is obviouslynecessary. Our findings suggest that future studies shouldbe careful to analytically separate the three forms of au-tocratic regimes commonly demarcated in the literature.They also demonstrate that future work on the subjectwould benefit greatly from the use of reciprocal esti-mates. This study consequently underscores an argumentthat Levy (1989) advanced two decades ago, but whichhas received little attention since. Reciprocal models arecrucial for diversionary studies for two interrelated rea-sons. They provide properly specified statistical models,and they significantly improve our ability to comprehenddifferent actors’ diversionary behavior in large N studies.Future research should also attempt to expand the tempo-ral scope of studies on autocratic diversion. Our analysisfocuses on a period of time when the international systemwas first bipolar and then briefly unipolar. Studies usingdifferent data collections may be able to extend temporalcoverage back to the nineteenth century, giving us a bettersense of the generalizability of our findings to multipolarand other system settings.24

Finally, political incentive theory not only appears toprovide the most useful theoretical platform for futureresearch on autocratic diversion, but it also may offer thebest explanation of autocratic conflict behavior in general.The key insights of the theory largely hold across previ-ous analyses of dyadic autocratic force (see, for example,Peceny and Butler 2004) and our study of autocratic di-version. Because single-party regimes have comparativelylarge winning coalitions among authoritarian states, theyseem to be the one autocratic regime type that exhibitsconflict behavior similar to democracies. This is not onlybecause dyadic relations among single-party regimes arerelatively pacific, as previous research has shown. It isalso because leaders in this particular autocratic regimetype, like those in democracies (Bueno de Mesquitaet al. 2003, 236–41), have a proclivity for diversionaryforce.

24At present, the most daunting obstacle for analysts who wouldlike to extend diversionary studies to the nineteenth century is thepaucity of cross-national, state-level use of force data prior to 1945.While dyadic data could be used and may provide useful insights,Fordham and Sarver (2001) and others caution that using dyadicdata to study state-level phenomena like diversion may producespurious findings. Note that the temporal coverage of this articleexceeds that of extant research on autocratic force. Lai and Slater’s(2006) study spans 1950–1992, while Peceny, Beer, and Sanchez-Terry (2002) and Peceny and Butler (2004) analyze 1945–1994.

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