Political Competition, Political Participation, and Democratic Peace in Asia and Africa

Benjamin E. Goldsmith (ben.goldsmith@sydney.edu.au) Gorana Grgić (gorana.grgic@hotmail.com) University of Sydney Dimitri Semenovich (dimitris@cse.unsw.edu.au) Arcot Sowmya (sowmya@cse.unsw.edu.au) University of New South Wales While empirical analyses of the relationship between regime type and international conflict are less common now than they were in the late 1990s and early 2000s, the theoretical foundations of “democratic peace” (the empirical pattern that democracies rarely fight each other) remain uncertain. In this paper we test propositions which place theoretical emphasis on one aspect of democracy, genuine competition among organized groups for power. This elite-based explanation points to the existence of a viable opposition as key to tempering conflict behavior. Our propositions about political competition are tested against competing explanations regarding political participation, which we relate to “selectorate” theory, which emphasizes the demand for public goods engendered in mass participation in genuine elections, another key aspect of democracy. We also examine institutions of constraint on executive governmental power. It is rare that specific components of regime type are tested against each other in the same models. This more nuanced specification of regime type, we argue, provides both a better test of competing theories, and a better specified econometric modeling approach. In order to provide a difficult test, we use data from regions which have previously shown little or no evidence for the democratic peace: Africa and Asia. Our modeling approach takes into consideration the potential complexity of the relationship between specific components of regime type, and external conflict behavior. We use selection models to account for the interrelated stages of conflict initiation and escalation. We have developed a new machine-learning based parameter estimation technique for Generalised Linear Models (GLM), and applied it to better understand the potentially complex interactions and non-linear effects between regime-type components and conflict and peace. We find that our proposed specification of monotonic and non-monotonic dynamics for the relationship between conflict initiation and escalation, on the one hand, and institutions of political participation and political competition, on the other, proves reasonably robust when tested on data for Sub-Saharan Africa and East Asia. The major exception is that both sorts of institutions have very different effects on dispute initiation in East Asia, than in Africa or globally. Paper prepared for presentation at the American Political Science Association annual meeting, September 2012, Seattle, Washington. Acknowledgement: We thank the Australian Research Council for funding through a Discovery Grant (DP1093625).

In this paper we examine the role of some institutional components of regime type in the process of interstate conflict initiation and escalation. Our goal is to advance the theoretical understanding of the regime type – conflict relationship. We assess whether our proposed specification is robust in two regions of the world which previous studies have noted exhibit distinct relationships between regime type and conflict (Goldsmith 2006, 2007a; Henderson 2009). Our findings, though preliminary, suggest that different political institutions have different sorts of effects at the stages of conflict initiation and escalation. We categorize these effects generally as either monotonic or non-monotonic, and consider their contributions to both the “democratic peace” and the “authoritarian peace.”

The next section details our hypotheses. Our central argument is as follows. States with high political competition are less likely to initiate disputes with democracies because it is harder to make a defensible moral or practical case for such disputes against the arguments of a viable opposition party, but leaders facing real political competition seek defensible policies in order to remain in power. If such states do initiate disputes with democracies, these are less likely to escalate to war for the same reason: the costs of backing down are perceived as lower than the costs of being held accountable for a costly and indefensible war. States with low political competition are less likely to escalate disputes which they initiated against authoritarian regimes because they find it easier to back down if the authoritarian regime has greater capability or resolve than anticipated, or if the dispute initiation was actually a bluff.

States with higher participation are more likely to initiate disputes with all regime types, because leaders have incentives to pursue populist or diversionary low-level conflict (a monadic effect). States with high participation are less likely to escalate disputes which they initiate against democracies because they anticipate the higher costs to the population of war, given that democracies can more credibly and clearly signal capabilities and resolve, and thus are able to achieve a politically and materially acceptable negotiated outcome without resort to war.

Our purpose in testing our expectations on regional dyads is to provide a hard test of robustness. For Africa, Henderson (2009) argues that democracies in the region are more belligerent than other states due to the specific interaction of neopatrimonialism and legitimacy. Others have argued that regime type might be irrelevant, due to state fragility and internal insecurity in the region (Goldsmith 2006; Lemke 2002). For East Asia, at least one study has not found any support for the democratic peace proposition in the broader Asia region (Goldsmith 2007a).

We find that both Africa and East Asia exhibit essentially the same regime-type patterns as obtain globally when we examine the process of conflict escalation to wars involving 1000 or more battle deaths. African polities also display a very similar pattern to the global pattern in the stage of conflict initiation. In East Asia, the main differences we find are that political competition seems to have no effect, or perhaps even a conflict-exacerbating effect, on militarized dispute initiation, while political participation seems to have an inhibiting effect on initiation, contrary to global patterns.

Why the East Asian difference? We point to the “developmental state” model of governance which is widespread in Northeast and Southeast Asia (Johnson 1982). We speculate that East Asian regimes stake their legitimacy more on economic performance than foreign policy, and therefore governments are not as strongly scrutinized for foreign policy behavior, regardless of regime type, but going beyond speculation must be left to future investigation.

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Expectations Domestic Political Institutions and Interstate Conflict As a theoretical starting point, we note that the relationship between regime type and international conflict is likely to be complex. First, it is not likely to be linear, because there is evidence of an authoritarian peace as well as a democratic one (Goldsmith, Chalup, and Quinlan 2008; Peceny, Beer, and Sanchez-Terry 2002). Second, it is not likely to be best explained as a single-shot type of interaction, but rather as a process of interaction, as suggested by bargaining theories of war (Reiter 2003), although few studies model it in this way (exceptions include Lemke and Braithwaite 2011; Lemke and Reed 2000; Rider, Findley, and Paul 2011).

We therefore put forward some expectations regarding how different institutional elements of regime type might be related to external conflict behavior considered as a process of interaction with a potential adversary. We consider international conflict as a two-stage bargaining process involving dispute initiation, and then escalation to actual fighting. To develop our hypotheses, we present plausible logic relating to each of three aspects of regime type and their effects on 1) the likelihood of a state choosing to initiate interstate conflict, and 2) the likelihood that such conflict will escalate to war.

Most empirical tests of regime type and conflict focus on the democratic peace, but don’t make further distinctions regarding dyadic regime-type combinations, and do not distinguish between initiators and targets, or initiation and escalation stages (exceptions using directed dyad data include Reiter and Stam 2003; Rousseau et al. 1996). We point out that the potential complexity of the hypothesis space is not fully explored by our discussion and eight hypotheses. If all monotonic and non-monotonic monadic and dyadic effects were considered separately, there would be a minimum of 24 hypotheses.

We make some simplifying assumptions to structure our theoretical discussion. One such assumption we borrow from existing literature is that the conflict process can be usefully considered to have just two key stages, initiation and escalation. Another is that states perceive each other in terms of overall regime type (democracy, anocracy, authoritarian), rather than along the lines of specific institutions. The propositions below therefore consider the political institutions of the regime initiating conflict, but the overall regime type of the target state.We first discuss our expectations regarding participation and conflict, then executive constraints, and finally, political competition. Institutions of Participation Political participation encompasses institutions that regulate how the executive leader(s) of the state are selected, and who may aspire to executive office. Dahl (1971, 4) characterized it as “the proportion of the population entitled to participate in a more or less equal plane in controlling and contesting the conduct of government.” It is not simply the idea of wide or universal suffrage, since elections can be rigged or otherwise fail to provide genuine choice. In essence, political participation indicates whether the one, the few, or the many hold ultimate, meaningful sovereignty and choice in a political system. Political participation might be related to external conflict behavior of states. We connect participation to selectorate theory, although we recognize that the authors of this theory use a somewhat different indicator that we do (for a discussion see Goldsmith 2007b).1 Selectorate theory focuses on very similar aspects of regime type to those usually categorized as political participation. Bueno de Mesquita, Smith, Siverson, and Morrow (2003, 42, 51) 1 We anticipate doing robustness tests with Bueno de Mesquita et al’s “S” variable, but have not undertaken these yet.

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define the “selectorate” as those who “have a government-granted say in the selection of leaders” which also gives them “the opportunity to become a member of a winning coalition.” The winning coalition is “a subset of the selectorate of sufficient size such that the subset’s support endows the leadership with political power over the remainder of the selectorate as well as over the disenfranchised members of the society.”

The logic of the “selectorate peace” hinges on the tendency of democratic states (with large selectorates and winning coalitions, by definition) to “spend resources on effective public policy” or “public goods”, of which national security is one (Bueno de Mesquita, Smith, Siverson, and Morrow 2003, 243-45). Leaders with society-wide selectorates and winning coalitions approaching 50 percent of the population will understand that their political survival is tied to the provision of such effective policies or public goods. Selectorate theory points to various scenarios in which leaders will be constrained from engaging in international conflict due to their overarching concern for political survival. In most circumstances, democracies thus might initiate disputes with each other, but these are unlikely to escalate because each state understands that the other will “try hard” to achieve victory in war, but each will prefer to choose contests which offer clear prospects for victory: “war… between democracies is unlikely, though disputes are not.” However, when a democracy confronts an authoritarian regime, “democracies are willing to fight autocrats so long as the prewar military balance plus the democracy’s additional effort give [it] a substantial probability of victory. Autocrats… are more willing to fight back under these conditions because victory is not essential for their political survival.” The logic also suggests that authoritarian regimes are likely to initiate disputes against democracies, but these are less likely to escalate because authoritarian regimes are aware of democracies’ tendency to try hard during war and pursue victory. The logic is less specific regarding contests involving jointly authoritarian dyads. The selectorate model proposes that “[b]ecause the war’s outcome is not critical to [either state’s leader’s] political survival, the decision to fight is more easily influenced by secondary factors – such as uncertainty, rally-round-the-flag-effects, a leader’s idiosyncratic desires, and so on….”

While we do not feel the selectorate theory leads to a strictly linear relationship regarding political institutions at either stage of conflict, it does present expectations which are most clear for conflict escalation. The chances of disputes escalating to war are lowest when states with wide selectorates face democratic adversaries. Wide-selectorate states will tend to choose weaker authoritarian targets, and so be willing to escalate disputes with them. But states with narrow selectorates will be less concerned about victory, and so will also be willing to escalate disputes – both those they initiate and those in which they are the target. Whether democratic-authoritarian or jointly authoritarian dyads will be more likely to escalate, ceteris paribus, is not clear, but both will be less peaceful than jointly democratic dyads. Thus a monotonic effect is expected for dispute escalation. It is not clear that institutions of participation will play any role in the dispute initiation stage, based on selectorate theory.

A different perspective on participation and conflict is that wider participation leads to more populist foreign policy (Goldsmith 2007b). This produces a monadic hypothesis that wider participation will lead to more low-level conflict based on nationalist rhetoric, saber rattling, and diversionary tactics. Hypothesis 1: The chance of a state initiating militarized interstate conflict will not be related to its level of political participation and the potential adversary’s level of democracy (monotonic).

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Hypothesis 1a: The chance of a state initiating militarized interstate will increase with its level of political participation regardless of the potential adversary’s level of democracy (monadic, linear). Hypothesis 2: The chance of a militarized interstate conflict escalating will be decreasing in the level of political participation of the initiator and the adversary’s level of democracy (monotonic). Institutions of Constraint on Executive Power We do not place great emphasis on executive constraints in this paper, rather we include them as a control variable since they may be closely related to participation, competition, and conflict. It has been suggested that leaders facing constraints on their domestic political and economic behavior will tend to behave less imperialistically or aggressively in their foreign policies (Lake 1992). Schultz (1999, 2001) points to informational transparency as an institutional factor making it difficult for democracies to bluff in crises, and either for potential adversaries to accurately gauge their capabilities and resolve.2 Schultz focuses on the openness of political communication in democratic regimes, relative to authoritarian ones. Because governments operate within institutions requiring open politics, there are “constraints on the government’s ability to conceal or misrepresent relevant information in a crisis” (Schultz 2001, 231-232). It is important to note that Schultz’s approach focuses on monadic conflict behavior, and thus is not a theory of democratic peace. Neither does it fit very neatly into just one of our institutional boxes, because it draws on elements of competition as well as institutions which create transparency and thus constrain governments. 3 Schultz (2001, 58) himself recognizes the conceptual distinction between “publicity and competition” and notes that his approach combines these two aspects of democracy. Among the institutions he highlights are “[r]ules safeguarding media freedoms” and “information gathering that is central to the legislative process” such as the investigative and deliberative activities of legislative committees (Schultz 2001, 60, 64). These are constraints on executive secrecy, and play an informational role in Schultz’s theory. Thus, the public aspect of his theory is tied to important institutions of executive constraint, at least in part. Schultz (2001, 233) argues that this informational function leads democracies to be less likely to initiate crises than non-democracies, because they will be less able to “engage in strategic misrepresentation.” He also argues that democracies will be less likely to see crises they initiate escalate to wars because the higher credibility of their threats makes other states more likely to back down (2001, 234).

2 Tsebelis (2002) has introduced the concept of veto players, which we take to be closely related to the idea of constraint on executive power. When there is no such constraint, the executive is the only veto player. However, Tsebelis does not see the number of veto players as a key factor distinguishing democracies from non-democracies. Rather, he sees democracies as regimes with competitive processes of veto-player selection, and non-democracies as regimes lacking such processes. 3 We believe we are correctly capturing the central logic of Schultz’s argument. However we acknowledge that he also focuses on political competition. However, it is the open nature of this competition that gives democracy its informational advantage in conflict. As he writes (2001, 232, “The political process in democratic countries resembles an open debate in which the government must share the stage with its domestic adversaries. The resulting interaction generates public information about the desirability of different policy choices and the government’s domestic political incentives. In nondemocratic systems, by contrast, arguments over public policy – and especially foreign policy – tend to take place in private; their public aspect more closely resembles a monologue than a debate.” Thus, the key is not political competition itself, but the degree to which it is transparent to foreign observers. Institutions which guarantee a free press, free speech, and free assembly are central to this, and also major constraints on executive power.

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Hypothesis 3: The chance of a state initiating militarized interstate conflict will be decreasing in its level of executive constraints and the potential adversary’s level of democracy (monotonic). Hypothesis 4: The chance of a militarized interstate conflict escalating will be decreasing in the level of executive constraints of the initiator and the adversary’s level of democracy (monotonic). Institutions of Political Competition Existing theory summarized above considers monotonic relationships between political institutions and interstate conflict. But there is evidence of non-monotonic effects of regime type: both a democratic and an authoritarian peace. Our expectations regarding institutions of political competition are formulated with an eye towards potential sources of such non-monotonicity.

Political theorists have often focused on political competition as something which distinguishes democracies from non-democracies. Joseph Schumpter (1950, 269) wrote “the democratic method is that institutional arrangement for arriving at political decisions in which individuals acquire power to decide by means of competitive struggle for the people’s vote.” Political competition, we suggest, should be related to more considered, state-level rational decisions at both the initiation and escalation stages of interstate conflict. This is so because a viable political opposition is more likely to point out the mistakes of the decision makers in power, and to call the attention of voters or other key power brokers to the costs to them of any sub-optimal government decisions. Leaders in competitive political environments must be able to defend their decisions at each stage of conflict on both practical and moral legitimacy grounds, because these are common and effective bases for criticizing foreign policy (e.g., Jentleson 1992). Leaders will face incentives for rational choice in the interests of the state vis-à-vis these two basic criteria, to avoid criticism that their choices are not in the national interest. Political competition will make decision makers more cautious, and often lead to wiser choices, which should help states avoid the costs of war, and conversely encourage them to be willing to go to war only when the chances of victory (and thus of the potential opponent’s choice for capitulation rather than escalation) are relatively high. We also suggest, however, that very low political competition will allow foreign policy decision makers to engage in bluffing behavior. This is so because the consequences of backing down from belligerent threats made during the initiation of a militarized dispute will be relatively mild.4 Without a critical opposition, such contradictory behavior might simply be downplayed or unremarked by national leaders. Questions will not be asked about the wisdom of such behavior, for example regarding costs in damaged trade relations or international reputation. This means that states with little competition should be more likely to initiate interstate disputes, but less likely to see those disputes escalate to war, than other states (for related arguments see Goldsmith 2007; Goldsmith, Chalup, and Quinlan 2008).

Schultz (2001, 6-10) also makes an argument about political competition and external conflict behavior.5 However, Schultz’s logic relies on the assumption that information and decision making will be more transparent with greater political competition. We are not fully

4 But see Weeks (2008) on audience costs and authoritarian regimes. 5 See our discussion in the Constraints section. Schultz’s argument rests considerably on the transparency of democratic polities to outside actors. But it is not clear that political competition is the main institutional source of this transparency. Participation requires transparency because voters must be informed of their choices, and constraints can create transparency because they require the executive to provide information in public fora, such as legislative hearings, and they empower non-governmental actors, such as journalists or watchdog groups, to seek and expose information about government policies.

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convinced of this. Especially in a highly partisan situation, when competition is most intense, governing parties might seek to conceal information from the opposition party or parties. Our approach is consistent with his in that he also expects states with high levels of political competition to be less likely to engage in bluffing behavior when initiating disputes with other states. However, here too the logical foundation is not identical. While Schultz argues that bluffing will be unlikely because the opposition will expose the bluff in order to undermine the party in government, we see this as not the most likely action. The governing party could let the opposition in on its plan to bluff, and the opposition might fear being seen as “playing politics,” unpatriotic, or even treasonous if it simply exposed the government’s position.

Rather, our argument hinges on the potential consequences for the governing party if its bluff is called by the foreign state with which it has initiated a dispute. The opposition would surely highlight this failed strategy to voters, whereas in a situation of low political competition, there would be no strong opposition voice, and so the government could more easily shift public attention away from the dispute, and/or make other arguments to explain away any apparent inconsistencies. Thus, we argue that governing parties facing strong competition refrain from bluffing because they more fully consider, and are more susceptible to, the risks of a failed bluff.

To summarize, our argument is that under effective institutions of political competition, foreign policy decision makers will be risk averse in order to avoid policy failure. They fear policy failure because of the existence of a viable opposition, with viable alternative policies, in a context of retrospective voting (Achen and Bartels 2004; Colaresi 2004). Under ineffective or non-existent institutions of political competition, foreign policy decision makers will be prone to bluff, because audience costs for backing down are small. However, they will consider state-level interests when making choices about costly interstate war, and thus will be likely to back down if victory seems unlikely. When considering international conflict behavior, this leads to the following monadic hypotheses. Hypothesis 5: High political competition will decrease the chance of a state initiating militarized interstate conflict, while low levels of participation will make initiation more likely (monadic, linear). Hypothesis 6: High and low political competition will decrease the chance of an interstate conflict escalating to war (monadic, non-linear).

However, we also propose dyadic effects regarding political competition, in order to assess its contribution to democratic and authoritarian peace effects. These focus on monotonic and non-monotonic aspects of competition’s interaction with the potential adversary’s regime type. Democracy: Polities with high levels of political competition will be less likely to target democracies, because democracies are aware that other democracies are stronger adversaries during war. Democracies are also more transparent and so better information about capabilities and intentions is likely to be available, facilitating bargaining and negotiation of differences without resort to violence to test credibility. Democratic regimes may also be perceived as more legitimate given international norms of governance, and so the moral case for war will be harder to make. Polities with low political competition may not distinguish between regime types when targeting an adversary in dispute initiation. However low-competition polities may be likely to underestimate democratic signals of resolve, if their leaders have less sophisticated understanding of democratic regimes, due to assumptions

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based on their own low audience costs for bluffing, thus making conflict escalation more likely. Authoritarian regime: Polities with high competition may target authoritarian regimes at the conflict initiation stage, because such states violate political and civil rights, and their leaders hold power without the electoral consent of the population, making low-level conflict justifiable against an opposition’s political criticism on moral grounds. In addition, such regimes often are better able to hide their true military capabilities, and intentions, which may make threats of military violence more necessary in order to learn about the resolve of an authoritarian regime. Because authoritarian regimes are not transparent, successful conflict outcomes may seem more likely at an early stage, until uncertainty over resolve is removed. Conflicts between high-competition and authoritarian regimes are also more likely to escalate to war because of the strong moral or political case which can be made to counter any potential criticism, and because victory may seem likely to the high-competition state as credible communication by the authoritarian regime is difficult even during crises, and thus resolve and intentions may remain unclear. The authoritarian state may underestimate the high-competition state’s resolve or intentions, on the other hand, due to a lack of insight into its competitive political processes. When low-competition polities face authoritarian regimes, however, the may not make distinctions at the initiation stage of conflict, but may find it easier to avoid escalation to war. This is so because both sides will be free to engage in flexible and quiet crisis bargaining, without concern for audience costs or political competition, and with a greater likelihood of common understanding of basic aspects of each other’s domestic political circumstances. Hypothesis 7: Higher competition regimes will be likely to target non-democracies for militarized conflict initiation (monotonic). Hypothesis 8: Higher competition regimes will be less likely to see interstate conflict escalate to war with democratic regimes, while lower competition regimes will be less likely to see interstate conflict escalate to war with authoritarian regimes (non-monotonic). Data Our data should distinguish between conflict initiators and targets. To do this, we use pooled, time-series directed-dyad data, 1950-2000. We include all pairings of countries (dyads) in the international system over the period. This post-World War II period is chosen to provide consistent measures of regime type and its component institutions across time and global regions, and to avoid missing data problems for regime type and other variables, which are more pronounced in earlier years. Economic data availability also restricts the time period. Conflict To model international conflict as a two-stage process, we use data on militarized interstate disputes (MIDs). An important aspect of the analysis is that we focus on dispute initiators by using directed dyads, which include all possible A-B and B-A pairings of dyad-years. A dispute enters the dataset only when the state on “side A” is the first to take a militarized action. The state on “side B” is then the target state. While we caution that the role of MID initiator is not always equivalent to that of the aggressor state which “started” the conflict, the first state to make a clear militarized move directed at another we feel is an important distinction, and one not often specified in democratic peace analyses.

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For the conflict initiation stage, we consider all MID initiations. For the escalation stage, we focus on those disputes in which at least 1,000 soldiers die (1,000 battle-deaths), which is a common threshold for identifying instances of interstate war. For our directed-dyad data, we use the Correlates of War (COW) dataset (Faten Ghosn and Scott Bennett. 2007), coding all years in which a MID was initiated by state A within a dyad as 1. A MID may include a “threat” to use force, such as a pronouncement by a political leader, or a “display” of force such as troop movements, as well as the actual use of military force which may include casualties.

Only a subset of dyads will escalate to the actual use of deadly force. We define escalation as involving at least 1,000 battle deaths, and code an escalation variable accordingly. Dyad-years of MID continuation are dropped because MID duration is not the topic of inquiry, and all other non-MID dyad-years are coded 0. The conflict indicators for both initiation and escalation are measured one year ahead of all independent variables (time t+1, a “forward lag”) to aid causal inference.

Because the MID data do not provide detailed information on potentially revealing aspects of the escalation process, such as the sequence of events prior to, during, and after MID initiation, leaders’ pronouncements during the process, or the time which passes between the initiation and escalation of a MID, we must assume that most conflicts do follow such a process. While not all MIDs follow a “ladder-like” escalation process (Jones, Bremer, and Singer 1996: 31), the available documentation indicates that the MID data reflect an underlying process of interstate tension and communication before, during, and after MID onset. Data on the 2119 distinct incidents which comprise 305 MIDs are available for 1992-2001 (Ghosn, Palmer, and Bremer 2004). Escalatory fatality patterns after the first militarized action can be identified. Eighteen of 280 MIDs with available data began with incidents involving 1-25 deaths, which did not experience a subsequent incident with more deaths, and one involved 26-100 deaths and did not experience a more deadly incident. But the 22 other MIDs which led to deaths recorded a more deadly incident subsequent to the first incident, including 13 with up to 25 deaths, three with up to 100, one with 101-250, three with 251-500, and two with 1000 or more. Thus, it is unlikely that many fatal MIDs erupt out of the blue with no prior pattern of escalation. Most importantly, no MIDs are initiated by incidents of over 100 fatalities. We therefore feel our assumption that 1000 battle deaths reflects the escalation of a previously initiated MID is quite realistic. Political Institutions We use data from the Polity IV project to code political institutions and political regimes (Marshall and Jaggers 2007). This provides a commonly used indicator of regime type, the polity scale, which ranges from full democracy to full authoritarianism (respectively, 10 through -10, on a 21-point scale). In order to measure the institutional components of regime type, we use Polity’s three components: “executive recruitment” (participation), “executive constraints” (constraint), and “political competition” (competition). These are discussed in detail in the Polity IV manual and in Goldsmith (2007b). We recode the polity variable and its components to a scale of -1 through 1 to aid interpretations of coefficients and interaction terms. In particular, this allows us to specify a non-monotonic multiplicative interaction term comprised of a component for state A and the regime type of state B. For example, the lowest values of each, when multiplied together, are -1 * -1 = 1, and the highest values of each multiplied by each other are 1 * 1 = 1. This produces a U-shaped functional form, which will be useful for assessing non-monotonic expectations as noted in the hypotheses above. For example, if hypothesis 8 is correct, the interaction of state A’s Competition term and state B’s regime type should have a negative relationship to MID escalation to 1000 or more deaths. As the interaction term takes higher

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values, approaching 1, the chance of escalation goes down. Thus, unless otherwise noted, all interactions for the regime type and component variables have this non-monotonic specification. We also include different specifications for monotonic hypotheses, later in the analysis, and note where this is done. These recode the polity and component variables on a scale of 0 to 2. Their interactions then create monotonic terms. So that the range covered will be comparable to that of the non-monotonic terms (-1 through 1), the monotonic terms are divided by 2 (range then is 0 through 2).

Of course, the polity variable and the component variables are highly correlated. Each component is correlated with polity at .92 - .94. The components are correlated with each other ranging from .79 through .83. Thus multicollinearity is a concern for the models, although the component variables do not produce a variance inflation factor (VIF) above 7. Robustness checks and our machine-learning based models also alleviate worries about misleading results due to multicollinearity. In addition, it is substantively plausible to assume that the components vary in meaningful ways cross-nationally. While participation, constraint, and competition tend to co-vary, their correlation is far from perfect. Examples of countries with relatively high levels of political participation, 7 of 8 on the polity component measure, while having relatively low levels of competition (2 through 5 out of 10) and constraint (3 or 4 out of 7) during the 1990s and 2000s are Tanzania (1995-2009), Kyrgyzstan (2005-2009), and Singapore (1990-2009). Examples of states with relatively high levels of executive constraint, but somewhat lower levels of participation and competition for periods during the 1990s and 2000s are Algeria, Nepal, and Zambia. These states had constraint scores of 5 (Zambia) or 6 out of 7, but competition scores of 7 or lower out of 10 and participation scores between 3 and 6 out of 8. Countries which have had relatively high levels of political competition, 8 or greater out of 10 on the Polity index, but considerably less effective institutions of participation or executive constraint, for recent years in the 1990s and 2000s, include Burkina Faso, Angola, Senegal, and Ghana. During periods when these countries scored 8 or higher on competition, but 5 or less on a scale of 8 for participation and 4 or less on a scale of 7 for executive constraints. Controls A range of control variables are included which might be related to both interstate conflict and regime type. At the MID initiation stage, we include a number of economic variables associated with international trade and with the “capitalist peace” proposition (Gartzke 2007), since democracy and market economics tend to covary. These include the volume of dyadic trade, the openness of trade with all partners as a portion of GDP of state A, the share of dyadic trade to GDP for state A and B, per capita GDP for state A and B, the per capita GDP of state A interacted with the contiguity of states A and B (see Gartzke 2007). Economic data are from Gleditsch (2002). Other controls include the degree of parity in the power of A and B (which ranges from 0 to 1, with 1 indicating equality in capabilities measured by the Composite Index of National Capabilities [CINC] from the COW dataset), the power capabilities of state A, the alliance portfolio similarity for the dyad (measured with Singorino and Ritter’s [1999] “S” statistic), a measure of contiguity indicating that the dyad shares land border or is separated by 24 miles of water or less, the distance between the capital cities of the states, and a cubic polynomials for the years since any previous MID for the dyad to account for temporal dependence in the data. (Carter and Signorino 2010). These control variables and the conflict

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indicators are generated using EUGene software (Bennett and Stam 2000). All analyses are run on a randomly selected 60 percent of dyads to reduce processing time.6 For the escalation stage, we include only controls for trade volume, alliance ties, and contiguity. Other variables proved insignificant at this stage. For the regional variables the following states are considered part of Sub-Saharan Africa: ANGOLA, BENIN, BOTSWANA, BURKINA FASO, BURUNDI, CAMEROON, CAPE VERDE, CENTRAL AFRICAN REPUBLIC, CHAD, COMOROS, CONGO, THE DEMOCRATIC REPUBLIC OF CONGO, COTE D'IVOIRE, DJIBOUTI, EQUATORIAL GUINEA, ERITREA, ETHIOPIA, GABON, GAMBIA, GHANA, GUINEA, GUINEA-BISSAU, KENYA, LESOTHO, LIBERIA, MADAGASCAR, MALAWI, MALI, MAURITANIA, MAURITIUS, MOZAMBIQUE, NAMIBIA, NIGER, NIGERIA, RWANDA, SAO TOME AND PRINCIPE, SENEGAL, SEYCHELLES, SIERRA LEONE, SOMALIA, SOUTH AFRICA, SWAZILAND, TANZANIA, UNITED REPUBLIC OF TOGO, UGANDA, ZAMBIA, ZANZIBAR, and ZIMBABWE. And the flowing comprise East Asia: BRUNEI DARUSSALAM, CAMBODIA, CHINA, INDONESIA, JAPAN, N. KOREA, S. KOREA, LAOS, MALAYSIA, MONGOLIA, MYANMAR, PHILIPPINES, REPUBLIC OF VIETNAM, SINGAPORE, TAIWAN, THAILAND, TIMOR-LESTE, and VIETNAM. Methods of Analysis We apply probit analysis with a Heckman (1976) selection model for the statistical analyses. Accounting for selection effects is a common suggestion in the literature on strategic interaction and interstate war (Fearon 2002; Sartori 2003). In addition, we apply machine-learning analysis which is capable of more flexibly assessing the shape of the functional form, even if very non-linear, for each variable of interest. We choose this approach because of our expectations regarding non-monotonic effects, in combination with the likely complexity of the regime-type-conflict relationship (Beck, King, and Zeng 2000; Goldsmith, Chalup, and Quinlan 2008). The machine-learning analysis also adapts a selection-model approach to consider the initiation and escalation stages of MIDs.

As will become apparent in the analysis section, using econometric modeling to test all possible linear, non-linear, monadic, and dyadic, monotonic and non-monotonic hypotheses is not practical, given the complexity, issues of collinearity, and space limitations. In order to overcome this significant empirical challenge, we employ a machine-learning based approach adapted specifically for this project. This allows us to assess graphically the likelihood of MID initiation and escalation to war conditional on interactions between state A’s political institutions and state B’s regime type. A Machine-Learning Approach with Additive Models For our machine learning-based analysis we adapt a generalised additive model framework introduced by Hastie and Tibshirani (1986, 1990). Generalised linear models form predictions based on a linear function of the features:

(1)

where are explanatory variables, is the link function and is the expected value of the dependent variable y. Additive models replace the linear combination with a sum of arbitrary functions of explanatory variables: 6 Results for the analyses with component variables are robust if the remaining 40 percent of the data are used instead.

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(2)

In the general framework the choice of functions is not prescribed and the richer class

of models can lead to overfitting without suitable regularization. Regularization is achieved by requiring the functions to be smooth.

We observe that it is possible to largely automate this process by casting it into non-smooth convex optimisation framework and taking advantage of sparsity inducing properties of l1-norm regularisation.

Let be the design matrix for the original problem and the associated parameter vector. We follow the standard procedure and transform the data by binning each feature into k intervals of equal length (we assume the same number of intervals for every feature for simplicity). This gives a new design matrix $ and a new parameter vector :

where is defined as follows (with denoting ):

(3)

Each observation is now transformed into a sparse vector of dimension km with m non-zero terms. While we lose some information about the features, we can now model non-linear effects in each coordinate. We can write down the parameter estimation problem as:

or in the equivalent Lagrangian form for some problem specific value of lambda:

where is negative log-likelihood or some other loss function and is a block matrix which evaluates discrete derivatives of the coefficients for each binned predictive variable:

We can choose appropriate depending on the structure of the problem and our objectives. For models additive in each coordinate, discrete approximations of the differential operator up to the third order are likely to be appropriate. This formulation of additive models can be seen as an extension of classical Whittaker mortality graduation procedure:

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known in macroeconomics as Hodrick-Prescott filtering (Hodrick and Prescott 1997) to a general regression setting.

Heuristically, the “fidelity” term encourages the solution w to be close to the original data y and the smoothness term penalises non-zero entries of , k-th order finite differences (or the discrete first derivative) of w. The value of the parameter determines the relative importance of the smoothness term. The second order finite differences matrix would then, for example, be as follows:

More recently extensions of this approach have been popularised in applied statistics and machine-learning literature as “fused lasso” (Tibshirani 2005). In signal processing the same formulation is called “total variation denoising.” This procedure usually gives a piecewise constant solution w (i.e. discrete first derivative has mostly zero entries due to “sparsity inducing” property of l1-norm penalties). Similarly, using second-order differences often results in a piecewise linear w and is known as “l1 trend filtering” (Kim et al. 2009). This is an effective approach to change point detection and is considerably simpler than many methods proposed to date. Variable interactions In an additive model the effect of all the explanatory variables is a sum of their individual effects. Individual effects show how the expected response varies as any single explanatory variable is changed with the others held constant at arbitrary values. For example in order to maximize the expected response we only need to separately maximise each of the component functions of the additive model.

In general there are no guarantees that an additive model will provide a satisfactory fit in any given situation. Non-additivity means that, as one explanatory variable is varied, the effect on the expected response depends on the fixed values of the other variables. Below is an example of how we would change equation (2) if the model is non-additive in variables and :

(4)

We can model non-additivity in parameters by including the corresponding interactions. Using the notation from equation (3) we can define the interaction as:

(5)

To obtain a piecewise constant solution we can use l1-norm penalty with the graph (which in this case is a regular grid) incidence matrix for regularization. The incidence matrix for a graph with n nodes and m edges is a matrix with each row representing an edge and composed of a 1 and a -1 in the columns corresponding to the two connected nodes and zeroes elsewhere.

Similarly to get an equivalent of “l1 trend filtering” over a regular grid we can consider horizontal and vertical second order differences. As in the one dimensional case, we

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minimize a weighted sum of the fitting error and a penalty on absolute value of slope changes in the horizontal and vertical directions. The resulting solution tends to be affine over connected regions. The boundaries between regions can be interpreted as curves along which the gradient of the underlying function changes quickly.

Findings Our first set of results focus on the overall effects of dyadic regime type using global data. Three different specifications of dyadic regime type yield somewhat different findings regarding global effects. The most common specification is used in Model 1. It is based on the “weak-link” assumption (Dixon 1994) and uses the lower democracy score of either state in the dyad. As is often done, we also include the higher democracy score. Model 2 gives a different specification of joint democracy, political distance (the similarity of regimes, across all types), and jointly authoritarian dyads. We feel this is a more precise specification of each concept than the weak-link indicators, but will not discuss it in detail here because the main aim is simply to demonstrate the role of regime type at each stage of conflict. The variables are discussed in detail in Goldsmith, Chalup, and Quinlan (2008). In Model 3 we show the straightforward coding of the regime type of each state in the dyad, using the polity regime type variables.

Overall, there is robust support for the democratic and authoritarian peace effects on the initiation of disputes. There is also support for a regime similarity effect above and beyond this, in Model 2. The negative coefficient for the Polity score of state A in the dyad at the initiation stage suggests that democracies are less likely to initiate MIDs with other states, regardless of the target’s regime type (suggesting a monadic effect). The evidence is much less clear regarding the escalation stage. The higher democracy score is significant (Model 1), but this may be interpreted as evidence for authoritarian peace, or for political distance. The political distance variable is also significant (Model 2). A democratic peace effect is not apparent for escalation of disputes to war.

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Table 1. Regime Type, MID Initiation and Escalation to War: Controlling for Economic Variables (1950-2000)

Model 1 Model 2 Model 3coef. s.e. sig. coef. s.e. sig. coef. s.e. sig.

Escalation to warDemocracyLower -0.328 0.254 0.197DemocracyHigher 0.330 0.169 0.050Joint democracy -0.143 0.326 0.661Politcal Distance 0.375 0.189 0.047Joint autocracy 0.025 0.186 0.895PolityA 0.146 0.109 0.180PolityB 0.077 0.102 0.448TradeVolume(ln) -0.034 0.010 0.001 -0.032 0.010 0.002 -0.040 0.010 0.000Alliance ties "S" 0.170 0.279 0.542 0.187 0.282 0.508 0.055 0.272 0.839Contiguity -0.480 0.343 0.162 -0.485 0.342 0.156 -0.590 0.305 0.053Constant -0.540 0.773 0.485 -0.207 0.678 0.761 0.160 0.547 0.770

MID initiationDemocracyLower -0.270 0.031 0.000DemocracyHigher 0.149 0.028 0.000Joint democracy -0.181 0.046 0.000Politcal Distance 0.164 0.029 0.000Joint autocracy -0.071 0.031 0.022PolityA -0.147 0.022 0.000PolityB 0.040 0.021 0.057TradeVolume(ln) 0.034 0.006 0.000 0.034 0.006 0.000 0.034 0.006 0.000TradeOpenA(ln) -0.059 0.020 0.004 -0.059 0.020 0.004 -0.052 0.020 0.011GDPshareA(ln) -0.009 0.011 0.433 -0.009 0.011 0.431 -0.014 0.011 0.186GDPshareB(ln) -0.033 0.010 0.001 -0.032 0.010 0.001 -0.033 0.010 0.001GDPpercapitaA(ln) 0.116 0.028 0.000 0.120 0.029 0.000 0.138 0.028 0.000GDPpercapitaA(ln)xContiguity -0.237 0.034 0.000 -0.239 0.035 0.000 -0.259 0.034 0.000GDPpercapitaB(ln) 0.056 0.017 0.001 0.058 0.017 0.001 0.055 0.017 0.001Parity 0.128 0.055 0.020 0.126 0.055 0.022 0.141 0.054 0.009PowerA 4.279 0.380 0.000 4.295 0.380 0.000 4.550 0.379 0.000Alliance ties "S" -0.332 0.052 0.000 -0.335 0.052 0.000 -0.418 0.051 0.000Contiguity 2.963 0.289 0.000 2.979 0.289 0.000 3.100 0.284 0.000Distance(ln) -0.204 0.017 0.000 -0.205 0.017 0.000 -0.206 0.017 0.000

Peaceyears -0.065 0.004 0.000 -0.065 0.004 0.000 -0.065 0.004 0.000

Peaceyears2 0.001 0.000 0.000 0.001 0.000 0.000 0.001 0.000 0.000

Peaceyears3 -0.000 0.000 0.000 -0.000 0.000 0.000 -0.000 0.000 0.000Constant -3.036 0.320 0.000 -2.938 0.327 0.000 -3.012 0.320 0.000

rho -0.520 0.167 0.018 -0.525 0.165 0.016 -0.572 0.144 0.005Number of obs 485232 485232 485232Uncensored obs 711 711 711Wald chi2 (5, 6, 5 df) 26.2 0.000 26.03 0.000 26.42 0.000

Note: Directed dyads; Dependent variable measured at year t+1; Regime-type variables scaled from -1 through +1; Statistically significant coefficients at .10 level or better indicated with bold font; Significance of rho based on the Likelihood Ratio test for independence of equations. Sample is random 60% of dyads.

We suspect examination of the roles of particular institutions across the range of their configurations will be more revealing than specifications including only overall regime type variables. Our hypotheses are based on this assumption, and we need to break regime type down into its institutional components in order to test them. But considering the interactions of specific institutional components of regime type, in the state which initiates conflict, with

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the regime type of the target state, immediately introduces a high degree of complexity and potential collinearity.

A straightforward model considering three types of institutions, and their interactions with the regime type of the target state, yields uninformative results. In Models 4-7, there is very little suggestion that regime type plays any role in the escalation process, and only weak evidence that political participation and political competition might be more promising factors for explaining dispute initiation than constraints on the executive. This is so whether we omit or include the economic control variables. Table 2. Regime Components, MID Initiation and Escalation to War: Monadic and Dyadic Variables

Model 4 Model 5 Model 6 Model 7coef. s.e. sig. coef. s.e. sig. coef. s.e. sig. coef. s.e. sig.

Escalation to warParticipationA -0.098 0.199 0.622 -0.008 0.233 0.973 -0.042 0.235 0.860 0.033 0.264 0.900ParticipationAxPolityB -0.324 0.295 0.272 -0.305 0.330 0.355ConstraintA -0.002 0.163 0.993 -0.139 0.190 0.463 -0.036 0.193 0.853 -0.146 0.214 0.496ConstraintAxPolityB 0.109 0.235 0.643 0.124 0.265 0.639CompetitionA 0.151 0.165 0.358 0.145 0.192 0.448 0.219 0.202 0.279 0.179 0.224 0.425CompetitionAxPolityB -0.262 0.260 0.312 -0.260 0.303 0.391PolityB 0.033 0.087 0.704 -0.016 0.146 0.914 0.091 0.103 0.379 0.026 0.166 0.875TradeVolume(ln) -0.041 0.010 0.000 -0.034 0.011 0.001Alliance ties "S" 0.225 0.234 0.337 0.347 0.253 0.171 0.061 0.276 0.826 0.154 0.288 0.594Contiguity -0.701 0.254 0.006 -0.590 0.309 0.056 -0.560 0.310 0.071 -0.436 0.355 0.220Constant 0.676 0.464 0.145 0.165 0.610 0.786 0.158 0.559 0.778 -0.307 0.681 0.652

MID initiationParticipationA 0.127 0.042 0.003 0.130 0.043 0.002 0.116 0.045 0.010 0.129 0.045 0.004ParticipationAxPolityB -0.090 0.056 0.112 -0.114 0.058 0.049ConstraintA -0.121 0.039 0.002 -0.119 0.040 0.003 -0.127 0.042 0.002 -0.129 0.042 0.002ConstraintAxPolityB -0.074 0.051 0.146 -0.041 0.053 0.438CompetitionA -0.110 0.037 0.003 -0.097 0.038 0.010 -0.122 0.040 0.003 -0.116 0.040 0.004CompetitionAxPolityB -0.103 0.050 0.040 -0.093 0.052 0.075PolityB 0.063 0.020 0.001 0.045 0.026 0.088 0.033 0.021 0.124 0.022 0.028 0.420TradeVolume(ln) 0.036 0.006 0.000 0.035 0.006 0.000TradeOpenA(ln) -0.053 0.021 0.011 -0.053 0.021 0.012GDPshareA(ln) -0.018 0.011 0.103 -0.014 0.011 0.209GDPshareB(ln) -0.033 0.010 0.001 -0.031 0.010 0.002GDPpercapitaA(ln) 0.140 0.029 0.000 0.121 0.029 0.000GDPpercapitaA(ln)xContiguity -0.251 0.035 0.000 -0.222 0.035 0.000GDPpercapitaB(ln) 0.061 0.017 0.000 0.071 0.017 0.000Parity 0.133 0.053 0.012 0.116 0.054 0.031 0.133 0.056 0.016 0.118 0.056 0.037PowerA 5.140 0.333 0.000 5.260 0.338 0.000 4.704 0.386 0.000 4.888 0.392 0.000Alliance ties "S" -0.514 0.047 0.000 -0.425 0.048 0.000 -0.412 0.052 0.000 -0.323 0.053 0.000Contiguity 1.001 0.045 0.000 1.051 0.046 0.000 3.024 0.290 0.000 2.819 0.296 0.000Distance(ln) -0.212 0.016 0.000 -0.218 0.016 0.000 -0.209 0.018 0.000 -0.211 0.018 0.000Peaceyears -0.064 0.003 0.000 -0.063 0.004 0.000 -0.067 0.004 0.000 -0.067 0.004 0.000Peaceyears2 0.001 0.000 0.000 0.001 0.000 0.000 0.001 0.000 0.000 0.001 0.000 0.000

Peaceyears3 -0.000 0.000 0.000 -0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000Constant -0.916 0.137 0.000 -0.948 0.138 0.000 -3.121 0.330 0.000 -3.043 0.331 0.000

rho -0.692 0.108 0.000 -0.644 0.132 0.002 -0.564 0.148 0.006 -0.509 0.170 0.020Number of obs 481633 481633 468693 468693Uncensored obs 708 708 690 690Wald chi2 (6,9,7,10 df) 12.92 0.044 21.17 0.012 26.38 0.000 26.3 0.003

Note: Directed dyads; Dependent variable measured at year t+1; Regime-type variables scaled from -1 through +1;Statistically significant coefficients at .10 level or better indicated with bold font; Significance of rho based on the Likelihood Ratio test for independence of equations. Sample is random 60% of dyads.

At this stage we turn to our machine-learning based approach for guidance as to functional form for the component variables. Figures 2 and 3 are “heat maps” which portray the results for the components for state A on the horizontal axis and the regime type of state B on the vertical axis. The left panels picture political competition for state A, the central panels

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participation for state A, and the right panels show executive constraints for state A. Red indicates a higher probability of conflict, blue a lower probability.7 Figure 2 MID initiation: Competition; Participation; Constraint.

The results in Figure 2 suggest that political competition of the initiating state has a monotonic interaction with the regime type of the target state in disputes (left panel). States with high political competition are less likely to initiate disputes with democracies (lower right corner is dark blue). This supports hypothesis 7. There is some evidence of a monadic effect of participation in the initiator state on the chance of dispute initiation (middle panel). This supports hypothesis 1a. There is also some evidence that executive constraints in the initiating state make it less likely that a dispute will be initiated with a democracy, consistent with hypothesis 3. However, this is a curious interaction because for most values of the target state’s regime type, the effect of variation in executive constraints is zero. Specifying a categorical interaction based on target-state polity scores of 6 or higher, roughly democracies, would seem to be too inductive an approach. A more conservative approach would be to assume at least a monadic effect of executive constraints, since on average (controlling for the regime type of the target), higher constraints lead to a lower chance of dispute initiation.

Overall, then, figure 2 implies a monotonic interaction with the target state’s regime type for the degree of political competition of the initiator, a monadic effect of the initiator’s degree of participation, and a monadic effect of the initiator’s degree of executive constraints. Figure 3 MID escalation to war: Competition; Participation; Constraint.

7 The control variables are included in all the machine-learning based analysis, but we do not present or discuss the results for these.

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The results in Figure 3 suggest that political competition of state A in a dyad has a non-monotonic interaction with the regime type of state B. While high competition states are less likely to experience escalation to war with democracies, low-competition states are less likely to experience escalation to war with authoritarian regimes. This is consistent with our expectations in hypothesis 8. Substantively the effect is fairly large. The effect of participation is also fairly large, and appears to be relatively monotonic in its interaction with the regime type of state B. The greater the degree of participation in state A, the less likely a MID it initiated will escalate to war with a democracy. This is consistent with hypothesis 2. The effect of constraint appears to be relatively small, and close to zero for much of the range of the data. Low constraint regimes are more likely to see MIDs escalate to war with highly democratic states. Thus overall institutions of participation and competition contribute substantially to the explanation of democratic peace, but only political competition also seems to help us understand the authoritarian peace.

But do these dynamics of political institutions at each stage of conflict translate into overall democratic and authoritarian peace effects? It is especially important to ascertain the effects of regime type on MID escalation to war, based on the doubts introduced by results in Tables 1 and 2. In Figures 4 and 5, state A (initiator) is on the vertical axis and state B (target) is on the horizontal axis. Examining the interaction of the overall regime type of states A and B, in Figure 4, the pattern of MID initiation of non-democracies against democracies stands out (upper right), as does the low likelihood of a democracy initiating a MID against another democracy (lower right). Figure 4 MID initiation: Regime type interactions.

At the stage of escalation to war, the interaction of the overall regime type of states A and B, in Figure 5, suggests that the authoritarian and democratic peace effects are both important causes of peace. The overall non-monotonic functional form of dyadic regime type is evident at this stage of conflict.

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Figure 5 MID Escalation to War: Regime type interactions.

Our machine-learning based analysis provides strong evidence supporting democratic peace at both the stage of MID initiation and the stage of MID escalation to war. It also provides evidence of an authoritarian peace effect at each stage, but most pronounced at the escalation stage. Institutions of political competition are substantively the most relevant for explaining democratic peace at the MID initiation stage, and have some relevance for authoritarian peace effects then, too. Political competition, or more precisely its relative absence, also provides the institutional foundation for authoritarian peace effects on MID escalation. Institutions of participation are most relevant for explaining the democratic peace effect at the stage of MID escalation to war, as anticipated in selectorate theory. Refined Selection Models We now turn to specifying our selection models based on insights from the machine-learning based results in figures 2 and 3. Our models for pooled global data with a reduced and refined specification more consistent with the machine-learning based heat maps show statistically significant effects. In particular, we find that political competition has a monadic effect at the MID initiation stage, such that greater participation in state A makes it more likely to initiate a MID. This is consistent with hypothesis 1a, regarding populism. We also find that political competition of state A has a monotonic negative effect on the chance of MID initiation, in interaction with the regime type of state B, as anticipated by hypothesis 7.

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Table 3. Regime Components (reduced), MID Initiation and Escalation to War: Interactions

Model 8 Model 9 Model 10 Model 11coef. s.e. sig. coef. s.e. sig. coef. s.e. sig. coef. s.e. sig.

Escalation to warPolityA 0.017 0.279 0.952 0.035 0.317 0.913 -0.185 0.302 0.541 -0.179 0.353 0.613ParticipationA 0.420 0.389 0.280 0.444 0.441 0.314(monotonic)ParticipationAxPolityB -0.867 0.390 0.026 -0.816 0.432 0.059CompetitionA 0.190 0.278 0.495 0.243 0.326 0.457CompetitionAxPolityB -0.375 0.182 0.039 -0.349 0.198 0.078PolityB 0.476 0.235 0.043 0.488 0.253 0.054 -0.094 0.124 0.447 -0.046 0.142 0.744TradeVolume(ln) -0.034 0.010 0.001 -0.035 0.011 0.001Alliance ties "S" 0.346 0.239 0.148 0.157 0.276 0.570 0.339 0.253 0.180 0.146 0.288 0.613Contiguity -0.677 0.273 0.013 -0.523 0.320 0.103 -0.581 0.307 0.058 -0.418 0.354 0.238Constant 0.787 0.439 0.073 0.278 0.529 0.600 0.188 0.594 0.752 -0.293 0.668 0.660

MID initiationPolityA -0.517 0.343 0.132 -0.388 0.363 0.285 -0.493 0.343 0.151 -0.371 0.363 0.306ParticipationA 0.330 0.136 0.016 0.275 0.144 0.056 0.322 0.136 0.018 0.270 0.144 0.061CompetitionA 0.300 0.125 0.017 0.220 0.133 0.098 0.286 0.126 0.023 0.210 0.133 0.115(monotonic)CompetitionAxPolityB -0.449 0.049 0.000 -0.409 0.051 0.000 -0.446 0.050 0.000 -0.407 0.051 0.000ConstraintA 0.053 0.120 0.660 0.001 0.127 0.992 0.049 0.120 0.682 -0.001 0.127 0.991PolityB 0.236 0.027 0.000 0.189 0.029 0.000 0.235 0.027 0.000 0.188 0.029 0.000TradeVolume(ln) 0.035 0.006 0.000 0.034 0.006 0.000TradeOpenA(ln) -0.053 0.021 0.013 -0.053 0.021 0.013GDPshareA(ln) -0.014 0.011 0.203 -0.014 0.011 0.208GDPshareB(ln) -0.031 0.010 0.002 -0.031 0.010 0.002GDPpercapitaA(ln) 0.122 0.029 0.000 0.122 0.029 0.000GDPpercapitaA(ln)xContiguity -0.223 0.035 0.000 -0.223 0.035 0.000GDPpercapitaB(ln) 0.071 0.017 0.000 0.071 0.017 0.000Parity 0.122 0.054 0.023 0.123 0.056 0.029 0.123 0.054 0.023 0.122 0.056 0.030PowerA 5.203 0.340 0.000 4.841 0.394 0.000 5.204 0.340 0.000 4.841 0.394 0.000Alliance ties "S" -0.423 0.048 0.000 -0.325 0.053 0.000 -0.424 0.048 0.000 -0.326 0.053 0.000Contiguity 1.051 0.046 0.000 2.832 0.296 0.000 1.050 0.046 0.000 2.834 0.296 0.000Distance(ln) -0.216 0.016 0.000 -0.210 0.018 0.000 -0.216 0.016 0.000 -0.210 0.018 0.000Peaceyears -0.063 0.004 0.000 -0.067 0.004 0.000 -0.063 0.004 0.000 -0.067 0.004 0.000Peaceyears2 0.001 0.000 0.000 0.001 0.000 0.000 0.001 0.000 0.000 0.001 0.000 0.000Peaceyears3 -0.000 0.000 0.000 -0.000 0.000 0.000 -0.000 0.000 0.000 -0.000 0.000 0.000Constant -0.768 0.141 0.000 -2.872 0.335 0.000 -0.765 0.141 0.000 -2.870 0.335 0.000

rho -0.679 0.113 0.000 -0.549 0.150 0.007 -0.642 0.131 0.002 -0.504 0.169 0.020Number of obs 481633 468693 481633 468693Uncensored obs 708 690 708 690Wald chi2 (6, 7, 6, 7 df) 21.48 0.002 26.3 0.000 19.91 0.003 25.81 0.001

Note: Directed dyads; Dependent variable measured at year t+1; Regime-type variables scaled from -1 through +1;Statistically significant coefficients at .10 level or better indicated with bold font; Significance of rho based on the Likelihood Ratio test for independence of equations. Sample is random 60% of dyads.

Among states experiencing disputes, we find that participation in the initiating state has a monotonic interaction with the regime type of the target state, consistent with hypothesis 2 and democratic peace. And we find that political competition has a non-monotonic interaction with the regime type of the target state, consistent with hypothesis 8 and democratic and authoritarian peace.

While the heat maps in Figures 2 through 5 show somewhat more subtle, distinct dynamics, these general patterns are consistent across the machine-learning and econometric results regarding monotonic and non-monotonic dynamics. Regional Analyses But is this institutional specification of the regime-type conflict relationship robust across global regions? Does it provide a better general specification such that apparent regional differences in previous research are no longer apparent?

We focus on East Asia and Sub-Saharan Africa, two regions which previous studies have found to lack a democratic peace (Goldsmith 2006, 2007a; Henderson 2009). Our specification does prove relatively robust. The major exceptions are the effects of political participation and competition on dispute initiation in East Asia. There are either insignificant or even positive effects, to those in Table 3. At the conflict escalation stage, our interaction

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terms show no significant differences between the effects of institutions globally and in these two regions. Table 4. Regional Interactions and Regime Components (reduced), MID Initiation and Escalation to War

Model 12 Model 13 Model 14 Model 15coef. s.e. sig. coef. s.e. sig. coef. s.e. sig. coef. s.e. sig.

Escalation to warPolityA 0.021 0.306 0.945 -0.232 0.355 0.515 0.025 0.342 0.942 -0.296 0.389 0.446ParticipationA 0.438 0.429 0.307 0.483 0.474 0.308(monotonic)ParticipationAxPolityB -0.824 0.425 0.052 -0.844 0.453 0.062(monotonic)ParticipationAxPolityBxRegion -2.267 2.181 0.299 -1.432 2.370 0.546CompetitionA 0.271 0.330 0.412 0.399 0.365 0.275CompetitionAxPolityB -0.399 0.205 0.052 -0.473 0.215 0.028CompetitionAxPolityBxRegion 1.081 0.860 0.209 1.663 1.184 0.160Region -0.092 0.525 0.861 -0.831 0.524 0.113 0.209 0.494 0.672 -0.557 0.794 0.482PolityB 0.501 0.256 0.050 -0.064 0.141 0.651 0.526 0.269 0.050 -0.017 0.154 0.913TradeVolume(ln) -0.028 0.011 0.007 -0.028 0.011 0.010 -0.036 0.011 0.001 -0.035 0.011 0.001Alliance ties "S" 0.232 0.269 0.389 0.204 0.283 0.472 0.082 0.288 0.775 0.099 0.300 0.742Contiguity -0.563 0.303 0.063 -0.391 0.342 0.253 -0.400 0.352 0.255 -0.267 0.382 0.485Constant 0.468 0.505 0.354 -0.182 0.655 0.781 -0.025 0.594 0.966 -0.642 0.717 0.371

MID initiationPolityA -0.272 0.365 0.455 -0.253 0.365 0.488 -0.430 0.370 0.245 -0.418 0.370 0.258ParticipationA 0.262 0.146 0.072 0.255 0.146 0.080 0.271 0.144 0.060 0.267 0.144 0.063ParticipationAxRegion -0.350 0.141 0.013 -0.346 0.141 0.014 0.135 0.137 0.324 0.134 0.137 0.327CompetitionA 0.163 0.134 0.223 0.151 0.134 0.260 0.293 0.137 0.033 0.285 0.137 0.038(monotonic)CompetitionAxPolityB -0.422 0.052 0.000 -0.420 0.052 0.000 -0.379 0.052 0.000 -0.376 0.052 0.000(monotonic)CompetitionAxPolityBxRegion 0.904 0.167 0.000 0.898 0.168 0.000 -0.931 0.304 0.002 -0.936 0.304 0.002ConstraintA -0.034 0.128 0.789 -0.037 0.128 0.773 -0.059 0.132 0.653 -0.062 0.132 0.639ConstraintAxRegion -0.014 0.129 0.916 -0.012 0.129 0.923 0.395 0.121 0.001 0.405 0.120 0.001Region 0.164 0.096 0.089 0.166 0.096 0.085 0.049 0.083 0.558 0.052 0.083 0.533PolityB 0.182 0.029 0.000 0.182 0.029 0.000 0.181 0.030 0.000 0.180 0.030 0.000TradeVolume(ln) 0.034 0.006 0.000 0.034 0.006 0.000 0.035 0.006 0.000 0.035 0.006 0.000TradeOpenA(ln) -0.045 0.021 0.034 -0.045 0.021 0.034 -0.040 0.022 0.063 -0.040 0.022 0.063GDPshareA(ln) -0.016 0.011 0.164 -0.016 0.011 0.168 -0.015 0.011 0.176 -0.015 0.011 0.181GDPshareB(ln) -0.032 0.010 0.001 -0.032 0.010 0.001 -0.031 0.010 0.002 -0.031 0.010 0.002GDPpercapitaA(ln) 0.136 0.029 0.000 0.136 0.029 0.000 0.112 0.029 0.000 0.112 0.029 0.000GDPpercapitaA(ln)xContiguity -0.222 0.036 0.000 -0.223 0.036 0.000 -0.268 0.037 0.000 -0.269 0.037 0.000GDPpercapitaB(ln) 0.074 0.018 0.000 0.074 0.018 0.000 0.053 0.018 0.003 0.053 0.018 0.003Parity 0.133 0.056 0.019 0.132 0.057 0.020 0.133 0.057 0.019 0.133 0.057 0.019PowerA 4.780 0.400 0.000 4.779 0.400 0.000 4.903 0.397 0.000 4.898 0.398 0.000Alliance ties "S" -0.322 0.053 0.000 -0.323 0.053 0.000 -0.317 0.053 0.000 -0.318 0.053 0.000Contiguity 2.824 0.299 0.000 2.829 0.300 0.000 3.196 0.308 0.000 3.200 0.308 0.000Distance(ln) -0.208 0.018 0.000 -0.208 0.018 0.000 -0.227 0.019 0.000 -0.227 0.019 0.000Peaceyears -0.066 0.004 0.000 -0.066 0.004 0.000 -0.065 0.004 0.000 -0.065 0.004 0.000Peaceyears2 0.001 0.000 0.000 0.001 0.000 0.000 0.001 0.000 0.000 0.001 0.000 0.000Peaceyears3 -0.000 0.000 0.000 -0.000 0.000 0.000 -0.000 0.000 0.000 -0.000 0.000 0.000Constant -3.058 0.338 0.000 -3.058 0.339 0.000 -2.518 0.349 0.000 -2.515 0.349 0.000

rho -0.595 0.140 0.003 -0.541 0.161 0.013 -0.460 0.176 0.033 -0.423 0.189 0.059Number of obs 468693 468693 468693 468693Uncensored obs 690 690 690 690Wald chi2 (9 df) 28.05 0.001 26.58 0.002 24.05 0.004 26.28 0.002

Note: Directed dyads; Dependent variable measured at year t+1; Regime-type variables scaled from -1 through +1;Statistically significant coefficients at .10 level or better indicated with bold font; Significance of rho based on the Likelihood Ratio test for independence of equations.

Region: East Asia Region: Sub-Saharan Africa

But do the overall dynamics also appear the same if we examine machine-learning based results for these regions? In Figure 6 we present results for Africa and East Asia.

For the initiation of MIDs, the patterns in Africa are not identical to those in Figure 2, but similar. We can still see a monotonic pacific effect for political competition in interaction with democracy (but this might even be better characterized as monadic). We can also still see a monadic effect of participation consistent with our hypothesis (1a) regarding populism, although there is more chance of high participation regimes initiating MIDs with authoritarian regimes (perhaps a monotonic interaction producing African authoritarian peace). Executive constraints appear to have little effect on MID initiation (as in Figure 2), but the pattern suggests a weak monadic positive effect (unlike Figure 2).

In East Asia, however, the institutional components of regime type produce very different patterns for MID initiation. There appears to be a monotonic positive relationship

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between political competition, the regime type of the target state, and MID initiation (left panel). States with greater political competition in East Asia are more likely to initiate MIDs with democracies. This directly contradicts hypotheses 5 and 7. Similarly, participation (middle panel) in East Asia appears to have a monotonic pacific effect, consistent with democratic peace, but not with our interpretation of selectorate theory as represented by hypothesis 1. Interestingly, the pattern for executive constraints in East Asia is very similar to that found globally (Figure 2), supporting hypothesis 3.

While these different patterns for East Asia do not allow us to claim that political competition and participation have completely universal effects at all stages of conflict in all regions, they are consistent with the statistical results presented in Table 4, suggesting a relatively pacific effect for participation and a relatively conflictual effect for competition on the chances of MID initiation in East Asia. This increases our confidence in our approach combining conventional econometrics and nuanced machine-learning based techniques.

The patterns for escalation in African dyads are less pronounced than is the case for the global data in Figure 3, but there is some hint of low participation and (very) authoritarian regimes have a lower likelihood of MID escalation to war, and also some indication that low participation for state A leading to a greater chance of escalation with authoritarian regimes, and a lower chance with democratic ones. Executive constraints seem to have very little effect on escalation, but the pattern is somewhat different to that in the global data, but still roughly consistent with hypothesis 4.

Of considerable interest, the patterns regarding MID escalation to war with at least 1000 battle deaths in East Asia are similar to those for the global data and for Africa. This is noteworthy given the distinct patterns for this region regarding MID initiation. It is also consistent with the econometric results in Table 4. Political competition appears to have a non-monotonic relationship with escalation in East Asia, consistent with authoritarian and democratic peace, as expected in hypothesis 8. Participation appears to have a monotonic relationship with escalation, consistent with democratic peace and hypothesis 2. Executive constraint’s effects are consistent with democratic peace, as anticipated in hypothesis 4, but also are consistent with authoritarian peace.

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Figure 6 Africa, MID initiation: Competition; Participation; Constraint.

Africa, MID Escalation: Competition; Participation; Constraint

East Asia, MID Initiation: Competition; Participation; Constraint

East Asia, MID Escalation: Competition; Participation; Constraint

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Turning to the overall regime-type effects in the two regions in Figure 7, there are more differences than similarities for the overall regime-type effects regionally and globally. The authoritarian peace seems to be a more universal phenomenon than the democratic peace. The exception being that authoritarian regimes in Africa are more likely to escalate disputes with each other. But in East Asia and Africa, authoritarian regimes are less likely to initiate MIDs with each other. In East Asia there appears to be a strong democratic peace effect on MID escalation to war, as well. Figure 7 Africa Initiation, Escalation

East Asia Initiation, Escalation

Discussion Our approach seeks to combine some existing and new theory regarding regime type and conflict, and empirical analysis using both standard econometrics as well as a machine-learning based approach. Consideration of the role of three components of regime type at two stages of conflict using this approach has produced some intriguing provisional findings. We focus on the roles of political participation and political competition. Examining the effects in East Asia and Africa test the robustness of these findings in regions which previous studies have shown have shown do not provide clear support for the democratic peace proposition. We find strongest support for our hypotheses 1a, 2, 7, and 8. The first two predict that political participation will lead to populism, which increases the likelihood of dispute initiation, but also that elites in high-participatory states will be less likely to escalate such conflicts, especially with democracies, due to the greater risks associated with losing a costly

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war than with backing down to avoid one. The latter two hypotheses focus on competition. Hypothesis 7 predicts that states with high levels of political competition will be unlikely to initiate disputes with democracies, but more likely to target non-democracies, due to the greater ability to advance practical and moral arguments in defense of such choices, if challenged by domestic opposition. Hypothesis 8 predicts that states with high levels of competition will be unlikely to escalate disputes with democracies, while states with low levels of competition will be unlikely to escalate disputes with authoritarian regimes. High competition regimes will be able to assess the capability and resolve of another democracy, and arrive at a negotiated settlement avoiding the costs of war. Low competition regimes will be able to climb down from a bluff or ill-considered confrontation with adversarial authoritarian regimes with minimal audience costs. These central findings are relatively robust in the statistical and machine-learning analyses. The main exception is in East Asia, where our expectations for the MID initiation stage were not supported. We speculate that this may relate to the East Asian developmental state model, but further examination is necessary. However, the most intriguing and we believe potentially promising aspect of the analysis we present is that the institutional components of regime type exhibit more robust and consistent behavior, when we introduce our refined variable specifications, than the overall regime type index. Different aspects of political systems may have different implications for foreign policy behavior, at different stages of the conflict process. On average, these seem to aggregate into clear democratic and authoritarian peace effects in pooled global data. But, we believe this should not obscure the need for theory to consider the microfoundations across all regime types, and all plausible combinations of political institutions within any given state. We also note some of the limitations of our analyses at this stage, which lead us to consider the results as only preliminary and suggestive. First, other important covariates may be omitted, such as the incidence of internal conflict in states (perhaps especially for Africa). Second, some low-populated areas of the data space may explain the different look of heat maps for regions versus the global heat maps. Machine-learning approaches such as ours are potentially vulnerable to high influence by small numbers of observations. We will appreciate comments and feedback regarding other areas of concern. References Achen, Christopher H. and Larry M. Bartels, “Blind Retrospection: Electoral Responses to Drought, Flu, and Shark Attacks,” (typescript, Princeton University, 2004). Beck, Nathianiel, Gary King, & Langche Zeng. 2000. “Improving Quantitative Studies of International Conflict,” American Political Science Review 94, 1: 21-35. Bennett, D. Scott, and Allan Stam. 2000. “EUGene: A Conceptual Manual.” International Interactions 26:179-204. Boyd, S. and L. Vandenberghe. 2004. Convex Optimization. Cambridge University Press. Braithwaite, Alex and Douglas Lemke. 2011. “Unpacking Escalation,” Conflict Management and Peace Science 28, 2: 111-123. Bueno de Mesquita, B., A. Smith, R. Siverson & J. Morrow. 2003. The Logic of Political Survival. Cambridge: MIT

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