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date: 24 September 2017

Conflict, Regions, and Regional Hierarchies

Summary and Keywords

Despite decades of scholarly attention to conflict and cooperation processes in international politics, rigorous, comparative, large-N analyses of these questions at the region level are difficult to find in the literature. Although this relative absence may stem in part from the difficulties related to the theoretical conceptualization or methodological operationalization of regions, it certainly is not for lack of interesting variation in terms of conflict and cooperation processes across regions. Between this variation and recent contributions toward a dynamic identification of regions, comparative analysis of conflict and cooperation outcomes at the region level are primed for exploration and increasingly salient as recent political elections in the United States (Trump election) and the United Kingdom (Brexit) have demonstrated a willingness on the part of policymakers to scale back efforts toward global interdependence.

Turning attention to a region level unit of analysis, however, does not require abandoning decades of scholarship at the state or dyad levels. Indeed, much of this work may be viewed as informing or complementary to comparative regional analyses. In particular, regional propensity for cooperation or conflict is likely to be conditioned by a number of prominent explanations of these phenomena at state and dyad levels, which may usefully be conceived in their regional aggregates as so-called regional fault lines or baseline conditions. These include the presence of major and/or regional powers, interstate rivalries, unresolved territorial claims, civil wars, regime similarity, trade relationships, and common membership in intergovernmental organizations.

Of these baseline conditions, the impact of major and regional powers on regional patterns of cooperation and conflict is notable for both its theoretical and practical implications. Power transition theory, hegemonic stability theory, hierarchical theory, and long cycle theory all suggest major—and to a lesser extent regional—powers will seek to establish order within areas under their influence; alternatively, the overwhelming capabilities these states bring to a region arguably act as a deterrent inhibiting conflict. Empirical analysis reveals—irrespective of the causal mechanism at hand—regions characterized by the presence of a major or regional power experience less conflict. Moving forward, future research should work to test the two plausible causal mechanisms for this finding—order building versus deterrence—to determine the true nature of hierarchy’s pacifying influence.

Keywords: regions, conflict, hierarchy, MIDs, major powers, regional powers, cooperation, empirical international relations theory

Introduction

Why are some regions in international politics more conflictual than others? Why have some regions developed complex mechanisms for collaboration over intraregional security or economic relationships while other regions have failed to do so? Despite decades of scholarly attention to conflict and cooperation processes in international politics, rigorous, comparative, large-N analyses of these questions at the region1 level are difficult to find in the literature.

The paucity of focus on region as the appropriate level of analysis is perplexing for at least three reasons. First, most states conduct their political relationships within their own regions, often within a single neighborhood within the region. With some significant exceptions, most states also conduct the bulk of their economic transactions within their regions as well. The immediate or proximate geopolitical environment in which most states act thus appears to be quite salient. Second, there is persistent evidence in the empirical models advanced by scholars studying conflict and cooperation dynamics that regions have a significant impact on numerous research questions of interest.2 Yet the salience of regional context as a contributing explanation to how states behave is typically not the focus of these studies, since regional considerations are usually integrated into the analysis for methodological purposes (controlling for fixed effects).

Third, it is clear that regions differ substantially from one another in terms of their conflict propensities. To illustrate how much they do, based on a recent categorization3 of regions (Volgy, Bezerra, Rhamey, & Cramer, 2017), the occurrence of severe militarized interstate disputes (MIDs) were used to construct Figures B1 through B5 in Appendix B. The figures reflect the number of severe MIDs in regions,4 controlling for the number of states in the region, across five decades that span the Cold War and post–Cold War periods. In addition, Table 1 identifies the two most extreme cases of high- and low-conflict regions across the five decades, and compares their per state MID scores to the global mean for each decade. Some regions consistently exhibit extremely high conflict propensity over time (Middle East5), some regions move from being highly conflictual to less so (East Asia, Southern Africa), and some regions are substantially pacific, consistently “underperforming” the global average on MIDs (Europe, North America) during and after the Cold War.

Table 1. Most and Least Conflictual Regions, by Severe MIDs, 1950s through 2000s.

Time Frame

Region

Severe MIDs/Capita

Region Mean minus Global Mean

1950s

Middle East

4.40

2.30

East Asia

4.00

1.90

South Central America

.50

−1.60

North America

0.40

−1.70

1960s

East Asia

4.33

2.56

Middle East

3.93

2.16

Central Savannah

0.25

−1.52

Western Europe

0.58

−1.19

1970s

Middle East

2.79

1.52

East Asia

2.18

0.91

Europe

0.48

−0.79

Southeast Asia

0.50

−0.77

1990s

Middle East

2.69

1.72

Central Africa

2.11

1.14

Southern Africa

0.11

−0.86

Europe

0.48

−0.49

2000s

South Asia

4.67

3.79

Central Africa

2.88

2.00

Southern Africa

0.11

−0.77

North America

0.25

−0.63

The absence of a substantial focus on region as an appropriate level of analysis in most quantitative scholarship is likely due to three reasons. First, there is virtually no consensus regarding the appropriate definition of a region and, consequently, little agreement on an appropriate method of delineating regions and state membership within them. This was the case more than four decades ago (Thompson, 1973), and it remains the case today (Volgy et al., 2017). Second, there appears to be a substantial disconnect between scholars who engage in large-N studies of conflict and those who, with different methodological and theoretical lenses, focus primarily on regions. For instance, the rich literature on regionalism and regional powers is seldom addressed or even cited by those who integrate regional variables in their empirical models. Third, the move from focusing on states or dyads to regions as the appropriate unit of analysis dramatically reduces the number of observations available to quantitative researchers. This creates vexing issues for testing critical hypotheses at the region level. Thus explanations and robust findings at the state and dyadic levels of analysis are seldom brought to the region level.

This lack of attention in the literature has not gone completely unnoticed, and there have been attempts to rectify it (e.g., Acharya, 2007; Fawn, 2009; Hurrell, 2007; Lemke, 2002, 2010; Nolte, 2010). The effort here differs from previous systematic, large-N analyses, however, in offering an explicit, comparative analysis at the region level, seeking two objectives. First, it integrates extant findings from other levels of analysis in order to stipulate conditions under which some regions are likely to be more conflict prone than others. Second, it offers an explanation regarding regional conflict patterns based on the presence or absence of regional hierarchies that may be able to manage conflicts.6

What follows here offers, first, a theoretical framework designed for a comparative analysis of regions for explaining variation in intraregional conflicts between states. Second, it highlights the Regional Opportunity and Willingness (ROW) approach to regional delineation that allows for changes in regional composition over time. Third, it tests two central hypotheses, derived from this theoretical framework. Lastly, it presents a discussion of results and additional thoughts regarding the plausible causal mechanisms between hierarchy and conflict mitigation at the region level.

Theoretical Framework

The central argument made here is that regions can be differentiated by whether or not they contain one or more dominant states—major powers and/or regional powers—that can mitigate conflict within their regions.7 At the global level, the centrality of major powers (and less so regional powers) in influencing the course of international politics is well acknowledged in the literature. Long cycle theorists, hegemonic stability theorists, power transition theorists, hierarchical theorists, and neorealists generally have all pointed to the salience of major powers in creating order and stability in international politics or, alternatively, for generating system-wide conflict when they contest for global leadership.

At the global level, two sets of causal factors appear to link major powers to patterns of conflict in international politics. One is the deterrence function created by their relative potential power over other states. To the extent that major powers possess unusual capabilities with which to pursue their interests and the orders they may seek to create, their active role in international affairs functions as a deterrent for conflict initiation by others. Carrying preponderant capabilities that signal substantial costs to those opposing them can dissuade less powerful states from challenging these very strong actors and their allies. This line of argument is supported by probabilistic evidence showing in most models of conflict that a preponderance of capabilities within dyads is negatively associated with conflict within those dyads (e.g., McDonald, 2015).

A second and more dynamic causal agency, however, is suggested by the notion that major powers seek to create rules and norms in international politics—order building—that simultaneously assist them in pursuing their objectives and function to minimize conflict and disorder in the system. Power transition theory, hegemonic stability theory, hierarchical theory, and long cycle theory all suggest this dynamic of order creation by major powers. Of course, at the global level, conflict may still arise under a number of circumstances, including when the distribution of power changes, the global hierarchy is weakened, or dissatisfaction with extant rules and norms on the part of rising challengers leads to leadership contestation and demands for changes to existing orders.

How does all this apply to an understanding of conflict propensity within regions? Major and regional powers do not exist in a vacuum. They reside in geopolitical spaces (regions) where their impacts should be even more salient than they are globally. The stability of the home region, furthermore, is vital to major powers seeking to pursue their interests in international politics, since ordering relationships within the home region is essential to such endeavors. For regional powers (states that are dominant in their own regions but are lacking in the capability, willingness, or status needed to actively engage outside of their regions), stable relationships within their own regions should be just as important: the status of being a regional power conveys that a state is capable and willing to exercise the leadership needed to create order within its own neighborhood, while an inability to do so likely jeopardizes its status as a regional power. Additionally, for regional powers with global aspirations (e.g., Brazil, India), disordered regional politics requires the commitment of finite resources to stabilizing relationships in the region rather than utilizing those same resources for a variety of interests outside of their own regions.

The two causal agents regarding global politics—deterrence and order building—should be just as applicable to regions, if not more so. The deterrence function, resulting from the existence of a dominant power within its own region, should act to dampen potential conflict emanating from less powerful states, and it should be more salient within regions than globally because of actors’ proximity and the consequent possibility of such conflicts potentially impacting directly the dominant state.8 The order-building explanation, a thicker and more thorough approach to ordering regional relationships, is also easier to accomplish within a region than seeking to create and enforce the same globally. These two plausible impacts at the region level correspond to two different “logics of hierarchy” advanced by scholars focused on the hierarchical nature of international politics.9 The approach taken here suggests that such logics can coexist where dominant powers reside; in addition, a comparative assessment of regions suggests that hierarchical arrangements at the region level are not constant but vary across regions and across time.10

We view dominant states—major powers and regional powers—as entailing more than substantial capabilities. Dominant powers not only have unusual capabilities (both economic and military), but are also willing to act in ways that are consistent with those capabilities, and they receive substantial status as dominant powers from the community of states for doing so (Volgy, Corbetta, Grant, & Baird, 2011; Cline, Rhamey, Henshaw, Sedziaka, Tandon, & Volgy, 2011). Additionally, major powers are distinguished from regional powers in several ways. Major powers have dominant capabilities compared to the entire international political system, not simply relative to their own region; their activities in international politics consistently span a number of regions beyond their own; and their status as a major power is attributed by the global community of states. Regional powers meet these requirements only with reference to their own regions of residence.

By way of example, prior to 1939, the United States may have had capabilities consistent with being a major power, but it was unwilling to consistently act as one and thus did not receive major-power status. Japan in the 1980s could have qualified as a regional power in East Asia on the basis of its capabilities and willingness to engage other states in the region, but it was not attributed regional power status by East Asian states (Cline et al., 2011). Likewise, after the end of the Cold War, Saudi Arabia had capabilities that could have allowed it regional power status in the Middle East, but its limited engagement inside the region (and more extensive engagement outside the region) would not have qualified it as the regional power (Cline et al., 2011).

This conceptualization of major and regional powers integrates a status attribution component to delineation.11 The inclusion of status attribution to major and regional powers by other states should have two effects. First, status likely adds additional “soft power” to those states receiving it, allowing for additional capability in pursuing objectives, including bringing order to their regions. Second, as status theorists have argued (e.g., Bull 1977; Dafoe, Renshon, & Huth, 2014; Larsen & Shevchenko, 2010; Sylvan, Graff, & Pugliese, 1998), status attribution involves both rights and obligations for the recipient, as well as some deference to the recipient by those attributing it status. This makes both the deterrence and the order-building arguments on the part of these powers more credible.12

The existence of dominant states in regions (major powers or regional powers or both) should critically differentiate regions’ conflict propensities. The list of regions noted in Appendix A suggests four types of regions. One type contains neither a regional nor a major power. A second type contains a regional power only. A third type contains a single major power. The fourth type contains a combination of powers, either major powers living within the same region or a mix of regional and major powers in residence.13

Irrespective of the causal agency involved, we suggest that, all else equal, regions lacking a major or regional power presence are likely to be much more conflictual than otherwise. Regions with mixed hierarchies—where two or more powers coexist—offer a category that, on first glimpse, suggests that potentially competing dominant powers within the same region are likely to exacerbate regional conflict. That was certainly the case for centuries in Europe and, intermittently, in Asia as well. We propose, however, that two factors may dampen such conflicts and make such regions less conflict prone than regions without any dominant powers. First, the coexistence of two or more major powers within the same region will not necessarily lead to major conflicts if those powers are relatively satisfied with the status quo in the region and can cooperate to create conditions and institutions to facilitate cooperation between states in the region. In fact, the cumulative capacity of more than one dominant power may be very useful in creating substantial regional institutions both in the security and the economic spheres. This in part may be the story of Western Europe and the rise of the European Community. Buttressed by dominant powers inside the region—the United Kingdom and France—as well as by an American global power, cooperation took hold, and conflict dissipated. Less successfully, it may also be the story of the nascent cooperative architecture developed after the end of the Cold War by the Russian Federation and China in Central Asia.

The second potential conflict-minimizing factor is that the introduction of thermonuclear military capabilities into the relationships between major powers through the Cold War and afterward has created a dramatic and, perhaps, unique amount of caution between major powers even when they contest global or regional leadership. No two major powers have directly fought a war with each other since 1945, and since 1962 (with the exception of the Cuban Missile Crisis), no two major powers have escalated tensions vis-à-vis each other to a point verging on a serious outbreak of direct hostilities.14 Such extraordinary caution should be even more pronounced when major powers share a region. Common living arrangements may lead to complementary security and economic institutions (such as the European Economic Community and NATO in Western Europe and the Comecon and the Warsaw Pact in Eastern Europe during the Cold War), each creating stability and order within distinct spheres of influence between the dominant powers coexisting in different parts of the region. It may even be possible to create common institutions of cooperation in regions where the preferences of the major powers coincide, along with a stable security environment, as is the case with Western Europe and the evolution of the European Union. We would expect that regions containing two or more dominant states in conflict with each other, however, would be unable to create strong and substantial organizational infrastructure for the whole region15; nevertheless, the creation of partial and even competing forms of infrastructure may function to mitigate some conflicts within parts of the region16 and thus reduce the total amount of intraregional conflict. At the same time, the deterrence function of dominant powers would continue to exercise substantial impact in mitigating potential conflicts rising from other states in the region.17

Thus, it is reasonable to anticipate that since the 1960s, regions with one or more dominant power(s), all else being equal, would also be more pacific than regions without any dominant power. Of course, all else is not equal, and we suggest that there are at least three sets of factors that condition the relationship between the presence—or absence—of such hierarchies in regions and regional conflict. First, we expect that regions will vary greatly in terms of what issues need to be mitigated, and consequently, where there are states at the top of the regional pyramid, they will vary in terms of the range of problems they will be confronting in their home region. Plausibly, some regions require little in terms of conflict management since there may be little potential conflict to manage. Other regions may be rife with fault lines that potentially generate substantial conflicts between members, making the task of conflict mitigation highly challenging for the dominant power(s) in the region.18 Regions are not automatically conflict prone. Depending on the characteristics of the states that compose them, regions should vary substantially with respect to conditions already identified in the literature that stimulate or inhibit conflicts between states. At the aggregate, different regions bring to the analytical table substantial differences among them with respect to such conditions. These considerations can be labeled “baseline conditions.”

There are six such baseline conditions that should differentiate regions. The first three are suggested by the literature as potentially generating substantial conflicts between states. These include interstate rivalries (Rasler & Thompson, 2005a), unresolved territorial claims (Gilber, 2012, 2016; Vasquez, 2001), and severe domestic disturbances in the form of civil wars whose consequences may diffuse through the region in terms of combatants and refugees (Gleditsch et al., 2008; Jenne, 2015; Salehyan, 2008; Schultz, 2010). Each of these three conditions has been empirically linked to severe militarized disputes and wars between states at the dyadic level. Thus regions containing a substantial number of these fault lines are likely to generate numerous conflicts between the states populating them.

In contrast, the literature also suggests three conditions that appear to ameliorate substantial conflicts between states. These include regime similarity (and especially similar democratic polities),19 extensive trade relationships,20 and common membership in (regional) intergovernmental organizations (IGOs).21 Members of regions rich in these three characteristics are likely to settle their policy differences short of militarized interstate disputes and wars.22

The baseline conditions suggest two important considerations regarding regional conflict propensity and its management by dominant states. First, we expect that regions will vary in terms of conflict propensity depending on these baseline conditions, and not solely due to the presence or absence of a dominant state in the region. For instance, the Middle East lacks both a regional and a major power, and it also constitutes a region whose baseline conditions predict very high levels of conflict. Would the presence of a regional or major power residing in the region ameliorate such conflicts? Our argument suggests a positive answer, but the baseline context in which we place the Middle East indicates that it is far from just the absence of a dominant state that is primarily responsible for its high levels of conflict.

Second, these baseline conditions suggest that in order to ameliorate conflicts, some dominant states will require much more extensive (and perhaps more creative) use of their capabilities than other major or regional powers because the severity of the challenges posed by these conditions place far greater burdens on some powers than others. For example, the baseline conditions in the South American region place fewer demands on the regional power (Brazil) to manage conflicts in the regions (no extant rivalries, mostly democratic regimes) than does the South Asian region (ongoing interstate rivalries, few democratic regimes, limited economic interdependencies) on its regional power (India).23

The last point underscores a second qualification. As regions are not homogeneous with respect to baseline conflict conditions, neither are major and regional powers with respect to their abilities to use their capabilities and the extent to which they may seek to influence relationships in their regions (Nolte, 2010; Prys, 2010). With regard to their ability to influence their regions, dominant states, by definition, have sufficient capabilities to do so. Where they may diverge is in the relative competence with which they can translate their extensive resources into effective conflict-mitigation strategies. By way of illustration, one can compare Brazil in South America to Nigeria in West Africa. Both countries enjoy dominant resource capabilities in their respective regions. However, according to World Bank rankings,24 Brazil’s governmental effectiveness index is consistently at least three times higher than that of Nigeria. This suggests that if both were confronted with similar challenges in their respective regions, Nigeria would have far less ability to utilize its substantial resources to effectively govern its region25 than would Brazil.

Major powers and regional powers may also differ in terms of how much and what types of control they wish to exercise over their regions of residence. For example, Prys (2010) suggests that regional powers vary from acting relatively detached to being regional “dominators,” depending on how they prioritize domestic,26 regional, or global concerns, as well as the extent to which their regions become permeable to global dynamics and the intrusions of outside powers.

The relative permeability of regions leads to the third qualification to the central argument: the literature on regions broadly acknowledges that regions, with or without dominant powers, are far from being closed subsystems (e.g., Buzan & Waever, 2003). Instead, they vary substantially in the extent to which they are open both to the global dynamics at play and to external penetration by major powers that reside outside of the region. To some degree nearly all regions are influenced by efforts of major powers to create system-wide norms and rules, the impacts accompanying security and economic institutions from those efforts, and the global contestation (along with efforts to enforce) over those rules and institutions. However, some regions are more likely to contest systemic rules than others, with or without the support of major or regional powers that may be dissatisfied with the status quo (Acharya, 2007). Likewise, regions will vary in the degree to which they are able and willing to resist or welcome external involvement by outside major powers in their security and economic affairs (Goh, 2007/2008, 2013; Katzenstein, 2005).

It can be expected that the presence or absence of dominant powers in regions will impact significantly on regional conflict propensity. However, these effects are mitigated by the three conditions noted here: the baseline conditions extant within regions; the capabilities of dominant powers to develop mechanisms to mitigate conflict; and the extent of penetration into the region by global forces and outside major powers. Within this context, two key hypotheses can be put forward:

H1: All else being equal, the presence of one or more major powers in a region will mitigate levels of conflict within a region, compared to regions where there are no dominant powers.

H2: All else being equal, the presence of a regional power will mitigate levels of conflict within a region, compared to regions where there are no dominant powers.

These two hypotheses do not address the causal links regarding the effect that dominant states would have on their regions; instead, they predict conflict outcomes based on the presence or absence of dominant powers. If it is not possible to show such outcomes, there is little use in searching for evidence regarding whether or not the causal link is a deterrence function or actual order-building by dominant powers. However, if there is evidence that the presence of a dominant power within a region leads to less conflict therein, then it may become worthwhile to move beyond testing the relationship between regional hierarchies and conflict to probing the two causal linkages suggested by the literature.

Research Design Considerations

Delineating Regions and State Regional Membership

Again, there is neither consensus nor any emerging “gold standard” for delineating regions in international politics. A recent review of the quantitative literature identifies no fewer than 70 categories used to identify regions across a variety of empirical models (Volgy et al., 2017). Typically, the choices for delineating regions consist of identifying parts or all of meta-regions (Asia, Europe, etc.), using prior generic classifications (World Bank, United Nations, Correlates of War), or identifying a specific characteristic around which states may cluster in a geographical space (ideational similarity, membership in a security complex or regional organization, or falling under the dominance of a very strong state). The static nature of these regional classifications, however, does not match the dynamic nature of the states they are comprised of and, in some cases, creates a troublesome tautology.

To test these arguments regarding hierarchy and conflict propensity in regions, it is necessary to take an approach to regional delineation that avoids tautological consequences and maximizes variation across both our dependent variable and our variables of interest. For example, Lemke (2002, 2010) delineates regions based on the existence of regional powers (hierarchy) residing within a region; we need to compare regions with and without hierarchies. Numerous other approaches use the existence of regional organizations (both security and economic organizations) to delineate the boundaries of regions; we need to compare regions with and without such structures of cooperation.

We opted for an approach that combines geographical proximity, opportunity by states to reach each other, and their willingness to do so, resulting in a clustering of states that constitute a region. We label this approach Regions of Opportunity and Willingness (ROW). The advantage of this classification scheme is that it creates regions that change over time: while geographical proximity is invariant, and opportunity (capability to interact) changes relatively slowly, willingness is much more variable. The delineation thus yields evolving regional clusters and allows for changes both to the numbers of regions in the system and the movement of states in and out of regions (within geographical limits), consistent with changes in geopolitical context (Fawcett, 2004).

The methodology for delineating ROW regions has been elaborated elsewhere (Rhamey, 2012; Volgy et al., 2017); a brief summary is provided here. The opportunity constraint for regional membership is measured by calculating each state’s ability to reach others in the international system by Bueno de Mesquita’s (1981) operationalization of Boulding’s (1962) loss of strength gradient, using a state’s GDP in proportion to global GDP (Heston, Summers, & Allen, 2012). This measure yields a series of capability “bubbles” radiating outward from each state’s capital that degrade across distance. We then designate the threshold at which states lose the opportunity to significantly interact at 50% capability loss from the projecting state’s capital to that of the target state (Lemke, 2002).

To estimate willingness, we aggregate the total number of scaled foreign policy actions flowing between actors that pass our threshold for opportunity annually from two events data sources: the Conflict and Peace Data Bank (COPDAB) for 1950–1978 (Azar, 1980) and the Integrated Data for Event Analysis (IDEA) for 1990–2013 (Bond, Bond, Churl, Jenkins, & Taylor, 2003; Goldstein, 1992, for scaling). For each dyad, the directed scaled foreign policy activity of each state flowing to each other state is calculated, annually, as a proportion of their total foreign policy activity. Those states that engage in an above average proportion of their total foreign policy activity directed toward another state surpass the willingness threshold.

Next, network analysis (e.g., Hanneman & Riddle, 2005) is used to identify unique clusters of interaction among three or more states, where nodes are coded as having a tie if they have met both thresholds for opportunity and willingness, annually. From this matrix of dyadic relationships, the clique algorithm determines patterns of connections between states, and the resulting endogram output27 depicts groups of states organized according to the extent of correlation in their patterns of ties within the network.

Two additional actions are taken to ensure geographic relevance and stability in regional membership. First is the requirement that clique members be contiguous over land or less than 500 miles of water. Second is placing states in the region within which they most frequently identify across each decade. Thus, each region has a 10-year lifespan. The shifting dynamics reflecting stability and change are consistent with the “observable power and purpose” of states (Katzenstein, 2005, p. 2), mirroring aspects of regional conceptions employed in comparative regionalism (Paul, 2012, p. 4).

Our approach yields between 8 and 14 regions (Appendix A) depending on the decade for three decades during the Cold War (1950s, 1960s, 1970s), and two decades after the end of the Cold War (1990s, 2000s).28 At least 75% of all states in each decade are included in one of our regions; the states excluded for their failure to cluster are typically microstates with very limited capabilities and interactions.

Delineating Regional and Major Powers, and Regions With and Without Hierarchy

The next step revolves around the identification of regional and major powers and their placement within the ROW regions, and relies on two earlier efforts to identify major powers (Volgy et al., 2011) and regional powers (Cline et al., 2011).29 The application of these procedures, excluding regions with fewer than four states, yields 18 regions without any hierarchy, 12 regions with a regional power, and 11 regions that contain at least one major power for the 1960s, 1970s, 1990s, and 2000s.30 Two binary hierarchical variables are then created. The first differentiates between regions with a regional power versus regions without any hierarchy—Regional Power Presence. The second differentiates regions with one or more major powers versus regions without any hierarchy—Major Power Presence. These function as the central independent variables of interest in the empirical models. Consistent with Lemke (2010), region year is employed as the unit of observation; across the four decades, accounting for lagging independent variables, utilizing region year as the unit of analysis yields an N of 369 observations in our base model.

Dependent Variables: MID Frequency and State MID Involvement

Two versions of the dependent variable are created, focused on severe MIDs31 occurring within ROW regions. One version is simply the number of severe MIDs occurring in the region32 annually, divided by the number of states in the region—MID frequency. The denominator controls for opportunity to engage in MIDs, making small regions and large regions comparable. Alternatively, it is plausible to gauge both the extent of regional conflict and its possible diffusion33 by observing the number of states in the region engaged in severe conflicts, again controlling for region size—state MID involvement. This is the second version of our dependent variable; the results using both versions are reported in what follows, and we expect similar results for both.

Independent and Control Variables

Corresponding to our baseline conditions, we develop three measures that are likely to exacerbate conflicts within regions. The first is identifying the number of interregional rivalries ongoing for each year within the region. The second is counting the number of civil wars occurring annually within the region. The third is counting the number of territorial claims made annually within the region. Next, three measures likely to create more pacific relationships within the region are developed: the percent of intraregional trade; the percent of democracies extant in the region; and the number of common memberships shared in regional organizations. All six variables are measured annually for the decade-long life cycle of regions, and are lagged one year.

Two additional variables are created that seek to tap global dynamics and major power intrusion into regions. The first is a binary variable that identifies whether or not the observations are during the Cold War or afterward. The second seeks to gauge long-term intrusion into the region by outside major powers and is measured by the number of defense pacts—External Alliances—between regional members and outside major powers.

Finally, a time counter is created to control for time effects during regional life cycles. Appendix C provides a list of all variables, their manipulation, and the sources utilized. Descriptive statistics for all variables are found in Appendix D.

Empirical Analysis

Analysis results are presented using OLS regressions34 for two different dependent variables. Table 2 reflects the results using the number of severe MIDs—MID frequency; Table 3 utilizes the number of states involved in severe MIDs—state MID involvement.35 In each table, the first model notes the effects on the dependent variable without consideration of hierarchical conditions: showing the cumulative impact of baseline conditions; global conditions; and time effect controls. The second model in the table adds major power presence, a binary variable contrasting conditions between regions with one or more major power with regions without any dominant powers. The third model adds regional power presence to the base model, contrasting those regions with a regional power to regions without any dominant powers.

Table 2. OLS Regression Models for Major and Regional Powers and Regional Conflict, with Number of Severe MIDs/Number of States in Region.

Base Model

Major Power Presence

Regional Power Presence

Hierarchy

−0.167**

(0.030)

−0.116**

(0.028)

# Intra-Regional Rivalries t−1

0.024**

(0.004)

0.018**

(0.004)

0.020**

(0.004)

# Civil Wars t−1

0.017

(0.007)

0.004

(0.007)

0.042**

(0.010)

Territorial Claims t−1

0.156*

(0.053)

0.262**

(0.071)

0.183**

(0.050)

% Regional Trade t−1

−0.033

(0.013)

0.009

(0.019)

% Regional Democracies t−1

−0.156**

(0.042)

−0.069

(0.053)

−0.166**

(0.039)

IGO Membership t−1

−0.142*

(0.044)

−0.180*

(0.056)

−0.159**

(0.048)

External Alliances t−1

0.082*

(0.026)

0.048

(0.029)

0.128**

(0.026)

Cold War

−0.072*

(0.023)

-0.061

(0.025)

−0.104**

(0.028)

Time Counter

−0.003

(0.004)

−0.004

(0.004)

−0.006

(0.004)

Constant

0.235**

(0.042)

0.217**

(0.048)

0.165**

(0.048)

Observations

366

261

267

Adjusted R2

0.316

0.408

0.451

AIC

−154.6

−176.0

−121.1

BIC

−115.6

−140.4

−81.62

Notes: Robust standard errors reported in parentheses.

(*) p < .05;

(**) p < .01;

(***) p < .001

The results for the baseline model are generally as expected. Numbers of intraregional rivalries, civil wars, and territorial claims are both significant and positively related to the frequency of MIDs and the number of states involved in MIDs in the two tables. As expected, IGO regional membership, percentage of regional trade, and percentage of democracies are all negative and significantly related to both dependent variables. Alliances in the form of defense pacts, reflecting external structural security involvement by outside major powers in the region, are related to increased intraregional conflict and increased regional state involvement in intraregional conflicts.

The one counterintuitive result that appears in the baseline model is the negative relationship between the Cold War and conflict, suggesting that more MIDs occur in regions after the Cold War. However, this result is consistent with empirical findings (McDonald, 2015, 2017) linking MIDs to global hierarchies: both global hierarchies during the Cold War sought to minimize conflicts within their spheres of influence. With the collapse of one hierarchy (the Soviet Union), regions without dominant states in the post–Cold War era would likely be more conflictual than during the period of bipolar organization. The result is consistent with our previous argument that competing infrastructures may complementarily work to reduce conflict within their separate, partial spheres of influence leading to system or region-wide effects.

Table 3. OLS Regression Models for Major and Regional Powers and Regional Conflict with Number of States in Region Involved in Severe MIDs/Number of States in Region.

Base Model

Major Power Presence

Regional Power Presence

Hierarchy

–0.287**

(0.052)

−0.133*

(0.048)

# Intra-Regional Rivalries t−1

0.058**

(0.007)

0.051**

(0.008)

0.055**

(0.009)

# Civil Wars t−1

0.023

(0.012)

0.005

(0.010)

0.059**

(0.017)

Territorial Claims t−1

0.236*

(0.084)

0.317*

(0.112)

0.236*

(0.084)

% Regional Trade t−1

−0.069*

(0.021)

0.001

(0.032)

% Regional Democracies t−1

−0.161

(0.071)

−0.032

(0.090)

−0.176

(0.072)

IGO Membership t−1

−0.309**

(0.071)

−0.352**

(0.092)

−0.368**

(0.080)

External Alliances t−1

0.137*

(0.045)

0.081

(0.051)

0.214**

(0.046)

Cold War

−0.116*

(0.038)

−0.084

(0.040)

−0.158**

(0.046)

Time Counter

−0.009

(0.006)

−0.010

(0.007)

−0.016

(0.008)

Constant

0.416**

(0.072)

0.345**

(0.079)

0.300**

(0.079)

Observations

366

261

267

Adjusted R2

0.368

0.449

0.469

AIC

216.5

111.7

164.4

BIC

255.5

147.4

203.9

Notes: Robust standard errors reported in parentheses.

(*) p < .05;

(**) p < .01;

(***) p < .001

Models 2 and 3 in both tables provide evidence for the central hypotheses forwarded earlier. The presence of a major power in a region, compared to regions lacking any dominant power, is associated with an approximately 59% reduction (Figure 1, left column) in the predicted frequency of severe regional MIDs and an approximately 60% reduction (Figure 2, left column) in the predicted numbers of regional states involved in severe MIDs.

Conflict, Regions, and Regional HierarchiesClick to view larger

Figure 1. Marginal Effect of Hierarchy on Severe MID Frequencies.

Turning to the potential effects of regional hierarchies, the presence of a regional power in a region also generates conflict-reduction effects compared to regions without dominant powers, albeit not as strongly: compared to regions lacking a dominant power, regions with a regional power are associated with a more than 41% reduction (Figure 1, right column) in the predicted frequency of severe regional MIDs and a more than 29% reduction (Figure 2, right column) in the predicted frequencies of regional state involvement in severe MIDs.

Conflict, Regions, and Regional HierarchiesClick to view larger

Figure 2. Marginal Effect of Hierarchy on Severe State MID Involvement.

Several additional results are worthy of note. First, further differentiating regions according to types of dominant powers, substantially increases the cumulative effect of the models. For example, the adjusted-R2 statistic for the Major Power Presence Models increases by 31% when the dependent variable is severe MID frequency, and by 23% when the dependent variable is state involvement in severe MIDs; for the Regional Power Presence Models, the corresponding increases are 44% and 28%. Despite the larger increases in adjusted-R2, however, the AIC and BIC indicate a preference for the Major Power Presence models throughout.

At the same time, it is clear that neither the presence of a major power nor of a regional power eliminates the conditions that may give rise to regional conflicts; this appears to be the case as well for the conditions associated with more pacific relationships. Most of the baseline conditions continue to be significant predictors in the Major Power Presence and Regional Power Presence models, and especially intraregional rivalries and territorial claims, which continue to be highly significant predictors of conflict under all conditions. The pacifying effects of trade, IGO membership, and democracy appear to be more mixed, although regional IGO membership appears to limit diffusion of conflicts consistently.

Additionally, the trade variable, acting as a pacifying influence in the baseline model, loses significance and changes direction in the regional power presence model, and is so highly correlated with major power presence that it was pulled from the major power hierarchy model. This led us to undertake a brief secondary investigation. Barbieri (1996) suggests a curvilinear relationship between conflict and trade, and when we included a quadratic term of percent regional trade in our baseline model (not shown), we found the relationship to be curvilinear. Contra Barbieri, however, we find conflict increases at low to middle levels of trade before tailing off at higher values. That may help account for the insignificant findings for trade in the regional model. The high correlation between trade and major power presence in the second model we discuss below.

Finally, there appear to be substantively interesting effects for external major power involvement in the region. Such involvement is measured as defense pacts between outside major powers and members of the region; the variable exhibits a strong association with both the frequency of regional conflict and the number of states involved in regional conflict in the baseline model. However, when regions are differentiated according to dominant powers, its effect disappears when comparing major power regions to regions without any dominant powers. A separate analysis, regressing all independent variables on MIDs frequency but separated by type of region (no hierarchy, major power hierarchy, regional power hierarchy) indicates that the primary effect of external major power alliance commitment operates primarily on regions with a regional power. The effect of such intrusion disappears for regions with one or more major powers.

Discussion

This analysis provides substantial evidence for our two central hypotheses: consistent with our theoretical arguments, the existence of dominant powers (both major powers and regional powers) in regions is strongly associated with the reduction of both the frequency of regional conflict and the number of states engaged in regional conflicts. Regions differ from one another not only in terms of baseline conditions that stimulate conflict or create more pacifying effects, but also by the extent to which dominant states reside in these regions.

These results, however, fail to directly test the two causal arguments suggested earlier: whether or not dominant states in regions create pacifying effects due to their preponderant capabilities (a deterrence function), or through a more complex set of order-building mechanisms involved with the creation of economic and security arrangements for their regions, or possibly due to both causal agencies at work. Future efforts should concentrate on creating research designs that can provide systematic evidence of these causal linkages.

However, creating a strategy for assessing these dynamics at work will not be an easy task. Consider the problem of identifying the formation and effect of regional security and economic institutions by dominant powers. Recall that our approach to regional identification allows both the number of regions to change over time and for the membership of each region to change. Indeed, both forms of change occur with some regularity across decades as states “move” from one region to another while several regions dissolve and others expand or shrink. Such changes are consistent with the social construction of regions, but they are inconsistent with the creation and adaptability of regional institutions. Few—if any—regional institutions are sufficiently flexible to accommodate changes to regional composition suggested by our approach to regional delineation. In practice, dominant states also create “regional” institutions that involve both regional members and nonmembers that are in close proximity.

Neither is it clear that evidence of regional institutional creation can be separated as having an effect independent of the dominance in capabilities of major and regional powers. This is especially the case for regions with major powers. Is it such dominance that creates a pacifying effect, or is it the creation of economic and security arrangements, or is it plausible that the creation of institutional arrangements simply reinforces the dominance of the major power, but does not provide substantial, independent causal agency?

In principle, this distinction can be tested if there are a large number of observations involving cases where dominant powers in some regions fail to create such institutions but do so in other regions. Unfortunately, there is not such a wealth of cases. Alternatively, where regional or major powers exist, it is plausible to examine the impact of regional institutions, in addition to major power dominance, by assessing the occurrence of conflicts prior to and after the creation of such institutions. To do so, we would want to examine cases of regions where sufficient baseline conditions exist to increase the probability of regional conflicts, and then to assess the amount of conflict occurring prior to and after the creation of regional institutions involving dominant powers. For instance, the number of conflicts in the North American region, given the dominance of the United States, are highly limited, even prior to the creation of NAFTA. Assessing NAFTA’s effects on conflict mitigation in the region is extremely difficult to estimate.

However, there is some limited, indirect evidence that the creation and maintenance of regional institutions—or at least the involvement of major and regional powers—does have a pacifying effect in hierarchical regions. While in all three models there are substantial and significant relationships between state membership in such institutions and lower levels of regional conflict, in regions with major and regional powers this effect is more pronounced than in regions without such dominant powers.

There also appear to be substantial differences between major power driven hierarchical arrangements versus regional power driven ones. The models suggest a consistently stronger impact on conflict in regions dominated by major powers compared to regions dominated by regional powers. Additionally, the creation and maintenance of economic relationships appear to function differently in the two types of regions. Note, for instance, that the trade interdependence variable was dropped from the major power hierarchy model because of the extremely high collinearity between it and the hierarchy variable.36 It is plausible that given the curvilinear relationship between trade and conflict, major powers are more capable of minimizing the initial conflict-prone trading period and enabling higher levels of intraregional trade to take hold. Regional powers may not be able to accomplish the same since they cannot deliver entrance into global markets to the same extent that a major power could. Thus, they cannot ultimately deliver the same level of benefits, leading regional members to continue to bicker among themselves over a smaller market.

While emphasis upon the region as a substantively interesting unit of analysis in international politics is long overdue, an understanding of the contributing causal variables in future research should include, and model appropriately, the nested reality of regional politics. Consistent in the seminal explorations of regional dynamics (Buzan & Waever, 2003; Katzenstein, 2005; Lemke, 2002), the impact of both internal and system level dynamics is conceptually important. Future research should fully engage the hierarchical, linkage politics dynamics of the regional unit of analysis by incorporating not only those variables that directly impact the region, such as alliances with external powers, but contextual information of the system or internal politics broadly, such as the distribution of power at the system level, the concentration or distribution of power or economic integration internally, domestic characteristics of internal political systems, or the power projection of external major powers across geographic space. While the region as a unit presents added complexity given its position in between the most oft studied levels of analysis in international politics, integrating contextual dynamics across levels may provide a more complete understanding of how regions develop and evolve.

The inability to probe these causal dynamics further, given our empirical approach to regional delineation, suggests one of its limitations in the form presented here. In particular, traditional methods of statistical inference may be less useful or applicable, given present demands on the data needed to carve the contours of regions. Since this approach also utilizes decade-long spells of events data—available only after World War II—we are limited to asking questions regarding regional formation and the delineation of regional powers and assigning regional membership for only the Cold War and post–Cold War periods. This, in turn, restricts the number of region year observations quite substantially, limiting the empirical environment in which to make assessments of causal agency. This problem is not meant to be a condemnation of using region year as the appropriate unit of analysis, but it does suggest that the approach will require very creative and new strategies to expand the research domain and explore these relationships in eras (including prior to World War II) where events data are not available.

The inability to expand our observations has also meant that we have not been able to gauge certain other dynamics suggested by our theoretical approach. For instance, we recognize that the relative competence of regional powers and their interest in creating stable regional relationships—in addition to their capabilities—likely impact on how much regional conflict will occur. Future efforts will need to focus on these distinctions, likely involving case studies and process tracing strategies to indicate the effects of these considerations. This will be especially important in regions where regional powers change their role conceptions (Butt, 2013) and in regions where the power’s competence may change over time.

While much additional work needs to proceed, hopefully we have provided sufficient empirical evidence to support our claims that we can differentiate between regions based on whether or not there are dominant powers residing in regions, and the effect of such hierarchical relationships on regional conflict. The results also indicate that using region year as an appropriate unit of analysis to investigate regional conflict is a useful one. Future work on conflict and cooperation in international politics should integrate these regional considerations into empirical models, moving beyond statistical fixed effects concerns and toward more theoretically useful ways of treating differences between regions.

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Appendix A. List of ROW regions, by decade and type of hierarchy.

Time Frame

Region

Number of States in Region37

Hierarchy38

1950s

North Central America

5

na39

Andes

7

Na

South Central America

4

Na

South America

4

Na

Middle East

10

Na

Core Europe

23

Na

Northern Europe

5

Na

East Asia

19

Na

1960s

North America

10

Major power

Andes

7

No hierarchy

South America

5

Regional power

Middle East

14

No hierarchy

Western Europe

12

Major power +

Benelux

3

No hierarchy

Scandinavia

4

No hierarchy

East Europe

8

Major power

West Africa

5

No hierarchy

Central Savannah

4

Regional power

Gold Coast

3

No hierarchy

Central Africa

17

No hierarchy

East Asia

9

No hierarchy

Asia Pacific

10

No hierarchy

1970s

North America

22

Major power

South America

6

Regional power

Middle East

14

No hierarchy

Europe

29

Major power +

African West Coast

4

No hierarchy

West Africa

13

Regional power

Southern Africa

21

No hierarchy

Northwest Asia

3

No hierarchy

Southeast Asia

12

Regional power

East Asia

11

No hierarchy

1990s

North America

6

Major power

Southern Caribbean

3

No hierarchy

South America

8

Regional power

Middle East

13

No hierarchy

Europe

27

Major power +

East Europe

12

No hierarchy

Baltics

3

No hierarchy

Maghreb

6

No hierarchy

West Africa

7

Regional power

Central Africa

9

No hierarchy

Southern Africa

9

Regional power

East Asia

36

Major power +

Central Asia

7

No hierarchy

2000s

North America

4

Major power

South America

10

Regional power

Middle East

12

No hierarchy

Europe

46

Major power +

Maghreb

3

No hierarchy

West Africa

6

Regional power

Central Africa

8

No hierarchy

Southern Africa

9

Regional power

Horn of Africa

3

No hierarchy

East Asia

32

Major power +

South Asia

6

Regional power

Appendix B. Patterns of Conflict Across Regions.

Conflict, Regions, and Regional HierarchiesClick to view larger

Figure B1. Frequency of Severe MIDs in regions, controlling for the number of states in regions, during the 2000s.

Conflict, Regions, and Regional HierarchiesClick to view larger

Figure B2. Frequency of Severe MIDs, controlling for number of states in region, by region, 1990s.

Conflict, Regions, and Regional HierarchiesClick to view larger

Figure B3. Number of Severe MIDs per region, controlling for size of region, for the 1970s.

Conflict, Regions, and Regional HierarchiesClick to view larger

Figure B4. Number of Severe MIDS per region, controlling for size of region, for the 1960s.

Conflict, Regions, and Regional HierarchiesClick to view larger

Figure B5. Number of Severe MIDs per region, controlling for size of region, for the 1950s.

Appendix C. List of variables, sources, and manipulations.

Variable

Source

Manipulation

State MID Involvement

COW MID v.4 (Palmer, D’Oranzio, Kenwick, & Lane, 2015)

Number of states involved in level four or five MIDs/total number of states in region

MID Frequency

COW MID v.4 (Palmer et al. 2015)

Number of level four or five MIDs/total number of states in region

Major Power Presence

Volgy et al. (2011)

Dichotomous; 1 = presence, 0 = no hierarchy

Regional Power Presence

Cline et al. (2011)

Dichotomous; 1 = presence, 0 = no hierarchy

# Intra-Regional Rivalries

Thompson & Dreyer (2011)

Number of states involved in rivalry with states of the same region; lagged one year

# Civil Wars

UCDP-PRIO v.4 (Pettersson & Wallensteen 2015)

Number of states involved in internal conflict with cumulative intensity of 1,000 battle-deaths or more; lagged one year

% Regional Trade

COW Bilateral Trade v.340,41

Amount of trade among states in a region/total trade of the region; logged and lagged one year

% Regional Democracies

Polity IV42

Percent of states with Polity IV score of 7+ states/total number of states with Polity IV scores in region; lagged one year

External Alliances

COW Formal Alliances v.4.143

Dichotomous; 1 = presence, 0 = no defense pact between a regional state and an external major power; lagged one year

Territorial Claims

Gibler and Miller (2014) 44

Number of territorial claims in a region/total number of states in region; lagged one year

Regional IGO Membership

COW IGO; FIGO45

Number of regional IGO memberships held by states in region/all possible regional IGO memberships; lagged one year

Cold War

Dichotomous; 1 = Cold War; 0 = post-Cold War

Time Counter

Time counter for each decade

Appendix D. Summary Statistics for Dependent and Independent Variables.

Variable

Standard Deviation

Minimum

Maximum

Mean

State MID Involvement

.403

0

2.166667

.330

MID Frequency

.231

0

1.333333

.198

Major Power Presence

.486

0

1

.379

Regional Power Presence

.489

0

1

.39

# IntraRegional Rivalries t−1

3.37

0

15

2.96

# Civil Wars t−1

2.05

0

11

1.57

% Regional Trade t−1

1.08

0

5.0119

3.21

% Regional Democracies t−1

.290

0

1

.311

External Alliances t−1

.455

0

1

.708

Territorial Claims t−1

.246

0

.875

.421

IGO Membership t−1

.253

0

.9166667

.338

Cold War

.500

0

1

.517

Time Counter

2.88

1

10

5.5

Notes:

(1.) A recent review of quantitative international relations literature found less than 1% of work focusing on region as the appropriate unit or level of analysis (Volgy et al., 2017).

(2.) When quantitative analyses do control for regional effects in their models, in most cases regional differences appear to be highly significant (e.g., Hegre & Sambanis, 2006; Volgy et al., 2017).

(3.) The regions and their membership are enumerated in Appendix A.

(4.) We exclude “mini-regions,” containing fewer than four states, consistent with studies that exclude micro-states at the dyadic or monadic levels of analysis.

(5.) It is only in the last decade that the Middle East does not register as one of two extreme cases, although its number of severe MIDs during the 2000s (31 severe MIDs across 12 regional states during the decade) are the highest of any region. South Asia and Central Africa, with fewer regional states (six and eight respectively), produce nearly the same number of MIDs.

(6.) As Flemes and Lemke (2010) note, systematic comparisons between regions with and without hierarchies are likely to be key to understanding the dynamics of regions, but have yet to emerge systematically in the literature. As we note below in our delineation of regions, we avoid classifications, utilized elsewhere, that identify regions based on whether or not they have a dominant power, or extensive cooperative architecture, so that we can address issues regarding the consequences of such differences across regions.

(7.) And plausibly make it costly as well for outside powers to interfere in regional affairs.

(8.) For an excellent summary of the theoretical arguments including both power transition theory and bargaining theories, their role in the literature, and their applicability to regions, see Peterson and Lassi (2016).

(9.) For an excellent review of the treatment of hierarchy in international politics, see Bially Mattern and Zarakol (2016). The authors propose three “logics of hierarchy” that provide different theoretical approaches to the causal mechanisms in hierarchies that may create stability and order in international politics. Of those, the deterrence function we note here approximates the logic of positionality; the order building explanation corresponds to the logic of trade-offs within hierarchies (Bially Mattern & Zarakol, 2016).

(10.) Butt (2013) suggests, regarding South America, that hierarchical arrangements may ebb and flow within a single region over time, due to the interests of the dominant state. We are suggesting that the composition of regions also change over time, so that some regions may acquire or lose a dominant power, some consistently hold a dominant power in residence, and some regions never develop the conditions that allow a dominant power to arise. However, we are not seeking to explain the conditions that create hierarchies in some regions but not others. Our task here is limited to assessing the effects of hierarchies once they arise.

(11.) For the salience of status considerations, see Paul et al. (2014).

(12.) Different from our approach, Lake (2009) conceptualizes hierarchy not as involving status but as authority and collective legitimacy that create more peaceful regional orders, with authority being variable as the scope of legitimate authority may range across hierarchies and across time. Both approaches, however, share a common social construction orientation to hierarchy.

(13.) Given our measurement strategies, discussed below, it is plausible for two or more major powers to exist in one region since measures delineating major powers are on a global scale. Regional power designation, however, makes it virtually impossible for a region to contain more than one regional power. Thus, we identify regions with more than one dominant power, but we have no cases of regions with more than one regional power.

(14.) There have been, of course, actions that could have led to substantial consequences between major powers, including the accidental bombing of the People’s Republic of China embassy in Belgrade by NATO forces in 1999, the more recent “provocations” between Russian and NATO aircraft in Europe, incidents in the South China Sea, or Chinese and Russian cyber hacking of U.S. targets. None of these actions created security tensions reminiscent of the Cuban Missile Crisis, however, and all nuclear capable major powers involved have been extraordinarily cautious not to escalate tensions further.

(15.) Note the creation of the Organization for Security and Cooperation in Europe (OSCE). Not only did the USSR initiate the first conference, but it also joined the OSCE, along with its Warsaw Pact allies, and remained as a member even as a Western focus on human rights issues emerged. In terms of economic and security cooperation efforts, China and Japan are both members of the Asia Cooperation Dialogue, the Asia Pacific Economic Cooperation, ASEAN Plus 3, East Asia Summit, and Asian Defense Ministers Meeting Plus. Though they are more than “talking shops,” these institutional foundations of cooperation lack organizational autonomy and have been more focused on conflict management than conflict prevention or conflict resolution (Wacker, 2015).

(16.) McDonald (2015, 2017) examines all dyads during the Cold War and finds that states linked to the Soviet Union’s “hierarchy” were more pacific in their interactions than states not linked to it militarily.

(17.) The unwillingness of China to curb North Korean belligerence in East Asia appears to be an exception to this generalization (McDonald, 2017, chap. 5). Yet, even in this instance, China agreed to support UN Security Council resolution 2270 in March 2016, sanctioning North Korea. Shortly after the nuclear test conducted by North Korea in September 2016, Chinese authorities also indicated at the UN General Assembly that they were willing to cooperate with the U.S. in restricting further North Korean access to nuclear technology (Mason et al., 2016).

(18.) In this sense, we concur with Butt’s (2013) argument that both the concepts of hierarchy and anarchy, rather than being constants, can be considered as varying across regions and within regions, over time.

(19.) For a recent review of findings, theoretical underpinnings, and theoretical contestations, see Hegre (2014). For the interrelationship between territorial peace and democratic peace arguments, see Owsiak (2016).

(20.) For a discussion of competing findings and caveats regarding trade impacts on conflict, see Bell and Long (2016).

(21.) For example, see Russet et al. (1998). Boehmer, Gartzke, and Nordstrom (2004) qualify the argument to suggest that it is primarily structured organizations that carry this impact on conflict.

(22.) We avoid here a discussion about what creates these conditions. For example, it is plausible that there are important interconnections between major powers’ influence on their regions in creating democratic regime change, resolution of territorial claims, structural changes encouraging intra-regional trade, etc. (see McDonald, 2015; Rasler & Thompson, 2005b).

(23.) For a similar argument, see Carranza (2014).

(25.) Whether or not such governmental effectiveness is a function of ineffective bureaucracies or cultures of corruption is not addressed here. However, we note that policymakers who are rent seekers also try to minimize potential domestic opposition to their rent-seeking behavior. In the case of Nigeria, this may yield a substantially hollowed out military that is incapable of revolting against civilian elites and of addressing substantial security concerns within Nigeria and in its region, despite the size of its military spending (Chayes, 2015).

(26.) Domestic politics may impact major powers as well. Consider the case of the Trans Pacific Partnership, which proposed to create an alternative set of rules and norms for economic relations between the United States and its Pacific Rim partners in order to mitigate Chinese influence. The net effect on the U.S. economy did not appear to be substantial (estimated at 1% of its GDP over a decade) but appears as a politically important counterweight to Chinese influence among Asian states. Yet, it was met with constant rejection from both the Republican and Democratic 2016 Presidential nominees as trade agreements had become unpopular with key segments of the public, leading to the newly-elected Trump administration’s withdrawal from the proposed agreement. Should NAFTA have carried an expiration date for regional economic collaboration in North America, we would have expected that, given the elections of 2016, re-ratification would have become extremely problematic.

(27.) For this portion of identifying ROW regions, UCINET software was used.

(28.) Consistent with dyadic and monadic analyses that may drop microstates from their analyses, all regions that include fewer than four states have been excluded from our analyses. Seven of the 56 regions identified are microregions. The decade of the 1980s is not included since reliable events data are not available for the first half of that decade.

(29.) Major powers are identified as such when their economic capabilities (GDP) and economic reach (trade and global trade), military capability (military spending) and military reach (military spending and military personnel), global activity, and status attribution (diplomatic missions received and staffed by high level diplomats) exceed at least two standard deviations from the mean for the global community. For regional powers, these variables are linked to the mean for the region. All variables are aggregated at five-year intervals.

(30.) These are noted in Appendix A. The delineation of regional powers requires approximations of status attribution using diplomatic missions. The data on diplomatic missions prior to 1965 is problematic (often failing to distinguish between mission in country and the head of mission), allowing us to estimate status attribution for major powers but not for regional powers during the 1950s. As a result, we drop from our analysis regions during the 1950s.

(31.) Those that take on hostility values of four or five in the MIDs database. For all sources and manipulations, see Appendix C.

(32.) However, accounting for the location of the MID is not an easy task. The following steps were taken to ascertain MID location: established coding guidelines based on geographic onset location; dispute context; and member involvement. MIDs must have met at least one of three criteria; most MIDs met at least two. For detailed steps, see kellygordell.com/research.

(33.) For a review of the diffusion literature and its implications for regions, especially to the extent that regions may or may not create firewalls against regional diffusion, see Solingen (2012).

(34.) By relaxing some assumptions regarding the applicability of count models, we are also able to run negative binomial regressions for the two dependent variables. The results for our key independent hierarchy variables are quite similar. For the utility of using OLS regression for region year units of observation, see Lemke (2010).

In all models, we opt for random effects over fixed effects. Fixed effects would assume that our regions are stable over time: for example, Europe in the 1970s is the same as Europe in the 1990s. Given that our regions are themselves dynamic, evolving in both number and composition, this assumption would be untenable. In monadic or dyadic analyses this assumption is much less troublesome; e.g., France is France in 1970 and 1990 and Cuba–U.S. dyads today are not independent of Cuba–U.S. dyads yesterday.

(35.) In the Major Power Presence models for both tables, we omit the regional trade variable as it correlates at more than 0.80 with the major power hierarchy indicator and introduces problematic collinearity. We discuss this in the context of our two plausible causal mechanisms more in the discussion section.

(36.) We assessed multicollinearity in each of our four primary models by calculating the variance inflation factors (VIF) for each independent variable. Chatterjee, Hadi, and Price (2000) suggest collinearity becomes problematic when any given variable’s VIF is greater than 10 and the model average is above 1. Across the Major Power Presence models and Regional Power Presence models, no individual variable’s VIF is greater than % Regional Democracies’ VIF of 2.57, which moves with IGO Membership (VIF = 2.10). This does lead to slightly elevated model averages, ranging between 1.59–1.73, but we are nonetheless reassured of the validity of our results by the low correlation between these two variables (~0.04) and the theoretical importance both play in the so-called Kantian Tripod (Russett & Oneal, 2001). Additionally, one would suspect a very high correlation between rivalries and territorial disputes, but territorial disputes only account for less than 25% of extant regional rivalries.

(37.) Regions with fewer than four states are not used in the analyses.

(38.) Major power + designates that there is more than one major power residing in the region.

(39.) While there are sufficient data to classify regions that contain major powers, the indicators used to gauge regional power status are only intermittently available for the 1950s, making hierarchical classification inappropriate for this decade, and the 1950s are subsequently not used in the analyses.

(40.) Barbieri, K., & Keshk, O. (2012). Correlates of war project trade data set codebook, version 3.0. Retrieved from http://correlatesofwar.org.

(41.) Barbieri, K., Omar, M., Keshk, G., & Pollins, B. (2009). TRADING DATA: Evaluating our assumptions and coding rules. Conflict Management and Peace Science, 26, 471–491.

(42.) Marshall, M.G., Gurr, T. R., & Jaggers, K. (2016). Polity IV project: Political regime characteristics and transitions, 1800–2015—Annual Time-Series Dataset. Vienna, VA: Center for Systemic Peace.

(43.) Gibler, D. M. (2009). International military alliances, 1648–2008. Washington, DC: CQ Press.

(44.) Gibler, D. M., & Miller, S.V. (2014). External territorial threat, state capacity, and civil war. Journal of Peace Research, 51, 634–646.

(45.) Formal Intergovernmental Organizations dataset, http://www.u.arizona.edu/~volgy/FIGO.pdf.