All International Politics Is Local: The Diffusion of Conflict, Integration, and Democratization

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Tables 3.1. Connectivities for the Middle Eastern States 4.1. Democracy and the Likelihood of Conflict 4.2. Democracy and Conflict with Alternative Estimates of Regional Context 4.3. Authority Structures and the Likelihood of the Onset of Conflict 4.4. Levels and Change in Authority Characteristics and Conflict 5.1. Integration and the Likelihood of Incidents of Conflict 5.2. Likelihood of Conflict as a Function of Changes in Deutschian Flows 5.3. Deutschian Flows, Authority Structures, and the Likelihood of Conflict 5.4. Deutschian Flows, Authority Structures, Time Dependence, and War Onset 6.1. Regression of Level of Democracy on Regional Context, Wealth, and Conflict 6.2. Dynamic Probit Results for Transitions by Spatial Context, 1876–1996 6.3. Predicted versus Observed Regime Status for Equation 6.3 6.4. Transition Years in the Polity and ACLP Data 6.5. Dynamic Probit Results for Transitions by per Capita GDP, 1950–90 6.6. Dynamic Probit Results for Equation 6.5, 1950–90 Page viii →6.7. Dynamic Probit of Transitions by Spatial Context and per Capita GDP, 1950–90 6.8. Predicted versus Observed Regime Status for Equation 6.7 A1. Independent States, 1816–1996 B1. Interstate Wars, 1816–1996 B2. Civil Wars, 1816–1996 B3. Extrasystemic Wars within Contiguous National Territory, 1816–1996 D1. The Construction of the Polity Institutionalized Democracy Scale E1. Symbols and Notation

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Figures 1.1. European integration and disintegration 1.2. Moran’s I for clustering of war involvement, 1875–1996 1.3. Moran’s I for clustering in years of peace, 1875–1996 1.4. Moran’s I for clustering in institutionalized democracy, 1875–1996 1.5. Moran’s I for variance in level of democracy over prior 10 years, 1875–1996 1.6. Moran’s I for regional trade to total GOP, 1950–92 2.1. A regional conflict, integration, and democratization nexus 2.2. The global distribution of democracy, 1800–1996 4.1. Marginal effects of actor’s level and regional context of democracy on conflict 4.2. Effects of internal and regional democracy on conflict, LOESS with span = 0.75 4.3. Effects of internal and regional democracy on interstate war, LOESS with span = 0.75 4.4. The impact of time at peace on the likelihood of interstate war 4.5. Democratization and the likelihood of interstate war 4.6. Democratization and the risk of civil war 4.7. Values of for democracy and time at peace, Belgium, 1875–1996 4.8. Values of for democracy and time at peace, Iran, 1875–1996 Page x →5.1. Likelihood of conflict by extent of compatibility and density of regional trade 5.2. Marginal effects, holding other variables at mean (or mode) values 5.3. Density of estimates given authority structures, similarity, and integration 5.4. Conditional covariance plots for Deutschian flows and authority structures 6.1. Predicted levels of democracy under a transition experiment 6.2. Observed first-order Markov transition probabilities 6.3. Estimated first-order Markov transition probabilities at time t + 30 6.4. Estimated survival and transition probabilities given spatial context of democracy 6.5. Transition and survival probabilities by spatial context of democracy and real per capita GDP 7.1. A revised regional conflict, integration, and democratization nexus

Maps

1.1. Wars, 1992–98 1.2. Years at peace, 1996 1.3. Democracy in the international system, 1996 1.4. Changes in democracy, 1986–96 1.5. Local trade, 1990 3.1. The Middle East, post-1990 borders

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Acknowledgments This book grew out of my doctoral dissertation at the University of Colorado. Among the many who have provided suggestions and comments on this research and helped make this manuscript more readable I wish to acknowledge Brian A’Hearn, Nathaniel Beck, Steve Chan, William J. Dixon, Andrew J. Enterline, Paul F. Diehl, Scott Gates, Erik A. Gartzke, Håvard Hegre, Matthew Johnson, Gary King, David A. Lake, David Lalman, Mark I. Lichbach, John McIver, John O’Loughlin, Bruce M. Russett, William R. Thompson, Richard M. Tucker, and Jonathan Wilkenfeld. Most of all, I am heavily indebted to Michael D. Ward. Without his help, advice, and encouragement, this manuscript would never have seen the light of day. The manuscript was completed while I was at the University of Glasgow, and I am grateful to the director of the Faculty of the Social Sciences’ postgraduate training program, Charles A. Woolfson, for his support and encouragement. I am also grateful for financial support from the Research Council of Norway and the Human Security Program at Harvard University. I would also like to express my appreciation to three maybe not so anonymous reviewers and Jeremy Shine of the University of Michigan Press. Finally, I would like to thank my parents for their support and understanding.

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CHAPTER 1 Zones of Peace, Conflict, and Democracy The key to understanding the real world order is to separate the world into two parts. One part is zones of peace . . . the other part is zones of turmoil. . . . [I]f you try to talk about the world as a whole all you can get is falsehoods and platitudes. (Singer and Wildavsky 1996: 3) [N]orms and rules of behavior internationally can become extensions of the norms and rules of domestic political behavior. . . . A system composed substantially of democratic states might reflect very different behavior than . . . one composed predominantly of autocracies. (Russett 1993: 137–38) States that became (and remained) democratic . . . found themselves in relatively cooperative niches that insulated them from extremely competitive, regional international politics. . . . [Such n]iches preceded substantial progress in democratization. (Thompson 1996: 142)

Prologue: A Disparate World The field of international relations focuses on the political, economic, social, and cultural relations among societies and states. This book is about changes in these relations, in particular how peace and conflict coevolve with the emergence of democratic governance and integration among states. Where should we look for such linkages? A common approach in international relations research is to address global trends. Is conflict becoming more or less common? Are there fewer or more democracies in the international system? Systemic features or trends at the global level, however, are rarely clear-cut. Even very dramatic changes such as the introduction of nuclear weapons or the implementation of formal treaties rarely have identical implications for all states. The heterogeneity in the international system ensures that states face dramatically different regional contexts. Page 2 →This heterogeneity is reflected in remarkably different descriptions of the international system in the post–World War II era. On the one hand, the period can be seen as an epoch of a remarkably “long peace” or relative absence of war (e.g., Gaddis 1987). Many states that had clashed repeatedly in the past experienced an unprecedented period of generally peaceful relations after 1945 — with France and Germany the most notable example. This lack of overt conflict has been accompanied by increasing intergovernmental cooperation, greater transnational linkages between societies, and more favorable group perceptions. The long peace in Western Europe appears to reflect something beyond successful nuclear deterrence or mere luck. Yet, by other criteria, the postwar period seems to be one of the bloodiest periods of world history (e.g., Brecher and Wilkenfeld 1991). Even though a disastrous global nuclear war between the superpowers failed to materialize, a cursory glance below the global level reveals both extensive and persistent armed conflict. No long peace prevented severe interstate conflicts in Korea, Vietnam, and the Persian Gulf (between Iran and Iraq), each of which claimed more than a million casualties. Countries such as Angola, Cambodia, and El Salvador have experienced violent conflict within, with equally disruptive consequences. The emergence of new states and the dissolution of multinational states such as Yugoslavia and Ethiopia, which split along ethnic cleavages, have been accompanied by pervasive violence. In the Middle East, rivalry, mistrust, and insecurity has persisted even in the absence of outbreaks of war. Seen from these perspectives, the term long peace seems to be a misnomer. The heterogeneity within the international system has become more salient in the wake of the Cold War. The international system — and Europe in particular — displays seemingly disparate tendencies that suggest both increasing cooperation and conflict. Figure 1.1 displays in somewhat exaggerated form the disintegration and polarization of Eastern Europe at a time when Western Europe is reaching unprecedented levels of formal integration.1 Although the changes in the former socialist countries have been remarkably nonviolent overall,

increasing latent hostility, if not overt violent conflict, has accompanied many transitions and the emergence of new states. In sum, the new opportunities for cooperation as well as conflict in the wake of the Cold War have yielded dramatically different outcomes at the regional level. Page 3 → Fig. 1.1. European integration and disintegration

Zones of Regional Clustering The marked regionalization of conflict and cooperation is well illustrated by Singer and Wildavsky (1996), who refer to coexisting zones of peace and zones of conflict and rivalry. Both cooperation and rivalry perspectives describe characteristic features of the international system, but they are best applied to certain regions or geographical clusters of countries. Similar patterns also apply for attributes such as political structures and economic relations. Zones of integration and compatibility coexist with zones of polarization, fragmentation, and conflict. This book is about the ways in which such regional differences in conflict and cooperation develop and evolve. Zones of regional clustering where states share many similarities can be delineated by variations and discontinuities in attributes of states and relations between them. I contend that regional clustering stems from dependence and shared influences between geographically proximate Page 4 →entities. Previous research has shown that the likelihood of interactions such as conflict and trade is inversely related to the distance between entities. The geographically determined interaction context strongly influences the constraints and opportunity structures for individual states. Given disparities among regions, the incentive structure and structural constraints states and actors face will vary considerably. In this sense, clustering and differences in its character have important implications for state behavior. Regional clustering of domestic attributes may have important implications for the risk of conflict and prospects for cooperation. Regional dynamics may also change domestic attributes. The recent so-called third wave of democratization (Huntington 1991) displays marked regional patterns, as does the earlier wave of autocratization following the breakdown of young democracies in the wake of decolonization. Rather than disassociating attributes of countries and their interactions from their larger context, we should approach international politics in terms of linkages between interdependent states. That there is widespread regional variation in the international system is hardly a novel claim. This study seeks to go beyond casual evidence and evaluate some explanations of why such clustering occurs and how it develops. In chapter 2, I link the prospects for regional conflict and cooperation to domestic attributes and relations among states. In this chapter, I first seek to clarify what I mean by regional clustering, how and why proximity induces interdependence among states, and the broader theoretical and empirical implications of interdependence. The more specific hypotheses relating to the emergence of zones of conflict, integration, and political authority structures are laid out in chapter 2.

Regional Interdependence: Willingness and Opportunity Actors are dependent when each is influenced by what other actors do or are expected to do. More formally, we have interdependence between actor A and a set of other actor(s), B, if the probability that A experiences some event x or does some action y changes depending on whether some condition z obtains in one or more countries, Bi, in B. I use the term interdependent region to denote clusters of jointly dependent actors. Interdependence implies that actors are locked into some form of Page 5 →collective dependence that structures their interaction (e.g., Cornes and Sandler 1996; Lake and Morgan 1997). This usage goes beyond the more restricted notion of economic interconnectedness. In an interdependent region, outcomes result from the interplay between actors and are typically not fully controllable by individual actors. Many outcomes are collective in the sense that they are shared by all parties alike. Each individual actor’s feasible set of actions is shaped by other

actors in its regional context. Outcomes and individual objectives and strategies must be considered relative to the context of interaction-structuring relations. International behavior does not occur in a vacuum, and interdependence may apply at many different levels of world politics. Interdependence is often analyzed as a systemic attribute. Although agents may be influenced by a variety of external events, few factors influence all states in the same fashion. Most actors, processes, and events within the international system are not related or interdependent in any meaningful sense of the word. But rather than treating interdependence among actors as an either-or issue dependence is more usefully seen as a matter of degrees of influence. The central question is whether we can identify in some systematic fashion those relationships that are likely to be most relevant in international interactions. In this book, I contend that the physical proximity of events and actors provides a good indicator of relevance with regard to other actors. Events and processes within the proximate environment provide the primary influences on actors in an interaction cluster. In this sense, the most interesting international politics is local rather than global. Proximity as Opportunity The regional basis of interdependence stems from a close relationship between geographical distance and the opportunity for interaction (Most and Starr 1989; Starr 1978). The density of different types of positive and negative social interaction will tend to be higher between proximate actors. Stated differently, the closer two actors are to each other the greater their mutual relevance. Several formal models represent the expected level of interaction between units as a function of the distance between the units. The best known of these is probably the so-called gravity model, which is loosely based on an analogy to physics, where the force of attraction between two Page 6 →points decreases by some exponential function with geographical distance.2 Many have tried to provide theoretical foundations for such models. Whereas Zipf (1949) saw this as a general law that could be derived from the somewhat obscure “principle of least human effort,” more conventional interpretations emphasize minimization of cost, which can be assumed to increase with distance (e.g., Anderson 1979). Høivik et al. (1974: 3–7) show that the gravity model can be derived probabilistically assuming an isotropic distribution of trips (i.e., identical in all directions) from some specific location. Distance decay models have been applied to several forms of international interactions such as interstate conflict and trade (e.g., Boulding 1963; Isard 1988; Linnemann 1966). Many stylized empirical facts in research on international interactions refer to distance. Some (e.g., Maoz 1996; Midlarsky 1975) argue that geographical proximity or shared borders are virtually necessary conditions for military conflict between countries other than major powers. Furthermore, conflicts have a tendency to spread or diffuse to proximate actors (e.g., Most and Starr 1980; Siverson and Starr 1991; Starr and Most 1978, 1985; Ward and Gleditsch 2000). Many have tried to capitalize on this finding by including distance as a “control variable” or to identify subsets of “politically relevant” relations between states with an actual opportunity of conflict (Lemke 1995; Maoz 1996). This rather indirect approach to interdependence tells us little about how interdependence affects linkages between other variables. In this book, I will show how we can use concepts from spatial statistics to address interdependence among states and actors. Willingness as Institutions If the geographically based interaction environment shapes behavior for all states alike, how can geography and proximity help account for regional variation? The substantial interdependence among proximate countries tells us little in itself about the character of their interaction. Interdependence can be both a pacifying element and an inducement to conflict. Proximity to an actor or event can constitute a threat to security as well as an opportunity for cooperative interaction. Regional interaction environments may range from hostile and conflictual to largely cooperative and compatible. The more interesting issue is how local interdependence plays out differently among regions in the international Page 7 →system. Why do some become zones of peace while others seem trapped in

perpetual zones of turmoil? A regional approach relating proximity to opportunities for interaction is incomplete if it is not integrated with what Most and Starr (1989) label “willingness,” or the preferences and perceptions decision makers hold with respect to alternatives and outcomes. Variations in willingness are reflected in prevailing patterns of amity and enmity between states. Willingness and opportunity are conceptually distinct, but in an interdependent interaction environment the two are not fully independent. Although observed behaviors reflect individual actions and decisions, the choices of individual agents are influenced by the external structure or context. An actor’s optimal strategy is contingent upon opportunity and feasibility structures, and the latter are to a large extent shaped by expected events and the actions of others. As such, heterogeneity in international relations cannot be fully reduced to differences in the preferences of individual actors since these are shaped by interdependence and interaction with other actors. The close association between opportunity and willingness makes it difficult to analyze the two separately. Empirical research indicates that it is often virtually impossible to determine whether some phenomenon is associated with opportunities for interaction or willingness to engage in interaction. Whereas many scholars focus on linkages between proximity and the propensity for conflict, others hold that the issues arising in interaction between contiguous countries — such as disputes over territory — constitute the principal causes of violent conflict between proximate countries (e.g., Diehl 1992a, 1992b; Huth 1996; Vasquez 1993).3 The relationship between opportunity and willingness is implicit in the notion of a regional security complex, defined as a “distinct and significant subsystem of security relations . . . among a set of states whose fate is that they have been locked into geographical proximity with each other” (Buzan 1991: 188). Geographical proximity to other actors and events shapes a state’s opportunity for interaction with others as well as its security concerns and preferences. Violence is more likely between close kin not only because of opportunities for interaction but because high interaction proliferates the number of issues that can spur violent confrontation. In this sense, willingness might be considered variation in the prevailing social institutions or the patterns structuring social interaction among actors in a regional cluster.4 Differences in social institutions shape the Page 8 →implications of interdependence for actors as well as their expectations about likely future behavior. For purposes of illustration, we can order the potential social institutions in a regional context on an idealized continuum.5 At the conflictual extreme, we find behavior characterized as “protracted conflict” or “enduring rivalry.” These concepts denote hostile competition between parties wherein each side views the other as a significant threat to its security and vital interests, and the likelihood of repeated confrontation is high. Azar et al. (1978: 50) stress how “hostile interactions which extend over long periods of time with sporadic outbreaks of open warfare fluctuating in frequency and intensity . . . are not events [but] . . . processes . . . where stakes are very high.” Hostility between parties persists beyond the duration of particular events and becomes a regular aspect of their interactions and behavior. Single disputes or clashes are parts of a broader sequence of interaction rather than isolated occurrences. Outcomes in regional interaction clusters involve elements of collective action problems. They often resemble social traps, in which actors through their interactions reach collective outcomes that are inefficient and suboptimal yet find themselves unable to improve on the outcomes unilaterally or achieve the required collective action (e.g., Cross and Guyer 1980; Sandler 1992). Protracted rivalries can be seen as security dilemmas, in which parties are locked into hostile competition and individual efforts to increase security unleash greater collective insecurity. Security dilemmas are typically held to arise from the rival and nonexcludable nature of security in an anarchic world. Security is considered rival because of its presumed zero-sum nature. An increase in the ability of one agent to ensure security is inevitably a threat that reduces the relative security of others. States cannot trust the intentions of other states and are inherently insecure unless they possess sufficient capabilities to deter aggression. Yet the capabilities allowing one state to deter constitute a possible threat to the security of another. Security is largely nonexcludable since states cannot fully control the ability of other states to pursue increases in their security. Conflict among states is always possible given the absence of a supranational authority that can regulate

interactions and enforce agreements. Many varieties of realism hold that these inherent structural problems render sustained cooperation in international relations nearly impossible.6 The prima facie basis for cooperation rests on the possible gains from exchange and coordination. Although contracting and commitment problems Page 9 →do not necessarily inhibit limited coordination and exchanges, sustained cooperation may not be feasible without social institutions that permit actors to transcend security and contracting problems. As long as the use of coercive force remains a possibility, states need to preserve security. The fear of exploitation by other states and mistrust may prevent mutually beneficial transactions as long as other states have incentives to exploit and the consequences of exploitation are disastrous. The presumed universal structural properties of anarchy suggest that all states in the international system should display similar concern over means of achieving security and willingness to engage in armed conflict. Merely a casual inspection, however, reveals that cooperation and compatible relations between states are clearly more widespread than one would expect if the constraints on cooperation were this insurmountable. Several qualifications have been put forward to account for how and under what conditions sustained cooperation between sovereign states may be feasible. Several forms of cooperation are possible despite anarchy. Even in traditional realist theory, the idea that states balance or align against a common threat implies forms of collective action (see, e.g., Gartzke and Gleditsch 2001 and Simowitz 1982). Wagner (1983) points out how differences in the ability to monitor and punish violations alter the prospects for international cooperation in different realms. Oye (1986) provides a series of studies on constraints and prospects for different forms of cooperation under anarchy.7 On the cooperative extreme of the conflict-cooperation continuum, we find forms of “integration” or “community.” Such relations decrease the element of rivalry between parties to the point where the use of coercive force is no longer considered a realistic prospect. This allows cooperative transactions to persist across issues and over time. There are numerous examples in which states possess ample opportunity to conquer, exploit, or use coercive force against neighbors yet display no seeming interest or “willingness” to engage in such activities. That the weaker parties typically do not expect such behavior attests to the fact that integration goes beyond mere acquiescence to power. Despite the claims of world federalists and realists, social institutions can provide feasible solutions to avoiding conflict even in the absence of formal solutions to “the problem of anarchy.” This range of variation among conflict and cooperative relations suggests that a region or interaction cluster may arrive at multiple feasible Page 10 →outcomes. Each of these states imposes certain constraints on the individual actor, and several may constitute relatively stable equilibria. Chapter 2 introduces two main sets of hypotheses on how clusters of countries or interaction environments arrive at different states and evolve from one state to the other. First, however, I will try to justify why we should study conflict, cooperation, and democratization through regional interactions rather than from more conventional perspectives that emphasize relations at the level of either the global system or individual states.

Why Study Regional Interactions? What are the benefits of studying regional interactions for understanding the prospects for conflict, cooperation, and linkages between domestic and international politics? If regions differ notably, it is clearly inappropriate to assume universal relations. If the main manifestations of interdependence are local or geographically confined, we can clarify linkages between conflict and cooperation among states and their relationship to state attributes by focusing on the relationship between states and their regional interaction context. It is hardly novel to recognize regional differentiation and heterogeneity throughout the international system. Earlier studies of “regions in world politics” argued that many regions operate with some autonomy from global influences and display particular dynamics. This literature originated with area specialists who found prevailing systemic theories of international relations insufficient to account for interstate behavior within some given region

or subsystem (e.g., Binder 1958; Brecher 1963; Zartman 1967). Despite the Cold War and the influence of the superpowers, many analysts felt that various regional subsystems simply did not operate according to the principles of bipolarity implied by general systemic theories of international relations. Although these studies pointed to important forms of regional variation and acknowledged local interdependence, most tended to focus on idiosyncrasies of particular regions and how these somehow “differed.” As such, these studies rarely achieved much by way of a general theoretical framework for studying regional variation (see, e.g., Thompson 1973). Obviously, we can describe differences between regions in empirical research quite well by taking such differences as given or empirical Page 11 →facts. Treating each region as unique or accounting for differences by means of proper names or dummy variables explains little beyond the information already used to generate the explanation. Theory development or generalization requires that we replace proper names with general variables (see Przeworski and Teune 1970). Social science seeks parsimony or to “explain as much as possible with as little as possible” rahter than descriptive completeness (King, Keohane, and Verba 1994: 29). We can transform local differences into variation on more general variables by focusing on properties of geographically shaped interaction clusters. This in turn allows comparative inquiry into the origins of regional differences. Relations other than distance may obviously also influence dependence between entities. Other factors pertaining to opportunity for interaction such as resource endowment and technology modify the relationship between distance and interaction. Regional subsystems are not fully autonomous, as states are exposed to many forces outside the regional context. The main question is whether the association between geographical distance and the density and relevance of interactions is so consistent that we can account for much of the variation in conflict and cooperation. In particular, since global influences should be relatively homogeneous or similar for all states, these are of little help in accounting for variation in international conflict and cooperation across states. Theories that relate international behavior to inherent properties of system structure also seem hard-pressed to account for change over time. Without a clear theory of change in the structure of the international system itself, the explanatory power of systemic theories seems less persuasive in light of the changes after the Cold War. Change in the international system may be interpreted in two different ways. First, relevant system-level attributes such as the distribution of power may change. Such changes in system structure pose no theoretical challenge to systemic theories, but systemic theories generally leave the sources of such changes unexplained and treat them as entirely exogenous.8 Second, change in the international system may stem from qualitative changes in the nature of interactions between states. According to most systemic theories — and realism in particular — the constraints of the international system rule out the possibility of qualitative changes in interactions. Mearsheimer (1990), for example, holds that the Post–Cold War period does not differ notably from previous multipolar eras. Disappointment with systemic explanations leads many scholars to Page 12 →look to attributes of individual states for sources of differences in international behavior. A focus on state attributes can in principle account for variation in international behavior by relating this to changes in domestic politics. Such approaches have generated a number of empirically supported propositions. This is seen most clearly in the mushrooming empirical research on the relationship between political institutions and international conflict and cooperation, which some characterize as evidence of a cumulative scientific research program in a Lakatosian (Lakatos 1970) sense (e.g., Bremer and Cusack 1995; Levy 1998; Nicholson 1996; Vasquez 1993). Despite evidence of empirical and theoretical progress, the current research on domestic to international linkages is wrought with ambiguities. Even though international relations by definition is the study of relations between states, research linking domestic attributes to international behavior tends to treat each state as an independent unit. Although states undeniably are different, it seems questionable whether all variation in conflict and cooperation can be reduced to differences between individual states. Interdependence implies that the interaction itself is essential and that the behavior of each individual state is influenced by the expected behavior of other states. External influences may lead different states to behave similarly, and similar states may behave differently if the external context changes. Most research on domestic-international linkages focuses on dyads — that is, a pair of countries — but does not

consider influences from other states or dyads.9 The dyadic emphasis furthermore creates units of analysis that do not always have meaningful behavioral referents and often reveals a disjunction between the original theoretical rationale and empirical analyses. Political democracy, for example, is not an inherently dyadic variable. The emphasis on the bilateral version of the democratic peace (democracies do not fight one another) stems more from the seeming robustness of the result at this particular level of analysis than any inherent dyadic character of the theories set forward to account for the finding. The steps required to translate domestic attributes into a property of bilateral units or dyad-years are often theoretically convoluted and ambiguous. Although researchers would like to know whether “democracy correlates with peace” more broadly, studies at other levels of analysis have been rather vaguely specified. As such, it is not surprising that the empirical findings have been weak and inconsistent. The near exclusive emphasis on dyadic linkages between domestic Page 13 →politics and international behavior has partially incapacitated researchers’ ability to understand how changes in domestic politics influence international conflict and cooperation. Many extrapolate from the dyadic democratic peace finding to an assertion that a spread of democratic institutions in the international system will decrease the extent of conflict. However, there is no necessary relationship between static and time-invariant evidence at the dyadic level and the dynamics of democratization and conflict. Some research even suggests that pairs of politically dissimilar regimes are more dispute prone than pairs of nondemocracies and that the process of democratization may increase the likelihood of conflict (e.g., Enterline 1996a; Mansfield and Snyder 1995; Maoz and Abdolali 1989; Raknerud and Hegre 1997; Ward and Gleditsch 1998). These findings do not follow from any of the existing dyadic theories. Indeed, current theories formulated at the dyadic level seem insufficient to derive additional observable implications about the consequences of domestic changes, or even much by way of informed guesses. Most researchers treat differences in political institutions merely as given, and it is widely assumed that such institutions are determined by domestic factors and events. However, as we will see, domestic attributes such as political characteristics tend to cluster geographically. It seems questionable whether domestic attributes such as political institutions can be considered entirely independent of interactions between countries, and the nonrandom geographical distribution of domestic attributes or changes may reflect patterns of dependence and influence between countries. Similarly, the local context within which regime change takes place may have important consequences for the potential effects on conflict and cooperation. The way changes in political authority structures have unfolded in the recent “third wave” of democratization strongly suggests that influences and interdependence between states, rather than purely domestic processes operating separately inside each country, might have been at play. To summarize, although interdependence is pervasive in world politics, it is usually regional or geographically confined rather than global. Focusing on regional clusters allows us to treat actors as interdependent at a level below global structure that contains the primary interactions that influence individual states. Focusing on how the regional context modifies domestic and international linkages can help identify where particular domestic and international relationships should be expected to hold. Page 14 →

Identifying Zones in World Politics So far, I have mainly relied on casual evidence and asserted that domestic attributes and international behavior patterns cluster in qualitatively different zones. Now it seems appropriate to explore the empirical record more carefully and probe whether we can systematically identify zones of regional clustering in conflict, cooperation, and political institutions. In this section, I present evidence of regional clustering in several common sources of data on interactions and attributes. I have suggested that we should see forms of regional confluence where the likelihood of certain events or phenomena for a given state varies with the characteristics of its regional interaction environment. More specifically, we should see geographical clustering in data on the distribution of interstate conflict, cooperation, and domestic political and economic structures. The individual observations should be correlated in a

geographically conditional pattern. The simplest way to assess spatial clustering and variation among geographical units is to plot the data as a map. Humans, however, are good at seeing patterns where none exist, and in many cases it is useful to explore the amount of clustering by means of more formal approaches.10 The principal building block of spatial statistical techniques is an n × n connectivity matrix W representing some hypothesized pattern of dependence among a set S = {1, . . . , n} of N spatial units. Each entry Wi,j in W indicates a relationship between two units, i and j, and is assigned a nonzero value if the two units are hypothesized to be dependent on one another.11 From a statistical point of view, dependence among observations across space is conceptually similar to the more familiar case of temporal dependence. The appropriate specification to test for possible spatial dependence, however, is typically more complicated. Spatial patterns lack the obvious inherent ordering found for time, which immediately suggests plausible correlation structures. Since space is multidimensional, the search space of possible forms of dependence is typically much greater. A connectivity matrix can be specified on the basis of any hypothesized pattern. In this case, the prevalent forms of interdependence are assumed to be local or inversely related to geographical distance. Research in international relations has tended to measure geographical distance between states either by categorical measures of whether states have physically contiguous boundaries or by continuous measures of the Page 15 →distance between some center locations such as their capital cities. In this study, I use a new data set to measure the minimum distance between the outer boundaries of polities in the international system.12 These data allow varying the cutoff criteria for what is to be considered “relevant” or assigning differential weights based on distance between units. The optimal distance threshold for relevance is not precisely known and may vary for different attributes. To ascertain whether results are robust and do not merely stem from a particular delineation of relevant distances, I consider connectivity matrices with cutoff thresholds for relevance set to 950, 475, and 50 kilometers. The most common descriptive statistic used to assess clustering in an input variable x in a sample of data on geographical units is the Moran’s I (1950) correlation coefficient. This is defined as where ij denotes an element (i, j) of a row-standarized connectivity matrix where each row i sums to 1.13 Moran’s I indicates the similarity between an observation xi and the values of xj for the set of J neighbors of i. The coefficient is not bounded by ± 1, and the expected value E(1) is – 1/(N — 1) rather than zero. The estimated standard error of the Moran’s I statistic allows us to test whether observations in an observed sample cluster significantly more geographically than would be expected under the null hypothesis of no spatial clustering.14 Moran’s I is a global statistic that indicates whether features are clustered geographically in the aggregate, but it does not indicate where aspects cluster geographically.15 In the following, I will rely on both visual examination of maps of the raw data at a single time slice and the aggregate spatial correlation over time, as indicated by the Moran’s I, to determine to what extent we can find qualitatively different zones. Clustering in War and Peace Conflict and its absence are typically measured as a dichotomous variable. The most common empirical data on wars are drawn from the Correlates of War (COW) project’s international and civil wars data set (Singer and Small 1994), which indicates incidents of major armed conflict involving more than 1,000 fatalities. Unfortunately, these data have Page 16 →not been fully updated beyond 1992. The Department of Peace and Conflict Research at Uppsala University has collected annual data on armed conflict since 1989 (Wallensteen and Sollenberg 1999). Since these data are classified by level of battle deaths, we can update the COW data with the more recent cases in the Uppsala data set that reach the level of war. Map 1.1 indicates the geographical distribution of wars in the period 1992–98.16 Africa, the Middle East, and the Indian subcontinent had the highest incidence of war over this period. The only interstate war occurred in 1998 between Ethiopia and Eritrea. However, several conflicts classified as “civil” wars,

such as those in Angola, Nagorno-Karabakh, Rwanda, and Chechnya, involved combinations of state and nonstate actors transcending national borders. Many sources of data on international conflict simply exclude any form of civil war in which the parties facing each other are not nation-states. Although these conflicts may not be interstate, they are nonetheless often internationalized, as neither conflict involvements nor their consequences are necessarily limited to the country experiencing civil war. Most of us would be hesitant to characterize areas with extensive civil war as “zones of peace” as long as they avoid interstate war. This underlines some of the potential problems involved with using precompiled data indiscriminately. Unfortunately, we often find large discrepancies between theoretical concepts and the measures actually applied in empirical research. I discuss these issues in greater detail and suggest some alternative measures of regional conflict in chapter 3. Wars are rare events in which both the number and the spatial distribution of incidents can change dramatically from one year to another. Whereas map 1.1 reflects only a snapshot in time, the notion of interstate rivalry or protracted conflict suggests that each onset of violent conflict over time is not an independent event but is influenced by previous interactions. Conflict is persistent and has a strong tendency to recur between past antagonists. Thus, we must also pay attention to how latent conflict and patterns of hostility build up over previous conflictual interactions and persist or decay over time. I will have more to say about these aspects in chapters 2 and 3, but a simple first approach that may help illuminate the more enduring patterns of conflict and peace over time is to examine the number of consecutive years of peace that countries have experienced since either the last conflict involvement or the emergence of statehood. The geographical distribution of consecutive years without war involvement, displayed in map 1.2, indicates strong clustering in regional patterns of conflict and peace. The map indicates a zone of clustering of low values in the Middle East, eastern Africa, and the Horn of Africa, reflecting recent regional conflict involvement. However, there is also clear evidence of zones with a converse clustering of high values of time at peace or longer spells without conflict involvement. We find such seemingly peaceful zones in parts of Europe and the Americas. Page 17 → Map 1.1. Wars, 1992–98 Page 18 → Map 1.2. Years at peace, 1996 Page 19 →Maps 1.1 and 1.2 are based on snapshots of the international system for brief time periods, and skeptics might ask how stable such patterns of geographical clustering are over time. We can get an appreciation of the degree of spatial clustering in the international system over time by examining the aggregate spatial correlation as measured by the Moran’s I coefficient for each year in the period 1875–1996. Rather than displaying hundreds of correlation coefficients in an unwieldy table, I plot the value of Moran’s lover time in a single panel with a separate graph for each distance threshold. Figures 1.2 and 1.3 display the Moran’s I coefficients for the spatial correlation of wars and consecutive years of peace. Years with significant spatial clustering are indicated by filled circles, whereas blank circles indicate cases in which the null hypothesis of no spatial dependence cannot be rejected at p < 0.05. The expected value of Moran’s I is plotted as a solid line.17 Fig. 1.2. Moran’s I for clustering of war involvement, 1875–1996 Page 20 → Fig. 1.3. Moran’s I for clustering in years of peace, 1875–1996 Wars are rare events, and figure 1.2 suggests that the distribution of wars seems generally random in space for most years. However, in some time periods we see clear evidence of clustering, notably around the outbreaks of larger multilateral wars such as World War I and World War II. The evidence for clustering is the strongest for very short distance thresholds, which probably reflects the fact that wars tend to take place and diffuse between adjacent states. The growth of the state system makes it hard to distinguish between states with few consecutive years of peace and those that had become independent in the first years after 1875 (fig. 1.3). After 1940, however, even aggregated to the global level, we see clear evidence of geographical clustering in recent conflict and longer spells of peace. The spatial Page 21 →relationships in conflict and peace seem reasonably robust across different

distance specifications. This lends support to the notion that these patterns of spatial clustering reflect enduring variation and heterogeneity in the international system and are not merely transient or erratic features. Clustering in Political and Economic Institutions We find similar geographical clustering in the distribution of political authority structures of states. The institutionalized democracy scale in the Polity data set is commonly used to measure political institutions (Gleditsch and Ward 1997; Gurr, Jaggers, and Moore 1989). The full democracy scale ranges from a low of – 10 for the most autocratic polities to a high of 10 for the most democratic. Map 1.3 displays the distribution of democracy in the international system in 1996. For simplicity, I collapse the values into three larger categories of regime types, as suggested by Jaggers and Gurr (1995), labeled coherent democracies (scores of 6 or above), coherent autocracies (scores of – 6 or below), and anocracies, which combine features of both democracy and autocracy (scores between – 5 and 5). Some polities were considered to be “in transition” in 1996 and have not been coded in the Polity data. Map 1.3 shows clearly discernible zones with similar authority structures in 1996. One cluster of democracies spans most of Europe, while there are two not fully connected clusters in the Western Hemisphere. At the opposite end of the spectrum of authority structures, a belt of authoritarianism stretches from Central and East Africa through the Middle East into Asia. Figure 1.4 displays the Moran’s I for the spatial clustering in the full 21 point institutionalized democracy scale for each year between 1875 and 1995. This figure provides strong evidence that political structures are nonrandomly distributed in space. With the exception of a few years (notably during World War II), there is a consistent pattern of significant spatial clustering since the end of the nineteenth century. In other words, the observed likelihood of a given country being democratic or not differs notably given the properties of neighbors. The pattern seems to be generally consistent and robust across different distance thresholds. Political structures tend to be relatively time invariant and rarely change from one year to another. Map 1.4 shows that we can find similar evidence of geographical clustering in changes in political structures as well over the decade 1986 to 1996. We see a cluster in changes toward democracy in both the Southern Cone and Eastern Europe, which underwent extensive transitions over the period. In addition, many countries in West and Central Africa became less autocratic over this decade, if not necessarily democratic polities, as can be seen in the distribution of regime types in the region in 1996 (map 1.3). The geographical clustering of changes in Map 1.4 corroborates the claim that the third wave of democratization in part was regionally based. Page 22 → Map 1.3. Democracy in the international system, 1996 Page 23 → Fig. 1.4. Moran’s I for clustering in institutionalized democracy, 1875–1996 Measuring the net change in democracy over a decade treats gradual and abrupt changes alike. Moreover, by looking at net change we may potentially overlook changes within time periods that revert back to the original institutional structures. Another way to look at political transitions is to examine the volatility in authority structures by way of the variance in the annual data over the prior decade. Countries that experience no change over the period will have a score of zero, whereas countries with changes have positive scores. Figure 1.5 displays the cluster in the variance of authority structures over the prior decade from 1875 to 1996. The proliferation of statistically insignificant white circles in figure 1.5 indicates that the variance of political authority structures is mostly not geographically clustered for most years. From the late 1970s on, however, the null hypothesis of no spatial clustering appears to be rejected on a more consistent basis. In this sense, even when aggregating changes up to the global level, we find some evidence of a geographical pattern in political processes and transitions in the international system during the third wave of democratization. Similarly, we see some evidence of clustering in changes prior to the outbreak of World War II in 1939, which may reflect the breakdown of democracy in many European states. Page 24 → Map 1.4. Changes in demoracy, 1986–96 Page 25 → Fig. 1.5. Moran’s I for variance in level of democracy over prior 10 years, 1875–1996

The sum of trade with neighboring countries as a fraction of GDP ratios may serve as a measure of the distribution of regional trade integration among states. Data on import and export flows in current prices are taken from the International Monetary Fund’s (IMF’s) Direction of Trade (DOT) data set (International Monetary Fund 1997) and measures of total gross domestic product (GDP) in current prices calculated from the Penn World Tables (PWT) mark 5.6 data set, with some modifications (Gleditsch 2002; Summers and Heston 1991). Map 1.5 suggests significant clustering of trade with neighbors in 1990. The extent of regional trade integration is high in Europe and North America, but much of the developing world and the zones of regional conflict in Africa, the Caucasus, and the Middle East (save for the large oil-exporting countries) have little trade with neighboring countries. Page 26 → Map 1.5. Local trade, 1990 Page 27 → Fig. 1.6. Moran’s I for regional trade to total GDP, 1950–92 Figure 1.6 displays the Moran’s I for regional trade as a share of total GDP for the postwar period. Up to the early 1960s, there is no significant geographical clustering. This may stem in part from the generally low levels of trade in the world economy during the first years of postwar reconstruction. Beginning in the 1960s, however, significant clustering in trade with neighboring states begins to emerge. The much touted “globalization” of economic processes often involves a more localized form of internationalization in economic exchange rather than an integrated global system. Page 28 →The evidence of geographical clustering presented here is consistent with what one would observe under substantial interdependence and influence between countries within an interaction environment. It does not by itself, however, prove that such influences actually occur or to what extent broader zones in one attribute coevolve with zones in another. In chapter 2, I outline a theory of regional linkages among conflict, integration, and democratization among spatial clusters of interdependent states. In chapters 4 to 6, I examine more systematically to what extent geographical clustering in one domain is associated with clustering on other variables.

Summary and Outline Regional heterogeneity is widespread in world politics. I have argued that neither entire system nor isolated state approaches will be helpful for understanding differences in conflict and cooperation between regions. Local variation in the regional interaction context that actors face leads to differences in opportunity and willingness that undermine both global relationships at the systemic level and direct relationships between attributes and behavior at the level of individual states. I have presented empirical evidence suggesting that such qualitatively different zones exist using standard data on international interactions and attributes. These relationships are relatively robust over time irrespective of specifications, and regional variation can be rendered as meaningful variables. In the remainder of this work, I analyze how and why such zones coevolve. In chapter 2, I introduce two principal hypotheses to explain why some regions or sets of countries evolve into zones of hostility or rivalry whereas other interaction clusters experience the emergence of forms of political community and increasing compatibility between state entities and autonomous groups below the governmental level. What I label “Deutschian” integration theory emphasizes how forms of integration between states can transform expectations of behavior and lead to the evolution of so-called security communities where violent conflict has become inconceivable as a means of resolving conflict. Such structures can facilitate peaceful cooperation and exchange between entities despite the absence of formal supranational authority. Approaches revolving around the notion of “democratic peace” suggest Page 29 →that the combinations of political authority structures in an interaction cluster hold strong implications for the interactions likely to prevail. Differences in the extent of democratic institutions in a regional context can account for the marked discrepancies between zones of peace and zones of conflict and shapes the effects of transitions and political change on conflict and cooperation. Although these hypotheses are not necessarily “new,” restating these propositions at the local level provides a new approach to these issues and allows us to address problems and lacunae in existing research. Although the two

hypotheses are not necessarily contradictory and may be related, there is no logically necessary relationship between the two theoretical traditions. Each can have different substantive implications and policy relevance for the evolution and prospects for peace and conflict in the post–Cold War era. I then integrate the initial set of hypotheses in a larger regional conflict and cooperation, integration, and political similarity nexus. Researchers frequently hypothesize that democratization may be related to prior war and peace or that integrative flows may stem from similarity in political authority structures, but so far they have not analyzed such linkages systematically. I also examine the implications of regional conflict and cooperation for the prospects for democracy and changes in domestic political institutions. Finally, chapter 7 summarizes the implications for the prospects for conflict, cooperation, and political democracy in the Post–Cold War era.

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CHAPTER 2 A Regional Approach to Conflict, Integration, and Democratization In this chapter, I seek to explain how some regional clusters in the international system develop interactions in which the use of violent conflict seems inconceivable while states in other parts of the system seem unable to escape from protracted conflict and perpetual insecurity. Figure 2.1 presents an overview of my argument. This heuristic device depicts the potential linkages between three conceptual factors. The principal explanans is variation in regional conflict and peace, indicated on the left of the figure. This can be observed in terms of both individual outbreaks of conflict and more enduring patterns of conflict and insecurity. I leave the issue of how to measure regional conflict aside until chapter 3. I first relate differences in conflict and cooperation between states to two broader factors, which I label Deutschian integration theory and democratic peace. These two theoretical components are found on the righthand side of figure 2.1. Briefly summarized, Deutschian integration theory holds that certain forms of integration can establish relations between states in which the use of force becomes inconceivable. The second holds that properties of democratic institutions can constrain the use of force. Although neither of these schools of thought can be characterized as “new” theories of international relations, my approach differs from previous research by relating them to regional conflict and cooperation. In order to understand how regional complexes evolve over time, we need to establish the ways in which Deutschian integration and democratic peace are related. I evaluate to what extent the two theories seem compatible or whether each theory yields substantive implications inadmissible under the other. Differences in regional conflict and cooperation may feed back to integration and domestic political institutions. The relationship between democratic institutions and conflict may also stem from a more general peace between similar or compatible states. I then explore the international context of democracy and democratization. Page 32 → Fig. 2.1. A regional conflict, integration, and democratization nexus Whereas most theories relate the emergence of democratic institutions to social requisites or processes within each individual state, factors and actors outside national borders may also change a state’s prospects for democracy and political transitions may diffuse among countries. Furthermore, regional conflict and peace may influence a country’s prospects for democracy. Finally, we need to separate linkages between levels of conflict, integration, and political institutions at a single point in time from the dynamics of change. Accordingly, I distinguish between the effects of stable political institutions and the dynamic effects of transitions and examine how the relationship between transitions and violent conflict is mediated by a state’s regional context.

Deutschian Integration Theory The initial work by Karl W. Deutsch on political community outlined a research program with the explicit aim of identifying “the conditions under which stable, peaceful relations among nation states are likely” (1954: 33). Deutsch and his associates (1957: 5) coined the term security communities to denote groups of countries “in which there is real assurance that the members of that community will not fight each other physically but settle their dispute in some other way.” Whereas much research on world politics adopts as a working assumption that relations Page 33 →between states are inherently conflictual, Deutsch et al. described historical examples of communities of states that do not see their interests as contradictory and display forms of compatibility that go well beyond mobilization against common enemies.

Deutsch et al. (1957) tried to clarify the minimum requirements for peaceful political community by comparing ten historical cases from Western Europe and North America. Security communities were deemed to emerge through two distinct types of integrative processes. First, political community could come about through what Deutsch (1954) labeled amalgamation or “the formal merger of two or more previously independent units into a larger unit.” Second, security communities can be achieved through pluralistic integration, wherein political centers or decision-making units retain their formal sovereignty or independence. Contrary to the claims of both world federalists and realists, Deutsch and his associates contend that overcoming anarchy does not require federation or formal supranational institutions but can be fostered through informal types of integration between states that bolster expectations about peaceful change and nondisruptive interaction. In fact, efforts to amalgamate through formal integration may in fact increase conflict and decrease the prospects for peaceful communities. Sources and Dimensions of Integration Processes Deutschian integration theory holds, rather generally, that the processes resulting in sources of integration and changing expectations between countries are located in the intensity and nature of their interactions. Transactions among agents over time and “the stream of experiences to which they give rise” will serve as formative influences (Deutsch 1954:54). Different types of interaction beget different perceptions of threats, or, conversely, compatibilities, which in turn influence expectations and future behavior. The sources of integration lie in the way interaction unfolds as well as its robustness to disruption, and the resulting integration will again feed back to shape interaction. Whereas traditional international relations theory focuses almost exclusively on states as the primary actors, Deutschian integration holds that a variety of autonomous groups mediate between individuals and the larger community. These include governmental entities and states with formal powers as well as organizations and actors with more informal methods of achieving compliance (see Deutsch 1977: 7). Sources of Page 34 →integration are often located in processes and events not commonly thought of as “political,” such as interpersonal communication and interactions transcending national borders. In this sense, Deutschian integration theory relates the prospects for peace and cooperation between states to emerging forms of transnational society. Deutsch (1954: 49–63) identified three principal dimensions of integration, labeled (a) the compatibility of autonomous groups, (b) the distribution and balance of different ranges of social interaction, and (c) the volume and dimensions of interaction within each major range. Autonomous groups are compatible to the extent that interaction is nondisruptive, and cleavages and coalitions in some settings supersede other group differences rather than reinforcing existing lines of division. Predictability bolsters expectations that future interactions will not be disruptive. The success and failure of political integration also depend on distribution and balance in transactions. Transactions across a multiplicity of ranges enhance community and integration. Transactions in one realm can support transactions in another and induce spillover effects to new areas. A relative balance in gains rather than transactions that consistently favor one party reduces conflict over distribution and enhances community. A mismatch between critical areas may undermine integration, as is illustrated by failed amalgamated communities such as the former Republic of Yugoslavia, where the central authorities held coercive powers vastly disproportionate to their integrative power. The Indeterminacy and Impasse of Integration Research Deutsch’s original work is intuitively appealing, and it is easy to find examples that resonate with the idea of integrated communities. As a theory, however, it remained relatively imprecise, and the concept of security communities has proved difficult to apply in empirical research. Deutsch explicitly suggests circular causality with references to feedback mechanisms and reinforcement over time, and there is no clear distinction between “cause” and “effect.” Integration is clearly seen as a multidimensional concept, but the specific relationships between dimensions are left unspecified, as is their relative importance. Despite Deutsch’s interest in pluralistic security communities as vehicles for peaceful relations, most of the later research on integration focuses almost exclusively Page 35 →on formal integration among states through supranational institutions such as the European

Economic Communities/European Union.1 Deutsch and his associates (1954: 59) suggested that security communities can be identified by their volume, density, and symmetry of interactions. High levels of integrative processes (relative to relations between other states) would indicate existing or emerging communities, and marked discontinuities in behavioral patterns would delineate their boundaries (see also Deutsch 1977). A wealth of empirical studies has examined transactions between states as a measure of “integration,” including economic flows such as trade or investment and measures of interpersonal communication such as the extent of mail, telephone calls, or tourism.2 Much of this work examines integration in “communities” defined on the basis of formal international organizations (10) such as the European Economic Communities/European Union. This approach, however, does not tell us whether members of such IOs cluster in a fashion distinct from relationships among other countries. Savage and Deutsch (1960) proposed an influential model for analyzing transaction flows between entities. This derives a baseline distribution based upon the marginal frequencies in contingency tables and uses these predictions to assess observed transactions. A number of subsequent studies proposed alternative models to study structure in transaction flows among states.3 Along the way, however, the initial interest in the relationship between integration and conflict or peace was largely lost in models of transaction flows. Many recent studies of international conflict explore whether “revealed integration” or high levels of transaction influence conflict and cooperation between states. One line of research examines whether trade decreases the likelihood of conflict at the margin (see, e.g., Oneal and Russett 1997; Polachek 1978, 1980, 1992; and Polachek, Chang, and Robst 1999).4 Others use observable measures of revealed affinities among states and examine how these predict conflict and cooperation. Suggested measures of compatibility include similarity in alliance portfolios (e.g., Bueno de Mesquita 1981) or United Nations (UN) General Assembly roll call votes (see Gartzke 1998b). Rarely have the dynamics of integration been approached directly, but some cues can be gleaned from work on stimulus-response models and the emergence of norms and rules in repeated interactions (e.g., Zinnes and Muncaster 1987). Repeated interaction in a social trap can Page 36 →yield spirals of hostility such as arms races. With changes in the relevant model parameters, however, repeated interaction processes can yield escalating integration that may exert an equally strong force of socialization (see, e.g., Boulding 1963, 1978; Cederman 1997; and Richardson 1938). Shubik (1970) first showed that a Prisoner’s Dilemma game repeated an unknown number of times gives rise to a new game in which mutual cooperation can be an equilibrium. Axelrod (1980a, 1980b, 1981, 1986) tested different rules in tournaments of repeated two-person games and popularized the effectiveness of “tit-for-tat” or matching responses. Empirical work has found matching or reciprocity to be characteristic of much international behavior. Hostile interactions tend to be followed by hostile responses, but cooperative initiatives generally elicit positive responses rather than exploitation.5 Ward (1981) even concluded that reciprocity constitutes a “golden rule of international politics.” More recently. so-called constructivist approaches stress how intersubjective “meaning” or “identity” can facilitate the emergence of security communities among states (e.g., Adler and Barnett 1998). This line of research emphasizes the generative interplay between actors and the structure of interaction. In this perspective, system transformations are possible through changes in actors’ intersubjective structure, such as identities, conventions, rules, and norms (e.g., Dessler 1989; Wendt 1987, 1992). Although newer constructivist work on regional identities raises ideas reminiscent of Deutsch, it differs markedly in insisting that constitutive relationships between agency and structural context require an interpretive approach (e.g., Hollis and Smith 1990). I will demonstrate in this book that an appreciation of socialization and changes in world politics does not require the rejection of social scientific methodology (see also Cederman 1997; Friedman and Starr 1997; and Østerud 1996). To recap, most research on Deutschian integration has remained at a conceptual level and has rarely been applied to empirical research. Empirical studies of integration have tended to focus on international organization and largely neglected Deutsch’s initial focus on informal integration and its relationship with regional conflict and cooperation. These gaps and discrepancies stem in part from the lack of analytical tools with which to consider linkages between regional transactions, affinity, and conflict. I will show in chapter 3 how spatial statistics can

help us analyze regional zones of conflict and peace. If Deutschian integration underlies the emergence of zones of peace, regional conflict Page 37 →should be negatively associated with a regional context of more extensive economic linkages and cooperative transactions across state borders. I examine these linkages empirically in chapter 5.

Polities, Conflict, and Peace The second concept in figure 2.1 emphasizes variation in political institutions. Regional differences in conflict and peace may also stem from differences in the attributes of individual states and their composition among states in regions. Traditional approaches to international relations theory insist that systemic constraints leave little room for more than marginal influences from state attributes on international behavior. By implication, there is no reason to expect that differences in political structures and institutions should exert any impact on relations between states. Even scholars not adhering to the realist tradition generally regarded domestic institutional factors such as political regime type or economic system as largely irrelevant to international behavior. The similarities in the behavior of the superpowers during the Cold War, irrespective of their domestic differences, bolstered beliefs in the seeming irrelevance of domestic attributes to international behavior. In a remarkable turnaround, international conflict research since the beginning of the 1990s has to a large extent revolved around the international consequences of domestic attributes. The so-called democratic peace – or the finding that no two democracies appear to have gone to war with each other – is now probably the best-known stylized empirical fact in international relations. The democratic peace is not usually thought of as an explanation for differences between regional clusters, but I will show how linkages between democratic political institutions and conflict can be restated at a regional level and how such a regional focus can help us to better understand the substantive meaning of the democratic peace. Origins of the Democratic Peace The origins of the democratic peace finding are relatively obscure.6 An early empirical study by Babst (1964, 1972) found that no wars appeared to have been fought between two countries with “electoral governments” and put forward some probabilistic calculations indicating that Page 38 →this outcome was unlikely to have arisen by chance. Since Babst did not publish in journals read by international relations scholars, his work remained unknown to this community until Small and Singer (1976) sought to refute it by pointing out that the set of participants in wars in the nineteenth and twentieth centuries included about as many democratic states as nondemocracies. This critique is largely irrelevant to Babst’s proposition. Little, if anything, can be said about the propensity for war among political institutions without some consideration of the relative shares of democracies and nondemocracies in the international system. Within the field of international conflict studies, the relationship between political structures and violent conflict was first examined empirically in studies of linkages between domestic and international conflict. An influential initial study by Rummel (1963) suggested that these two types of conflict were largely independent and unrelated. Wilkenfeld (1968), however, demonstrated significant relationships between domestic and external conflicts once the total sample had been partitioned by different regime types. This study is rarely considered to be a forefather of the democratic peace – the partition of regime types employed now seems somewhat arcane and the effects of regime type were a secondary concern – but it was in many ways the first to demonstrate that foreign policy behavior varied systematically across political regime types. Rummel (1976) examined the relationship between social system and political structures and the overall propensity for conflict through factor analysis. He later (1983,1984,1985) put forward a theory on libertarianism and conflict that spurred a new wave of research on linkages between domestic political structures and conflict. Rummel’s central thesis is that there exists a freedom dimension that is inversely related to conflict within and between nations. The broad and sweeping nature of Rummel’s theory elicited immediate criticism (e.g., Chan 1984; Vincent 1987; Weede 1984), and is often rejected on the basis that democracies do not appear less likely to fight wars than other types of political systems are. However, the dyadic version of Rummel’s proposition – that

freer countries are less likely to wage war on each other – turned out to be considerably harder to refute (e.g., Maoz and Abdolali 1989; Maoz and Russett 1992). It is this empirical relationship of an absence of war between pairs of democratic states that has become known as the democratic peace, which has been characterized by Levy (1989a) as the closest thing to an “empirical law” in international relations. Page 39 → Democratic Peace: A Finding in Search of Theoretical Foundations The empirical finding itself largely motivated the initial research on democracy and peace. Whereas Rummel hypothesized general linkages between freedom and conflict, subsequent scholars have tried to devise explanations for the dyadic finding. Maoz and Russett (1993) distinguished between so-called normative and structural explanations. Normative explanations hold that something about democracy induces certain values or preferences for peaceful conflict resolution. Some argue that democracies externalize internal norms of peaceful conflict resolution in interactions with other democracies (e.g., Russett 1993). Others hold that democracies are more likely to rely on third-party mediation or arbitration in disputes with other democracies (e.g., Dixon 1994, 1996; Raymond 1994). Structural explanations posit that properties of democratic institutions make a resort to force or escalation to violent conflict less likely. The most relevant features constraining the use of force are leaders’ need for popular approval and the informational content of institutions. Democracy is a form of governance in which the public formally delegates authority over political decisions to various institutions, with an executive government handling most day-to-day decisions. The public can sanction officials by revoking power, and governments in democracies can potentially lose power in open elections. These domestic bases imply that leaders in democracies must play a “two-level” game when dealing with other states, as the range of feasible solutions in international bargaining is shaped by what is politically acceptable on the domestic scene (e.g., Putnam 1988). Given certain conditions, domestic audiences can constrain leaders in democracies from the use of force in situations in which a nonconstrained leader could have resorted to force. Differences in the use of force are sometimes traced to variations in the costs of conflict for leaders in democracies and other political systems. Some argue that domestic audiences in democracies punish leaders for backing down in international crises (e.g., Fearon 1995). Others point out that foreign policy failures put leaders in democracies at greater risk than autocratic rulers of being replaced (e.g., Bueno de Mesquita and Siverson 1995; Bueno de Mesquita, Siverson, and Woller 1992).7 Greater sensitivity to political risk makes leaders in democracies less likely to use force than leaders in autocratic systems. Page 40 →Bueno de Mesquita et al. (1999) posit that the size of winning coalitions in different polities induces differences in the supply of policy. Whereas winning coalitions tend to be restricted in many nondemocracies — either because the set of actors with potential influence is very small (e.g., limited to small nobility) or because the resources needed to achieve political power are unevenly distributed — competitive democracy requires large winning coalitions. Under small winning coalitions, pivotal individuals can easily be paid off with private goods. When the winning coalitions are large, however, it is no longer feasible to maintain power by allocating private goods. Whereas autocrats can compensate for foreign policy failures with private goods, leaders in democracies need to be more cautious and must pay greater attention to collective goods. Institutions also differ in their informational content. Since political processes in democratic institutions are more transparent than in nondemocratic regimes, their domestic constraints and international behavior are generally more predictable as well. It is easy to recognize democracies as “doves” despite potentially “hawkish” rhetoric. The risk of unnecessary escalation therefore decreases (e.g., Bueno de Mesquita and Lalman 1992; Kydd 1997; Siegel 1998). Schelling (1960) conjectured that leaders could commit themselves to bargaining positions by transferring veto power to other agents. Fearon (1995) argued that domestic audiences in a democracy exert such a veto in international crises. Because other states recognize that democracies find it difficult to back down from their positions, opponents facing democracies are less likely to act in ways that might spur escalation. Thus,

regime type itself may serve as an effective signal to other states about a country’s resolve (e.g., Fearon 1995; Schultz 1999). These explanations point to important differences between democracies and other kinds of polities. It is more dubious, however, whether these properties alone are sufficient to derive differences in international behavior. All of these explanations presume that there exists conflict between the preferences of leaders and the domestic public on the use of force. Unless leaders differ systematically between polities, differences between regimes must stem from leaders in democracies acting in ways they would not have in less constrained polities.8 Democratic institutions may induce executives to internalize popular majority preferences, but the rationale for differences between polities hinges critically on public opinion being consistently more pacific than rulers’ unrestricted Page 41 →preferences. Structuralist explanations are in this sense indeterminate without assumptions about preferences. A democratic polity may constrain the use of force only given some form of popular pacifism. Upon closer scrutiny, most structuralist explanations do in fact implicitly or directly assume popular pacifism. Bueno de Mesquita and Lalman (1992: 45), for example, assert that “the very need to resort to force suggests a failure of diplomacy, a political failure of the national leadership, and it opens opportunities for opposition factions.” This is not necessarily an unreasonable assumption. Since it is almost never explicitly justified, however, we know little about whether it is true. The essentially dyadic character of research on the democratic peace raises several problems. The theoretical reasons for focusing on dyads or pairs of states are not particularly strong. Although many useful models of conflict are dyadic, it is questionable whether violent conflict in and of itself is a dyadic phenomenon. Even in bilateral disputes, the processes and crises that may lead to wars and their absence can involve interactions inside and beyond each pair of sovereign states. Data on international conflict are usually not coded on a dyadic basis, and the criteria for constructing dyads from the existing data are unclear. The appropriate level of analysis is not some inherent feature of conflict but follows from the proposition to be examined. In the case of the democratic peace, neither political democracy nor its principal properties hypothesized to prevent conflict — that is, norms and institutional constraints — are dyadic. Many of the common explanations are “posteriors” that have been put forward in order to explain a known dyadic regularity rather than “priors” or implications deduced from a larger theory of authority structures and conflict. In this sense, it is not surprising that a particular explanation is consistent with the absence of war between democracies. However, most explanations are hard-pressed to explain why one should see democracies behaving differently only in interactions with other democracies. Much of the writing on additional implications of the democratic peace has revolved around whether phenomena such as a lack of monadic effects of democracy or a relationship between democratization and conflict undermine the validity of the dyadic democratic peace. As a result, this literature sometimes resembles a battle over the virtues of the democratic peace.9 In the absence of a broader theory outlining the ways in which democracy influences international behavior, it is difficult to determine whether extensions and findings on other levels of analysis Page 42 →and phenomena other than war are consistent with or pose problems for existing explanations. There has been little progress on reconciling what the evidence at different levels of analysis should look like under a reasonable general theory linking polities to conflict and peace.10 In this sense, the dyadic democratic peace can be characterized as a strong empirical finding lacking a clear theory. At this point, it seems misguided to question whether the empirical finding is true. Although critics have pointed to alleged anomalies, these are relatively few and are typically related to questionable definitions of democracy and dyadic wars.11 More methodologically sophisticated analyses that address pathologies in previous work tend to conclude that the finding remains quite robust,12 and it is unlikely that new methods or revised data will fundamentally overturn the finding that “dyadic democracy correlates with dyadic peace.” A more relevant line of criticism is that this empirical finding can be subsumed under alternative explanations that render democracy in and of itself of little importance. I will return to the question of whether Deutschian integration or linkages from conflict to democracy may underlie the democratic peace later in this chapter.

Conflict as Belligerence Versus Local Security Researchers are rarely explicit about what sort of conflictual events domestic institutions are hypothesized to constrain. This is in part a question about the magnitude of the appropriate events: does the relationship between political institutions and conflict pertain to major armed conflict such as wars only or should it hold for any type of conflict?13 More fundamentally, “conflict” is often taken as a self-evident concept, and empirical research seldom discusses what various measures of involvement, initiation, or escalation are supposed to indicate. Researchers have largely ignored a fundamental conceptual distinction between general conflict participation and exposure or threats to security. Conflict involvement might be a relevant measure of a country’s aggressiveness, belligerence, or willingness to use force, but it is not necessarily indicative of a threat to a state’s security. As we will see in the next section, the relationship between conflict and authority structures can look quite different depending on which aspect we emphasize. The failure to clarify what is meant by conflict has particularly severe consequences at the monadic level of analysis. Consider, for example, a country, X, that participates in many UN operations that Page 43 →take place in various locations far from its own territory. This could lead to many observed disputes involving a large number of countries in common data sources. Measured by counts of disputes, this country might seem to be quite conflict prone. Although these observations may be “correct” according to a data set’s criteria, they may not correspond to the characteristics that we usually have in mind when we talk about conflict. Many contributions to the democratic peace debate clearly assess whether democracies are more or less belligerent than other regimes (e.g., Galtung 1995; Ray 1995). The notion that democracies are less belligerent by nature fits well with common normative preconceptions, but it is also an easy target for critics. It is undeniable that democracies have participated extensively in violent conflict. Many researchers point to examples in which democracies have acted aggressively against vastly inferior states in faraway locations or supported aggression indirectly through client states, insurgencies, or covert actions (e.g., Forsythe 1992; James and Mitchell 1995; Wolfson 1995). Democratic states include major powers that define their interests on a global scale and former colonial powers that have maintained extensive involvements in former colonies. Both critics who reject linkages between democracy and conflict from such examples and adherents who reject their theoretical relevance by reverting to dyadic propositions ignore substantively important, distinctive characteristics of many of the conflicts in which democracies are involved. Much democratic “belligerence” differs from the standard model of conflict between two relatively equal parties, A and B, where each constitutes a plausible threat to the security of the other. Some democracies may go to great lengths to exert influence in other areas of the world, but this use of force does not necessarily imply that these conflicts constitute threats to their vital security. Consider the case of the Vietnam War. U.S. involvement undoubtedly constituted a severe threat to the vital security of the states in the region. However, the conflict involved no acts of warfare on U.S. territory or any threat to the territorial integrity of the United States, nor was there much risk of diffusion and local expansion elsewhere in North America. Many of the examples of belligerent democracies tend to be cases in which democracies engage in conflict outside their immediate regional contexts. In fact, it is in many ways difficult to find clear-cut examples in which weak democracies are threatened by powerful and belligerent nondemocracies.14 Page 44 → A Regional Interpretation of Democracy, Security, and Peace Rather than looking at all cases of conflict participation and debating whether democracies are less belligerent than other states, we can obtain a more informative measure of threats to security by looking at cases in which states experience conflict on their own territories or in their immediate neighborhoods. This will also help us to make sense of the alleged monadic-dyad conundrum or to reconcile the stylized fact that democracies do not fight each other yet fight no less than other states. Much of the conflict waged by democracies in locations far from their core territories or regional contexts is pertinent to assessing belligerence, but it does not necessarily reflect threats to their vital security.

We saw in chapter 1 that both political authority structures and conflict tend to cluster geographically. Since democracies are generally clustered or close to other democracies, the more interesting implication of the peace between pairs of (proximate) democracies is that many democracies appear to face fewer immediate threats to their vital security. The bulk of the evidence for a democratic peace at the pairwise or dyadic level is taken from countries located in broader zones of democracy. Similarly, many of the mixed dyads exhibiting conflict are taken from the boundaries or regions of discontinuities between zones of democracies and autocracies. By considering these as a series of independent pairs, we may get nice correlations between “joint democracy” and “dyadic peace.” However, in the process we lose track of the regional context in which these dyads are situated. We can surmise from the stylized empirical facts that something about widespread democracy enables states to reduce the element of rivalry in their security. Following the logic of institutional explanations, we can hypothesize that political institutions with greater executive constraints make it easier for parties to predict political outcomes and responses in neighboring states. This does not mean that states never have conflicting goals or resort to coercion. However, transparency enables states to reduce uncertainty and signal what actions and outcomes are within the realm of feasibility. As a result, states have common knowledge of when and to what extent disputes are “unlikely” to escalate to conflict. Over time, such dynamics can become self-enforcing and give way to a stable peace within larger zones of democracies. As suggested by Russett (1993: 137–38), changes in the attributes of individual actors Page 45 →can change the overall structure of their interactions. As most interactions are local, we should look for such changes in a regional rather than an aggregate global system. I will show later that the regional composition of institutions covaries with the propensity for regional conflict and cooperation.15 Whether a single country is democratic in isolation may not be sufficient to ensure differences in security and the likelihood of conflict. But variation in conflict and peace is not inherently dyadic. Consider, as an example, Norway and Zambia. Both states may be democracies at some given point of time,16 but a prediction that this dyad is unlikely to experience conflict will probably be correct regardless of regime type given the great distance separating the two. This does not mean that whether an individual country is democratic cannot have any pacifying effects. In a situation in which its neighbors are relatively democratic, the regime type of Zambia might have considerable impact on the prospects for peace in the region. Focusing more specifically on regional conflicts that constitute threats to vital security can enable us to see where and when we can expect democracy to make a difference. Distance, Preferences, and Peace If institutions constrain the use of force within zones of democracy, why are democracies less constrained from engaging in such forms of conflict in faraway countries? As we have seen, formal properties of democratic institutions allow restraining influences on the use of force, but it makes little sense to examine institutions in the absence of preferences. Preferences may vary considerably between foreign policy issues, and democratic institutions are unlikely to constrain the use of force unless there is some active interest in the issue at hand. Institutional explanations hinge critically on preferences, yet one cannot derive these preferences directly from institutions. Rather, there must be something about the distribution of preferences aggregated through institutions that constrains conflict between democracies in zones of peace but does not necessarily inhibit conflict participation elsewhere in the system. Electoral processes can — within certain limits — enhance the “efficiency” of democratic institutions, as judged by the agreement between collective outcomes and the distribution of preferences among individual voters (see, e.g., Mueller 1989a). However, democratic outcomes Page 46 →are only likely to be peaceful when the median voter displays preferences for peaceful resolution of “avoidable” conflicts. Closer attention to the linkages among distance, integration, and preferences, as implied by Deutschian integration theory, provides some answers to the question of why we see clear geographical limits to the constraints on the use of force in democratic institutions. The role of domestic audiences in constraining the use of force hinges on available information and the share of attentive voters. Foreign policy issues vary considerably in salience, and we should expect to see variation in the

relevant “domestic audiences” with some interest in the topic at hand. Voters generally display little interest in foreign policy issues, even when issues such as war and peace can be as salient as important domestic ones (e.g., Aldrich, Sullivan, and Borgida 1989; Almond 1960). Votes are not the only valuable resources for sustaining political power, as leaders may derive benefits from catering to special interest groups. The availability and costs of information to voters shape whether the representation of interests in democratic institutions resembles a perfectly representative “civics class” or a “legislative capture” dominated by interest groups (e.g., Denzau and Munger 1986). When voters are perfectly informed, advertising can have no effect and legislators will maximize votes and internalize the preferences of the electorate (see also Wittman 1989). In contrast, when voters are less than perfectly informed and partly susceptible to advertising, legislators can derive resources from catering to special interest groups that can then be devoted to remaining in office. Democracies may be less sensitive to the rent-seeking efforts of special interest groups (e.g., Lake 1992), but they are not immune to the influence of special interest groups in foreign policy decision making when salience is low (see, e.g., Hobson 1938; and Kaempfer and Lowenberg 1988). Political salience is high when countries experience severe conflict or perceive high risks. Since information about and the perceived salience of foreign policy issues to domestic audiences are a function of the density or web of relations between actors, there is a geographical limit to the constraining effects of democratic institutions on the use of force. Issue salience is highly associated with spatial aspects since the density of social interactions tends to decay with distance. People have stronger preferences for peaceful resolution of conflict within a country’s Page 47 →regional context or when war and peace involve plausible threats to security. Democratic institutions may then internalize these preferences to a greater extent than do systems that are less sensitive to public opinion. However, widespread preferences against the use of force require some degree of familiarity and empathy with the other party. Distance correlates systematically with the salience that actors associate with other parties and can thus suggest limits to constraining effects on the resort to force. When information is low, states with the power to exert force and influence in faraway locations may cater to smaller groups and particular interests that are not necessarily less belligerent. Democracies that possess capabilities to wage war in faraway locations, where the locus of fighting is removed from their regional contexts, are likely to face less restraint. Conflicts with actors in faraway locations do not become politically salient at the domestic level provided that the costs of war remain moderate. This may account in part for the fact that democracies can display considerable belligerence in dealing with colonies and states in the developing world but often face difficulties when the cost of conflict becomes more obvious. Survey data on U.S. attitudes regarding the Vietnam War, for example, displayed a clear relationship between the number of casualties and opposition to the war (e.g., Gartner and Segura 1998).17 Foreign policy success is measured in the number of casualties in many contemporary democracies. The Gulf War was considered to have been successful insofar as casualties remained low. A total of fifteen casualties forced the U.S. withdrawal from Somalia (Mueller 2000).

Deutsch, Democracy, and Peace In this section, I examine the relationship between the Deutschian theory of integration and the theory of democratic zones of peace as sources of regional differences in conflict and peace. I evaluate to what extent the two are compatible and to what extent one would yield substantively different implications deemed inadmissible under the other theory. There are many similarities between the Deutschian theory of integration and the theory of democratic zones of peace. Both posit that the Page 48 →variation in state attributes and regional relations will condition the prospects for regional conflict and peace. Finally, both hold that such qualitative differences in relations among states can be observed over space and time and that change is possible in world politics. Despite these shared features, the two research traditions have evolved largely independently of one another. As the two perspectives rarely have been explicitly contrasted and compared, the relationship between them has remained unclear. Deutsch et al. (1957) did not explicitly address whether security communities would be limited

to democracies, although all their cases were zones of peace between liberal democracies. Two questions are keys to determining the relationship between Deutschian integration and democratic constraints as explanations of regional conflict and peace. (1) Are democracy and integration mutually supportive forces that characterize no-war communities or does one render the other superfluous? In other words, does a Deutschian peace underlie the democratic peace or does Deutschian integration stem from democracy? (2) If compatibility arises from institutional similarity, can no-war communities emerge between similar states that are not liberal democracies? Three main perspectives on Deutsch, democracy, and peace answer these questions in different ways. 1. Virtuous Cycles of Democracy, Integration, and Peace Many conclude that security communities develop only within clusters of liberal democracies. The absence of war between democracies is often seen as evidence that liberal democracies form a pluralistic security community (e.g., Russett 1998; Starr 1997). Democracies that can transcend security dilemmas in their interactions are also better able to take advantage of gains from trade despite an anarchic international system. In this perspective, Deutschian integration among states and peace between democracies are seen as interrelated and complimentary. Oneal and Russett (1999) suggest that Deutschian flows and interdependence may constitute good observable indicators of affinity but that it is democracy that permits open markets and such stable affinities between states to emerge. Accordingly, we should observe both democracy and integration influencing regional conflict and cooperation as well as seeing synergy effects between the two. Page 49 → 2. Deutschian Integration Underlies the Democratic Peace Many scholars who are skeptical about the merits of the democratic peace accept that democracy, integration, and affinity are interrelated. However, in their view the relationship between democracy and peace is merely a manifestation of a more general form of peace through shared interests between compatible states (e.g., Farber and Gowa 1995; Gartzke 1998b; Mueller 1989b; Polachek 1997; Rosecrance 1986). A combination of Deutschian integrative processes and affinity remains a plausible candidate for the commonly invoked “hidden variable” underlying the observed absence of war that renders democracy spurious. Various efforts have tested whether the association between democracy and peace stems from factors such as higher levels of trade, wealth, joint alliances, and shared interests associated with both democracy and an absence of conflict. Even though most dyadic studies have concluded that these factors either do not appear to be strongly associated with conflict involvement or do not render linkages from democracy insignificant (e.g., Beck and Tucker 1996; Maoz and Russett 1992; Raknerud and Hegre 1997), they have not considered the regional context of broader zones of peace or the actual location where conflict takes place. If democracies tend to cluster and Deutschian integration emerges among countries with widespread integrative relations, the dyadic democratic peace finding may stem from the spatial clustering of both democracy and Deutschian integration. The problem of spatial dependence raises questions about whether two adjacent democracies would be unlikely to clash under low integration, negligible interdependence, and a history of hostility. Until recently, we might have been unlikely to observe such dyads. This is not necessarily the case in the Post–Cold War era, however, given the large number of recently democratic states that have surfaced in the aftermath of the third wave. This perspective holds that when we take regional integration into account democracy in and of itself will have little explanatory value. 3. Similarity, Integration, and Peace A second critical point is whether Deutschian regional zones of peace are necessarily limited to clusters of democracies. Deutsch (1954) used Page 50 →the label “pluralist security communities” to refer to societal pluralism in terms of the number of agents in integration processes and the absence of a single supranational

organizing body rather than political pluralism per se. Pluralism and compatibility may conceivably exist at the intergovernmental level without much internal political pluralism or popular participation. Although the historical case studies of successful security communities in the Deutsch et al. study (1957) were limited to clusters of pluralistic democracies within Western Europe and North America, one can imagine compatibility or zones of peace emerging between politically similar nondemocratic polities. The notion that the democratic peace stems from affinity or similarity in political orientation suggests that similar regimes other than democracies may display comparable forms of peaceful relations (e.g., Cohen 1995; Farber and Gowa 1995). Examples of independent regional communities of states that display certain similarities and affinities but are not democracies include nationalist (pan-) African and Arab states as well as socialist societies. Some argue that clusters of states such as the Association of South East Asian Nations (ASEAN) countries, the Southern Cone, and even West Africa display evidence of emerging zones of peace among states that are not liberal democracies (e.g., Adler and Barnett 1998; Kacowicz 1998; Kivimaki 2001). This perspective can claim additional support from the finding that “jointly autocratic dyads,” although they are more conflict prone than “jointly democratic dyads,” have a lower likelihood of war than “mixed” dyads do. This peace between autocracies does follow from any of the proposed theories of the democratic peace (e.g., Bremer 1996). In chapter 5, I address whether regional political similarities can account for differences in conflict and cooperation and evaluate some of the proposed new peaceful security communities that have emerged in the Post–Cold War era. The Diffusion of Democracy and Autocracy I believe we are on an irreversible trend toward more freedom and democracy — but that could change. (attributed to Dan Quayle, 22 May 1989, Esquire, August 1992) Most studies relating conflict and peace to domestic political institutions examine the international consequences of democracy when it is in Page 51 →place, but they take the distribution of political institutions as given. This implicitly assumes (1) that the distribution and changes in political structures result from purely domestic processes or “social requisites,” and (2) that the distribution of political institutions is not influenced by the distribution of conflict and peace. In this section, I show that both of these assumptions may prevent us from understanding the substantive linkages between zones of conflict and zones of democracy and how they evolve. Research on democratization differs greatly with regard to which actors, processes, and attributes are considered to be key factors. Many scholars emphasize a society’s level of development, wealth, or disposable income as the primary determinants of the prospects for democracy (e.g., Burkhart and Lewis-Beck 1994; Jackman 1973; Lipset 1960, 1994; Lipset, Seong, and Torres 1993; Londregan and Poole 1996). Some emphasize that culture or certain types of norms or values are favorable to the emergence and sustainability of democratic rule (e.g., Almond and Verba 1963; Bollen and Jackman 1985a; Muller and Selligson 1994; Putnam 1993). Distributional aspects such as inequality or the strength of different social groups or classes are accorded pride of place by others (e.g., Muller 1988, 1995; Przeworski 1991; Vanhanen 1990). Others relate democratization to the timing of national development, pacts between elites, events at “critical junctures,” or other forms of path dependence in political development (e.g., Bollen 1979; Moore 1973; O’Donnell, Schmitter, and Whitehead 1986; Rueschemeyer, Stephens, and Stephens 1992). These explanations vary considerably, and each suggests quite different implications for cross-national variation in authority structures. Yet these schools are in one sense all similar in that they put forward explanations that relate a country’s prospects for democracy to various domestic economic, societal, and political factors. In chapter 1, we saw that neither political authority structures nor transitions seem to be geographically random. I argue that the distribution of democracy itself reflects the influences of international processes and interactions among states. I will show that approaches that ignore the international context of interdependence among countries discard central aspects of the process of democratization. Moreover, I will show that treating democracy as a country attribute detached from the regional context ignores substantively important influences of democratization on the prospects for conflict and peace. Page 52 →

Democracy over Time Although most work on democratization assumes constant causal relationships with social requisites, the global distribution of democracy within the international system varies considerably over time, as is shown in figure 2.2.18 Since the domestic conditions typically assigned causal importance for democracy tend to change relatively slowly over time, it seems questionable whether the variation in figure 2.2 can be attributed to these factors alone or whether the relationship between democracy and domestic social requisites is structurally stable over time.19 The recent third wave of democratization (e.g., Huntington 1991) has increased researchers’ attention to the ways in which trends in democratization may reflect external determinants in a changing environment rather than similar processes operating in a parallel fashion within each state (see also Starr 1991). In a remarkable change of emphasis, Whitehead (1996) claims that of all the democracies in existence at the beginning of the 1990s only in Sweden, Switzerland, and the United Kingdom did political democracy evolve independently of international events. Although recent work has focused almost exclusively on the contemporary diffusion of democracy, figure 2.2 clearly indicates that changes at the global level have not been consistently toward more democracy. The breakdown of fragile democracies in the interwar period and immediately following the process of decolonization suggests that it was autocracy rather than democracy that diffused during parts of the twentieth century (e.g., O’Loughlin et al. 1998). Ghana can be seen as prototypical with respect to the development of postcolonial societies. After a relatively democratic constitution was adopted at the time of independence in 1958, President Nkrumah became increasingly dictatorial and severely limited political opposition. A one-party system was introduced in 1964, and this idea of governance was quickly adopted by many other African states. Merely attributing democratization or autocratization to some form of “international context,” however, explains little without some reference to the relevant context or how some hypothesized mechanisms that influence the emergence of democracy play out within the international context. Some look to the global level itself for such differences in external context. Many emphasize changes in the relative status of different political ideologies over time (e.g., Fukuyama 1992). Various Marxist and “world system” theorists attribute the recent wave of democratization to the changing nature of hegemony over time. In particular, the position of the United States with respect to democracy is sometimes seen as critical (e.g., Robinson 1996). These studies rarely provide explicit hypotheses as to why the nature of hegemony or ideological balance should change in such a way as to favor democracy over time. As such, they essentially assert that whatever changes occur are due to the changing nature of the system – thereby assuming what is to be proven. Page 53 → Fig.2.2 The global distribution of democracy, 1800–1996 Global-level influences on democracy are often presented in a fashion so general as to render systematic empirical tests difficult. In one of the few empirical studies of global-level influences, Ray (1995) seeks to evaluate the extent of total variance in political transitions to democracy that can be attributed to system-level and national attributes respectively. His analysis indicates that the global share seems to be relatively modest, and Ray posits that global influences on democracy may have been overstated. These largely negative findings may be due to the all encompassing nature of the notion of global context invoked. Assuming that everything is related to everything else makes empirical analysis nearly intractable, and universal global influences might be as grossly inaccurate as Page 54 →assuming that fully identical processes operate within each country in isolation. The idea of global context, furthermore, implicitly assumes that the external influences on political authority structures are similar or consistent across all countries at any given point of time. Chapter 1 demonstrated a strong geographical clustering in political institutions and changes over a ten-year period. I argue that the regional context is where we should look for external influences of democratization. Diffusion at the local level can yield dramatically different implications for two otherwise similar states, depending upon the composition of states and political institutions in their regional context.

Toward a Theory of Diffusion In many ways, it is easier to demonstrate local diffusion of authority structures than to account for what factors underlie such phenomena. Much of the recent literature on democratization argues that democracy emerges as an outcome of enduring social conflict at the point where no single actor possesses sufficient resources to impose itself on other groups (e.g., Olson 1993; Przeworski 1988; Vanhanen 1990). Institutionalizing methods for sharing power and establishing political and civil rights becomes a rational option when social actors are unable or unlikely to see their unrestricted preferences prevail. There is no inherent reason why such struggles over influence and resources should “stop at the water’s edge” or be fully confined within the boundaries of individual countries. The balance of power resources between groups may be altered decisively by outside events as well as by strategic coalitions and assistance from actors outside state boundaries. State actors will often take an active interest in events occurring in neighboring countries and may supply important resources to actors that affect political outcomes at the margin. In addition, a number of nongovernmental social and political networks are clearly transnational in nature and operate across national borders. Some contemporary examples include ethnic groups such as the Irish and the Kurds and the revolutionary varieties of Islam. History exhibits several examples of international networks and substate actors that actively attempted to change the course of events in other countries (e.g., Deutsch 1954; Randle 1991). The effects of such coalitions on authority structures are likely to be most dramatic when there are shifts in the coalitions that hold power in proximate entities, as these augur great changes in the balance of Page 55 →resources or means of influence that actors can mobilize. Tipping models show how small changes in external context can yield cascades of individual changes and generate a critical mass in political contestation (e.g., Kuran 1989, 1991; Lohmann 1994; Schelling 1971). Such processes are often held to have played out in Eastern Europe in the early 1990s, where the initial political changes in Poland and Hungary altered the relative influence of actors and constraints on feasible actions in other states, thereby spurning the later changes in Czechoslovakia and East Germany. As will be discussed in greater detail later, the diffusion of conflict and insecurity within regions might severely constrain a country’s prospects for democratic rule. The recent process of regime change in Central Africa indicates that diffusion processes have induced outcomes other than democracy. Many hold that Ugandan support was critical in the Tutsi-dominated Patriotic Front (RPF) takeover in Rwanda. This had an impact on the armed uprising that led to the fall of Mobutu and the coming of power of Kabila in the neighboring state then known as Zaire (see McNulty 1999). Many such locally interdependent regime or leadership changes, however, would not necessarily show up in the properties of countries’ authority structures as measured by the degree of democracy. Democratization and the Diffusion of Conflict and Peace Treating democratization as exogenous is unsatisfactory on a different level as well, since conflict and threats in the regional context may influence the prospects for democracy. This makes it problematic to treat changes in democracy and democratization as predetermined when examining the implications for conflict and peace. Researchers who suggest that the prospects for democracy may in part be related to peace itself disagree on whether such linkages provide forms of positive feedback or a reverse causal relationship between peace and democracy. According to the former view, the linkages from peace to democracy are seen as reinforcing the democratic or broader liberal peace proposition. Some researchers suggest that there exist various feedback mechanisms between peace and democracy wherein democracy first makes peace more likely and peace enhances the prospects for democracy (see Russett 1998). Under the latter view, the notion of democracy as a path to peace Page 56 →confuses the direction of causality as well as the substantive implications of the association between the two (see Thompson 1996). Many assert that peace is a prerequisite for preserving democracy as a self-evident proposition. Critics of the democratic peace often argue that democracy is likely to break down under the threat of war (e.g., Layne 1994). Others hold that efforts to wage war may induce at least temporary restrictions on political rights and civil liberties in democracies

(e.g., Gates, Knutsen, and Moses 1996). Numerous cases in which stability and the lack of belligerence go together with autocratic rule show that peace alone certainly cannot be sufficient for democracy. Nor can peace or the lack of conflict involvement be strictly necessary for democratization since many democracies have participated in interstate wars or sustained internal conflict and yet remained democracies. In many cases, such as those of Greece and Argentina, democratization appears to have followed wars that discredited the old regime. The three waves of democratization appear to have followed in the aftermath of the two world wars and the latent Cold War. Although a few seemingly contrary cases of course do not exclude all potential effects of peace on democratization, these examples clearly show that general assertions that democracy is inconceivable under conflict are not evidently correct and that such hypotheses require emendation before they can be subjected to meaningful empirical tests. Thompson (1996) has put forward a historical perspective on democratization through war making and state making. He holds that rulers’ need to mobilize for military efforts strongly shape the political systems that eventually emerge historically. Sustained perpetual rivalry and threats to vital security foster authoritarianism as power becomes more centralized. A situation of relative regional peace, in contrast, may facilitate the initial emergence of political pluralism, as internal political processes could unfold within some degree of insulation from external demands or shocks. Thompson argues that contemporary and historical “zones of peace” emerged when dominant states eventually were forced to abandon ambitions of regional hegemony. This reduction in regional threat was an important prerequisite for the emergence of democratic political systems. From this perspective, it is less surprising that “peace” or the absence of dyadic war correlates with attributes such as the extent of political democracy or interstate trade, since a condition of regional peace may have been a prerequisite for these phenomena to emerge in the first place. Although the end of the Cold War implied a reduced Page 57 →threat of violence and external intervention for many states in Eastern Europe, persisting hostilities continue to make democratization more difficult in other regional contexts. Barzel and Kiser (1997) hold that the security of rule is essential for the possibility of contracting between rulers and the ruled. The less secure a ruler the lower the potential level of cooperative contracting and the lower the rate of development of voting institutions. In addition to lower internal threats, they argue that geographical isolation and protection from external threat may in part explain why voting institutions were more developed and durable in England than in France. Although these linkages are quite different from those of Thompson (1996), they imply similar observable implications for linkages between regional peace and democracy. Such propositions linking war to democracy have rarely been empirically tested in any systematic manner beyond casual references to historical cases. Some studies have examined whether war involvement exerts some effect on the prospects for democracy at the margin (e.g., McLaughlin 1996; Mousseau and Shi 1999). These indicate that conflict involvement generally does not seem to decrease the extent of democracy, but they also reveal some of the weaknesses in many studies linking conflict to democracy. Researchers typically examine whether participation in conflict is associated with democratization and autocratization and tacitly assume that all incidents of conflict and “peace” as the absence of war are qualitatively equivalent. Existing efforts fail to distinguish between general conflict involvement and local threats to vital security. An overall measure of conflict involvement includes participation in UN peacekeeping forces or in remote colonial wars even though there is no particular reason why such conflicts should lead to a breakdown of democracy in developed societies. The relevant variable is the security threat in a country’s regional interaction environment. A relationship between conflict and the evolution of democracy may not manifest itself immediately following outbreaks of war only, but it may hinge upon more enduring forms of insecurity and latent threats that do not necessarily lead to open warfare all the time. As such, we should look not only at the incidence of conflict that results in war but at the amount of hostile interaction that takes place within a country’s regional context. It is the perceived insecurity through the risk of recurrent conflict or diffusion that can affect a country’s long-term prospects for democracy, and greater attention to an enduring interaction context Page 58 →over time and space helps strengthening the foundations of peace-to-democracy propositions. Understanding the constraints on initial democratization is critical for assessing the substantive importance of linkages between peace and conflict and

prospects for a wider peace between democracies. I examine these linkages from conflict to democratization in chapter 6.

Zones of Democratization, Zones of Turmoil? Much of the research on the relationship among democracy, conflict, and peace fails to distinguish between the effects that institutions exert once they are in place and the effect of changes in polities. The static evidence from comparing propensity for conflict among polities does not necessarily translate directly into evidence on the effects of political transitions. Many extrapolate from the democratic peace and conclude that democratization inevitably will enhance the prospects for international peace as well (see Russett 1990 and Singer and Wildavsky 1996). However, this reasoning implies a host of unstated intermediate clauses. Rather than trying to spell out all of them and test whether they hold, I shall study the dynamics of democratization directly to try to understand if and how zones of democracy and zones of peace coevolve. Some recent research argues that although stable democracy may promote peace democratization may in fact increase the risk of conflict. Mansfield and Snyder (1995, 1997) argue that democratization can increase the likelihood of war involvement though the diversionary use of force. When faced with high levels of domestic pressures and challenges, leaders in unstable transition regimes may be tempted to seek involvement in conflict abroad in order to generate “rally round the flag” effects or instigate outbursts of nationalistic fervor. Externalization may divert attention from the problems in the domestic arena and thereby help to consolidate leaders’ political positions. Such theories of externalization have a long tradition in research on international conflict, often based upon rather direct analogies to work on in-group out-group dynamics in social psychology (see, e.g., Levy 1989b, James 1988, or Enterline and Gleditsch 2000 for more comprehensive reviews). Domestic concerns are held to motivate many historical conflicts. Recent formal work has identified situations in which diversion could be a plausible strategy (e.g., Hess and Orphanides 1995, 1997; Richards et al. 1993; Smith Page 59 →1996). Empirical studies, however, have generally found little, if any, support for such linkages.20 The idea that democratization can increase the likelihood of war draws much of its strength from conflicts in the Balkans and the Caucasus region after the Cold War. In many of these regional conflict formations, widespread armed conflict seems to have followed in the wake of a decline in political autocracy and increased political participation. The “dangerous democratization” hypothesis is not necessarily inconsistent with the stylized facts of the more restricted democratic peace. It is certainly possible that levels of democracy may have one effect and changes another. This is nevertheless an important challenge to some of the interpretations of the relationship between democracy and peace, especially in the wake of the numerous political changes that have followed the third wave of democracy. In addition, any such linkages are relevant for foreign policy prescriptions for promoting democratization on the basis of its presumed pacifying consequences (e.g., Allison and Beschel 1992; Franck 1992; Lynn-Jones 1998). However, neither Mansfield and Snyder’s hypothesis nor their empirical findings are beyond dispute. Various studies using different research designs have reached conclusions at variance with theirs. Some of the earliest criticisms held that Mansfield and Snyder misinterpreted their statistical results and that regime changes leading to autocracies were associated with a higher risk of war (e.g., Enterline 1996a, 1996b; Thompson and Tucker 1997). Ward and Gleditsch (1998) find, using the same data as Mansfield and Snyder, that substantial democratization or changes toward political democracy tended to reduce the risk of war, although high levels of instability and changes that go back and forth could increase it. In a subsequent study, Mansfield and Snyder (1998) no longer argue that it is democratization per se that increases the likelihood of war but rather that failed democratization and transitions to weak regimes at risk of reversal can increase the likelihood of war. As such, the assertion that existing studies are contradictory is somewhat misleading. Nonetheless, the overall results of existing studies seem somewhat inconclusive and confusing. Is there a way to reconcile the seemingly “dangerous democratization” in cases such as Albania, Bosnia, and Croatia with the empirical finding that democratization reduces the likelihood of war? I will demonstrate in chapter 4 that these can indeed be reconciled. I will show more systematically how democratization reduces Page 60 →the risk of

interstate war yet may be associated with an increase in the risk of domestic conflict or insurgencies. In the following section, I set forth a new theoretical interpretation of linkages between political change and conflict. Incorporating the regional context within which democratization occurs and disaggregating between different types of conflict help clarify why studies aggregating the differing effects on different types of conflict result in seemingly confusing findings. Political Conjunctures and Violent Conflict Mansfield and Snyder (1995, 1998) relate democratization to an increased risk of war based on the presumed greater likelihood of externalization in unstable transition regimes. However, we know that the diversionary theory of war hypothesis is highly disputed (e.g., Levy 1989b; Ward and Widmaier 1982). I contend that a more plausible linkage between democratization and conflict lies in how institutional changes alter political conjunctures or opportunity structures. The so-called resource mobilization school has long insisted that political opportunity structures can exercise a strong influence on the likelihood of violent conflict when there exist social groups seeking to mobilize against the state or regime (Lichbach 1989; Tarrow 1994; Tilly 1978). A large body of research has shown that political violence is particularly common in anocratic polities that combine features of both autocracy and democracy. These regimes combine features of autocracies and democracies and have both sufficiently restricted opportunities to increase the incentives for violent protest and sufficiently large opportunities to make such strategies feasible. Most empirical work has assessed the relationship between authority structures and opportunity structures by examining whether semirepressive regimes are more likely to see violent protest (e.g., Hibbs 1973; Muller and Weede 1990; Schock 1996). However, the effects of changes in such structures have rarely been examined directly (although see Hegre et al. 2001). A decline in the extent of autocracy in a polity can increase the opportunities for political mobilization for actors who seek to topple the existing government or institutional structures. Even though greater political democracy provides more opportunities for political mobilization through institutionalized channels, a decrease in the repressive character of a polity diminishes its ability to deter contention and violent protest. Page 61 →Such effects are likely to be exacerbated when democratization reflects regimes that are forced to make concessions to remain in power. A regime perceived as weak may also encourage insurgent or separatist groups to intensify their efforts to topple the government. Unlike theories emphasizing externalization by leaders in transition regimes, the effects of democratization on such political conjunctures or opportunity structures yield distinct implications for different types of conflict. Democratization may be associated with an increase in the likelihood of internal armed conflict as opportunities for nonstate actors to mobilize increase, but it should decrease the likelihood of interstate wars as leaders become more constrained, everything else being equal. Much of the previous work on democratization and war has compounded interstate, civil, and extrasystemic conflicts. As we will see in chapter 4, these different effects of democratization underlie some of the confusion that surrounds the empirical research. Upon closer inspection, it turns out that most of the examples Mansfield and Snyder invoke are internationalized civil wars rather than interstate wars.21 Some may be tempted to dismiss the relevance of civil wars to determining whether there is a relationship between changes in authority structures and the likelihood of conflict. Studies of democracy and peace have tended to focus exclusively on conflict qua interstate war, probably in part because civil wars do not fit the conventional dyadic framework.22 To merely exclude all conflicts not classified as interstate, however, seems unsatisfactory on several counts. Substantively, we would be hesitant to accept zones of democratization as zones of peace if these were more likely to experience civil war. I will show in chapter 3 that the distinction between external and internal conflict is not as clear cut as the terminology would lead us to expect. Many civil wars, including those in Bosnia, Lebanon, and Armenia, display various forms of external involvement by neighboring countries. Moreover, there are strong reasons to suspect that external involvement and the provision of resources or material support for actors can be of key importance for the outcome of conflicts and the ways in which they unfold.

Most of the previous research on democratization and war—including Ward and Gleditsch (1998) — has examined the relationship on a country by country basis. However, the regional context or the composition of regimes in the regional interaction environment in which democratization occurs may strongly influence the likelihood that democratization Page 62 →will be associated with violent conflict within states. Since democratization tends to unfold on a regional basis, Mansfield and Snyder’s externalization hypothesis suggests that zones of democratization could become zones of turmoil as clustering of democratizing states increases the likelihood of externalization and the risk that such conflicts will diffuse geographically. Conversely, if more constrained polities in a regional context decrease the likelihood of interstate conflict, we should be more likely to see democratization accompanied by war for states located in an autocratic regional context. For autocracies, democratization in neighboring states can be seen as both a threat to these regimes and an opportunity to intervene and induce outcomes more in line with their own preferences. The regional context of democracy says something about the constraints neighboring states face not only in direct involvement in interstate wars but in other, more direct forms of involvement such as support for neighboring regimes or groups challenging the legitimacy of neighboring regimes. The importance of such regional contexts to civil wars can be seen in postcolonial southern Africa, where the nationalist South African government financed armed insurgencies in many neighboring states. Similarly, the Nicaraguan revolution provided an impetus to both Marxist guerrillas elsewhere in Central America and the neighboring countries’ support of the Contra movement, which was trying to topple the Sandinista government. More recently, the ending of Syrian material and logistical support appears to have caused major problems for the Kurdish autonomy movement, the PKK, in its armed struggle against Turkey. The role of outside actors seems to have been largely neglected in research on violent civil conflict. That unconstrained rulers are more likely to intervene does not imply that democracies have never supported insurgencies or tried to topple governments. Interventions by the United States in Central America and the Caribbean provide prominent examples. However, such interventions tend to take place against vastly inferior states outside the immediate regional interaction environment. It is precisely the relatively low cost and salience of these ventures that render such activities possible. Nevertheless, such efforts are often met with considerable opposition, illustrating the potential constraints that more democratic polities face. This accounts in part for the incentives to carry out such operations through covert actions or third parties (Forsythe 1992; James and Mitchell 1995). Page 63 →

Conclusion In this chapter, I have examined the broader linkages between integration, authority structures, and regional conflict and peace. I have restated the Deutschian integration theory and the theory of democracy as a source of peace at the regional level. I have outlined three different perspectives on possible linkages between Deutschian integration and regional peace between democracies. If integration and the composition of political structures within regions are closely associated, the two elements interact and reinforce one another in reducing the risk of regional conflict and improving prospects for peace. Conversely, the apparent relationship between democracy and regional conflict might stem from a more general relationship between greater regional integration, affinity, and peace. Such integrated communities may conceivably emerge between similar states that are not liberal democracies. Moreover, the effects of changes in institutions may not be mirror images of the effects of established democratic constraints. I have argued that democratization should decrease the risk of war between states but may increase the risk of civil war, especially when democratization occurs within a regional context of less constrained polities. I evaluate these hypotheses on democracy and integration in chapters 4 and 5. Finally, I have addressed the implications of regional interdependence for democracy and democratization. Whereas most research on democratization assumes that the distribution of political structures is independent between countries and that changes stem from purely domestic processes, I have argued that regional processes and interactions among states influence the prospects for democracy. I outlined two international dimensions of democracy pertaining to forms of diffusion in authority structures and regime change and the effects on political institutions of diffusion of regional conflict or insecurity over time and space. These aspects will be examined empirically in

chapter 6.

Page 64 → Page 65 →

CHAPTER 3 Empirical Data, Measurement, and Methods To this day many of our comrades still do not understand that they must attend to quantitative aspects of things. . . . They have no “figures” in their heads and as a result they cannot help making mistakes. (Mao Tse Tung 1962: 379–80) This chapter addresses issues of data and measurement that arise in analyzing the hypotheses outlined in chapter 2. I first delimit the domain of the analysis. I then explain in greater detail how I derive measures of local or regional context based on the minimum distances among polities. I review the theoretical rationale for the particular sources of data used as indicators of the concepts and address various issues of measurement and operationalization.

The Domain and Units of Analysis The principal unit of analysis here is the sovereign polity or nation-state. States are obviously not the only actors in world politics. Important nonstate actors include intergovernmental organizations such as the United Nations and the Organization of Petroleum Exporting Countries (OPEC), transnational commercial enterprises such as IBM and Microsoft, nongovernmental organizations such as Greenpeace and Amnesty International, and subnational actors such as the Basque and Albanian separatist movements Euzkadi Ta Askatasuna (ETA) and the Kosovo Liberation Army (KLA). However, most comparative data are available for nation-states only, and the nation-state remains the best available unit of aggregation – or even the only feasible one — for observing the influences that such nonstate actors exert. The Modern State System and Its Origins International relations theory typically traces the modern interstate system back to the Treaty of Westphalia, signed in the wake of the Thirty Years’ War in 1648, which established the territorial sovereignty of states. The principle of state sovereignty did not itself imply an end to all Page 66 →intervention in internal affairs. But when it was coupled with the growth of the coercive and extractive powers of the state, the modern nation state emerged as the undisputed central actor in international relations. States’ ability to monopolize the use of “legitimate violence” went hand in hand with the principle of sovereignty, which conferred on states exclusive jurisdiction over their territories and citizens by virtue of the existence of the state itself. As the power of central authorities became more pervasive in the domestic arena, the influence of states relative to other actors in world politics — such as the church — grew dramatically as well. Despite the focus on sovereignty, the evolution of formally sovereign states was closely shaped by their interaction. Scholars such as Gurr (1988), Tilly (1985, 1990), and Rasler and Thompson (1989) emphasize the duality between “external” and “internal” aspects of state making. Internal violence against opponents allowed state-building elites to establish effective rule within the state, and external violence intended to keep enemies at bay also facilitated the growth of the power and capacity of the state apparatus. The development and evolution of one state frequently shaped the development of others. State sovereignty and the process of state building diffused from a network of European states to European settlements in the Western Hemisphere, changed the nature of existing states in Asia, and eventually came to encompass the entire international system through the process of decolonization. A second wave of nation-state building followed in the wake of the nationalist revolutions of the mid-nineteenth century. Nationalism derived the legitimacy of the state by reference to some form of national community among citizens that had preceded the state and was held to exist outside the institutions of the state itself.1 The shift to the right to national self-determination as the basis for statehood was radical insofar as it frequently challenged the

territorial sovereignty of existing states. Even though most states are not ethnically homogeneous and one might question the “authenticity” of national communities, national selfdetermination has effectively become the primary criterion of legitimate statehood. In this sense, the unification of the last major European nation-states — Italy in 1861 and Germany in 1871 — can be seen as a plausible beginning for the contemporary international system of nation-states. In order to avoid the lingering influences of the Franco-Prussian War, the specific starting date adopted here is 1875. The growth in the number of nation-states within the interstate system over the study period has been quite dramatic. By some accounts, starting with 49 polities in 1875, the international system encompassed Page 67 →a total of 157 polities by 1996 and possibly more by other criteria. This change in the composition of the international system has altered the regional context confronting many actors. The Composition of the International System I have previously argued that distances between a state and other sovereign entities can be used to delineate countries’ relevant interaction environment. In order to determine distance between polities and the relevant regional context, however, we must first identify the universe of sovereign state entities in existence over the observation period. Several efforts have been made to delineate the population of nation-states within the interstate system over the time period of interest to this study. The best-known effort is undoubtedly the Correlates of War project’s system membership data (Singer and Small 1972), which have provided the basis for many empirical studies (see also Russett, Singer, and Small 1968).2 In an earlier article authored with Michael D. Ward (Gleditsch and Ward 1999), I have questioned many of the COW project’s decisions regarding membership in the international system. The project’s criteria for inclusion change over time.3 There may be good reasons for adopting flexible and context-specific criteria, but such differences over time raise several problems for this study. By construction, the data may not be comparable over time. Especially in the early part of the time period, countries often appear in the COW data several years after their formal and practical independence. Some of the older nation-states outside of Europe that never were colonized, such as China, Ethiopia, Iran, and Japan, are not considered to have become independent states until 1855 or 1860. Canada, which is commonly held to have been independent since 1867,4 does not appear in the COW list until 1920. Tomz (1998) finds that the COW list assigns dates of independence for the South American states after these were already active on the international credit market. The largest discrepancy is the case of Oman, which has been formally independent since the seventeenth century but only appears in the COW list in 1971. These issues are not mere technical details but have substantive implications for inferences. If Canada is considered an independent entity after 1867 rather than 1920, the 1867–1920 period provides additional years without war between the United States and Canada as well as democratization without conflict. Furthermore, the actual times when states emerged as independent — even if this is not recognized by the COW criteria — are essential to an assessment of whether new states are Page 68 →associated with conflict, as witnessed in the breakup of the former Yugoslav Federal Republic, or tend to emerge in the aftermath of major wars, as in the case of Czechoslovakia after World War I. Gleditsch and Ward (1999) developed an alternative list of independent states since 1816, outlining relevant local actors, that avoids some of the pitfalls of legalistic definitions of membership in the international system or definitions that change over time. Our assessment is simple and largely procedural. In essence, we consider a state formation to be an independent polity if it (1) has an independent and relatively autonomous administration over some territory, (2) is considered a distinct entity by local actors or the state on which it is dependent (even if they are not recognized as actors by states elsewhere in the system), and (3) has a population greater than 250,000 (see Gleditsch and Ward 1999 for further details). The list of independent states since 1816 is reproduced in table A1, appendix A. Measuring Regional Context In chapter 1, I suggested that we could get a handle on a state’s relevant regional context by considering the

proximate neighboring states. Spatial statistics can help us construct measures of local context that capture local interdependence in world politics.5 I have developed a data set with Michael D. Ward on the minimum distance between states that we can use to delineate the regional contexts for states (see Gleditsch and Ward, 2001).6 Chapter 1 introduced some descriptive measures for detecting hypothesized spatial patterns. Here I will focus primarily on how spatial statistics can be used in a regression context. Map 3.1 illustrates in a more concrete way how we can use the minimum distance data set to specify connectives for states in the Middle East. Table 3.1 displays the connectivities of each state to other actors at varying minimum distance thresholds defining the regional context. Disregarding their relations with other states for the time being, we can numerically represent the relations among the states in Map 3.1 in a n × n connectivity matrix W. Equation 3.1 displays a connectivity matrix W1 between the entities in map 3.1, taking states to be connected if they share a land border. The W1 matrix provides a network representation of the linkages among all the polities in this subsystem. We can use W1 to create variables indicating the regional context for each state defined by its neighboring states. Page 69 → Map 3.1. The Middle East, post-1990 borders Page 70 → Page 71 → TABLE 3.1. Connectivities for the Middle Eastern States Page 72 →The most common way to construct a spatial variable xR, indicating the local context of some attribute x, is to premultiply the vector x with a row-standardized connectivity matrix .7 The product xT, or xR, will be a vector in which the values indicate the average of x among the neighbors for each state i.8 Row standardization has the advantage that the regional context variable xR will have the same metric as the original variable x. The influence of each neighbor on the regional context for each state in x R is assumed to be proportional to the number of neighbors. Although few applications have explored alternatives to the regional mean so far, in many settings it makes considerable sense to devise spatial variables, including contributions from a country itself to its spatial context, or devise spatial variables based on moments other than the mean. Some plausible candidates among the basic moments include the maximum, minimum, or variance of the values of the contiguous entities. In other cases, it might make sense to use the unweighted total sums over the regional context as a measure of the spatial context. The appropriate construction of measures of spatial context must be determined specifically in each case. Merely reverting to average values based on standardized matrices with zeros on the diagonal entries may not be warranted as a standard solution for all purposes (see Gleditsch and Ward 2001 for a further discussion).9 Variables and Measurement So far, I have used relatively standard international relations data in their raw form. Given the specific interest in regional zones of peace and conflict, however, we will need to reconsider some aspects and use these data in ways that differ slightly from established conventions in international relations research. In the following section, I briefly outline the various data sources and discuss issues of operationalization for measuring the extent of conflict, integration/cooperation, and political authority structures. Defining Violent Conflict A definition is a sack of flour compressed into a thimble. (attributed to Rémy de Gourmont) There is a strong tendency within international relations research to simply assume that “everyone knows” what violent conflict is. Nonetheless, Page 73 →there are several nontrivial problems in measuring armed conflict systematically. Although there exists considerable work on conceptualizing conflict (see, e.g., the review in Most and Starr 1989), this has rarely been integrated with empirical research.

Many researchers tend to assume that available data on conflict usually will accurately reflect the theoretical concepts. To be sure, as in other areas of the social sciences, there may be large amounts of measurement error in the available data. However, measurement error merely introduces random noise and should wash out in the aggregate provided that there are no systematic sources of bias and misleading attributions. Unfortunately, as I show in this section, there are reasons to suspect that current data on conflict display problematic systematic biases. Since different researchers are interested in different aspects of conflict, the existing data in their raw form may not be appropriate for all research questions. In the following, I discuss some problems of measuring regional conflict and peace in the context of this book and devise some solutions. In the most general sense, the term conflict simply denotes some form of incompatibility between parties. Most definitions stress incompatibility explicitly perceived by the parties rather than conflicting objective goals or the structure of their relationship.10 Boulding (1963:5), for example, defines conflict as “a situation of competition in which the parties [of which there are at least two] are aware of the incompatibility of potential future positions and in which each party wishes to occupy a position that is incompatible with the wishes of the other.” Incompatibility may arise over a continuum of issues ranging from tangible and material objectives such as territory, access to resources, and control over the state apparatus to more intangible aspects such as autonomy or religious doctrines. Incompatibility can also arise through situational constraints such as commitment problems that induce incompatible aims, even when parties might prefer to avoid conflict. Although some degree of conflict is inherent in virtually any social relation,11 the intensity of conflict comes in qualitatively different levels. Most researchers draw a fundamental distinction between violent and nonviolent conflict and focus on actual manifestations of a resort to violence. Violence, of course, is by no means the only way of inflicting punitive measures, and a final resort to violence is arguably the result of larger processes that mayor may not lead to violence.12 I will return to this later and indicate some possible ways to distinguish between qualitatively different forms of “no war.” Page 74 →Restricting the focus to violent conflict still yields a rather large and heterogeneous concept. Most analysts (at least implicitly) distinguish violent social conflict from interpersonal violence or temporary outbreaks of violence. Violent social conflict is limited to hostile interaction between some reasonably well defined set of actors that involves violence above some magnitude and persisting for some period of time. Domestic violence arguably affects a larger number of persons directly than interstate conflict does, but this would not be considered social conflict since neither perpetrators nor victims constitute actors in the sense of a unified group.13 To ensure tractability, most researchers adopt some minimum threshold of fatalities or casualties. Richardson’s (1960) pioneering work on conflict used a minimum of 35 deaths to identify deadly quarrels. In this study, I will rely on the Correlates of War definition that delineates cases of violent armed conflict as wars if they involve more than 1,000 battle deaths (see Singer and Small 1972 and Small and Singer 1982). Internal and External Conflict Parties to violent social conflict may vary considerably in both organization and formal status. Most studies of conflict tend to focus almost exclusively on interstate conflict among parties that are formally sovereign states. For many research questions, however, it is problematic to restrict analyses to conflicts classified as interstate wars. Conflicts between states make up a relatively limited share of the armed conflict involving nation-states in the contemporary international system. According to one account (Wallensteen and Sollenberg 1998), only six out of 103 armed conflicts in the period 1989–97 were interstate (see also Holsti 1996: 22). Many argue that the ratio of “international” to “civil” or other conflicts increased over the twentieth century (see Pfetsch and Rohloff 2000).14 To understand regional formations of conflict and peace, conflicts in which both parties may not be formal sovereign states but nonetheless contribute to regional insecurity cannot be excluded out of hand. I will argue later that classifications of zones of peace are suspect if they disregard all conflict that does not occur between states. Why has the focus on interstate conflict become so dominant in research on conflict? The standard model of conflict as interaction between two parties, X and Y, has come to be identified with states and does not always

translate easily to situations with other types of actors. Page 75 →Researchers have generally been skeptical about applying theories of international conflict behavior to conflict within countries or transnational conflict involving both state and nonstate actors. That states constitute the principal actors has been taken as something of an article of faith in the field of international relations. Much of international relations theory holds relations between states to be fundamentally different from relations within formally sovereign states given the “anarchy” of the international system. A probably not fully intended side effect is that most researchers simply assume that sovereignty is effective within nations and that civil war is thus qualitatively different from interstate war. Yet sovereignty is clearly less than fully effective within many existing states, and similar problems of enforcement and contracting under anarchy obtain within states as well. Hobbes had relations within states rather than the international system in mind when he related “Warre” to anarchy.15 The Correlates of War project (Singer and Small 1994; Small and Singer 1982) distinguishes between international and civil wars. In addition to interstate wars between members of the interstate system, Singer and Small identify a second class of international wars, labeled extrasystemic, in which system members engage in war with a political entity that is not a system member.16 Many major armed conflicts in the post-World War II era with obvious international dimensions, such as those in Afghanistan, Angola, Lebanon, and BosniaHerzegovina, are classified as “civil wars with outside intervention” rather than international wars. Whether something is judged to be an external or internal conflict in retrospect seems to be quite sensitive to legal and definitional aspects unrelated to the properties of a conflict. The Vietnam War, for example, is regarded as an international war after 1965 when the U.S. intervention is judged to have become the dominant element. Prior to that date, it is classified as a civil war that grew out of an extrasystemic war involving France. More generally, a given conflict can become an international or civil war depending on how conflict and foreign intervention unfolds. As intervention often occurs in connection with attempts to replace existing governments, the outcome of interventions or which party is considered the legitimate government at the time of intervention can “determine” whether an intervention becomes an interstate war or an intervention in an ongoing civil conflict. If the anticommunist Herat uprising in Afghanistan in 1979 had toppled the government, a Soviet intervention could Page 76 →have marked the onset of an interstate war. Additional ambiguities arise as to whether conflicts revolving around the breakup of entities and the emergence of new states, as seen as in the former Yugoslavia, constitute wars between sovereign nations or “internal” wars. My argument here is not that the COW classifications are wrong, but that they may be trying to impose a distinction that often is untenable. Conflicts between states and nonstate actors carry a potential for diffusion and escalation to interstate wars and are classified one way or the other based in part on whether they do or not. Closer scrutiny often reveals a discrepancy between conflict data and the events to which researchers seek to generalize. Mansfield and Snyder (1995), for example, invoke conflicts in the former Soviet Union and the Balkans to illustrate their argument about democratization and war. However, the conflicts in Chechnya and Bosnia are not considered to be international wars in the COW data and would not be included in their statistical analyses. This clearly suggests that limiting conflict to interstate wars fails to capture the relevant conflicts to which the hypothesis pertains. A Digression on Wars versus Disputes The original Correlates of War international wars data have recently been supplanted by a new data set indicating a broader category of incidents labeled so-called militarized interstate disputes. In addition to wars, these include “cases in which the threat, display or use of force by one member state is explicitly directed towards the government, official representative, official forces, property, or territory of another state” (Jones, Bremer, and Singer 1996: 168). It is often argued that events that do not cross the war threshold can provide important elements for understanding the contexts in which wars may arise (e.g., Bremer and Cusack 1995). However, the MID data turn out to be problematic for this study on a number of counts. The MID data include several events that do not involve overt violence. Latent conflict and underlying tension might be important for assessing regional clusters of conflict and peace. However, the MID data contribute little in

this respect given their exclusive emphasis on official state actions and declarations. The MID data set is a highly truncated sample of conflictual events since it excludes all events that do not take place between two government entities or do not lead to official declarations. Page 77 →A seemingly plausible alternative is to restrict the analysis to only those MIDs with a hostility level that includes actual overt violence, that is, event categories 4 and 5, indicating “use of force” and “interstate wars, ” respectively. However, a closer examination of incidents included in the use of force category raises questions as to whether these can be considered to be actual armed conflicts. Only 364 of the 2,034 disputes in the MID data set involve casualties. More importantly, it is frequently hard to ascertain to what incidents use of force entries actually refer. Some examples involving Norway illustrate the problems involved. According to the MID data, Norway was a participant in a total of six MIDs deemed to have involved use of force in the post-1945 period. On 31 August 1981, Norway is supposed to have engaged in a “raid” against Denmark (MID 2970). Similarly, on 1 September 1969 Norway allegedly engaged in a “seizure,” with Denmark, the Soviet Union, and the German Democratic Republic on the opposing side (MID 2939). Furthermore, Norway is coded as having been involved in three bilateral disputes involving use of force with the Soviet Union (MID 2848, 3067, 3225) in which the parties are held to have engaged in seizures and a “show of ships.” None of these cases appear to have led to any casualties, and the specific response or action for any of the other parties is coded as “not available.” There is no mention of these events in standard Norwegian reference works, but the incidents are probably related to fishing disputes in which the Norwegian Coast Guard is seen as having acted as an official military entity. Although NorwegianSoviet relations during the Cold War arguably were characterized by some tension, it is a mystery why these confrontations are singled out as notable over events such as the U2 affair and other East-West issues arising out of Norway’s membership in the North Atlantic Treaty Organization (NATO).17 Earlier on, Norway is held to have been in a dispute involving a “clash” with Germany from 4 November 1939 to 9 April 1940 in which Germany is coded as “joining an interstate war.” The end date of this dispute actually coincides with the German invasion of Norway on 9 April 1940. The element of surprise that has been attributed to this invasion would indeed seem quite puzzling if there had been overt use of force five months before the invasion. Unless a dispute can be documented from historical sources, it is highly unlikely that it will display the behavioral characteristics associated with “conflict.” If not, it makes little sense to expect to observe corresponding values on independent variables. Why, for example, Page 78 →should political institutions be expected to exert any effect on a “dispute” or event that politicians and the opposition alike are unlikely to have known about? It verges on the meaningless to single out such events as cases of “use of force.” Note that use of force is the modal category in the MID data. The MID data suffer additional problems with the timing of events. The data report the maximum level of hostility reached over the course of a dispute. Since the threshold for when something is said to constitute a MID is much lower than that of wars, the data often seem to “backpolate” the maximum hostility levels to improbably early starting dates. The duration of the Mexican-American War, for example is given as 1843–48 in the MID data as opposed to the conventional dates 1846–48 found in the COW war data. Although there was a border dispute prior to the war, it seems overly inclusive to code the 1843–45 period as an interstate war between the United States and Mexico. The annexation of Texas occurred in last days of December 1845, and Taylor’s “invasion” was in April of the subsequent year.18 In theory, a war may be preceded by a series of smaller scale MID events. However, since most events are linked in one way or another, it is difficult to ascertain whether something is “the same” or “a different” conflict. Whereas it is straightforward to identify the actual location of wars, in most cases we cannot clearly tell where the MIDs that states participate in are fought. The geographical distribution of MID participation in the 1990s corresponds poorly with other indicators of conflict. We see a cluster of countries participating in MIDs in Europe and surprisingly few states participating in MIDs in Africa. There are strong reasons to suspect that the MID data overreport incidents of conflict in countries that are more exposed to international media and understate the extent of conflict in countries with poor coverage. Even if MIDs could be identified systematically, their theoretical

universe seems unclear. All these factors taken together, I conclude that the MID data are not appropriate for identifying regions of conflict and peace in this study. Measuring Incidents of Conflict For this study, I generate data on whether a country experiences violent conflict based on the Correlates of War international and civil wars data (Singer and Small 1994) and the data of the Uppsala University Conflict Page 79 →Data project (Wallensteen and Sollenberg 1999). I do not require that both of the opposing parties must be system members and include cases of civil and extraystemic wars when states engage in conflict with nonsystem members. I also classify the specific locus or place where conflict occurs to distinguish cases in which states experience conflict on their territories or its regional context from cases in which states participate in conflict elsewhere in the system. The latter may provide pertinent evidence of the belligerence of that state, but only the first constitutes clear cases of threats to its security from other states and is pertinent to assessing zones of conflict and peace. The locus of conflict was classified on the basis of geographical distance from the location or area where fighting took place. In some cases of doubt, I relied on the number of battle deaths suffered by each participant to determine whether the extent of involvement indicated that its vital security was at risk or whether it experienced conflict in its regional context. Following the same logic, I include extrasystemic wars that take place within the core or contiguous territory of the system member state along with civil wars.19 I use three indicators of violent armed conflict: (1) interstate wars exclusively, (2) all noninterstate wars (i.e., extrasystemic and civil wars), and (3) general conflict, including interstate as well as civil and extrasystemic wars. I denote the three variables Cli,t, CCEi,t, and Ci,t respectively, indicating whether a country i was involved in a conflict of a particular type in year t. The data on conflict since 1816 and the modifications made to the COW data are listed in greater detail in tables B1 through B3 in appendix B. Conflict in Time and Space The empirical study of zones of conflict and peace raises some additional challenges. We need to assess the extent of threats to security or conflict taking place within a country’s interaction environment rather than just that country’s participation in conflict. Wars and conflict are rare events, but the notion of a zone of peace or conflict implies some degree of persistence and latent risks of diffusion over time and space. A threat to security is a latent characteristic that is not fully observable, but we can gain a handle on it by ascertaining where conflict takes place and the risk that it will recur or spread. Much empirical research treats conflict incidents as independent. Page 80 →This assumption is rather implausible given the clear evidence suggesting that conflict often recurs among past antagonists or diffuses among states once it is under way. The statistical consequences of the dependence of conflict — in particular, dependence over time — have been addressed in various ways. Many researchers apply more robust estimation methods to remedy the influence of temporal dependence on coefficient estimates and their standard errors.20 To treat duration dependence as a mere nuisance, however, is less satisfactory for this study, in which the prospect for peace or the way the risk of conflict decays over time is a central substantive concern. Another approach is to try to model the temporal dependence of conflict and peace. Based on an analogy to event history analysis, this can be done by considering how long a state has “remained at peace” and how this affects the risk of conflict. More specifically, define a variable Ti,t indicating the number of consecutive years in which unit i has not experienced the conflict up to time t – 1 (i.e., not including observation time t itself). By conditioning on Ti,t we can introduce the effects of time dependence on the likelihood of new conflict directly in a statistical model. We would normally expect the hazard or risk of recurrent conflict over time to be quite high immediately

following conflicts but then to decline monotonically with time. Raknerud and Hegre (1997) suggest modeling a declining risk or insecurity with time by means of a simple exponential decay function where α denotes a half-life parameter, indicating the speed with which the latent risk decays. Setting α = 8 implies that the “risk” of recurrence is halved every six years. Although we would expect conflict and peace to display positive temporal dependence, its exact shape or form is not known with certainty. Beck and Tucker (1996) suggest a nonparametric approach in the absence of clear expectations about the exact shape of time dependence. The effects of Ti,t or the duration of peace, on the likelihood of conflict can be estimated by means of a smoothing spline in a semiparametric generalized additive model (GAM). This approach is attractive on grounds of its generality and flexibility. Researchers can simply test whether time dependence exists without having to make strong assumptions about functional form. Although GAMs do not yield parametric coefficient estimates, the substantive implications of time dependence can be examined graphically. The technical aspects of the GAM framework are outlined in greater detail in appendix C.21 The information about prior history in the years of peace Ti,t variable Page 81 →is obviously quite sensitive to problems of left censoring or missing information prior to the first observation in the sample (e.g., Yamaguchi 1991). Since we have conflict data dating back to 1816, it is not necessary to assume that all actors start from scratch in 1875.22 To summarize, in order to assess the extent of a specific threat, we need to determine not only the actual locus and duration of conflicts but the implied risk of diffusion over time and space as well. A higher perceived risk should in turn be expected to have observable implications for the behavior of actors. We cannot directly observe how such latent perceived risk develops over time, but we expect perceived risk or the likelihood of conflict to decay monotonically over distance and time. Measuring Regional Conflict and Insecurity In the absence of clear optimal measures, it seems advisable to employ several alternate measures of how conflict and insecurity decay over time and space. In this section, I outline a variety of different measures of regional conflict and insecurity. These measures may not be fully equivalent, and each of them has stronger and weaker sides. However, if multiple indicators yield results that are consistent with expectations, we can have greater confidence that these measures pick up underlying regional hostility and compatibility and that the results do not merely follow from a particular specification. I summarize the notation and construction of the different measures in appendix E. The first alternative is simply to examine actual incidents. This approach is in many ways reasonable and attractive. First, it requires no assumptions about how the risk of conflict decays over time and space. If latent hostility and diffusion of insecurity in space and time underlie outbreaks of conflict, we should nonetheless expect to observe marked regional patterns in these outbreaks and to find that these covary with the factors hypothesized to account for zones of conflict and peace. Local clustering measures, indicating to what extent similar values appear to cluster around some observation i, provide another way to identify regional conflict and peace. Ord and Getis’s (1995) G*i is the most common local clustering statistic (see also Getis and Ord 1992). This is given by for some input variable y. This yields an observation-specific value comparing the deviation of each observation’s cluster from a randomized pattern that can be compared to the standard normal distribution. The clustering of conflict incidents around an actor i given by G*i (Ct) can be interpreted as a measure of the extent to which each entity i is located in zones of high conflict or relative peace. Similarly, , or localized clustering in time at peace, indicates the extent of the stability of peace in the states surrounding actor i. In order to gauge sensitivity to different relevance thresholds, I use varying criteria of 950,475, and 50 km. Page 82 →It is clear from equation 3.2 that the G*i scores for local clustering will depend upon the total number of surrounding entities of an observation i. In some settings, this can make sense. The extent of potential

insecurity emanating from neighboring countries will be higher the larger the number of neighboring entities and relatively trivial for physically more isolated entities (e.g., Richardson 1942,1960). A country like New Zealand is in this sense less exposed to threats, given its vast geographical separation from other entities. Taken to the extreme, the idea of localized clustering is meaningless for countries that have no neighboring entities. The G*i statistic may work well for a regular lattice, but it seems problematic for the geographical configuration of the international system in which states come in all shapes and sizes. The G*i statistic thus seems less satisfactory as a general measure of spatial heterogeneity. A peaceful environment is less likely to display significant clustering the lower the number of surrounding entities that can display similar values. Leaving clustering aside, we may also devise a measure of the average insecurity or extent of conflict within a country’s regional context from the regional average based on the fixed conflict exponential scores for neighboring states. In this case, it would seem appropriate to let a country’s own value influence regional conflict and to include this in the connectivity matrix. Using a row standardized connectivity matrix we can derive an insecurity score bounded between zero and one. However, it is not obvious whether the matrix should be normalized, since the potential extent of conflict and threats of spill-in from other actors in all likelihood is positively not identical among countries given differences in their total number of borders and physical shapes. An alternative variable is based on the raw binary connectivity matrices and indicates the sum of the conflict scores in a state’s regional context. Although the continuous measures of regional conflict and insecurity differ, they are all based on similar exponential functions. The aggregate Page 83 →correlations are generally high, and density plots reveal that the distributions of the various measures are largely similar. Measuring Regional Integration In chapter 2, I suggested that Deutschian integration theory could be restated as a theory of regional integration and community. We can assess the density of Deutschian flows as a measure of revealed integration or the extent to which cooperation prevails over conflict at the local level. The concept of cooperation has been accorded a variety of different meanings in international relations research (e.g., Young 1989). Nonetheless, most define cooperation as processes of exchange and coordination, entailing some — if not necessarily equal – gains for all parties involved. Even if the raw data sources available for this study are not ideal indicators of cooperation — let alone of transnational integration or regional interdependence — under Deutschian integration we should expect to find covariation between positive and negative indicators of community and regional conflict and peace. Regional Trade and Economic Exchange Trade is one indicator of the extent of cooperative interactions between parties (Bliss and Russett 1998; Morrow, Siverson, and Tabares 1998; Pollins 1989a, 1989b). The potential for gains from trade suggests that actors should engage in economic exchange across borders when commodities can be acquired at a lower costs than under autarchy.23 International relations theory stresses that an anarchic international system may create obstacles to cooperation and exchange. When trade is in place, however, the gains from trade increase actors’ sensitivity to the costs of potential trade disruptions. Greater affinity between states provides an international setting with a potential for economic exchange that may bolster the barriers to disruptive conflict. Even though aggregate trade is a sum of decisions made by various nongovernmental entities, these allocations also reflect the context within which these decisions are made since actors incorporate the perceived risks of disruption. Since distance between states is a key determinant of expected interaction in most models of interaction (e.g., Coleman 1964), we can use high regional trade flows as a measure of revealed integration between states. Page 84 →Measures of interstate imports and exports in current prices can be taken from the International Monetary Fund’s (1997) Direction of Trade data. These are available from 1948 to 1997. We can use the size of the total gross domestic product as a normalizing factor for the absolute size of economies. I derive data on total gross domestic product in current prices using figures from the Penn World Tables and a U.S. GDP deflator from the Bureau of Economic Analysis.24 These data are unfortunately available only for the time period 1950–92.

There are several problems with these data. Trade data are notoriously unreliable, and many of the accounting identities that should be true by definition may not hold and diverge by several orders of magnitude (e.g., Rozanski and Yeats 1994). These differences stem in part from divergent reporting practices and incentives to misreport trade. Other problems stem from the mismanagement of data by collecting agencies. The available IMF data appear to have linearly interpolated observations, and data below some threshold value are regularly truncated. Thus, zero entries could reflect absence of trade flows as well as missing data. Several dyads have no recorded values whatsoever. This category includes a large share of bilateral relationships in which we might expect to see fluctuations in both trade and conflict, such as those between China and the Soviet Union, China and Taiwan, and North and South Korea. If data are not missing at random, we may have severely misleading selection biases in the observed data (e.g., Berk 1983; King et al. 2001). The likelihood of missing trade data may be correlated with the likelihood of conflict. In Gleditsch 2002, I discuss some procedures for handling these data and replacing missing data with “best estimates” based upon other information. The principal indicator of localized trade here is simply the unweighted sum of total trade to GDP ratios for all entities j within some distance d of a given polity i. This measure of regional trade densities around each country i is denoted TRi,t. In chapter 6, I will also use a measure of GPD per capita in purchasing power parities, denoted Pi, t as a separate indicator of the “social requisites” or economic wealth of country i. To make these comparable over time, I use constant prices in 1985 U.S. dollars for Pi,t. Measures of the Nature of Interactions Although international relations research tends to treat conflict and cooperation as binary phenomena that are either present or absent in a Page 85 →given relationship, many feel uncomfortable with such a dichotomizing and highly aggregate approach. War and treaties are not isolated, one-shot events but merely peaks in more continuous chains of interactions that also encompass forms of conflict and cooperation at a lower scale. The larger sequences and events underlying these peaks may be important forces in producing changes over time, and we lose the ability to track such dynamics over time by focusing only on the extremes. More detailed data on sequences of interactions may help us to probe whether there is a “flip side” to conflict and whether such differences in affinity and integration underlie regional conflict and peace. Several researchers have collected more disaggregated event data in order to study interaction processes in greater detail. These categorize “newsworthy” nonroutine incidents, or “events,” according to originator, target, type of action, and date of occurrence.25 Two widely used general event data projects are Edward Azar’s (1980) Conflict and Peace Data Bank (COPDAB) and the World Event/Interaction Survey (WEIS) initiated by Charles McClelland (e.g., Tomlison 1993). The COPDAB data have been widely used in empirical research but are available for 1945–79 only.26 The WEIS data are available from 1966 to 1992 and are nominally still in existence.27 Most researchers aggregate individual events into composite time-series measures on a conflict-cooperation continuum.28 Rummel (1963) tried to scale events using factor analysis. Azar and Havener (Azar 1980) and Goldstein (1992) devised explicit coding scales to rank events according to their intensity on a conflictual and cooperative dimension. Reuveny and Kang (1996) concluded that no systematic differences exist between COPDAB and WEIS and that the two data sources can be spliced.29 For this study, the advantages of combining these sources seem to outweigh comparability problems. I rescale the Azar and Havener scale to range from – 10 to 10 to make it comparable with the Goldstein index. Existing event data are far from perfect indicators of the nature of interactions and to what extent this displays evidence of integration or rivalry. Although COPDAB and WEIS include various activities by nonstate actors, their explicit emphasis on nonroutine transactions means that many nonstate actors and processes relevant to Deutschian integration are not included. Nonetheless, these data should provide reasonable measures of the intensity and type of interactions between entities. If Deutschian integration theory is correct in that there exists a converse side to latent hostility, we should expect to find covariation between these indicators and regional conflict and peace.

Page 86 →I create an undirected composite event scale score for each dyad by taking the weighted sum of the undirected Goldstein score of all WEIS events and the undirected Azar and Havenar conflict-cooperation scores. From these dyadic scores, I then create a vector of regional conflict cooperation measures for each country i by taking the spatial lag of the values of the adjacent entities of some given entity i. The notation and construction of these measures are summarized in appendix E.

Democracy and Political Authority Structures Several attempts have been made to measure political democracy and institutions on a comparative basis. Much of the early work was relatively impressionistic and employed unsystematic criteria that varied between cases and over time (cf., e.g., Lipset 1960). Since the late 1970s, a new generation has measured political institutions and rights more systematically. Notable examples include Bollen’s (1979, 1980, 1986, 1990, 1993) latent variable approach to measuring political democracy from multiple observable indicators, the Freedom House annual ratings of political freedom (e.g., Gastil 1985), and Vanhanen’s (1990) attempt to operationalize Dahl’s (1971, 1989) two dimensions of polyarchy — that is, the extent of participation and competition in a political system — through electoral data. Most of these measures are available only for a few select years, use varying criteria for different countries, or rely in part on indicators of dubious validity such as the extent of turnout as a measure of popular participation. The larger temporal coverage and reasonably explicit criteria have made the Polity data on aspects of authority structures an attractive alternative source for information about institutions. In addition, the Polity data are explicitly institutionally based and do not purport to measure the more subjective aspects of political democracy such as participation and civil liberties. The Polity project grew out of efforts to test Eckstein and Gurr’s (1975) congruence theory and were not initially devised to measure democracy per se. The institutionalized democracy and autocracy measures suggested by Gurr et al. (1989) were explicitly tentative. Most secondary analyses, however, have taken the analytical construction of these indices as given. Gleditsch and Ward (1997) explore the analytical construction of democracy and auotcracy indices in Polity from its various Page 87 →subdimensions and show that the subcomponent tapping the extent of executive constraints dominates the construction of the scale. From a theoretical point of view, this is a desirable outcome. Although the emphasis on different aspects of democratic ideals has changed over time, limitations on executives are an enduring feature of democratic institutions. As such, these data are more comparable over time than measures defined on the basis of aspects that change considerably over time such as the scope of suffrage.30 In this study, I use a 21 point scale of levels of institutionalized democracy ranging from a low of – 10 to a high of 10 based on the Polity data. Appendix D illustrates how this is constructed from five different subcomponents or dimensions of authority. I also devise additional measures of aspects of democratization processes over the prior decade similar to the measures used in Ward and Gleditsch 1998 and Gleditsch and Ward 2000.31 One measure, denoted ΔDi, indicates the total amount of change a country i experienced in its level of democracy over the prior decade. Another variable denoted indicates the direction of net change in the level of democracy over the prior decade. This is valued −1 for changes that decrease the level of democracy in a country, + 1 for changes that increase the level of democracy, and 0 if there was no net change over the decade. I use the standard deviation of values of Di,t over the prior 10 years as a measure of the rockiness of democratization.32 This variable, σDi, will be high for large movements back and forth between democratic and autocratic regimes and when countries have interruptions in their democracy scores over the decade. We can devise a measure of democracy in a country’s regional context by the average of institutional structures among neighboring states. I denote the regional context of authority structures by the symbol DRi,t. I devise a measure of the dispersion or similarity between polities in a regional context a polity i faces at time t from the variance of the political structures among neighboring states. This variable, SRi,t denotes the degree of dissimilarity among regional institutional structures. Similarly, we can measure regional democratization as well by aggregating political changes in a country’s regional context over the prior decade. I denote these measures of change in the regional context by for the total change, direction, and standard deviation in authority structures, respectively. The construction of all the measures is illustrated in appendix E. Page 88 →

Remarks in Lieu of a Conclusion This chapter is primarily concerned with issues of measurement in the empirical analysis of regional conflict and peace. I have highlighted various problems in the ways existing research handles the measurement of conflict, cooperation, and democracy. The large discrepancies that often exist between theoretical constructs and empirical measures may have led researchers to reject their theories more often than is actually warranted. In some sense, our theories might make more sense than we give them credit for, but they are obscured in empirical work by flaws in measurement and operationalization. Recent attention to statistical problems in the democratic peace has raised the level of methodological sophistication in the statistical analysis of conflict and clarified many aspects of conflict processes (e.g., Beck and Jackman 1998; Beck et al. 1998; Beck, King, and Zeng 2000; Beck and Tucker 1996; Gates and McLaughlin 1996; Jackman 1998; Raknerud and Hegre 1997; Ward and Gleditsch 2000). By contrast, there has been relative neglect of measurement and efforts to examine the validity of the data. I hope the efforts here provide a modest contribution to improving cumulation in international relations research. Having squared off the data issues, it is finally time to see whether these efforts will yield visible payoffs in empirical analyses.

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CHAPTER 4 Do Zones of Democracy and Peace Coevolve? In chapter 1, I showed that democracy and autocracy as well as armed conflict and peace cluster in regional zones. In chapter 2, I argued that a regional perspective provides a more useful approach to linkages between domestic institutions and conflict than purely monadic or dyadic perspectives do. In this chapter, I test whether zones of democracy and autocracy go together with differences in regional conflict and peace. I first examine whether the incidence of armed conflict varies with whether a country is democratic and the composition of institutions in its regional context. In chapter 2, I further argued that evidence from relationships among levels of democracy and conflict does not necessarily translate into evidence on the effects of democratization or political transitions. In this chapter, I examine these dynamic effects on the likelihood of conflict directly. Finally, I explore whether zones of peace and conflict coevolve with zones of democracy and autocracy by means of tests for cointegration or joint trending over time. To anticipate the conclusions, the empirical findings suggest that both higher levels of democracy in a country and higher levels of democracy in its surrounding regional context decrease the likelihood of conflict. However, the composition of political structures in the regional context turns out to be more important and exert larger substantive effects than a country’s own political institutions. I will also show how incorporating regional context and disaggregating different types of conflict help us to reconcile the stylized facts of “dangerous democratization” with the finding that democratization reduces the likelihood of interstate war. Finally, I present evidence of cointegration suggesting that zones of democracy and peace trend together over time. Page 90 →

Are Zones of Democracy and Zones of Peace Related? To probe whether regional conflict and peace covary with the regional composition of political institutions, I first estimate a logistic regression with armed conflict as a function of an actor’s own level of democracy as well as the extent of democracy prevailing within its proximate interaction environment. I delineate the regional composition of authority structures in a country’s localized interaction context by a threshold of minimum distances less than 950 kilometers between states. The probability that a country i will experience conflict at time t can be expressed as a logistic regression equation, where denotes the estimated probability of conflict, Di,t indicates a country i’s level of democracy at time t, and DRi,t denotes the regional context of democracy as defined in chapter 3. If democratic states are able to reduce the extent of perceived threats and rivalry in security in their interactions, we should see a negative relationship between the extent of democracy in a country’s regional context and the likelihood that a country will experience violent conflict. Countries do not control their regional contexts and neighbors, so whether a country is a democracy in and of itself should not be as strongly associated with differences in conflict and peace. When differences in the regional context of individual states are taken into account, however, we may find that the country’s own level of democracy has a clearer and more consistent negative effect on conflict. The results of estimating equation 4.1 on data for the period 1875–1996 are presented in table 4.1. The leftmost column of the table displays the estimated results with the conflict variable limited to interstate wars. The

rightmost column displays the results for all wars. The significant likelihood ratio chi-square tests indicate that model 4.1 yields a significant improvement over the null model for both of the conflict measures. The coefficient estimates for both a country’s own level of democracy and the regional context of democracy are negative, suggesting that these factors reduce the likelihood of conflict. The coefficient estimates are statistically significant and consistent with expectations for both conflict variables. Page 91 →The negative signs for the coefficients for an actor’s own level of democracy indicate that the more democratic a country, the lower the likelihood that it will experience armed conflict. However, these results indicate that higher levels of democracy in a country’s regional context decrease the likelihood that a state will experience conflict to a greater extent. The difference in the relative effects for the two factors can be seen by comparing the two coefficient estimates. The coefficient estimate for the regional context of democracy exceeds that of a country’s own level of democracy by a factor of more than two. Since the metric for the two variables is identical, these results demonstrate strong evidence that the regional context is substantively more important in decreasing the likelihood of war. When we control for regional context and the locus of conflict, democracies are generally less prone to conflict. However, above all it is within broader zones of democracies that the prospects for peace improve the most. Figure 4.1 illustrates the implied predicted marginal effects of differences in internal or regional democracy on the likelihood of war. As can be seen, although there is a substantial proportional reduction in the likelihood of conflict with a higher level of democracy in a country, the extent of democracy in the regional context decreases the risk of conflict to a greater degree. There is already a wealth of empirical research on the effects of democratic institutions on the likelihood of conflict. The results just reported here, however, differ from purely dyadic or monadic studies on democracy and peace in several important respects. A focus on the dyad may yield a robust association between democracy and peace. Most purely dyadic studies, however, disregard the regional context. The jointly democratic dyads that appear to be consistently peaceful are created by pulling spatially proximate democracies from broader zones of peace. These findings also suggest that the discrepancies between dyadic and monadic findings may have been overstated. As noted in chapter 2, the idea that democratic institutions have effects for individual states may have been prematurely dismissed in part by weak conceptions of what sorts of conflict democracy can constrain and where it should be expected to exert less impact. When we consider the actual locus of conflicts and the regional context surrounding states, we find constraining effects at the state level consistent with those implied by institutional explanations. The magnitude of the differences in predicted probabilities of conflict exceeds the comparable figures from many of the studies of relationships among democracy, conflict, and peace at the purely dyadic or monadic level.1 TABLE 4.1. Democracy and the Likelihood of Conflict Page 92 → Fig 4.1. Marginal effects of actor's level and regional context of democracy on conflict Page 93 →The idea that the regional context of interaction matters is of course not new to international relations research. Dyadic studies often try to put forward ex ante criteria for identifying sets of “relevant dyads” or interactions in which wars with some plausibility might occur (e.g., Lemke 1995, 1997; Maoz 1996; Maoz and Russett 1992). In these studies, regional context is limited to selecting important dyads and the dyads are still treated as independent of other states. Some studies acknowledge regional differences and try to address differences in regional context by inserting dummy variables indicating whether states are part of particular regions. This approach has a number of inherent drawbacks. A dummy variable can tell us that certain regions are different in one way or another, but it tells us little about why, say, Africa is different from Europe. Moreover, most classifications of regions, such as the COW project’s data, treat regions as mutually exclusive categories in which states are either members or not. Such classifications do not distinguish between distances within regions but by construction treat distant states as

equally important as proximate states. There is also some inevitable arbitrariness in delineating mutually exclusive regions that, for example, force “Europe” or the regional context of European states to end at the Urals and the Strait of Bosporus (Lake and Morgan 1997). In the COW data, for example, the Middle East category encompasses all the states in North Africa but excludes states in the Caucasus and Central Asia. Many countries may be actors in more than one of these “regions.” Turkey, for example, is close to states in the Middle East, the Caucasus, Europe, and Central Asia. Page 94 →Whereas previous studies treat regional context with a proper name or dummy variable, I here treat regional context as a state-specific variable, based on the attributes of actors inside a given distance around each state, that can be compared across countries. Do We Have the Right Context? One of the most immediate possible objections is that the findings may follow from a seemingly arbitrary specification of regional context. How do we know that a distance threshold of 950 kilometers will capture the appropriate context of interaction? One of the primary analytical advantages of using minimum distance data is that these actually permit us to test alternative specifications of regional context. We can examine the sensitivity of the results by reestimating equation 4.1 with context variables based on alternative cutoff threshold for relevance. In chapter 1, I suggested two shorter alternative distance thresholds of 475 and 50 kilometers. The upper part of Table 4.2 replicates 4.1 using a threshold of 475 kilometers to delineate the regional context. The lower part of Table 4.2 employs a 50 kilometer threshold.2 The second column of Table 4.2 indicates that the results for interstate war at 475 kilometers are largely similar to those with a 950 kilometers threshold in table 4.1. The effects of the regional interaction environment exceed the substantive effects of a country’s own. Not surprisingly, when we insist on a very restrictive distance threshold of 50 kilometers the regional context seems to matter less. As the rightmost column in Table 4.2 indicates, the results for all conflicts using distance thresholds at 475 and 50 kilometers are largely similar to those in Table 4.1 at 950 kilometers. For this more comprehensive conflict variable, the regional context retains its greater explanatory power even with the most constrained distance threshold. TABLE 4.2. Democracy and Conflict with Alternative Estimates of Regional Context Page 95 →These results indicate that even though there are no strong theoretical grounds for a threshold of 950 kilometers the results do not appear to be overly sensitive to the choice of distance threshold. At least in this case, the empirical results seem to be generally consistent across the three thresholds. Since very restrictive definitions of context based upon direct physical proximity alone can become quite arbitrary (see Gleditsch and Ward 2001), a relatively broad delineation criterion seems to be more appropriate for studies of conflict. To convince skeptics that the regional context of democracy influences the prospects for conflict and peace, however, we must consider some additional potential threats to the validity and robustness of these results. Isolated Incidents or Zones of Conflict and Peace? The results in Table 4.1 are largely consistent with what we would expect if more persistent forms of regional hostility underlie the observed outbreaks of war over time. However, although the discussion has emphasized broader regions or zones of peace and conflict, these results essentially apply to singular incidents of violent armed conflict for individual states rather than localized clusters or zones extending over time and space. In chapter 3, I developed a series of alternative measures of conflict that incorporate a decay of insecurity or risk of conflict over time and space. To assess whether similar or qualitatively consistent empirical results can be found across the alternative conflict indicators and different context thresholds, I reestimate variations on equation 4.1 using the alternative continuous or quasi-continuous conflict measures as the dependent variable. Page 96 →The number of results and their complexity increase exponentially with the number of permutations of variables and context thresholds. For three different raw indicators for incidence of conflicts, four alternative measures of the localized extent of clustering, and three different relevant context thresholds, for example, we

have a total of 3 × 4 × 3 = 36 different sets of results and regression estimates for equation 4.1 alone. To present all of these empirical results in full detail would take up an excessive amount of space, so I will just summarize the main results. Overall, the empirical results with the alternative measures of regional conflict or insecurity are qualitatively very similar to those that were found with binary incidents. The results consistently indicate that predicted levels of insecurity are significantly lower for more democratic countries in more democratic zones or regional contexts. The coefficient estimates for a country’s level of democracy and the regional context of democracy are statistically significant and imply effects similar to those in table 4.1. Furthermore, the regional context appears to exert a larger substantive effect than a country’s own institutions do. Thus, these results lend additional credibility to the argument that the extent of democratic polities in a regional context induces differences in the prospects for conflict and peace. These measures are all tentative attempts to tap into the extent of insecurity or expectations of stable peace prevailing within the regional context surrounding a country. Since these latent aspects cannot be observed directly, the measures inevitably remain approximations based on assumptions that are difficult to validate. The results differ by measures and link function and cannot be compared directly. In spite of such problems of comparison, the consistency across different specifications of conflict is quite reassuring. This strengthens our confidence that the findings stem from more persistent features of conflict and peace rather than any single and arbitrary transformation of the data. Furthermore, it suggests that we can use simple indicators of incidents rather than resorting to more complicated measures that are harder to interpret. Independent or Interactive Effects? The results so far suggest that even if the regional interaction context may in some sense “matter more” than an actor’s own level of democracy, both exert independent effects on the risk of conflict. In fact, by Page 97 →construction equation 4.1 assumes that the contributions of each democracy variable on the prospects for conflict and peace are entirely independent of the other, and the results thus suggest that combinations of the two aspects will yield a net effect that is simply the sum of the two independent contributions. But are these effects really independent of one another or do the two variables interact so that the direction or size of the effects of one variable vary at different levels of the other? Researchers typically resort to multiplicative interaction terms to assess such interactive relationships between variables. In this case, estimating equation 4.1 after adding a multiplicative interaction term between a country’s level of democracy and the regional context of democracy yields a statistically significant coefficient estimate. The interaction term is negative but relatively small, and the individual coefficient estimates for the other two terms are only marginally modified. In this sense, the previous results are not noticeably changed with the standard approach to examining interactive effects. There are several reasons, however, why a multiplicative interaction term may not be the most helpful approach to evaluating interactive relationships between a country’s level of democracy and the regional context of democracy. Statistically, multiplicative terms for continuous variables are often highly collinear with the original variables. Fixes such as centering variables around their means can sometimes reduce this but will in turn change the substantive interpretation of the estimates. More generally, multiplicative terms capture only particular types of interaction. They are not appropriate when the nature of the interactive effects is not linear with respect to the dependent variable or the functional form differs across the range of possible values of the independent variable. This would be the case, for example, if the effect of one variable changes direction or magnitude over different ranges of the other variable. Since a multiplicative interaction term is still constrained to be “linear” in the effects on the log-odds, we risk making inferences about effects over certain ranges of the independent variables that do not actually coincide with the observed data located at those ranges. The generalized additive models introduced in chapter 3 provide a promising approach to exploring interactive relationships between the two democracy variables and the risk of conflict. We can assess any interaction between

a country’s democracy and the regional context of democracy on the risk of conflict nonparametrically by applying a localized smoother to the distribution of the data at certain ranges. I apply a Page 98 →so-called bivariate localized scatterplot smoother, or LOESS (see Cleveland and Develin 1988; and Cleveland, Grosse and Shyu 1993), to fit the likelihood of conflict across ranges of combinations between an actor’s own democracy and the regional context of democracy. I set the span or smoothing parameter to 0.75. This implies a relatively high degree of smoothing, which should pick up strong interactive relationships without being too sensitive to idiosyncracies in the data. I refer the reader to appendix C for further details on GAMs and the LOESS smoother. We can test whether the effects of the two democracy variables appear to be linear by means of a chi-square test for the significance of the nonparametric component.3 The value of the chi-square test is 39.72 with three degrees of freedom for the sample of all conflicts. For the interstate wars sample, the corresponding value is 18.32 at three degrees of freedom. These tests indicate that the likelihood of conflict over the two dimensions of democracy does not seem to display a fully linear surface. We can evaluate the substantive effects of the nonparametric LOESS smoother graphically by plotting the surface of the predicted probabilities of conflict over the two dimensions. Figures 4.2 and 4.3 show the predicted values from the bivariate LOESS smoother for different combinations of democracy along the two dimensions. The leftmost plot displays the predicted surface from the most autocratic angle. In the rightmost plot, the highest values or most democratic internal and external states are located at the front left corner of the graph. Figure 4.2 indicates the effects on the likelihood of all conflict, whereas figure 4.3 indicates the effects limited to the set of interstate wars. The essential shape of the surface seems reasonably consistent irrespective of whether conflict is measured by the full composite category or is restricted to interstate wars only. Figures 4.2 and 4.3 on one level largely confirm the previous conclusions. A more democratic regional context tends to decrease the likelihood of war. Whether an actor is itself democratic generally decreases the likelihood of conflict but has a less consistent effect. However, these plots also indicate that the effects that an actor’s own level of democracy exerts on the likelihood of conflict and that of the regional level of democracy are not fully independent and complementary. The nature and substantive magnitude of one variable can change markedly depending on the value of the other variable, and the shapes of the predicted surfaces have various interesting substantive implications. As can be seen most markedly in figure 4.2, at the highest level of country autocracy in highly autocratic regions there is a stable region where we find the highest log-odds of conflict. In such autocratic settings, there is a modest but almost imperceptible decrease in the log-odds of war as a country’s level of democracy increases from the minimum of –10 to the highly democratic level at 10. If this were true irrespective of the regional context, there would be little evidence of a monadic impact of a country’s own level of democracy. However, the pitch of the surface is actually quite steep within certain ranges of the regional context. As can be seen more easily in the right panes of figures 4.2 and 4.3, for democracies in a highly democratic context the predicted likelihood of war increases quite rapidly the more autocratic a state or the regional context is. Page 99 → Fig. 4.2. Effects of internal and regional democracy on conflict. LOESS with span = 0.75 Page 100 → Fig. 4.3. Effects of internal and regional democracy on interstate war, LOESS with span = 0.75 Page 101 →The slopes over the left axes in these plots demonstrate more systematically that the regional interaction context is substantively more important for the prospects of conflict and peace than the effects of differences in an actor’s own level of democracy displayed in the slope over the right axes. More constrained or democratic polities are associated with a lower likelihood of war only within relatively democratic regional interaction environments. As can be seen from the flat slope or lack of curvature across an actor’s own level of democracy at the low levels of regional democracy, changes in an actor’s own level of democracy will contribute little if anything to reducing the likelihood of war when the regional context is highly autocratic. In regional interaction environments that are relatively democratic, however, we find a more substantial difference in the likelihood of conflict between autocracies and democracies. In addition, there is some evidence indicating that anocracies or polities that combine features of both democracies and autocracies may be associated with a somewhat higher likelihood of war than the most autocratic polities in relatively democratic interaction contexts.

Incidents, Onsets, and Time Dependence Serial dependence between observations in time constitutes another potential threat to the previous results. In chapter 3, I argued that the likelihood of observing a country i experiencing conflict at time t is probably not independent of whether it has experienced conflict in previous years at t – 1. This temporal dependence between observations is likely to lead to serially correlated errors. Serially correlated errors will bias the standard error of the coefficient estimates, typically downward, and can Page 102 →induce overconfidence in coefficient estimates. The apparent strength or significance of the previous results could thus be partly misleading. If prior years of conflict have a negative effect on the prospects for democracy, these results could also be affected by the temporal dependence of both peace and democracy. Since conflict has been assessed in terms of all incidents or the presence of conflict or its absence rather than the onset of new conflicts breaking out at time t, the results may be misleading if ongoing conflict affects the prospects for sustaining democracy. Logistic regression does not yield residuals comparable to those of linear regression with a continuous dependent variable case, so the standard tests for examining whether the errors appear to be serially correlated between adjacent observations over time do not apply. There are few applicable measures to test for serial correlation for limited dependent variable models. Pregibon (1981) suggests inspecting the standardized deviance residuals.4 For the results in table 4.1, the Pearson correlation of the deviance residuals p(di,t di,t-1) is about 0.71. What can be done about serially correlated errors when the dependent variable is binary? Beck and Tucker (1996) suggest a nonparametric approach that allows testing whether data display temporal dependence without having to specify the exact form of time dependence. I control for the impact of the duration of peace on the likelihood that a country will experience conflict by reestimating equation 4.1 as a GAM with a cubic spline smoother of Ti,t or the time at peace a country has experienced up to time t, as explained in chapter 3. I furthermore distinguish between outbreaks and ongoing conflicts and limit the dependent variable to new outbreaks by censoring incidents of conflict after the initial year. The new model of the probability that a country i will experience an outbreak of conflict at time t estimated as a binomial GAM with a logit link can be expressed as where S(Ti,t) denotes the smooth function of time elapsed since either the initial observations or the last observation of conflict involvement. I use three interior knots in the cubic smoothing spline. See appendix C for further details on GAM and the cubic smoothing spline function. The results of estimating equation 4.2 for a sample with the onset of any war and a sample limited to the onset of interstate wars only are displayed in table 4.3. The results indicate that the data display duration Page 103 →dependence, as the likelihood ratio chi-square test indicates that the restriction of no time dependence can be clearly rejected against the alternative hypothesis of time dependence. The plot in figure 4.4 suggests that the relationship between time elapsed and conflict is reasonably monotonic, though not necessarily linear, as additional years contribute increasingly less to reducing the likelihood of interstate war.5 The risk of new outbreaks of conflict decreases consistently with further years of peace up until about 30 years. At this point, the risk of conflict essentially does not change with further years at peace. The line actually appears to increase slightly after about 35 years. However, when we take into account the standard errors for the estimated effect of time at peace on risk, indicated by the dashed lines in the plot, there is no basis for concluding that there are any significant differences in the risk of outbreaks of conflict after 30 years without conflict involvement. For either of the conflict variables, the effect of an actor’s own level of democracy on the likelihood of outbreaks of war becomes considerably weaker and nonsignificant once we control for time dependence and censor ongoing conflict involvement. That is, much of the evidence for effects of an individual state’s level of democracy appears to be associated with ongoing conflicts rather than outbreaks of new ones. The effects of a more democratic regional interaction environment on inhibiting conflict, however, remain significant and quite consistent. The negative relationship between time at peace and the likelihood of conflict displayed in figure 4.4 suggests that the duration of peace is self-sustaining.

Substantively, these results modify the results in the time dimension somewhat, but provide supportive evidence that zones or the distribution of conflict and peace tend to go together with broader zones of democracy over time. There seems to be a strong regional basis to the linkages to conflict and peace in that the regional context of authority structures influences the likelihood of conflict whereas the actor’s own level exerts a less consistent effect on the absence of conflict. For outbreaks of new conflict (excluding states that are experiencing conflict), the effects of the regional context of democratization appear to be the most decisive linkage. In this sense, the main results are upheld again. TABLE 4.3. Authority Structures and the Likelihood of the Onset of Conflict Page 104 → Fig. 4.4. The impact of time at peace on the likelihood of interstate war

Democratization and Conflict in Space and Time Two paradoxes are better than one; they may even suggest a solution. (attributed to Edward Teller) The results so far have shown that more democratic regions and states are less prone to conflict. It is tempting to conclude from this that changes toward greater democracy should be associated with greater Page 105 →prospects for peace. In chapter 2, however, I showed that evidence about stable levels of democracy does not automatically translate into evidence of the dynamic effect of changes in democracy. We must examine the consequences of democratization for the likelihood of war directly rather than trying to extrapolate this from evidence at other levels of analysis. To examine the effects of democratization, I estimate a logistic regression of the probability that country i will experience armed conflict as a function of levels of democracy in country i at time t and moments of change in democracy over a 10 year period. The measures of democratization or change in level of democracy over time were defined in greater detail in chapter 3 and are summarized in appendix E. Whereas previous research considered democratization only in terms of changes in a country’s own authority structures, I here include separate terms for levels and changes in both country i’s authority structures and its regional context or the composition of authority structures in neighboring regimes. I estimate the model all the terms as previously defined. In chapter 2, I suggested that the level of democratization could have different effects on the likelihood of war between states and conflict between state and nonstate actors. I include cases of both interstate and civil or extrasystemic wars but estimate separate regressions for incidents of each as a function of levels and changes in internal and regional democracy. The results for the regression on the incidence of interstate and civil war are displayed in table 4.4. The coefficient estimates in the upper part of the left column of the table indicate how democratization or changes toward greater levels of democracy in a country influence the likelihood of interstate war. The upper section of the table indicates the effects of changes in a state’s authority structures. These results are largely consistent with the findings of Ward and Gleditsch (1998), who conclude that democratization decreases the risk of interstate war. Although the sign of change has a positive coefficient estimate, the magnitude of change and level of democracy terms, in contrast, all have negative coefficient estimates. This is consistent with what we would expect if minor changes toward greater Page 106 →democracy on the Polity scale — if not necessarily changes in democratic polities — could be associated with an increase in the likelihood of war but more substantial democratization of some magnitude enhances the prospects for peace. Given the growth in democratic polities and the trend toward democracy in the sample over time, we are somewhat more likely to observe positive than negative changes over a decade. These results differ from Ward and Gleditsch (1998), however, in that the coefficient for instability or rockiness of change is not only insignificant but has the wrong sign and appears to be negative rather than positive.6 The lower section of the left column in Table 4.4 contains the coefficient estimates for the extension of the previous model to the effects of changes in the regional context of democracy over a 10 year period on the likelihood of interstate war. These coefficient estimates in many ways resemble the effects of changes in a

country’s own set of authority structures. However, the coefficient estimate is now negative for the dichotomous sign of change indicator. As such, we find no difference between different types of changes. This suggests that large and small positive changes alike in the regional context of democracy, as well as prevailing levels of current regional democracy, all tend to reduce the likelihood of interstate war. The coefficient estimate for the extent of instability in the prior 10 years is now positive, suggesting that high degrees of instability or changes that shift back and forth in the regional context increase the likelihood of war. However, the coefficient estimate is not significant. TABLE 4.4. Levels and Change in Authority Characteristics and Conflict Page 107 →Since the covariates in model 4.3 in some sense are direct functions of each other and by their definitions in chapter 3 must be related, it is somewhat hard to assess the expected substantive implications of changes in authority structures on the likelihood of war from the individual coefficients in Table 4.4 alone. To illustrate the substantive implications of the coefficient estimates for the risk of war, I calculate the “net” predicted probabilities associated with a scenario in which a country changes from a perfect autocracy to a perfect democracy over a 10 year period and experiences a transition from a fully autocratic environment to the most democratic regional context over the same period. For simplicity, I assume that the country and its regional context were stable at the starting level and over the prior decade. The estimated probabilities for this scenario preserve the definitional relationship between the variables.7 I plot the surface of the predicted probabilities over the range of possible values along the two dimensions of democracy in figure 4.5. As can be seen from the values of the vertical axis, interstate wars are rare events and the predicted probabilities of interstate war remain quite low throughout. Nonetheless, these results indicate a substantial decrease in the likelihood of war following changes toward greater levels of democracy both in the countries themselves and within their regional interaction environments. The reduction can be seen in the declining shape of the surface at the front edge of the graph, where both dimensions of democracy reach their highest values and the likelihood of conflict achieves its minimum. In addition, this two-dimensional graph allows direct comparisons of the substantive effects of changes along the two dimensions. Contrasting the slope over changes toward greater levels of democracy within the country itself along the right axis with the slope over the left axis, indicating changes within the regional context, reveals that the latter yields a proportionately greater decrease in the likelihood of interstate war. Assuming no change on the other dimension and setting all the other values to zero,8 a change from the maximum to the minimum level of democracy for a country reduces the predicted likelihood of interstate war by about two-thirds. In the case of changes in the regional extent of democracy, the proportional reduction in the likelihood of war is about 90 percent. Page 108 → Fig. 4.5. Democratization and the likelihood of interstate war So far, all of the evidence has indicated that democratization tends to consistently decrease the likelihood of war. I now turn to the effects of democratization on conflicts between states and nonstate actors. The rightmost column in Table 4.3 indicates that the effects of democratization on civil war appear to be somewhat more complex. The results indicate that greater democracy within countries as well as a more democratic regional context are associated with a lower risk of conflict. However, the coefficient estimates for changes in the level of democracy are both positive and indicate an increasing risk that a country will experience civil war. In this sense, the net effect of democratization can be ambiguous given the opposite sign of the two effects. There is also an effect of instability for changes within a country, as high levels of variance in the prior 10 years are associated with a higher likelihood of civil war. How large are the potential risks of civil war associated with democratization? As in the case of interstate war, we may illustrate the effects by means of the predicted probabilities for a scenario in which a stereotypical autocracy changes to a stereotypical democracy, and we observe similar changes in the authority structures within the regional interaction context over a decade. Figure 4.6 is a contour plot of how the estimated probabilities change over the course of such a scenario. The slope of the surface as we move horizontally across the graph lends some support to the likelihood that war may increase as countries democratize. Even though more democracy and a more democratic regional context reduces the risk of war, changes in the level of democracy can be associated

with a higher level of conflict and may offset the pacifying effects of higher levels of democracy, at least in cases that yield end outcomes at low levels of democracy. If we consider figure 4.6 as a map, it can easily be seen that we are “walking uphill” with horizontal movements from changes at the low end of the democracy scale. In addition, the highest probabilities of conflict are associated with anocracies or polities combining features of both autocratic and democratic polities. Page 109 → Fig. 4.6. Democratization and the risk of civil war Moreover, we find a strong effect of the regional context of authority structures. Democratizing states located among relatively democratic neighbors have significantly lower risks of experiencing civil war than do countries located in a zone of more autocratic and less constrained polities. Within highly democratic regions, the risks of civil war from democratization are rather small and always less than 0.1. By contrast, the estimated probabilities reach above 0.22 in the most autocratic regions. Page 110 →These differences associated with qualitatively different contexts are proportionally larger than the differences following changes in a country’s own level of democracy. The predicted values in figure 4.6 are based upon a case with consistent changes toward greater democracy. In this setting, the effects of changes are outweighed by the pacifying effects that higher levels of democracy exert as changes exceed some magnitude. Under higher levels of instability within a country or changes that shift back and forth, however, the variance in levels over the prior decade could conceivably be higher and could outweigh the pacifying effects of greater levels even at higher levels of democracy at time t. The likelihood of civil war would decline at a slower rate at higher levels of democracy or potentially not decline at all. It is difficult to display the probabilities associated with such repeated changes back and forth adequately in a two-dimensional graph. However, we can think of the results across the range of end states for such scenarios as yielding contours that are “less oval” than those in figure 4.6 or do not bend down at the right end of the figure. In this sense, much of the increase stems from political change in and of itself and is unrelated to the character of institutions in and of themselves. This is consistent with what we would expect to find if rocky processes of change and institutional turmoil increase the opportunities for violent political mobilization in cases in which there exist groups in opposition to the state. These findings help clarify the seemingly confusing results in the existing democratization and conflict literature. Although democratization tends to reduce the risk of interstate war, changes toward greater levels of democracy may under certain circumstances be associated with an increased likelihood of civil war. Much of the previous work has conflated the effects on the two types of conflict even though democratization has quite different effects on the likelihood of interstate and civil war. In this sense, the stylized facts of dangerous democratization in some sense were “true,” but Mansfield and Snyder (1995) tried to generalize to the wrong empirical phenomenon when they cast their argument in terms of the risk of interstate war and as a challenge to the dyadic peace between democracies.9 Most of the cases cited in Snyder’S subsequent book (2000: 1–2) are civil rather than interstate wars. Even if democratization may not increase the risk of interstate war involvement, a link between democratization and greater risks of civil Page 111 →war remains substantively important for zones of conflict and peace and whether these coevolve with zones of democracy. If changes toward greater democracy can increase the risk of violent civil war, can regional democratization still be said to enhance the prospects for peace? The answer appears to be a qualified yes since the regional context of authority structures strongly influences the likelihood that democratization will be associated with civil war. The regional context of a state strongly influences the prospects for conflict and peace during democratization processes and is in some sense “independent” of the institutional structures in the country itself. For example, the risk of civil war in India may be related more to proximity to Pakistan than to deficiencies in its domestic institutions. Conversely, regional democratization among neighboring countries may help settle political conflict within states. The above findings also provide a basis for comparing the alternative theoretical explanations of the link between democratization and conflict. I have shown that there is a limited positive relationship between democratization

and the risk of civil war as well as a negative effect on the likelihood of interstate war. These findings seem to be inconsistent with the externalization interpretation presented by Mansfield and Snyder (1995) since a theory relating democratization to pressure for diversionary conflict cannot account for why we see different effects on interstate conflicts and civil wars. The difference in the effects of democratization on interstate and civil wars is consistent with the conjunctural explanation put forward in chapter 2. Greater constraints reduce the likelihood that states will go to war but may increase the likelihood that internal actors will wage war on the state. Regime change and democratization may increase the opportunity for separatist movements and insurgencies that seek to topple a ruling government, but such conjunctures do not increase the risk of interstate war. I have also shown that the regional context of democratization exerts a powerful influence on whether democratization is likely to be associated with conflict. Whereas an externalization hypothesis provides no indication of such an effect, the conjunctural explanation in chapter 2 argues that differences in the constraints on involvement in domestic strife in neighboring countries that executives face influence the likelihood that domestic strife will escalate to interstate war. The transnational dimensions of civil war and internationalized conflicts between state and nonstate actors emerge as very important for this analysis. Page 112 →

Long-Run Relationships between Democracy and Conflict So far, I have shown that zones of democracy go together with variations in regional conflict and peace. However, the notion that zones or regions with clustering of high or low levels of democracy coevolve with clustering in conflict has been examined only in a somewhat indirect fashion and at a fairly high level of aggregation. As such, we do not yet know whether the paths or trajectories that particular regions follow over time display the dynamics that have been inferred from the pooled data. The concept of coevolution suggests a relationship of common trends between sets of variables over time. So far, we have examined the short-term dynamics following changes in the Polity democracy score on the risk of conflict. If zones of democracy were associated with changes in conflict, one would expect to find some immediate relationship between such changes in democracy and conflict. However, looking solely at the first differences may lead us to discard potentially interesting information about the long-run relationship between regional democracy and conflict proneness. Economists suggest that the concept of cointegrated series provides a useful approach for studying the long-run equilibrium between trending series. In technical terms, a time-series y, is said to be integrated on order 1, or I(1), if its first difference, Δyt, is stationary or if its mean or variance does not depend on time. Stationary time-series are integrated on an order of zero or I(0). Two time-series, yt ~ I/(1) and xt ~ I/(1), are said to be cointegrated if there exists some value β such that yt, – βxt ~ I/(0) (i.e., it is stationary). If the series yt and xt are cointegrated, there exists a long-run relationship between yt and xt in the sense that the two series do not drift too far away from each other over time.10 Cointegration in itself is a purely statistical concept, but the idea makes considerable substantive sense here. The idea of coevolving zones suggests a relationship between trends in regional levels of democracy and conflict over time, where changes in the concentration of democracy and autocracy should be associated with changes in the clustering of conflict and peace. The notion of waves of democratization tells us that the distribution of democracy is not stationary but displays clear trends over time. If democracy and peace coevolve, we would expect to see some relationship between such waves of democracy and trends in regional conflict and cooperation. Thus, if these aspects do coevolve Page 113 →over time we should observe cointegration between trends in democracy and conflict within zones of clustering on either extreme of the hostility-compatibility continuum. We observe major conflicts as discrete events. As was discussed in chapter 3, it is not trivial to devise suitable continuous measures of the prevailing latent conflict or extent of insecurity. I argued that localized clustering statistics such as the values of the G*i,t statistics could be used to assess the extent of regional clustering in

conflict around individual observations i. We can thus use the local clustering in consecutive years at peace G*i,t (λt) and the local clustering in democracy G*i,t (Dt) as measures for the trends in conflict or peace and democracy around a country i. Engle and Granger (1987) suggest a two-step test for whether two series yt and xt are cointegrated. The first step is to test for unit roots in the two series. A series yt has a unit root if it is difference stationary and the effect of any shock will lead to a permanent difference in the subsequent values of y. Stated somewhat technically, we have a unit root if the root a in the model is 1 rather than < 1. Here I test for unit roots using the Dickey-Fuller (1979) test of whether the coefficient for the first lag in a regression of the lag on the first difference as well as a time trend yields a coefficient estimate statistically different from 1.11 The null hypothesis in these tests is that the series are I(1). If we fail to reject this hypothesis, we proceed to the second step and test whether a linear combination of yt and xt is stationary or I(0). More specifically, the test consists of regressing xt and a time trend on yt then taking the first difference of the residuals and testing whether the coefficient for the lag of the residuals when regressed on the first difference is equal to –1. The two tests are asymmetric in the sense that the null hypothesis in the first is that the data display a unit root, whereas the null in the second is that the series are not stationary or cointegrated.12 A Tale of Two Regions In chapter 1, we saw that that Western Europe in 1992 appears to be a contemporary zone of peace whereas the Middle East provides a plausible case of a zone of turmoil. If the changes over time within these regions result from a coevolving relationship between democracy and peace, we should expect to find some evidence of cointegration between the clustering of democracy and peace within these two regions. I have run tests for a number of states within the two regions at a variety of Page 114 →different distance thresholds. In the following, I will focus on Belgium and Iran as prototypical or characteristic cases. Since the evidence is the clearest at 475 kilometers, I will focus on this in the discussion. In addition to problems of measurement and selection on the dependent variable, this analysis is plagued with problems of interrupted data on political institutions, which often coincides with the outbreak of wars. The results vary considerably between countries and different context thresholds. For some countries, we reject the null hypothesis of unit roots in the G*i,t (Dt) of localized clustering in democracy or the G*i,t (Dt) of localized clustering in peace. The tests for cointegration are significant only in some of the cases that pass the second hurdle. Nonetheless, the findings are interesting in that we find some evidence suggesting that the two aspects go together over time. To see what cointegration or coevolving trends implies substantively, consider the relationship between the localized clustering in democracy and the localized clustering in peace in the cases of Belgium and Iran displayed in figures 4.7 and 4.8. The G*i,t (Dt) values for localized clustering in democracy are indicated by the dashed line, whereas the solid line indicates the of clustering in time at peace. Figure 4.7 indicates a very close relationship between the two series for Belgium in the period up to about 1905. As the clustering in democracy declines, we find a dramatic decline in the clustering of peace with the outbreak of World War I. We find a large, but temporary, increase in the clustering of democracy following World War I, although this time span is too short for the clustering of time at peace to increase much. The outbreak of World War II seems to be preceded by a large decrease in the clustering of democracy. This is followed by an all time low in the clustering of time at peace, reflecting near universal war involvement in the regional context. In the postwar period, the two time-series generally increase steadily. The high levels of the two toward the righthand side indicates that contemporary Belgium is located in a zone of strong clustering of democracy as well as seemingly stable peace. This outcome seemed far from certain in 1875, when Belgium had a highly divided society and had been the scene of major wars at the outset of the nineteenth century. King Leopold II had no qualms about pursuing a ruthless policy of colonization in Central Africa, and the Belgian Parliament and government were unable to exert much influence over the monarch. Without a regional context moving toward greater democracy, the outcomes might well have looked quite different. Page 115 → Fig. 4.7. Values of G*t for democracy and time at peace, Belgium, 1875–1996 Fig. 4.8. Values of G*t for democracy and time at peace, Iran, 1875–1996

Page 116 →In the case of Iran, displayed in figure 4.8, we find that the values of both of the clustering scores tend to hover around zero for much of the pre-1945 period. In the aftermath of World War II, there is some evidence that both increase, although the localized clustering of democracy begins to drop in 1960 and fluctuates considerably in later years. The fall in the localized values of democracy before the 1980s are followed by a deep plunge in the localized values of time at peace, indicating the First and the Second Gulf Wars as well as various armed insurgencies and civil wars that took place in the regional context. In stark contrast to the case of Belgium, this suggests the evolution of a zone of clustering in conflict and autocracy. These tests are highly tentative, but the two figures provide examples of processes that resemble the evolution of a security community between democracies as well as the transformation of a mixed zone to a region strongly characterized by clustering in both conflict and autocracy. The plots are consistent with what we would expect when zones of democracy precede zones of regional conflict and peace. Given the construction of the time at peace variable, it is problematic to draw any conclusions about the temporal ordering of conflict and democracy from these data. I explore the relationship among conflict and peace and democratization in chapter 6.

Summary and Conclusions In this chapter, I have shown that democracy influences the likelihood of local involvement in conflict and interstate wars and that the relationship between the two appears to be the strongest when we look at the attributes of polities in the broader regional context. How do these findings relate to the stylized facts established in previous research on democratic peace? Is there a monadic peace, suggesting that democracies are generally more peaceful? These results provide some evidence that democracies are less prone to conflict. However, these effects are quite context specific and are only likely to be observed when countries are located in a relatively democratic interaction context. Is the finding that external context matters more a roundabout way of confirming what has sometimes been labeled the “dyadic nature” of the democratic peace (e.g., Rousseau et al. 1997)? The monadic effects of democracy can be dismissed altogether if the effect of a country’s own Page 117 →level of democracy is trivial or nonexistent. However, the findings here do not fully support such a view. Even though the effects of a country’s level of democracy are not entirely consistent across the range of different contexts, their substantive magnitude cannot be dismissed as small across all regional contexts. As can be seen from the bivariate localized regression surface in figures 4.2 and 4.3, the effects of monadic democracy can be quite large within a relatively democratic context. By ignoring the multilateral regional context of interaction, we are unable to see when democracy on the monadic level matters. Shifting the focus to the country and its interaction context provides conceptually clearer inferences about the substantive implications than does a purely dyadic or unspecific monadic focus. Finally, the predicted effects found here are generally larger than the comparable predictions of dyadic or monadic studies. This chapter provides new evidence on democratization and conflict and goes a long way toward explaining the perceived puzzle of discrepant findings in previous studies. Taking the regional context into account, we can reconcile the finding that democratization tends to reduce the likelihood of interstate war with stylized facts of dangerous democratizations or cases in which transitions are associated with civil war. Changes toward more constrained polities decrease the likelihood that a state will become involved in wars with other states, but they may also provide greater opportunities for violent insurgencies that seek to topple the state or government. Although the risks of democratization differ strongly given the regional context of democracy or the composition of regimes for both interstate and civil wars, such regional influences on civil war have so far received little attention in research on contentious domestic politics. These findings seem to be more consistent with explanations linking democratization and conflict to changing political opportunity structures than explanations emphasizing diversionary conflict behavior. These results also suggest that institutional structures are important in themselves rather than because of the normative properties attributed to a democratic political system as we observe a decrease in the risk of interstate wars and civil war attendant upon changes in constraints or institutional structures. Given that norms and a political culture would be expected to develop as political practices become more established over time, we should not necessarily expect to see such changes in the wake of institutional change if the relationship among democratic institutions hinged exclusively on normative aspects.

Page 118 →I have also shown some tentative evidence of cointegration between the G*i,t (Dt) values of clustering in democracy and the G*i,t (λt) for time at peace. This provides additional support, at a more disaggregated regional level, that clustering in authority structure and clustering in conflict coevolve over time. Taken together, these findings are consistent with what we would expect when clusters of democracies are able to reduce the perceived risk of violent conflict in their interactions. Focusing on the threats to security that states face in interactions rather than some unspecific property of “belligerence” provides a clearer indication of the substantive meaning of the relationship between democratic authority structures and conflict and peace and how these coevolve.

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CHAPTER 5 Deutschian Integration and the Democratic Peace In chapter 4, I presented evidence indicating that zones of democracy go together with zones of peace. There is also a clear tendency for a decline in the likelihood of conflict following changes toward greater democracy within regions. Taken together, the findings indicate considerable support for the idea that zones of democracy coevolve with zones of peace. In this chapter, I examine the relationship between Deutschian integration and regional conflict and peace. I furthermore address the relationship among integrative flows and interactions, authority structures, and regional conflict and peace. Many have hypothesized that Deutschian integration and the democratic peace may be related, but researchers differ on the relationship between the two. The purpose of the empirical analysis in this chapter is not so much to establish whether Deutschian integration theory or the democratic peace “explains” something in isolation or which of the two explains the greatest amount of variation in regional conflict and peace. Rather, I am interested in how these fit together, that is, whether one proposition can fully accommodate the facts and observations covered by the other or whether each makes an independent contribution supplementary to the other. At this point, we do not know whether Deutschian integration underlies the seeming absence of war between democracies or whether Deutschian integration and the democratic peace are indistinguishable or separate and distinct phenomena. Finally, I use the empirical results to evaluate some recent claims about prospects for security communities and zones of peace between states that are not liberal democracies.

Regional Integration, Conflict, and Peace Deutschian integration theory suggests that the element of rivalry of security in a region decreases the more integrated states are. As levels of Page 120 →integration become very high, the relations between countries may over time evolve into security communities in which the use of force between states becomes inconceivable as a means of settling disputes. If such processes operate, we should expect to find some covariation between indicators of integration and variations in conflict and peace. A large number of studies have examined linkages between trade and conflict or the evolution of rivalry (see Barbieri 1996; Bennett 1996, 1998; de Vries 1990; Diehl 1998; Goertz and Diehl 1993, 1995; Oneal et al. 1996; Oneal and Russett 1997, 1999; and Sayrs 1988, 1990). Virtually all of these studies, however, are couched exclusively in dyadic terms and research designs. I argued in chapter 2 that the relationship between integration and conflict depends critically upon the actual location of actors. Greater trade linkages with actors elsewhere in the system may not advance a country’s security if the extent of integration with neighboring countries remains negligible. The relationship between integration and the prospects for conflict and peace may depend upon third parties and larger regional networks. Relating the density of integration at the regional level to conflict provides a better way to approach the processes emphasized by the Deutschian theory of integration. I measure Deutschian flows or integrative interactions by means of the density of trade relations and the relative extent of cooperative and conflictual interactions between entities in a state’s regional context. (See chapter 3 and appendix E for further details on the sources of data and construction of these measures.) Do higher levels of regional trade and a greater density of cooperative interactions predict less conflict and greater prospects for peace? I assess this issue by estimating a logistic regression on the likelihood of conflict as a function of state i’s regional trade density and mean regional conflict and cooperation scores as defined in chapter 3. We can represent the model symbolically as all the terms as defined in chapter 3 and summarized in appendix E. The estimated results for equation 5.1 using a critical distance threshold of 950 kilometers for samples of interstate wars and all conflicts as the dependent variables are displayed in table 5.1. The available data limit the feasible

sample to the period 1948–92. Most notably, the Page 121 →Penn World Tables are currently only available for the postwar period and lack values for many polities and time periods. The sample size is thus considerably lower than for the empirical analyses in chapter 4. The results of equation 5.1 in Table 5.1 indicate that regional contexts with higher regional trade densities and greater shares of cooperative interactions appear to be associated with a significantly lower propensity for conflict. This is consistent with what we would expect to find if the density of such integration flows is indicative of the expectations of conflict and peaceful change prevailing among actors in the region. Similarly, the nature of the interstate interactions within regions is associated with clear differences in the risk of conflict as well. In this sense, there seems to be a clear relationship between the revealed compatibility of states within regional interaction clusters and the likelihood that they will experience violent conflict. The results are statistically significant and qualitatively similar for both incidence of interstate wars and the composite category of both interstate and civil wars. Levels of statistical significance aside, what do these coefficient estimates imply for the marginal effects of integration on regional conflict and peace? Although the difference in predicted effects along the full range of possible values for the density of trade or conflict-cooperation scores would appear to be quite dramatic, it is evident from the distribution of the two variables that most observations fall within a relatively restricted range of the possible values. To extrapolate predictions for extreme values of trade densities and conflict-cooperation scores might thus be substantively misleading since they are so infrequent. I therefore restrict the predicted marginal probabilities to a “reasonable” range of values for the two variables or where the bulk of the data lie. More specifically, I consider the marginal effects on war over differences in conflict-cooperation scores ranging between – 5 and 5 and the marginal effects for trade densities varying between 0 and 0.2. The substantive marginal effects over these plausible ranges of values on the independent variables are plotted in figure 5.1. As can be seen in the figure, the substantive implications of the predicted effects are quite large over the range. As the interactions between states become relatively more cooperative, the likelihood of conflict declines by several orders of magnitude. Although the absolute levels of predicted probabilities of conflict are considerably smaller for the more infrequent incidence of interstate war, the implied differences in prospects for regional peace are still proportionately quite large. In the case of trade, we can see that countries located in regional contexts with higher trade densities appear to face considerably smaller proportional risks of conflict. The coefficient estimates in table 5.1 yield differences in the risk of war of a magnitude comparable to those found in dyadic studies as well as the results inferred for the effects of authority structures in chapter 4. TABLE 5.1. Integration and the Likelihood of Incidents of Conflict Page 122 →The finding that greater economic interdependence, as measured by the extent of trade, is associated with peace is certainly not novel or unprecedented. These findings differ from those in dyadic studies by relating the extent of interdependence to relations between states in the regional context. This is important for assessing the implications of trade for the security of states. Norway and Nigeria may have a relatively large volume of bilateral trade,1 but variation in this trading relationship is unlikely to exert much influence on the risk of conflict in either state given the great distance that separates them. By contrast, South Korea may have a large total trade yet it has negligible trade with North Korea with which the risk of conflict is substantial. Given the emphasis on measures of the density of local economic linkages rather than global trade, these results provide a more relevant approach to the direct implications of trade for the prospects for regional conflict and integration. The linkage drawn between the nature of intergovernmental relations and the likelihood of local conflict is somewhat more unorthodox. Since the most extreme case of rivalry on the conflict-cooperation scale defined in chapter 3 would be virtually all out war, it might be contended that these results verge on the tautological. Some skeptics might surmise that this finding merely indicates that as states come to hate each other to a significant extent conflict becomes more likely between them. This is in a sense “correct,” but it overlooks the fact that there is a flip side to extreme forms of conflict as well. All cases of absence of overt hostility are far from substantively equivalent. There is a large qualitative difference between a regional interaction environment in which parties just coexist and an integrated regional context. Affinity and integration can be socializing forces on state behavior, potentially as strong as those of conflict. Integration can transform relations within regions, alleviate the perceived rivalry of security in their interaction, and provide a feasible solution to security dilemmas. Many states display

values on the local conflict and cooperation score indicating that relatively cooperative interactions dominate. Page 123 → Fig. 5.1. Likelihood of conflict by extent of compatibility and density of regional trade Do these results hold up with different distance specifications and alternative measures of conflict that incorporate decay over space and time as well? The estimated results using alternative distance threshold criteria and measures of conflict tend to be qualitatively similar and are not shown for considerations of space. The estimates seem to be relatively consistent across different distance threshold specifications, although the Page 124 →coefficient estimates for local trade in some cases do not achieve statistical significance at very restrictive distance thresholds or less comprehensive definitions of regional context. This lends additional support to the notion that differences in regional integration may underlie variation in the more persistent aspects of conflict and peace. On a summary assessment, the clear effects on variation in conflict and its absence uncovered here suggest that the idea of integration — even measured on a fairly crude basis—as a source of differences in regional prospects for conflict and peace has some merit. Regional Integration, Time Dependence, Conflict, and Peace So far, I have provided evidence of a relationship between levels of indicators of integration and variations in regional conflict and peace. If zones of higher levels of trade and greater affinity between parties tend to be associated with peace in terms of the absence of war, we would expect that changes toward greater trade and compatibility should predict to prospects for conflict and peace. A cross-sectional association does not necessarily mean that the same relationships hold for changes over time. Thus, these findings do not necessarily demonstrate that changes in integration precede changes in the risk of conflict. To assess whether greater integration reduces the likelihood of conflict, I estimate the likelihood of conflict and peace as a function of changes in Deutschian flows over the preceding five years. More precisely, I consider the difference in the density of trade and mean of state interactions between time t and t – 5. Even if the specific length of the time period is somewhat arbitrary, we should expect to observe a negative relationship between increases in integration over time and the likelihood of conflict.2 This can be represented symbolically as where ΔTRi,t and ΔCERi,t indicate change over a five-year period in the density of trade and the regional conflict and cooperation score between time t and t – 5, respectively. The estimated results for equation 5.2 using a critical distance threshold of 950 kilometers are displayed in table 5.2. The results in the table indicate some support for the idea that Page 125 →changes in Deutschian flows predict to differences in the prospects for conflict and peace. Changes toward more cooperative interactions are associated with a decline in conflict, measured by both incidence of interstate war and the composite category of conflict. The coefficient estimate for changes in the density of trade is positive and highly significant for the full set of conflict involvement. The coefficient estimate for changes in the density of trade score for the restricted set of interstate wars has the correct sign but is much smaller and falls short of statistical significance. It might seem puzzling that changes in the density of trade should be associated with a lower propensity for conflict in general but not decrease the risk of interstate war. Some may be tempted to dismiss the relevance of this discrepancy and attribute the difference to the larger number of events in the composite category. However, the coefficient estimates are very similar if we exclude all interstate wars and limit the dependent variable to civil wars.3 I have suggested that “civil wars” often display external dimensions. The extent of Deutschian integration prevailing between adjacent states indicates something about the type of resources that actors can mobilize at the domestic level and within the broader region. Integration is indicative of what forms such external influences upon domestic conflict are likely to acquire. Low trade may go together with mistrust and tension between states and a willingness to support insurgencies and thus systematically covary with the likelihood that domestic conflict will escalate to violent rather than nonviolent forms of action. Outside support from other states might obviously aggravate conflict, and such external influences can be critical to prospects for the success and failure of insurgencies. The end of Syrian support led to severe difficulties for the

Kurdish separatist organization PKK’s campaign in Turkey in the late 1990s. Conversely, a positive integration may help reduce the likelihood that many contentious issues will escalate to violent domestic conflict. Consider the potential implication for the conflict in Northern Ireland of integration between the United Kingdom and Ireland. Improved relations between the two central governments could lead the Irish central government to exert more pressure to restrain the use of force by militant republicans. Similarly, transnational linkages between actors in Ireland and the United Kingdom could induce pressure for peaceful political change among actors with some power over radical unionist and republican groups. In sum, Deutschian integration opens avenues for exerting political influence by means other than violence. The previous results do not in themselves prove that such dynamics obtain, but they are consistent with what we would expect if this were the case. TABLE 5.2. Likelihood of Conflict as a Function of Changes in Deutschian Flows Page 126 →If the baseline probability for interstate war is so low that predicting “peace” or its absence is more trivial, the relationship between changes in regional integration and a more inclusive category of conflict, including civil war, could be considered substantively more important. The relative costs of waging war on nonstate actors (or, alternatively, for nonstate actors to wage war on states) are lower than the costs of waging war between states. These considerations led Rummel (1979) to conclude that international relations are generally more peaceful than domestic politics. In one sense, integration might actually be more important in preventing conflict involving nonstate actors than in conflict between states.

Regional Integration, Democracy, and Conflict The foregoing analyses suggest that Deutschian integration seems to be associated with variation in regional conflict and peace. However, the relationship between integrative flows and political institutions has been left open. In chapter 2, I noted that many see a democratic and a Deutschian peace as related through virtuous cycles of reinforcement. Others hypothesize that the effects of democratic institutions largely stem from higher integration and affinity between states rather than democracy per se. Finally, each component may add something that is at Page 127 →least partly independent of the other. Given the limitations of existing empirical research, however, we know relatively little about the relationship between the two. There are a couple of different ways in which the Deutschian and the democratic peace can be compared to determine whether one offers any additional empirical content over the other. First, one could conduct some nonnested test based upon the likelihood of two separate models, such as the Cox test (1961, 1962), to assess which of the two displays the greatest “verisimilitude” or provides the best fit to the data. This would be a reasonable alternative if we insisted that the two were necessarily in contradiction, so that one could only be true at the expense of the other (of course, both may also be “false”). It is clear from chapter 2, however, that clearly these two perspectives cannot be said to constitute “incommensurate paradigms” in a Kuhnian (Kuhn 1970) sense, as neither entails central assumptions that cannot be reconciled with those of the other. This is not to say, however, that one perspective logically implies the other. A more interesting question is whether the covariance “explained” by either of the two perspectives can be subsumed under the other or whether these explanations provide reasonably independent contributions to the prospects for regional conflict and peace. I assess this by extending equation 5.1 to additional terms for a country’s level of democracy as well as the regional context of democracy. Chapter 2 alluded to the idea that a general political similarity effect might induce “security communities” between similar states that are not necessarily liberal democracies (e.g., Bebler 1987; Oren and Hays 1997; Peceny 1998; Weart 1998). The Polity institutional democracy data set is not a fully symmetric measure of similarity for autocracies.4 At the extreme, fascist and communist states can obviously be very “different” even if both have institutions that are autocratic. These problems of measurement, however, are somewhat less acute when we look at regions, as autocracies within regional clusters tend to be of similar structure and orientation. Thus, if the similarity proposition is correct we would expect to find a lower propensity for conflict and peace among polities with little dispersion among institutions in the regional context. In this study, I assess this

hypothesis empirically by adding a term for the dispersion or variance in authority structures, denoted SRi,t as a measure of the extent of similarity between entities within an interaction cluster. Accordingly, I estimate a logistic regression model of incidents of conflict Page 128 →as a function of the indicators of Deutschian integration, international and regional democracy, and similarity among institutions in a region. This can be expressed as

all the terms as previously defined and summarized in appendix E. The results using a critical measure of 950 kilometers for determining relevance are shown in table 5.3. The estimated coefficients in the table are all in the hypothesized direction. The coefficient estimates are all statistically significant, with the exception of the dispersion in authority structures, which is significant only for interstate wars. More importantly, the coefficient estimates are largely consistent with the results presented earlier in this chapter as well as those presented for authority structures in chapter 4. These findings are broadly consistent with the view that more constrained polities as well as higher levels of Deutschian integration flows reduce the likelihood of conflict. Although Deutschian integration and relatively more democratic authority structures may be associated, whatever influence one appears to exert does not merely stem from a failure to consider the other. Rather, each element appears to provide some degree of independent contribution to the prospects for regional conflict and peace and neither can be fully reduced to the other. The regional basis of such linkages is evident in the foregoing results. As in chapter 4, the regional context of democracy exerts a substantially larger effect than a country’s own level of democracy does. We find a positive coefficient for dispersion among institutions, indicating that greater variation or regional heterogeneity appears to be associated with a higher risk of conflict. As such, there is some evidence of a homogeneity effect that cannot be reduced to the extent of democracy in a region alone. The estimate, however, is not significant for the composite conflict category. TABLE 5.3. Deutschian Flows, Authority Structures, and the Likelihood of Conflict Page 129 →These results take into account some aspects of spatial dependence between states and their regional context but not the temporal structure. Conditions associated with protracted and ongoing conflict are not necessarily reliable ex ante predictors of new disputes. To gauge whether these results seem to display vulnerability to such overconfidence, I reestimate the regression equation 5.3, adding a smooth term for prior time at peace, s(λi,t), where s denotes a cubic smoothing spline as explained in appendix C. The dependent variable here is restricted to outbreaks of new disputes, and all cases of ongoing disputes beyond the first year are censored. Symbolically, the equation can be represented as The results of estimating equation 5.4 are displayed in table 5.4. The data appear to display duration dependence, as the likelihood ratio chi-square test on the difference in deviance over the null model indicates that the time trend provides a statistically significant contribution to the model.5 In addition, we can conclude from the chisquare test for s(λi,t) that the shape of the duration dependence of peace does not appear to be fully linear, though the estimated shape of time dependence is reasonably monotonic. The estimated shape of time dependence is qualitatively very similar to that found in figure 4.4. To preserve space, I simply refer to that figure for a stylized plot of the shape of the effect. This indicates that the likelihood of conflict declines rapidly during the first years but that additional years at peace contribute increasingly less after the first time period. Thus, the previous conclusions about the self-sustaining and enduring aspect of conflict and peace over time still hold, Page 130 →despite the differences in variables, models, and the temporal and spatial domain of the sample. What are the implications for the coefficient estimates of the other variables and how do they differ from those in table 5.3? As in chapter 4, many of the previous results are attenuated when we control for time dependence and focus on new outbreaks. Although the sign of the estimated coefficients remains in the hypothesized direction, many estimates in table 5.4 – most notably the term for trade – are no longer significantly different from zero and their effects seem to be quite time dependent. The estimates for local conflict and cooperation as well as the regional dispersion of institutions remain significant for interstate wars but seem less consistent when we consider

all conflicts. This reflects, in part, the greater persistence of civil compared to interstate wars. We thus have fewer outbreaks and more censored years with ongoing conflict. The regional extent of democracy retains a significant effect, decreasing the likelihood of conflict of either type. The coefficient estimate for a country’s own level of democracy, however, is no longer statistically significant. What are we to make of these results? From table 5.3, we know that greater levels of trade and state affinity appear to be associated with differences in regional conflict and peace. In this sense, trade as an indicator of Deutschian integration is associated with zones of peace. However, once we distinguish between ongoing conflicts and outbreaks much of the association appears to pertain to ongoing conflict and does not necessarily translate to the likelihood of new conflicts.6 In this sense, it is questionable whether trade flows “lead” to or are causally prior to peace. TABLE 5.4. Deutschian Flows, Authority Structures, Time Dependence, and War Onset Page 131 →However, trade flows and economic linkages are not necessarily devoid of any importance for the prospects for regional conflict and peace, as trade linkages may help sustain peace over time. Trade may be indicative of “conditions of peace” associated with an absence of war even though differences in levels of trade may not differ much between initial conflict years and the nonconflict years once we censor subsequent years of conflicts.7 Similarly, we may surmise that conflict inhibits regional trade once it is under way. These results for economic interdependence and time dependence are broadly consistent with those of other dyadic studies (Beck and Tucker 1996; Gartzke and Jo 1998). Given the problems with data here and with trade as a measure of interdependence, these results must be interpreted with caution.8 The implied relationship between institutions and conflict seems quite consistent with our findings in chapter 4. Controlling for time dependence and censoring ongoing war, the coefficient estimate for the regional context remains substantively and statistically significant whereas the effects of a country’s own authority structures become weak and nonsignificant. Zones of democracy are thus not only negatively associated with conflict, but states in such zones are also significantly less likely to experience outbreaks of new conflict. Furthermore, regional authority structures are more susceptible than integrative flows to changes in the short term, which may require some degree of trust and may evolve quite slowly over time. What exactly do these coefficient estimates imply with respect to the combined effects of integrative flows, interactions, and political institutions for regional conflict and peace? Figure 5.2 shows the predicted marginal effects of each variable, holding all the other variables at their means or medians as appropriate. To preserve space, I collapse democracy and the regional context in a joint composition of authority structures category.9 Even though the proportional reduction in likelihood of conflict following changes from the low to the higher end of the range of plausible values might be relatively large, the baseline probabilities are quite low and the absolute probabilities on the vertical axes of the figure are all generally low. Since the predicted marginal change in probabilities of new conflicts at the most extreme values of each variable is so low, must we conclude that these effects matter relatively little? At this point, we need to consider whether these variables tend to go together and reinforce one another over time and space. In this sense, a more interesting matter than gauging the marginal effects of changes in one variable in isolation at some arbitrary or “average” baseline will be to examine how the propensity for conflict varies according to specific combinations of authority structures and integrative flows in a regional interaction cluster. Page 132 → Fig. 5.2. Marginal effects, holding other variables at mean (or model values One way to assess these implications is to examine the predictions for a stylized “best-case” and “worst-case” scenario. In the former, a country is located in a highly democratic and interdependent regional context characterized by compatible interactions. The latter corresponds to an autocratic and heterogeneous interaction environment with little trade and predominantly hostile interactions. The proportional difference Page 133 →between the point estimates for each setting is quite dramatic. The worst-case scenario is associated with a probability of conflict of about 0.53. The predicted likelihood of war in the best of worlds is less than 0.00005 or

for all practical purposes zero. These predicted values, however, do not take into account the uncertainty associated with the statistical model. King, Wittenberg, and Tomz (2000) point to two forms of uncertainty in the predictions from statistical models that have been neglected thus far. First, these predictions involve estimation uncertainty reflected by the standard error of the estimated parameters in the model. In addition, there is some element of fundamental uncertainty associated with the stochastic component of the model. The uncertainty of the point estimates of interest in a model can be approximated using numerical simulation. King, Wittenberg, and Tomz suggest simulating a large number of draws of parameter estimates from a multivariate normal distribution with means equal to the estimated coefficients and ancillary parameters and variance equal to the observed variance-covariance matrix V. We can then use the distribution of the simulated draws to infer both the mean or central tendency of estimates given combinations of right-hand-side variables and the uncertainty of estimates by assessing the variance around the mean. I simulate 20,000 draws from a multivariate normal distribution based on the estimated results presented in table 5.3. To preserve space, I will focus on the results pertaining to incidence of interstate war only. The plots in figure 5.3 display the probability density estimates for the likelihood of war under several qualitatively different scenarios. The plot in the upper left quadrant illustrates the estimated probability distribution for the likelihood of war in a best of worlds scenario in which a democracy is located in a highly integrated and democratic region. As can be seen from the values on the horizontal axis, the estimated probabilities for such a case tend to be extremely low. Furthermore, the spread of the density is very restricted, reflecting a very “sharp” distribution of estimates. In cases in which democracies are located in a regional context of other democracies, levels of regional trade are high, and cooperative interactions dominate within the region, we can infer that war is unlikely with a very low degree of uncertainty. In contrast, the plot in the upper right quadrant illustrates the density of estimates for a converse case of a worst of all worlds scenario, with an autocratic polity located in a regional context with negligible integration and other autocratic polities. The estimated probabilities of conflict look dramatically different, and the bulk of the mean estimates lies well above the area where the probability of conflict exceeds that of its absence. The likelihood of conflict is much higher in the least fortunate case, but the distribution of estimates also displays a much wider spread. In this sense, although conflict is much more likely in a worst of worlds case, the point estimates are associated with considerably more uncertainty. Not surprising, conclusions may be quite erratic from one sample to another. Page 134 → Fig. 5.3. Density of estimates given authority structures, similarity, and integration The two plots in the lower row indicate estimated probabilities associated with mixed scenarios or combinations of values at the extremes of the two dimensions. The thickest of the two lines in the plot in the lower left quadrant indicates the probability of conflict associated with a highly constrained regional context, holding the other variables at their average or modal values. By contrast, the thinner line displays the Page 135 →distribution of estimates associated with a highly integrated regional context, holding authority structures at their mean values. The probability of conflict remains consistently relatively low in either case, although the density of the estimated probabilities in the integrated case displays somewhat greater dispersion. The thicker line in the plot in the lower right quadrant indicates the estimated probabilities associated with a scenario for a constrained but highly nonintegrated, regional context. The thinner lines indicate the associated estimates for an integrated yet highly autocratic region. As can be seen, although the estimated probabilities of conflict are considerably higher, they remain fairly marginal in comparison with the worst-case scenario. The density of estimates for the constrained region remains relatively sharp and has a much lower mean than the shape of the distribution for the integrated autocratic regional context. Even though these results indicate that a worst-case scenario in which regions are both autocratic and nonintegrated is associated with a very high likelihood of conflict, the results also indicate that regional context

high on either democracy or integration but low on the other could still be relatively peaceful. A highly democratic regional context could be peaceful even if states lack widespread economic integration and have divergent views on a number of issues. On the one hand, a third-wave democracy could be as peaceful as a firstwave one, provided that it is located in a consistently democratic regional context. On the other hand, highly integrated regions could also be less prone to conflict even when the states are not necessarily liberal democracies. Does Democracy Correlate with Deutschian Integration? Whether these predictions about such best and worst of all possible worlds scenarios are reasonable hinges critically on the plausibility of observing such combinations of values in the data. We can assess more systematically to what extent Deutschian flows covary or go together with greater democracy or more constrained polities by means of so-called conditioning plots (see Cleveland 1994). The basic idea is to graphically evaluate the covariance between sets of variables by generating a series of bivariate scatterplots of variables, xi and yi, while conditioning on a third variable, zi These plots can help us detect whether the association between xi and yi is stable over different ranges of values for the third variable,zi. Page 136 →For our purposes, we can use such plots to assess whether conflictual and integrative interactions and trade flows are as closely associated as the notion of integration would indicate and to what extent these go together with more democratic institutions. The panel of graphs in figure 5.4 displays how the density of trade within an interaction cluster and the values on the conflict-cooperation scale covary at different levels of the regional context of democracy. More specifically, the six sub-plots show the distribution of observations along levels of trade densities on the left and the extent of conflict and cooperation at different intervals for levels of regional democracy. The subplots are arranged in increasing order of more constrained authority structures from the bottom left corner to the upper right. The three horizontal bars below the dashed line indicate the ranges of values for the three subplots in the lower row. The pane in the upper display at the top of the graph indicates the intervals, or range of values for the regional composition of authority structures, that each of the six subplots covers. As can be seen from the bar in the lower left corner in the horizontal pane on top of the figure, the leftmost plot in the lower row corresponds to values between – 10 and 6. This is the range of values on the institutionalized democracy scale that Gurr et al. (1989) use to identify individual polities characterized as “coherent autocracies.” In contrast, the rightmost plot in the upper row corner corresponds to observations with values ranging between 6 and 10 on the composition of institutionalized authority structures. These correspond to the range Gurr et al. and others use to demarcate polities as “coherent democracies.” Figure 5.4 suggests that there is some evidence that both trade densities and average conflict-cooperation scores tend to be lower for states located in clusters with low levels of regional democracy. The secular mean of either variable also tends to increase somewhat with democracy. However, the association between the nature of interactions and the density of local trade is not particularly strong in the aggregate. Only within the most democratic regional context do we find clear evidence of a linear association between the two. We thus find some evidence of a possible “Kantian” community of liberal republics for states in strongly democratic regions. However, the extent or scope of such zones at present seems to be somewhat limited. It is also more dubious whether changes in one of the components alone can drive an entity toward a Kantian peace by inducing higher values on the other components as well. Page 137 → Fig. 5.4. Conditional covariance plots for Deutschian flows and authority structures These graphs also reveal that the trade to GDP ratios used as indicators of trade densities appear to be rather skewed, with a few observations having relatively extreme values. From the construction of the measure, it is clear that this may not be a well-behaved indicator of interdependence. This ratio not only will be high when the levels of trade with neighboring countries are high, but it will increase as the size of GDP decreases, holding the absolute volume of trade constant. An inspection of the observations with trade densities above 0.5 reveals that cases with very high local trade densities indeed comprise a heterogeneous set of states located in regional interaction clusters that otherwise seem

qualitatively quite different. This group encompasses some relatively unsurprising cases of seemingly integrated countries such as Belgium and Luxembourg. These are both wealthy states with extensive trade and in some sense classical examples of high interdependence, Page 138 →with “integration” reflected in high values on the regional conflict and cooperation scale. However, in this group we also find Cuba (in the years prior to the revolution), Libya, Singapore, and Taiwan. The latter two are developing societies with open economies that are engaged in extensive foreign trade. The very high trade densities are not supported by evidence of integration in interstate relations within the region, as these states display neutral to strongly negative values on the localized conflictcooperation scale.10 Prerevolution Cuba is a classic example of regional asymmetric dependence on a dominant state. Map 1.5 indicates that the bulk of clustering in high trade densities in 1992 occurs in Europe and Western Europe in particular. Since trade densities are relatively low elsewhere as well, it appears that much of the evidence that a higher degree of economic interdependence is associated with a lower propensity for war or peace derives from the European experience. Although Western European states have engaged in conflict elsewhere in the international system, it was after all the peaceful relations between these countries that provided the main motivation for Deutsch et al. ’s initial work on security communities (1957). Thus, the potential for interdependence as a source of future zones of stable peace is in many ways a question of whether developments in Europe can be replicated elsewhere.

Similarity, Democracy, and Community As discussed in chapter 2, recent work has suggested that security communities may emerge between integrated states that are not liberal democracies. These findings provide a basis for commenting on the feasibility of such zones of peace outside Europe. Even if no regions outside the North Atlantic display markedly high levels of integration and peace, these results can be interpreted as supporting the notion that zones of stable peace can develop between countries with extensive trade and similarity, even if they are not liberal democracies. The example most frequently mentioned is probably the case of the Southeast Asian ASEAN countries. Until recently, these states generally experienced sustained economic growth and often are said to share a common set of Asian values (e.g., Adler and Barnett 1998; Kacowicz 1998; Kivimaki 2001). Creating a “zone of peace, freedom, and neutrality” has in fact been an explicit goal of the organization, which was Page 139 →launched at a ministerial summit in Kuala Lumpur in 1971 (e.g., Ciprut 1996). At this point, it might be helpful to hark back to Deutsch’s distinction between so-called no-war communities, those with an absence of overt conflict, and fully integrated “security communities” as sets of states where the use of conflict has become inconceivable and can be avoided through the parties’ mutual expectations of peaceful change. Most observers seem to agree that aspects associated with security communities other than the mere absence of overt war do not seem to obtain at the present, and most applications tend to emphasize the potential for ASEAN to “eventually” become a security community (e.g., Adler and Barnett 1998). Some of the major conflicts and security concerns that have characterized the region, such as the Indochina wars, may be partly attributed to the “overlay” of the superpowers. If this is the primary cause of the violent turmoil in the region, the end of the Cold War might bring enhanced prospects for peace and regional integration. Of course, using the future as evidence involves a host of potential problems, and such counterfactuals must be judged according to more clearly identified standards. Tetlock and Belkin (1996: 16–31) propose six criteria for evaluating counterfactual arguments more systematically. They emphasize that valid counterfactuals must satisfy conditions of (1) clarity, (2) logical consistency, (3) historical consistency or the “minimal rewrite” rule, (4) theoretical consistency, (5) statistical consistency, and (6) projectability, that is, whether testable additional observable implications seem consonant with observable facts. Assuming that the first five criteria can be said to be satisfied in the case for ASEAN as a future security community, it is less clear that the projectability criterion will be met in light of recent events. First, it is not obvious that the ASEAN countries currently can be said to display even the weaker condition of a no-war

community. Second, the high levels of armaments and military preparedness in the region are clearly not consonant with emerging expectations of peaceful change in the absence of direct superpower involvement (e.g., Ciprut 1996). Clearly, many of these countries are armed to the teeth and substantially increasing their military capabilities. Not only has the region seen extensive conflict in the recent past, but many of the countries are ridden with protracted internal conflict. In many of these countries, ethnic religious groups, such as ethnic Chinese and Christian or Muslim minorities, exist on either side of national boundaries. This situation is further complicated by the fact that Page 140 →in many cases groups persecuted in one country are dominant in others and there are strong asymmetries between the political and economic power these groups wield. Such “houses divided among themselves” are unlikely to be associated with peaceful relations among state entities or social groups (e.g., Gurr and Moore 1997; Wolfson 1995). Current events in Malaysia and Indonesia and the increased emphasis placed on human rights at ASEAN meetings seem to indicate that any developments toward integration in all likelihood also will involve some form of advance in political rights or a process of democratization throughout the region. Security communities and liberal democracies are not necessarily related or inseparable in a logical sense. Yet the idea of a security community built on Asian instead of liberal values may remain only a hypothetical counterfactual since it is hard to see how widespread integration could take place and not be associated with some form of political opening or democratization in the region. My own guess is that changes toward more democratic forms of governance in many ways seem more feasible within a relatively short-run time span than does the evolution of a peaceful community built on shared “Asian values.” Similar considerations seem to apply to other cases of suggested no-war communities among nonliberal states. Cohen (1995), for example, claims that conservative Arab states have been able to maintain peaceful relations. The Middle East obviously cannot be said to constitute a “zone of peace” given the pervasive conflicts between Israel and its Arab neighbors. In all fairness, it must be conceded that Cohen’s point is that some dyads other than jointly democratic ones also appear to be peaceful. Leaving aside the issue of whether this claim is correct, to derive from this meaningful inferences about political similarity as a condition for zones of peace would require the counterfactual assumption that the prospects for war between Arab states in the Middle East also would have been negligible in the absence of Israel as a common unifying enemy. This seems somewhat dubious given the obvious lack of amity in the relations between such Arab states as Iraq, Syria, and Kuwait. The events surrounding the Second Gulf War revealed much of this discord between Arab groups and movements. Similar tendencies can be seen in the case of the Yemeni civil war that followed the 1990 unification. Without the unifying influence of opposition to Israel, many inter-Arab relations would conceivably have been even more conflictual. In few places does the “enemy of my enemy is my friend” logic apply with greater force than in the Middle East. Others, like Kacowicz (1998), have suggested that parts of Latin Page 141 →America (and the Southern Cone in particular) have been “zones of peace” since the end of the nineteenth century. This claim first disregards a series of internal conflicts. Kacowicz, for example, excludes Central America from the Latin American zone of peace, “given the internationalized character of the civil wars” in the region, but similar considerations would also seem to apply to much of the domestic turmoil, repression, and conflict found elsewhere on the continent.11 Second, conflicts with “external powers” such as the Falklands/Malvinas war are deemed irrelevant to the South American zone of peace. More importantly, Kacowicz disregards the Chaco war between Paraguay and Bolivia in the 1930s. This is especially problematic since this conflict is a contender for the dismal distinction of being the bloodiest interstate war of the twentieth century, as measured by the Paraguayan losses relative to its total population (Small and Singer 1982). Others point to the fact that there have been no international wars between any two developed socialist countries (e.g., Oren and Hays 1997). This hinges critically on excluding incidents such as the 1953 uprisings in Berlin, the 1968 intervention in Prague, and the 1956 invasion of Hungary, which is considered an interstate war in the COW war data. Although there is some evidence that the extent of integration or transnational relations between states in Eastern Europe might have been relatively high during the socialist era and the Cold War, these linkages proved to be quite fragile and tended to break down quickly after the fall of state socialism. This underscores the ways in which the effectiveness of forms of integration may hinge on the extent to which different ranges or dimensions of

integration coincide. High levels of affinity or integration between national governments may prove to be quite vulnerable when state structures suffer from a fundamental lack of popular legitimacy. The issue of international and civil war and whether zones of no war, as the absence of interstate war, alone are significant is crucial here. Kacowicz (1998) suggests that western Africa constitutes a zone of peace since there have been so few international conflicts between states in the region. Western Africa is a surprising candidate for a zone of peace since countries such as Liberia and Sierra Leone often are associated with anarchy and the collapse of state power (see Kaplan 1997 for a popular account). In addition, much of the civil conflict prevailing in western Africa is clearly partly internationalized, as may be seen in Nigeria’s interventions in many ongoing civil wars. Even if these cannot be said to be integrated communities in the Page 142 →Deutschian sense, it may be argued that such cases deserve interest as no-war communities without interstate wars. Our images of Africa as a zone of turmoil build largely on civil wars. In fact, according to the COW data (Singer and Small 1994; Small and Singer 1982) only two incidents in Africa after decolonization are considered to have been international wars, namely, the Tanzanian invasion of Uganda in 1978 and the Somali-Ethiopian conflict over Ogaden in 1977–78.12 The implicit assumption here is that the duration of an absence of war observed in the postindependence period is unlikely to be observed by chance alone. Kacowicz (1998) does not attempt to compare this to some explicit baseline expectation in order to assess the extent of deviation. Many scholars in this line of research seem to exaggerate the amount of interstate war and its prevalence in the interstate system. Interstate wars are rare events, and the modal observation for entities in the international system at any given point in time is “peace” or the absence of war (e.g., Gates and McLaughlin 1996; Rummel 1979). Lemke (1997) shows more systematically that the amount of interstate war in Africa indeed seems to be less than the expected value given the number of borders alone. However, he attributes the absence of war between states to a lack of interaction opportunities and low levels of capability and holds that most African dyads simply are not “politically relevant” with respect to the likelihood of international war for much of the study period. This lack of interstate war may come as surprise to many, since African countries combine many of the conditions believed to be associated with the potential for interstate conflict such as divided ethnic groups, unresolved border claims, authoritarian governments, and poor economic performance with ample incentives for diversion. The notion of Africa as a zone of conflict with a great potential for diffusion led many of the initial studies of diffusion to focus on this case.13 Deutsch (1977), however, points out that much of the literature holding that African borders are arbitrary since they fail to coincide with ethnic groups misses a very central point. Colonial borders were drawn around city centers and marked the boundaries of the areas that could effectively be ruled.14 In this sense, these boundaries reflect the limits of the coercive powers of the colonial state. They are generally also close to the limits of where the postindependence states can wage war without major advances in infrastructure and technology. Even though the availability of military technology has increased since independence, contemporary Page 143 →fighting in states such as Congo still differs markedly from warfare in a European context. Kacowicz (1998) posits his study as an attempt to uncover “necessary and sufficient” conditions for zones of peace. However, he does not explicitly discuss the possibility of a trivial condition for regional peace, namely, the lack of opportunities for conflict between very weak states with poor infrastructure despite common borders.15 Ironically, “the incompetent state,” which lacks the capacity for waging war against other states, may well be a sufficient condition for the absence of war involvement. This is not only a trivial condition for an absence of interstate war, but any definition of conflict that requires the main antagonists to be sovereign nation-states excludes the modal type of conflicts in developing societies (e.g., Ayoob 1991). These results illustrate the importance of conceptualizing conflict in empirical research and considering data and measurement relative to the hypothesis of interest. The existing literature imposes a problematic distinction between “external” and “internal” conflict and does not distinguish between belligerence and regional security. Many wealthy or more developed states are clearly belligerent in the sense that they participate or intervene in

conflicts elsewhere in the system. Such forms of conflict, however, do not necessarily place the security of these states at risk. In contrast, many states in developing societies have few resources with which to engage in warfare beyond their borders and have seldom been involved in clear-cut cases of interstate conflict. Cuban intervention in the Angolan conflict contributed to escalating civil war and insecurity in Angola, but it did not necessarily expose Cuba itself to risk. To say that countries such as Angola do not experience violent conflict and threats to their vital security because they are not involved in interstate wars, however, verges on the meaningless. These problems have marred much of the discussion of zones of peace outside of the North Atlantic area.

Deutsch and the Democratic Peace: Conclusions In this chapter, I have examined the relationship between regional integration and the prospects for regional peace as well as the relationship of integration to linkages between authority structures and conflict. There is indeed some evidence that differences in the density of regional trade Page 144 →and the affinity between states are associated with zones of regional peace and conflict. In addition, increases in the regional density of trade and a change toward more cooperative interactions between states also appear to be associated with improved prospects for peace in a regional interaction cluster. However, the relationship between trade density and the absence of conflict seems to display considerable duration dependence. Thus, although trade may be a condition of peace, it is less clear whether outbreaks of conflict are associated with systematic differences in trade. Much of the seeming association appears to stem from low trade densities in conflicts already under way. The nature of prevailing interactions, however, is consistently associated with the presence of conflict as well as outbreaks of new conflicts. In addition, political similarity or heterogeneity is also associated with variation in regional conflict and peace. Despite all the caveats with respect to problems of measurement, these results yield considerable support for the idea that the extent of integration between states may be associated with systematic variation in regional conflict and peace. Furthermore, variation in observed regional integration does not appear to render the effects of more democratic authority structures on regional conflict and peace without importance. The two components appear to provide separate contributions, and zones with more constrained polities do not seem to be associated with peace merely because of a failure to control for patterns of integration and compatibility between states. Moreover, there is some evidence that integration and authority structure may not be as closely associated as the proponents of virtuous cycles as well as many critics of the democratic peace have contended. At an empirical level, these components appear to be both separate and to a large extent autonomous. More specifically, democracy and integration seem to coincide primarily among the members of the Organisation for Economic CoOperation and Development (OECD) and there are few examples of interdependent regional contexts outside Europe and the OECD countries. At the same time, there is more variation in political institutions outside Europe that appears to be associated with regional conflict and peace. This suggests that zones of peace may develop outside the North Atlantic region through constrained institutions even in the absence of widespread integration. This partial autonomy between authority structures and integration also lends some support to the idea that Page 145 →integration and affinity associated with peaceful relations can also arise between entities that are not necessarily liberal democracies. I have examined the case for some of the most common contenders for nondemocratic peaceful communities in greater detail and find the evidence wanting in several respects. Most proponents seem to argue the potential for such communities in the future rather than positing that they currently exist. Although it is hard to establish that something is impossible, I contend that it seems dubious whether many of the required developments seem particularly likely or less implausible than prospects for change in the composition of authority structures. In this sense, integration may be quite important for the prospects for stable peace over time, but it is less clear whether widespread integration is likely without progress in democratization.

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CHAPTER 6 Wealth, Conflict, and the Diffusion of Democracy In this chapter, I will examine how various factors influence political structures and the likelihood that states will experience political change. Whereas most previous analyses have focused on the relationship between political institutions and attributes and processes internal to countries, the international dimensions of democratization will figure prominently in this chapter. In previous chapters, I have examined some hypothesized consequences of democracy and political institutions for international behavior. In these analyses, the distribution of authority structures between countries was treated merely as given and exogenous. The descriptive analyses in chapter 1, however, suggested that both the distribution of authority structures and changes in them over a 10 year period appear to cluster geographically in a nonrandom fashion within the international system. In this chapter, I examine the hypotheses outlined in chapter 2 on the relationship between domestic political authority structures and the regional interaction context. I have on the one hand argued that authority structures can diffuse among states. Similarly, I have argued that regional conflict and insecurity, which I have shown diffuses among states as well, can impede the prospects for democratization. I assess these international effects and evaluate their importance relative to the effects that may be attributed to a country’s level of economic wealth, the primary domestic aspect emphasized by the so-called social requisites of democracy tradition. In chapter 2, I argued that associations between variables and levels of democracy do not necessarily translate into effects on the transition to democracy. As was noted in chapter 1, however, there is some evidence that the variance of authority structures appears to cluster geographically in a nonrandom fashion, too. I will here examine the issues of transitions directly and show that it is implausible that the changes observed in the Page 148 →distribution of democracy over time can be attributed to the consequences of domestic processes alone. However, whereas some have inferred that “democracy appears exogeneously as a deus ex machina” (Przeworski and Limongi 1997: 159) or is entirely random, I show that the regional context in which countries are located provides an important element predicting to the likelihood of transitions and changes in political institutions. On the basis of such international dynamics, we should not expect to find strong and structurally stable relationships between domestic attributes of authority structures over time.

Democracy and Democratization in Time and Space Numerous empirical studies have examined variation in the distribution of political institutions. Most of these have focused on various forms of the social requisites hypothesis associated with Lipset (1960) or examined whether there is a tendency for wealthier countries to be more democratic (e.g., Bollen and Jackman 1985b; Cutright 1963; Lipset 1994; Lipset, Seong, and Torres 1993; see Vanhanen 1990 for a review). On a summary assessment, this research indicates that there is a relatively strong positive association between a country’s level of development and its propensity to be democratic. This holds for most samples of countries at any given period in time. However, for various reasons that will be explained shortly, it is less clear whether the causal inference that commonly is drawn from this — that greater economic development “causes” or precedes transitions to democracy — actually obtains as strongly as many have assumed. Although such studies on the relationship between democracy and various social and economic conditions hypothesized to be associated with democracy may differ considerably in several ways, they are similar in two key respects. First, they examine exclusively domestic processes and effectively treat the distribution of democracy as independent between countries.1 Second, most rely on a purely cross-sectional research design and fail to distinguish between relationships to levels of political democracy and the dynamics of democratization or change over time. I will discuss these issues in greater detail later.

If the idea of diffusion of authority structures within regions discussed in chapter 2 has some merit and countries are influenced by neighboring entities, we would expect to observe a positive relationship between Page 149 →the regional composition of authority structures and a country’s own political institutions. In the following, I will examine empirically whether there appears to be evidence of such a positive relationship between a country’s level of democracy and the composition of authority structures prevailing in its regional interaction context. The notion that authority structures may be influenced by international aspects rather than purely domestic factors has gained considerable popularity in recent work (e.g., Huntington 1991). However, relatively few empirical analyses have examined the importance of diffusion between countries at the local level. In addition, most efforts to analyze cross-national diffusion of democracy and authority structures (see O’Loughlin et al. 1998 and Starr 1991) have largely disregarded the potential influences that domestic attributes and processes may exert. Merely reporting an aggregate relationship between a country’s authority structures and the composition prevailing within its regional context does not in and of itself provide evidence of diffusion. In all likelihood, there is comparable geographical clustering among the other social and economic conditions hypothesized to influence democracy. Analyses that ignore domestic aspects altogether are thus vulnerable to the criticism that whatever is attributed to diffusion of authority structures may simply stem from geographical clustering in the domestic attributes hypothesized to influence the prospects for democracy. The primary hypothesis emphasizing domestic processes is obviously the so-called social requisites hypothesis or the proposition that democracy is related to a country’s level of socioeconomic development (e.g., Lipset 1960, 1994). In a previous study (Gleditsch 1996), I tried to compare the influences of diffusion and socioeconomic development on democracy more systematically. However, this study was conducted on a relatively limited sample of countries and time periods and relied on the controversial Freedom House data (e.g., Gastil 1985) on political rights and civil liberties (for an overview of these criticisms, see Bollen 1986, 1993; and Hartman and Hsiao 1988). Furthermore, this study suffered from problems of nonsystematic coding of proximity, or “closeness” between entities, based upon subjective assessments of each individual case. A replication over the longer time span and with the new and improved data on distance seems warranted. In addition to the possibilities of diffusion of political institutions, in chapter 2 I also introduced a second hypothesis on international influences on a country’s domestic authority structures pertaining to diffusion Page 150 →of conflict and insecurity. The idea that “conflict” qua participation is incompatible with democracy in and of itself is obviously too simplistic and patently incorrect. Yet the hypothesis that the initial emergence of democracy may depend on the extent of conflict or external threats provides a more plausible link and point of departure for a better-specified empirical test. In chapter 2, I argued that it is the persistence of insecurity over time rather than single cases of conflict involvement at an instance in time that can inhibit the emergence of democracy. In addition, a proper test of this hypothesis must distinguish between localized conflict or threats to security at the local level and conflict involvement elsewhere in the international system. I argued that connecting this argument more clearly to the local interaction context and how this develops over time provides a clearer specification of the linkages and threats deemed relevant in Thompson’s (1996) case studies. If these hypotheses have some merit, we would expect to observe a relationship between the stability of peace in a country i’s regional context as measured by G*i,t T and its level of democracy. Most studies of democracy have relied on largely cross-sectional designs. Therefore, the variance in these studies is predominantly between countries rather than variation within countries over time. However, most researchers are interested in the likely implications of changes in the independent variables over time. In many cases, researchers make inferences about the prospects for democratization from cross-sectional evidence. Though rarely saying so explicitly, most have tended to assume that the temporal dynamics simply would be mirror images of the cross-sectional differences between countries. In principle, however, there is no logical connection between the two empirical domains, and it can easily be shown that inferences about temporal dynamics based on crosssectional variation can be misleading if the two are not identical (e.g., Brunner and Liepelt 1972; Smith 1995).2 The relative lack of longitudinal studies on democratization is probably due in part to constraints on computation and data. Most measures of democracy have until recently been available for a single year or relatively short time periods.3 The basic point that the dynamics of democratization cannot be directly inferred from levels or the

distribution of democracy at a given point in time, however, appears to have received little attention in this literature. Although various, more historically grounded studies have examined Page 151 →changes in democracy over time (see, e.g., Moore 1973), many of these rely on unsystematic methodologies in their inferences. Many point to how researchers engaging in macrocomparative historical studies often rely on rather controversial historical interpretations as unambiguous and indisputable evidence (see Goldthorpe 1991, 1994; and Lustick 1996). The cases examined in these studies are far from random samples and are usually selected to illustrate a theory or because the cases themselves motivated the theoretical argument in the first place. Others criticize the extreme determinism in many of these studies, in which class constellations and events that took place several decades, if not centuries, earlier are held to fully determine current regime structures (e.g., Przeworski and Limongi 1997). Many other longitudinal studies of democratization do not evaluate the dynamics of the development and democracy thesis directly (e.g., Lichbach 1984). Bollen (1979) examined whether the timing of development underlay the contemporary relationship between development and democracy for a sample of countries in the 1960s, but he did not evaluate the effects of changes in development over time. The end of the 1980s marked a new series of studies on democracy and development with greater emphasis on incorporating variations over time. Many of these studies were critical of the development and democracy thesis and indicated that the relationship between change and development was modest at best or that there were large variations between countries (see, e.g., Arat 1988; and Gonick and Rosh 1988). Some of these studies, however, failed to address the problems the pooled structure of the data poses for analysis. A more sophisticated study by Burkhart and Lewis-Beck (1994) using a panel of 130 countries between 1973 and 1994 found considerably more support for the development and democracy proposition. As will be demonstrated in greater detail later, even though their estimates may be statistically “valid,” the treatment of the temporal component in this study essentially amounts to purging the serial correlation of observations over time from the data before the analysis.4 Thus, the Burkhart and Lewis-Beck study probably under-states the extent of permanence in the data over time. This in turn may have led to exaggerated inferences about the expected changes in democracy following changes in the level of development or income. In the following analysis, I will take the extent of stability in authority structures over time directly into account. Page 152 → Conflict, Diffusion, Wealth, and Democracy How does the distribution of democracy vary more systematically with income, aspects of regional context, and the extent of conflict that has prevailed in a country’s regional interaction environment? To assess this issue empirically, I regress a country i’s level of democracy at time t on the natural logarithm of its GDP per capita in purchasing power parities at time t, the regional level of authority structures at time t, the stability of peace in the polities surrounding i, and i’s level of democracy in the preceding year. These covariates are denoted Di,t In (Pi,t), G*i,t (Tt) and Di,t-1 respectively. Symbolically, we have the regression equation all the notation and measures as defined in chapter 3 and summarized in appendix E. In the following, I will focus on the results of estimating equation 6.1 using a minimum distance threshold for a country’s regional interaction context of 950 kilometers. A couple of issues in equation 6.1 must be addressed before we proceed to the empirical results. First, the rationale behind using the natural log of GDP per capita income may not be obvious. Many researchers have suggested that the relationship between GDP per capita and level of development is unlikely to be linear, as a given absolute increase probably constitutes a comparatively greater change when per capita income is low (see Burkhart and Lewis-Beck 1994 and Jackman 1973). On the basis of these arguments, I use the natural logarithm of the level of development. This is obviously a somewhat arbitrary transformation, and of course other types of nonlinear functional forms are possible (see, e.g., Jackman 1973 for a more extended discussion). Some have

included an additional a square term of GDP per capita (e.g., Przeworski and Limongi 1997). We may expect that effects conceivably could differ in magnitude at different levels of GDP per capita income. Yet, as we nonetheless would expect effects to be monotonically increasing at higher values of GDP, this specification seems to be theoretically inappropriate. A square term will force the effect of additional GDP per capita to become negative beyond some flex point, but no one has suggested a reason why additional income above some threshold should be associated with a lower level of democracy. Page 153 →The motivation for including the level of democracy in the previous year may not be immediately obvious. The inherent temporal ordering within a set of annual observations for some country i, Di,t Di,t-1 Di,t-2 Di, t-j implies that it would be tenuous to assume that these annual data points are independent. Rather, since the nature of authority structures rarely change from one year to another, these observations are likely to be highly associated. If this temporal dependence between the observations is not taken into account in a statistical model, the errors of the model will be serially correlated and the coefficient estimates as well as their standard errors will be inconsistent and biased. There is strong reason to suspect that correlation between the residuals is likely to induce overconfidence in the statistical results presented here. The variance-covariance matrix V of the coefficient estimates for a model is given by –1. Generally stated, we have an autocorrelated error structure whenever Ω is not an identity matrix I and the expected value of the offdiagonal entries ωij are not all zero.5 This implies that the error terms for different observations are correlated rather than independent of each other. Several solutions have been proposed to address the problem of serial correlation in a continuous dependent variable setting.6 One possibility is generalized least squares (GLS) techniques that try to model the correlationstructure Ω explicitly (e.g., Greene 1997; Hsiao 1986). Such estimators can be shown to yield consistent estimates and have various desirable asymptotic properties. Obviously, the “true” structure of Ω is generally not known. As a result, in practice the researcher will have to resort to some hypothesized estimate of the correlation structure . Accordingly, the implementation of such estimation procedures on these grounds is more appropriately referred to as feasible generalized least squares (FGLS). Although there are a number of plausible alternative structures, by far the most common solution for applied settings in the social sciences is to assume that the error structures follow either AR(1), MA(1), or ARMA (1,1) processes. Under an AR(1) structure, the specific correlation between two residuals εt, εt-j reflects a common correlation coefficient |p| < 1 as well as the temporal distance between the observations. Hence, cor (εt, εt-j) = pj Although the serial correlation is always larger than zero, for longer temporal distances the serial correlation will become Page 154 →increasingly smaller and negligible. Under an MA(1) structure, the distribution of the error term incorporates the values of prior residuals εt-1 in addition to the stochastic component μi, so that . Many analysts try to derive some estimate of ρ from the autocorrelation of the residuals in an ordinary least squares (OLS) regression and address serial dependence by subtracting the autoregressive component and then test whether the estimated residuals from the model appear to be white noise. There are a number of problems with such procedures. Since the properties of GLS hold only asymptotically, these may not obtain in an actual limited sample situation. Thus, it does not follow that GLS techniques necessarily will be generally more efficient than OLS in applied settings. Beck and Katz (1996) provide Monte Carlo simulation results indicating that feasible generalized least squares estimates are not generally more efficient than regular OLS regression with some minor corrections to control for autocorrelation and heteroskedasticity, at least under the properties of data common in comparative cross-national studies of political institutions. More importantly, even if purging the serial correlation might be an adequate statistical solution with respect to the consistency of the estimates, the approach can easily be analytically misleading since the resulting estimates will fail to reflect the degree of impermanence or autoregressive structure of the data. Stated differently, we are likely to exaggerate the substantive implications of changes in the right-hand side variables on the dependent variable if we simply subtract away the autoregressive element before the analysis and interpret the resulting coefficients. Beck and Katz (1995, 1996) argue that the extent of persistence of time in the data should be considered pertinent

information about the phenomenon under study rather than a mere nuisance and an impediment to statistical estimation. A term with the first lag of the dependent variable will, under quite general conditions, be sufficient to remove the serial correlation from the errors, and this parameter can be interpreted substantively as a measure of the degree of persistence over time or “stickiness” in the dependent variable. In the analysis that follows, I heed their advice and include the first lag of the dependent variable on the right-hand side of equation 6.1. The pooled nature of the data is also likely to invalidate the assumption of homoskedasticity or that the variance in the expected values of the error term is constant between observations. We have heteroskedasticity if the entries on the diagonal of Ω are not identical but vary in size. Page 155 →In this setting, nonconstant variances or heteroskedasticity are likely since the model probably will not fit all countries equally well. We might surmise, for example, that some of the larger countries, such as the major powers, may display greater inherent variation in level of democracy and be somewhat less sensitive to conflict, the regional interaction environment, or aspects of socioeconomic development. If this is the case, these observations may display greater variance in the residuals than other entities do. Under heteroskedasticity, the coefficient estimates themselves may not be biased, but the standard error estimates will no longer be efficient. White (1980) showed that a consistent estimate of σ2Ω under very general conditions could be obtained by a socalled sandwich estimator, Sw, or diagonal matrix with the squared estimated residuals of the regression on the diagonal. MacKinnon and White (1985) developed this further and suggested some alternative estimators. One of these, known as the “jackknife” estimator,Smw, weights the diagonal entries (/1 – ) according to the influence that each observation exerts on the coefficient estimates, as measured by the diagonal elements of the hat matrix, H.7 On the basis of performance in simulation experiments, Davidson and MacKinnon (1993) suggest that the jackknife estimator Smw tends to perform better than the original White estimator Sw in small samples. The results of estimating equation 6.1 are displayed in table 6.1, with heteroskedastic-consistent standard errors based on the jackknife estimate. These results indicate an almost direct correspondence between the level of democracy in the previous year and that of the current year, as reflected in the 0.96 coefficient estimate for the term. Substantively, the estimate suggests that a country’s level of democracy is extremely unlikely to change from one year to another and that there is a high degree of persistence in authority structures over time. Therefore, variation in the explanatory variables is unlikely to be associated with dramatic effects on the level of democracy, at least in the short term. This estimate for the autoregressive parameter corresponds almost perfectly with the estimated value in a similar analysis (see Gleditsch 1996), with a different panel, using the Freedom House data on democracy and a distinct set right-hand-side variables in the model. Hence, the high degree of permanence indicated here cannot be dismissed merely as an idiosyncratic feature of the Polity data but should be seen as an actual feature of political structures. Of course, dichotomous indicators of “democracies” and “nondemocracies” or discrete regime categories would display even greater persistence than the relatively continuous Polityinstitutionalized democracy scale. TABLE 6.1. Regression of Level of Democracy on Regional Context, Wealth, and Conflict Page 156 →The finding that authority structures tend to be very persistent over time might be seen as trivial. However, empirical studies based upon time-series data that do not take this permanence into account are likely to overstate the influence of the exogenous variables. This appears to characterize much of the existing research and the inferences that have been made from the results. I will address the issue of changes and transitions in greater detail shortly. The coefficient estimate for the other right-hand-side variables are all in the hypothesized direction and statistically significant at conventional levels. As in previous research, there is a positive association between the natural log of a country’s GDP per capita in purchasing power parities and its level of democracy. However, if we consider the metric of the variable it is evident that the actual implied differences following differences in per capita GDP are relatively limited. The values for per capita GDP in PPP in 1985 constant dollars vary between $221 and $31,969 in the sample. The higher value limit, however, is somewhat misleading since the distribution is so highly skewed. The largest values stem from a few select percentiles with rather unrepresentative countries.

Notably, some of the oil-producing countries in the Middle East display very high per capita GDP values, although these do not necessarily correspond to many of the aspects attributed to “developed societies.” By comparison, per capita GDP in 1990 for the United States is about $18,000 in constant figures. This figure corresponds to a natural log of about 9.8. If we take the difference between the minimum GDP values and the values corresponding to developed OECD countries Page 157 →in Western Europe and North America as a more reasonable upper limit, we can see that the coefficient estimate actually translates to a relatively marginal predicted difference between the very poorest and richest societies. The predicted difference in level of democracy for a country at the low end and the high end of the level of development scale as measured here turns out to be less than a full point on the overall institutionalized democracy scale.8 Furthermore, attributes such as per capita GDP or economic income are likely to remain relatively static or display changes slowly over time. Consider a developing society with a per capita GDP of about $2,000 – roughly equivalent to Spain in the 1950s or Guatemala in the 1970s. If we assume that this society was to experience a sustained real growth rate of about 7.5 percent annually, even over a period of 20 years, its per capita GDP would grow “only” to about $8,500. The predicted implied difference in the country’s propensity for democracy would increase only marginally as a result. Some may blame the measure of wealth or development used in this study for the seemingly weak association found here. The concept of “development” is often used in a much broader sense than an increase in the monetary value of economic output, including factors such as economic diversification, levels of education, and at time even the legal status of women and minorities. It has been argued that any proper test of the economic development-todemocracy hypothesis should include various other indicators of economic development as alternatives to per capita GDP or additional variables (see Gasiorowski 1988). However, proposed composite indexes of development typically lack a coherent theoretical foundation and are often not comparable over time. Adding a series of alternate variables of indicator in the same regression would induce massive multicollinearity and unstable inferences. The other social and economic aspects hypothesized to be important for democracy, such as material inequality (e.g., Muller 1995), are likely to display even less change over time than per capita GDP. It is unlikely that these would display a stronger association with authority structures over time. Of course, it may be contended that any such changes in the level of democracy are expected to be gradual and thereby should be reflected in changes in past values as well. Lichbach (1984), however, finds that such gradual transitions do not appear to have been the rule in the evolution of European polities. As a summary assessment, there are strong reasons to expect that Page 158 →the impact of development may have been overstated in many previous studies. Transitions to democracy cannot be directly predicted on the basis of level of development alone. At the same time, low levels of income or wealth need not render transitions to democracy impossible or ruin all prospects for sustaining democracy. Studies that do not take into account persistence in time in this sense appear to have exaggerated the impact of domestic economic conditions. If social requisites alone cannot account for variations in democracy among states, can we do better if we take the regional context into account? The coefficient estimate for the regional context of democracy would seem to be negligibly small. However, the range of the metric for this variable is considerably more restricted than that of per capita GDP, and the distribution actually covers the entire span of possible values. As such, the difference over reasonable ranges of this variable turns out to be of a magnitude that is comparatively at least as large as the potential implications of variation in per capita GDP. In addition, the regional context of authority structures is more susceptible to change over time. The feasibility of variation over a short time period is obviously much greater for the regional context of democracy than most social and economic attributes are. Shocks and large-scale regional transitions may not be common, but such large shifts in values can and do occur. This indicates that the regional context of democracy can be substantively more important than economic development, especially when changes in polities elsewhere in a region may diffuse into adjacent countries. Although the high degree of persistence over time might make it somewhat of an exaggeration to say that this model can “predict” diffusion of authority structures, the estimated coefficient values are consistent with such “waves” of diffusion among states. Finally, Table 6.1 indicates some evidence of a positive relationship between a country’s levels of democracy and the geographical clustering in peace within its regional interaction context, as measured by . Stated differently,

countries located in more peaceful interaction environments tend to display more democratic authority structures than countries located in regional contexts in which threats to security are more pronounced, as was hypothesized by Thompson (1996). To my knowledge, this constitutes the first empirical evidence for a negative relationship between conflict or insecurity and democracy. Why do the results here differ from those found in previous work indicating no relationship or a positive relationship between democracy Page 159 →and peace? Most studies have disregarded the qualitative differences between different types of absence of war and have failed to distinguish between localized conflict and general belligerence in terms of conflict involvement. In addition, previous studies have examined whether incidents of conflict involvement exert an immediate impact on authority structures, although the effects of threats on the prospects for democracy go beyond the individual incidents and stem from more enduring aspects of insecurity. A combination of these problems could easily wash out relationships between security and democracy. Although there are numerous problems of measurement, this study gives some support to the notion that there are broader substantive linkages between authority structures and conflict than just the democratic peace proposition. Levels of significance aside, as in the case of level of economic development, the relationship among conflict, peace, and the prospects for democracy does not appear to be as strong as some have surmised. Based upon the values in the aggregate data, I will consider variation between — 3 and 5 as the range of feasible values on G*i,t (Tt Over the full range of differences in regional contexts, the predicted differences in authority structures for countries located in highly conflictual compared to relatively peaceful regional contexts are still relatively limited. The magnitude of the effects here might be understated due to problems with the measure of insecurity and the fact that missing economic data exclude many developing societies where such conflict and insecurity linkages to authority structures are particularly likely to apply.9 Domestic or International Conditions: A Thought Experiment What exactly do these coefficient estimates imply with respect to the likelihood that countries will become democratic over time? If we assume that the continuous values reflect some form of latent propensity for a country to be a democracy (with values above six indicating the propensity to be democratic), we can examine the associated likelihood that a country will be democratic over time as a function of changes in the associated righthand-side variables. Now consider the case of a country starting out at a per capita GDP of about $2,000 and assume an annual growth rate of 5 percent, keeping the other values at zero (which is roughly similar to the aggregate means). Even over a 40 year period the predicted value on the continuous scale does not reach the threshold at which a country would be considered to be “democratic.” Page 160 → Fig. 6.1. Predicted levels of democracy under a transition experiment Consider then a different scenario in which a country has the same growth rate but during the first 10 years is located in a zone of protracted conflict containing polities with low levels of political democracy. Then assume that — following some external shock — we see democratization in neighboring polities coevolving with a decrease in threats reflected in gradually increasing years at peace in the regional context until the end of the period. What would the associated predicted propensity for democracy look like for a country that starts out with the most autocratic type of authority structures and then experiences changes in the properties of its location toward a more democratic and peaceful context? I plot the estimated values for this scenario in figure 6.1. As can be seen in figure 6.1 the predicted prospects for democracy decline at first, reflecting a situation in which protracted conflict and regional autocracy are perpetuated in the regional context. Following the exogenous shock in the regional context in which the country is located after the first 10 years, however, the estimated underlying propensity increases quite dramatically. Toward the end of the period, it eventually reaches the threshold value of six for “democracy,” indicated Page 161 →by the dashed line. This example is admittedly somewhat arbitrary, and different starting values and assumed changes over time would of course yield different predictions. However,

this hypothetical thought experiment shows that the distribution of democracy is unlikely to change as a result of parallel domestic social and economic processes within societies alone. Rather, changes are in all likelihood influenced by external factors and “shocks” in the structure of interaction and the composition of attributes in a state’s regional context. International influences or the regional context can exert very important influences on a country’s authority structures. These factors can both work independently and support or countervene other domestic economic, political, and social processes. Although we cannot conclusively predict what aspects local interaction environments will acquire or the distribution of exogenous shocks, we can make better-informed predictions if we know something about how these aspects change.

Political Transitions and Persistence in Time The analysis so far indicates that although both international influences and domestic conditions appear to be significantly and consistently associated with levels of democracy, the autoregressive component or persistence over time in authority structures is so large that the additional effects of other covariates appear to be relatively limited. The findings here are consistent with and largely replicate those of Gleditsch (1996). Other recent analyses relying on somewhat different approaches, such as that of Londregan and Poole (1996), have similarly found that the relationship between changes in development and democracy over time seems to be relatively weak. Gleditsch and Ward (1997) showed the relative lack of variance in data on authority structures more generally by means of a rather different approach. Suggesting that changes in authority structures over time can be analyzed as a Markov chain process,10 Gleditsch and Ward showed that the observed unconditional probabilities of transitions in the Polity III data were rather low. Even over very long time periods spanning up to several decades, the observations for a given state tend to remain at the same state of authority structures. Figure 6.2 displays the estimated first-order transition probabilities with the full democracy scale based on the updated Polity data. The rows of the matrix, or the values on the left axis, indicate the state at time t – 1, while the columns or values on the right-hand axis indicate the state at time t. As can be seen, almost all observations fall on the diagonal, and the ondiagonal entries are never lower than 0.86 for any single state on the 21 point democracy scale. Page 162 → Fig. 6.2. Observed first-order Markov transition probabilities Although it is not readily apparent from figure 6.2, there is some tendency for the transition values to be somewhat higher for the “anocracies,” which combine features of both autocracies and democracies, in the middle of the range. This yields some support to Eckstein and Gurr’s (1975) so-called congruence theory of authority structures, which holds that incongruous anocratic polities are less stable and tend to become more consistently autocratic or democratic over time. If we power the first-order matrix a large number of times, we find greater concentrations at the extremes of the institutionalized democracy scale. The expected values from the estimated first-order transition probabilities over a time span of 30 years are displayed in figure 6.3. The figure clearly indicates two main peaks of concentration or stability in the density of the expected transition probabilities over a period of 30 years, located at the extreme poles of autocracy and democracy. The probabilities that polities will remain at these two stages over a period of 30 years are 0.52 and 0.81, respectively. In the middle ranges, the likelihood of observing no change over three decades is generally less than 0.2. As such, even the seemingly static relationships of the estimated first-order transition probabilities do indicate greater differences in the long-term expected stability for polities over time as well as some indications as to where polities with different combinations are likely to drift over time. “Perfectly” consistent autocratic and democratic polities tend to remain coherent over time, whereas anocracies combining elements of both are likely to become either more autocratic or more democratic over time. The asymmetric shape of the surface of the off-diagonal entries reflects the secular trend toward greater levels of democracy over the eighteenth and nineteenth centuries. The number of autocratic polities that have experienced changes toward greater democracy exceeds the number of polities that have experienced changes in the opposite direction toward more autocratic forms of governance. Page 163 → Fig. 6.3. Estimated first-order Markov transition probabilities at time t + 30 Page 164 →

A Markov Process Specification of Transitions So far, I have examined the raw or net transition probabilities over time alone. We can extend the Markov chain model to derive conditional transition probabilities given covariates of interest. Przeworski and Limongi (1997, esp. 178–83) use a Markov chain process representation of transitions to estimate the conditional likelihood of transitions between regime types from one year to another given a country’s per capita GDP or level of development. Przeworski and Limongi’s (1997) results indicate little effect on changes resulting from differences in level of development. On the basis of this finding, they take a considerably more radical position than merely characterizing the relationship between development and transitions to democracy as weak. Rather, they insist that no relationship exists between development and the likelihood of transitions to democracy. Any association that may appear to exist between development and democracy stems, according to them, from differences in the ways in which economic performance influences the survival of different types of regimes. Regimes are held to be endogenous to performance in the sense that growth or increasing development enhances the survivability of democracies.11 Furthermore, performance is relatively more important for the survival of democracies than autocracies. Autocracies are considered to display a “bell-shaped” curvilinear pattern of instability and are most likely to be replaced at moderate levels of performance. Although these processes may induce an apparent relationship between development and democracy, transitions to democracy are in themselves unrelated to economic performance. In fact, Przeworski and Limongi (1997) claim that regime change is fully exogenous (meaning that there are no systematic causes of transitions to democracy) and simply emerges as a deus ex machina. In the following section, I will demonstrate, using a modified conditional Markov model, that this claim is incorrect. This is the case because a very strong relationship obtains between regional context and the likelihood that countries will experience transitions. A Markov Model of Transitions and Regional Context By estimating the probability of transitions from one year to another conditional on the spatial context of democracy, we can gauge the importance Page 165 →of spatial diffusion or association in a country’s interaction environment and directly compare this with the results in Przeworski and Limongi (1997). Przeworski and Limongi reiterate the arguments in Alvarez et al. (1996) in defense of dichotomous indicators of political democracy. Despite skepticism over the appropriateness of dichotomous indicators of democracy (e.g., Bollen 1993; Bollen and Jackman 1985a; Gleditsch and Ward 1997), I will here dichotomize democracy to facilitate comparison with the earlier study. The specific threshold employed for a country to be a “democracy” or “autocracy” is a value of six or above on the Polity democracy scale, as discussed in chapter 3 and appendix E. For the purposes of this analysis, define a binary variable Ri(t) indicating the state or regime type of country i at timen t. At any given time period, this can be either autocratic or democratic. The probabilities that a given regime Ri is autocratic at time t can be denoted as p[Ri(t) = (Autocracy) = i,t]. Since there are only two mutually exclusive outcomes or regime types a state may have at any point in time t, it must by implication be the case that the probability that a regime is democratic must be p[Ri(t) = (Democracy) = i,t] = 1 -p[Ri(t) = i,t]. For simplicity, I will hereafter simply denote these two states as i,t and i,t for country i at time t, where one condition must be true and the other by implication false. Let Pjk(t) be the probability of being at state k at time t given that an entity was at state j at time t – 1. In this case, we can for simplicity denote the set of transition probabilities in p(t) as Paa (t), Pad, Pda(t),Pdd(t). These indicate the probabilities of a country remaining autocratic from one year to another, experiencing a transition to democracy, experiencing a transition to autocracy, and remaining democratic, respectively. Assuming a first-order Markov process with no exogenous variables where the state Ri(t) at time t only depends upon the state at the preceding period Ri(t – 1) and that the transition probabilities or survival rates Pjj between states are constant over time, the expected probabilities of observing either state are fully described by E[Ri(t + 1)] = p(t) X Ri(t). Since

each column is exhaustive and the possible ways in which a democracy or autocracy can be observed at time t must sum to one across each row, the probability of observing an autocracy must be

Page 166 →where estimates for the probabilities in the last expression can be taken directly from the observed values in the aggregate observed data. Amemyia (1985: 414–15) shows that stationary first-ordinary Markov chain models conditional on some set of exogenous variables X can be parameterized in a fashion similar to limited dependent variable models as Pik(t) =F(Xtβ) for some function where If regional context matters for the likelihood of transitions, the conditional probabilities Pjj should differ according to the extent of democracy in the spatial context, DRi,t-1, or the composition of regimes in a country i’s set of J neighboring countries at time t – 1. Thus, we can estimate the conditional probability of observing an autocracy at time t given a country’s spatial context of democracy at time t – 1 by estimating a regression without an intercept term with either a logit or a probit link and conditioning on the regime status of country i in the previous year t – 1.12 The probability of observing a democracy and the probabilities of transition can be derived from this. Although I have previously used the logit link – which tends to be more common in applied research – I use a probit link here to facilitate comparison with Przeworski and Limongi (1997). Thus, I estimate the equation where Φ is the cumulative density function of the standardized normal distribution. The results for estimating equation 6.3 are displayed in table 6.2.13 As can be seen from the negative coefficient estimate for β1, the likelihood that a country will be autocratic declines quite dramatically as the spatial context of its interaction environment becomes relatively more democratic. The negative sign of the interaction coefficient (α1 indicates that the effect of the regional context is relatively greater for countries that were autocratic in the previous year. This suggests, on the one hand, that higher levels of autocracy prevailing in a country’s regional context will decrease the probability of a transition to democracy even further when a country was autocratic in the previous year. However, this effect is reversed when the level of democracy is high in the spatial context. In other words, autocracies are much less likely to remain autocracies when the level of democracy is high in the adjacent countries or its regional context. Since the probabilities of regime survival and transition by construction are mirror images, the results imply that democracies and autocracies are considerably less likely to survive in a regional context characterized by authority structures that differ from that of the country itself. Substantively, although the odds of transitions in the aggregate may seem to be generally low, there seems to be a clear tendency for transitions toward states that are more similar to the spatial context. TABLE 6.2. Dynamic Probit Results for Transitions by Spatial Context, 1876–1996 Page 167 →The implied predicted likelihood of regime survival and change from these coefficients are plotted in figure 6.4. As can be seen, the estimated probabilities covary closely with the values of the spatial context. In fact, the estimated values approach zeros and ones. These results suggest an almost deterministic relationship between spatial context and the likelihood that the regime in a country will endure or experience changes in ways that make this resemble the composition of authority structures in its regional interaction context. Autocracies are almost certain to endure in highly autocratic regional interaction contexts, and the predicted likelihood of observing a democracy among other autocratic states virtually approaches zero. However, the estimated probabilities that an autocracy will endure if it is located in a highly democratic regional context are negligible. Conversely, changes to democracy become more likely as a country’s regional context of authority structures becomes more democratic. By the same token, democracies are predicted to break down when the regional context becomes more autocratic. These parameter values are broadly consistent with the pattern of transitions many states have displayed in both the recent third wave of democracy and the second wave of autocracy in the period that followed decolonization. The “fit” of the model, or its predictive ability, can be evaluated by means of the cross-tabulation of predicted

states versus the observed regime states given in table 6.3. As can be seen, there is a reasonable correspondence between the predicted and the observed outcomes. The overall percentage of observations that are classified correctly is 73 percent. However, the validity of the overall classification as a measure of prediction is somewhat limited by the preponderance of autocracies. Similarly, there is no clear null model with which to evaluate the increase in predictive ability. Perhaps more interestingly, we also find that the proportion of democracies predicted correctly by the model is about 54 percent. Page 168 → Fig. 6.4. Estimated survival and transition probabilities given spatial context of democracy TABLE 6.3. Predicted versus Observed Regime Status for Equation 6.3 Page 169 →These results not only indicate that authority structures cluster, but there appear to be strong effects of the regional context of authority structures on regime changes. Since the diffusion of authority structures appears to be so strong between countries, the basis for the claim that regime change is entirely random and a fully exogenous deus ex machina seems to be incorrect or at least overly strong. Knowing a country’s location and the characteristics of surrounding entities does yield some predictive power, and there is a marked tendency for cases to change in ways similar to their regional context over time. On one level, it might be held that the results are so strong that they indicate that the likelihood that a country will be a democracy and its regional context of authority structures are so closely associated that they are almost synonymous. We should be hesitant to accept this conclusion outright. The relative neglect of international influences on democratization certainly indicates that the idea is at least not obvious and cannot be dismissed as trivial. However, at a somewhat different level this would indeed be a consequence of aggregate data displaying very strong geographical clustering. It is hard to come up with clear examples of holdouts or persistent polities in stark contrast to their surrounding entities or regional contexts. Many of the examples that come to mind are countries that are somehow “isolated” from the influences of their interaction environment, either geographical1y or through self-sufficiency, size, or the pervasive influence external actors exert on regional dynamics. An example of the former might be Cuba, while India and the superpower “overlay” in the case of Israel and its Middle Eastern neighbors might exemplify the latter (e.g., Buzan 1991; Vayrynen 1984). Is There an Equilibrium Probability of Democracy? How do the conditional probabilities of transitions given regional context compare with the results for economic wealth? Would these results differ if we were to consider the potential influence of economic linkages as well? More specifical1y, we might wonder how these results compare with the original study by Przeworski and Limongi (1997) as wel1 as what implications regional context and diffusion might have for their inferences. Are these findings compatible with their finding that economic wealth does not predict to transitions? Do their conclusions about the Page 170 →existence of stable equilibrium probabilities of democracy given a country’s level of economic wealth hold up when the regional context is taken into account? In the next section, I compare the impact of economic wealth and regional context more systematically and reexamine their conclusions. Przeworski and Limongi’s actual analysis is somewhat opaque and not fully documented. Based on the description that they “estimate transitions probabilities on level [of per capita income] . . . plus its square” (1997: 160), I infer that they estimated a probit model with the functional relationship between per capita GDP and democracy specified as a second-order quadratic term, that is, all the terms as defined in chapter 3 and summarized in appendix E. The squared term in the functional relationship is justified by the “nonlinearity of observed patterns” in transitions. First, one might ask whether their study can be replicated with the data used in the present study. Przeworski and Limongi (1997) use the dichotomous indicator of democracy in the Alvarez et al. (1996) data set (hereafter ACLP)14 while in the present study I rely on the institutionalized democracy scale in Polity to create a binary indicator of democracies and autocracies. In addition, the two studies differ in terms of the time period and countries in the sample considered. The Penn World Tables constrain the original sample of the Przeworski and

Limongi study to the 1950–90 period, while data on regional context are available for virtually every country-year in the 1875–1996 period.15 Their study also includes a number of microstates. Finally, the dates of national independence employed in their study and the present work appear to differ considerably. As data on economic wealth are missing for a large number of countries, the composition of the two samples could look quite different.16 Most importantly. the data on democracy used in the two studies appear to display some noticeable differences. Alvarez et al. (1996) report high aggregate correlations between their binary democracy measure and other measures, including Polity. Since the institutionalized democracy scale in the Polity data is heavily bimodal, it might be assumed Page 171 →that, if dichotomized, it should for all practical purposes be identical or at least very similar to their measure. This, however, turns out not to be the case. Of all the country-years for which the coverages of the two data set overlap,17 the overall percentage of observations in agreement between the Alvarez et al. regime indicator and the dichotomous democracy based on Polity is about 92 percent. Some of the discrepancies in classification seem to be relatively large. Botswana is never considered a democracy in the ACLP data, despite its having been assigned a perfect score of 10 on the institutionalized democracy scale in the Polity data since 1966. Similar examples include Gambia (1965–93) and Malaysia (1957–68), neither of which is ever considered to be a democracy in ACLP. In addition, several series of country-years assigned extremely low scores in Polity are considered to be democracies in the ACLP data. Some of the most glaring differences include Argentina, 1950–61 (ranging between -9 and -1 in Polity); the Dominican Republic, 1966–77 (-3 in Polity); and Guatemala, 1950–54,1958–62,1968–81, and 1986–90 (never above 2 in Polity). Alvarez et a1. (1996: 10–13) discuss the case of Botswana at some length in the context of what they call “type II” errors in classifying democracies. According to them, some systems in which chief executives are elected in seemingly free multiparty elections may not be genuine democracies since it is not clear whether the ruling party would actually cede power to the opposition if it were to lose an election. On the basis of this consideration, they opt for classifying only regimes in which there has been a peaceful transfer of power as democracies. Periods prior to a turnover of political power — for example, Norway until 1965 and Japan for most of the postwar period — are then “backcoded” retroactively as democracy-years on the basis of subsequent turnovers. There are numerous problems with this approach. First, several polities commonly considered to be democracies on other criteria are classified as autocracies by this operationalization.18 Most fundamentally, turnovers or transfers of power are not a defining property of political democracy but should rather be seen as a consequence of democracy being in place. Although a turnover criterion has often been used as a litmus test for classifying democracies (e.g., Huntington 1991), turnovers in and of themselves do not appear in any of the common definitions of the concept (see, e.g., Vanhanen 1990 for a comprehensive review). Even if we are interested in the “stability” of democracy in Page 172 →the face of opposition victories, the consequences of democracy should be distinguished from definitions of the concept itself. This is in many ways analogous to the problem with operational definitions of democracy incorporating stability in the measure itself (see Bollen and Jackman 1989). Measures defined in such a way that they are systematically associated with elements that are not part of the definition of democracy will display a nonrandom measurement bias or a “method factor” that impedes our ability to study the consequences of democracy (see Bollen 1993 and Bollen and Paxton 2000). Second, since many of the polities that would commonly be considered democracies do not meet the Alvarez et al. (1996) turnover criterion and are never classified as democracies, we can by construction not observe a breakdown of democracy in these countries in the ACLP data. However, by the criteria set forward in Przeworski and Limongi (1997), it would appear that these countries can provide pertinent information about the survival of democracies. The two data sets clearly contain incommensurate definitions of democracy. Furthermore, they are coded differently with respect to the timing of transitions in the aggregate annual data. Polity will generally indicate the regime that was in place throughout the greater part of the year,19 while ACLP explicitly codes the transition year

according to the characteristics of the regimes that emerged in that year. As such, it is not surprising that the degree of agreement on transitions between the two data sets is not particularly high. As can be seen in table 6.4, only about 40 percent of the transitions in the ACLP data set can be retrieved from the Polity data, and only slightly more than half the transitions in Polity are in the ACLP data set. Despite the relatively low agreement between the data sets, I am able to essentially replicate the basic results reported by Przeworski and Limongi (1997).20 These results from estimating equation 6.4 based on the Polity binary democracy data are displayed in table 6.5. Przeworski and Limongi hold that their results indicate that Hunting ton (1968:43) “was correct with regard to dictatorships: they exhibit a ‘bell-shaped pattern of instability’” (Przeworski and Limongi 1997: 160). They use their results to derive conditional “equilibrium probabilities” (180) or proportions of democracies and autocracies that the distribution will converge to and remain stable, “whatever the initial distributions,” in the absence of exogenous disturbances. However, they provide no theoretical rationale for why there should be such stable patterns over time. Moreover, these claims seem to treat the empirical data with an almost extreme reverence as an immaculate arbiter. Even if such equilibrium probabilities or shares of democracies exist, can these be corroborated as “inherent features” of the data in the absence of a theory? In the following, I will show that their empirical findings stem by construction from what I see as an arbitrary parameterization. I then evaluate whether their conclusions hold up under other plausible alternatives. TABLE 6.4. Transition Years in the Polity and ACLP Data Page 173 → TABLE 6.5. Dynamic Probit Results for Transitions by per Capita GDP, 1950–90 Since there is no theory that explains why the “equilibrium share” of democracies should decline at higher levels of economic wealth, a model with per capita GPD in logged values provides a reasonable monotonic alternative to the model with the additional squared term. An alternative model conceptually similar to equation 6.1 for the likelihood of observing an autocracy given per capita income and regime state in the previous year can be specified as all the terms as previously defined. The estimated results for equation 6.5 are displayed in table 6.6. The table shows that the simpler equation 6.5, with two fewer restrictions or a smaller loss in degrees of freedom, has a smaller residual deviance than Przeworski and Limongi’s more Page 174 →complicated model in equation 6.4. Thus, the logged per capita GDP specification seems to be more consistent with the data than the model proposed by Przeworski and Limongi (1997). Under the results in table 6.6, the interpretations of Przeworski and Limongi (1997) no longer hold. The coefficient estimate for β1 still indicates that democracies are less likely to break down the higher their per capita GDP income. In addition, the coefficient estimate for α1, indicates that a higher per capita GDP income increases the likelihood that autocracies will remain in place and that this effect is comparatively larger. In this sense, these results lend little support to the idea that greater economic wealth increases the likelihood of transitions to democracy. However, the stable equilibrium proportion of democracies or the idea of a “bell-shaped” survival pattern for autocracies no longer obtains under the alternative parameterization. Rather, these results essentially indicate that the initial distribution over time could remain relatively stable over time irrespective of wealth. These results illustrate how Przeworski and Limongi’s interpretations follow directly from their choice of functional form. Since they do not hold up in a plausible rival model that is more consistent with the data, it is hard to argue that these are inherent features of the data. Why should we expect the “true” relationship to be square rather than, say, cubic or leptokurtotic? The lack of available data and relative scarcity of transitions do not permit estimating Przeworski and Limongi’s (1997) original model adding the spatial context of democracy to gauge the potential contribution of diffusion. However, we can estimate a version of the specification in equation 6.5 with parameters for the spatial context of democracy. This yields the following model, TABLE 6.6. Dynamic Probit Results for Equation 6.5. 1950–90

Page 175 →all the terms as defined earlier. The results of estimating equation 6.6 are displayed in table 6.7. The estimated parameters for the effect of the economic variables are virtually indistinguishable from those displayed for equation 6.5 in table 6.6. Although the estimated parameters for the spatial context are smaller than in table 6.2, the relationship between the coefficients is similar. As such, the qualitative conclusions and implications do not change, even when the magnitude of the effects is somewhat reduced. These results lend considerable support to the proposition that the spatial context of democracy provides a dynamic component in transitions and democratization processes and indicate that the relationship between the transition and survival probability of regimes and the regional context does not merely stem from a failure to control for per capita GDP. Figure 6.5 shows how the transition and survival probabilities of democracy and autocracy vary in twodimensional space over per capita GDP and the regional composition of authority structures. Looking at how the transition probabilities vary with respect to GDP along the left axis indicates how Przeworski and Limongi got part of the story right: transitions cannot be predicted by wealth alone. In fact, the two rightmost plots indicate that autocracy is much less likely to break down in wealthier countries than in the very poorest and that transitions to democracy under certain conditions are more likely to occur in poorer societies. However, given the greater instability of regimes at low levels of per capita GDP, Przeworski and Limongi (1997) are correct in suggesting that democracy is more likely to endure in wealthier states. Whereas Przeworski and Limongi (1997) assumed that regime probabilities depend only on per capita GDP, we can see that the effects of per capita GDP on the transitions and survival probabilities vary dramatically depending on the regional context. The effects of wealth on whether autocracy persists or perishes are negligible when the regional context is autocratic. Similarly per capita GDP is unlikely to exert much effect on the prospects for survival for democracies in highly democratic contexts. Democracies are more likely to break down in highly autocratic regional contexts, and autocracy is unlikely to be sustained in highly democratic contexts. The qualitative conclusions about the effects of regional context do not change, even when the magnitude of the effects is somewhat reduced. Since the change in curvature over the democracy axis is larger than that over per capita GDP and the regional context is considerably more amenable than economic wealth to change in the short run, these results suggest that the spatial context of democracy provides a dynamic component in transitions and democratization processes. As can be seen from table 6.8, the overall prediction success of the model is very high, with about 98.6 percent of all the observations correctly predicted. TABLE 6.7. Dynamic Probit of Transitions by Spatial Context and per Capita GDP, 1950–90 Page 176 → Fig. 6.5. Transition and survival probabilities by spatial context of democracy and real per capita GDP Page 177 → TABLE 6.8. Predicted versus Observed Regime Status for Equation 6.7

Conclusions This chapter has examined some internal and external determinants of democracy and democratization. I have shown that the distribution of democracy within countries over time is rather static and displays strong permanence. Second, even though democratic states on average tend to be wealthier than nondemocratic states, there is limited evidence that socioeconomic development yields changes toward democracy. Taken together, these two findings indicate that previous studies may have overstated the substantive implications of the relationship between economic income and the likelihood of democratic rule. Third, I examined the relationship among external conditions, levels of democracy, and the likelihood of transitions to democracy. I found that a history of prior conflict involvement is negatively associated with the likelihood that a country will be democratic. Thus, there is some evidence that a hostile regional context may have adverse effects on democracy, although it is more dubious whether this relationship in itself can be said to underlie the association between democracy and peace. I have demonstrated a strong association between a country’s authority structures and the levels of democracy prevailing in the surrounding regional context. Taken jointly, the external influences on democracy appear to be as important as the domestic “social requisites.” Furthermore, these conditions are much more permeable to changes in the short term than are socioeconomic factors.

The conditional Markov model of transitions indicated that not only is there similarity between regimes but there is a also strong tendency for transitions to occur in ways that make regimes more similar to their adjoining regional contexts. These results lend considerable support to the notions that democracy diffuses in the international system and that Page 178 →the distribution of democracy is strongly influenced by processes between states rather than a result of parallel relationships to social requisites played out within each country in isolation. We may not be able to predict transitions and how regions evolve over time, but information about the composition of authority structures and the history of conflict in a regional interaction environment allows a better delineation of plausible trajectories.

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CHAPTER 7 Conclusions and Implications Everything has been thought before; the problem is to think of it again. (Attributed to Wolfgang Goethe) Talk is cheap. Supply exceeds demand. (Unknown) When all is said and done, more is said than done. (Unknown) In chapter 1, I argued that regional interdependence and regional variation lie at the heart of world politics. There is a strong regional or geographical dependence among the states and actors that conduct what we call international relations and that we compare in cross-national research. Theories relating domestic attributes to conflict and cooperation again imply that local heterogeneity in the attributes of states within regions should have observable implications for regional conflict and peace. In addition, the distribution of domestic attributes itself reflects local dependence between states and their interactions rather than merely processes operating within each country in isolation. In this study, I have considered the relationships between political institutions, Deutschian integration, and regional conflict and peace among states from a local interaction perspective. I have examined how interdependence induces international dimensions of democratization through the diffusion of political institutions and insecurity among states. I have shown how concepts and techniques from spatial statistical analysis can help us address interdependence among actors in international relations and its implications. Along the way, I have developed new data and recoded old sources to better examine linkages among political structures, integration, and conflict. I claimed at the outset of this book that a localized state-regional perspective held great potential for clarifying existing theory, determining the implications of empirical findings, and resolving ambiguities in existing research. It is now time to take stock of the results and evaluate whether any corroborating proofs have been found in the pudding after Page 180 →eating. Talk is relatively cheap, and the demand curve for a theory is sharply increasing in the empirical evidence it is able to muster. In this chapter, I first address the primary knowledge claims about linkages among conflict, integration, and authority structures that have been borne out of this study and how these empirical findings fit together on a larger theoretical basis. I then try to look ahead and consider some implications of these findings for alternative futures in world politics as well as consequences for research strategies. After all is said and done, I hope that what has been done will appear in favorable proportion to what has been said.

What Have We Learned and How Does This All Fit Together? The meaning of life depends on the parameter values. (Unknown) What has been learned in this study about conflict, integration, and democratization that we did not know in advance? Of course, there already exists an enormous amount of research on conflict, integration, and democratization. Although the theoretical perspectives examined here are not entirely novel, I have restated theories of conflict and democratization in a local interaction perspective emphasizing interdependence among actors, and the structure of the theories and analysis is quite different from that of previous research. Figure 7.1 outlines the main hypothesized linkages among the regional compositions of authority structures, integration, and regional conflict and peace that have been examined empirically in this study. The risk of regional conflict, Deutschian integration, the “true” level democracy or the nature of political regimes, and a country’s

social requisites are all latent concepts that are not directly observable. Even if we cannot measure them directly, however, we observe various indicators that reflect the theoretical concepts. I follow the convention from structural equation modeling (e.g., Bollen 1989) and indicate latent variables by circles and directly observable indicators by rectangular boxes. The relationships between observables and latent constructs – that is, which indicators are “consequences” or are caused by the latent variable – are indicated by thick, dark gray arrows. I use a series of thin arrows to indicate the findings or the structure of our beliefs about the linkages that emerge from the empirical analyses. Black arrows indicate positive directed relationships, and light gray arrows indicate converse negative relationships. A solid line indicates a robust and consistent linkage in the expected direction. Dashed lines indicate less consistent linkages that are either not robust or only obtain under certain conditions. None of the linkages examined was found to be clearly inconsistent or contrary to what was expected. Page 181 → Fig. 7.1. A revised regional conflict, integration. and democratization nexus My immediate aim here is to summarize the findings of this study, and I make no claims that figure 7.1 is a fully complete account of the causal structure. Moreover, it does not indicate the definitional relationships that exist between several of the observed variables, as these in some sense are functions of values on other variables. The moments of a Page 182 →country’s democratization over a 10 year period, its level of institutional democracy, and the regional context of democracy, for example, are clearly related. However, there is no one-to-one mapping between values on these variables. Furthermore, figure 7.1 does not include any potential linkages between these aspects that have not been considered explicitly in this study.

Conceptualizing Conflict and Peace The number of lines connected to the regional conflict and peace in figure 7.1 indicates how this concept is a key explanandum on the left or an explanans on the right-hand side of the conceptual equation in most of this study. Thus, the validity of the empirical analysis will hinge crucially on whether regional conflict and peace are adequately operationalized. I have argued that much research on conflict has been characterized by a schism between theory and the data considered. Studies on conceptualizing conflict have rarely been integrated with empirical research. Scholars have tended to treat conflict as a largely self-evident concept and have assumed that the vast amounts of data on conflict are universally applicable. In chapter 3, I pointed to many systematic influences on existing empirical data that may have especially pernicious consequences for studies of conflict and peace that are not cast at a dyadic level. My main point is not that conflict cannot be adequately measured. However, rather than merely using the “available data,” researchers must consider the set of events to be included relative to the hypotheses of interest. Much of the existing research has failed to clarify what existing measures of conflict are supposed to be indicative of. For many purposes, it is essential to distinguish among all forms of conflict involvement and conflict that a country experiences on its territory or in its regional context. A country’s participation in conflict is a perfectly valid indicator of its “belligerence” or willingness to use force. However, not all such incidents constitute threats to security. Not all cases of conflict participation are qualitatively equivalent or symmetric between the parties involved, and the specific locus where conflict takes place is pertinent to assessing such differences. Taken to its most absurd limits, Norwegian participation in UN peacekeeping operations in Lebanon does not involve risks to Norway’s territorial integrity, even though such activities reflect severe threats to security in Lebanon itself. Thus, participation in Page 183 →conflicts that may have no direct relationship with security seems too wide a category to assess zones of regional conflict and peace. Since the risk of conflict is the greatest in relations between neighboring countries and there is a strong tendency for conflicts to diffuse across space and time, local conflict seems to be a more informative indicator of threats to security in a state’s regional context. When we identify location, we find clear evidence of geographical zones of conflict and peace. Such differences in zones of peace and rivalry have a clear temporal component as well. Outbreaks of new wars

and even war involvement are relatively rare events, and very few countries are “at war” at any given point in time. Outbreaks of conflict, however, are not independent but reflect more enduring underlying patterns of hostility or perceived risk of conflict that evolve through interactions between parties over time. The suspicion that not all cases of “absence of war” are fully equivalent and that historical trajectories condition the risk of future conflict has been strongly borne out by this study. Zones of peace and conflict endure over time as well, and peace can become as entrenched as protracted rivalries. Most of the literature on conflict has maintained a strict distinction between internal and external conflict. A cursory review of how such categories have been applied in empirical data, however, reveals that the distinction is not as conceptually clear-cut and straightforward as the terminology suggests. Much of what empirical data such as the Correlates of War classify as “civil” wars display clear international dimensions and linkages. In fact, civil wars across the alphabet from Afghanistan to Zaire often involve the direct or indirect participation of other states. This is not to say that the Correlates of War data and other efforts to generate empirical data that distinguish interstate and noninterstate conflicts are somehow “wrong.” Nor are interstate and civil wars always equivalent or the same, and in many settings it may be of interest to try to separate the two. For many purposes and theories of conflict, however, it is not clear why violent conflict should be deemed of interest or completely devoid of interest solely on the basis of whether states wage war against states or nonstate actors. We should be hesitant to consider a given region a zone of stable peace if it has experienced widespread civil conflict. Clearly, there is ample room for generating dubious zones of peace, such as West Africa, by means of a questionable delimitation of the events of interest. Page 184 →The localized interaction perspective highlights and clarifies conceptual issues that often have been brushed aside in previous work on conflict and cooperation. It is hard to express these distinctions between types of conflict in figure 7.1 itself, but a regional interdependence perspective enables us to pose our theoretical questions in more specific ways that are amenable to operationalization. In the following, I will demonstrate more specifically how thinking through such issues has yielded considerable analytic gains in this empirical analysis. Democracy, Institutions, and Regional Conflict In figure 7.1, a large number of arrows connect variations in political authority structures or democracy to variations in regional conflict and peace. The empirical absence of war between pairs of democracies has led to an enormous amount of research hypothesizing linkages between domestic political systems and conflict behavior. Although the empirical findings at the dyadic level have remained quite robust and consistent, I have argued that the almost exclusive emphasis on dyadic research designs has rendered the substantive implications partly obscure and hard to interpret. Most importantly, democratic institutions are not dyadic attributes, and it is not clear why the theoretical mechanisms invoked in existing approaches to the democratic peace should only be observable at a dyadic level. In this analysis, I have showed how an entity-environment perspective can help clarify broader linkages between domestic politics and international behavior. Much research on the democratic peace — in particular, outside minimally dyadic studies — has clearly evaluated whether democracies are “more peaceful” based on their overall participation in conflict. Participation in the aggregate is too unspecific and lumps together many potentially different forms of conflict. Much of the evidence for an absence of war between democracies derives from pairs of states in broader zones of democracy and zones of stable peace. Thus, a theoretically more interesting question is what features of institutional structures make states in zones of democracies better able to contain violent conflict and perceived threats to security in their interactions than other forms of political regimes. I have argued that the more direct relationship between preferences and the range of feasible actions and outcomes in more constrained polities enhances their transparency. The predictability of democracies makes them better able to signal “dovish” behavior and avert unwanted escalation. Page 185 →Democracies are not necessarily peaceful in and of themselves, but democratic institutions facilitate preferences for nonviolent outcomes to exert some influence when these exist. As critics of the democratic peace

are quick to point out, democracies have undoubtedly engaged in extensive violent conflict and in many instances have actively pursued violent conflict or escalation without major opposition. However, both critics and proponents of linkages between democracy and conflict may have drawn the wrong conclusions from these examples. To conclude from such incidents that linkages between authority structures and conflict have no merit or, alternatively, discard such cases by retreating to “the dyadic nature” of the democratic peace overlooks important differences in the conflicts that democracies engage in and when we should expect to see strong popular preferences against the use of force. Many of the wars democracies have waged have been fought in faraway locations that have not necessarily exposed their vital security to any clear risk. In this sense, there is a clear “geographical limit” to the democratic peace. Insights from the Deutschian theory of integration help clarify aspects of why democratic institutions do not constrain the use of force as much outside the regional context. This study demonstrates that authority structures and conflict appear to be related. As indicated by the solid gray arrow emanating from the regional composition of authority structures in figure 7.1, the analysis in chapter 4 consistently indicates that these linkages are the strongest at the regional level. As the composition of regimes in a state’s regional context becomes more democratic, the likelihood of conflict decreases and the prospects for peace increase. This is consistent with what we would expect if democratic institutions allow countries to reduce the element of rivalry in security in their interactions. The results appear to be quite robust under alternative specifications. Even if the main linkages are between the regional composition of authority structures and interaction, so-called monadic effects of a country’s democracy cannot be dismissed out of hand. The localized regression in chapter 4 indicated that a country’s own level of democracy can exert some effect in inhibiting conflict. This effect is not stable across the range of possible regional contexts, but within regions composed of relatively democratic or constrained polities the magnitude of monadic effects is quite substantial. In figure 7.1, the dashed line of the arrow linking a country’s own authority structures and the likelihood of conflict reflects these limitations. Previous efforts to test hypotheses at the monadic level have often Page 186 →been too unspecific to yield meaningful answers. Rather than trying to search for some magic, “true” correlation between democracy and peace, researchers must specify when we would expect a country’s authority structures to exert some impact on the prospects for conflict and peace. The regional perspective enables us to determine when a country’s domestic authority structures may matter as well as when it is unlikely to exert any effect on the likelihood of conflict. Democratization, Opportunity Structures, and Conflict I have emphasized at various points that inferences from comparisons of levels of domestic attributes and conflict behavior do not necessarily translate directly into the effects of changes in such domestic attributes. Thus, the likely effects of democratization cannot be inferred from static and time-invariant evidence on whether levels of democracy correlate with peace alone. Without evidence from examining the dynamics of democratization directly, we are on shaky ground in making predictions about the prospects for peace in a world of more democracies. Mansfield and Snyder highlighted the importance of this distinction in their study (1995), claiming that democratization tended to increase rather than decrease the likelihood of war. Some recent events in the Balkans and the Caucasus seem to attest to the fact that changes toward greater democracy are not always associated with improved prospects for peace. At the same time, other studies have found that democratization by and large appears to reduce the likelihood of war (Enterline 1996a, 1996b; Thompson and Tucker 1997; Ward and Gleditsch 1998). These seemingly divergent pieces of evidence have left the existing research on democratization and conflict in a confusing state. This study has outlined a partial solution to this conundrum and clarified how democratization can both reduce the risk of interstate war and be associated with conflict. As is shown by the two lines drawn from the moments of democratization in figure 7.1, when we take the regional interaction context into account and distinguish the effects of dimensions of democratization on interstate and civil or extrasystemic wars in chapter 4, we find that

democratization consistently reduces the likelihood of interstate wars but in some cases may increase the likelihood of internal conflict. Much of the literature on democratization and conflict has emphasized the risk of diversionary dynamics in weak transitional regimes. The Page 187 →lack of evidence for such diversionary use of force in over three decades of research should make us skeptical of such claims (Levy 1989b). I argue that a more likely linkage lies in the fact that regime changes and democratization may create enhanced opportunities for actors challenging the legitimacy of the existing government or state formation. Although greater levels of democracy may increase the constraints on states’ ability to resort to conflict directed against other states, a decrease in autocracy may increase the opportunities for antagonists to wage war on or retaliate against the state. The opportunity structure hypothesis suggests that democratization could have quite different implications for interstate and civil conflict. Although more democracy can provide greater opportunities for nonstate actors to further their political goals by means of routine political action, a decline in autocracy also decreases the state’s ability to deter political violence through repression. Even though the overall likelihood of civil war is considerably lower in more democratic states, the process of change in itself may be associated with an increased risk. The effects of instability can outweigh the effects of greater democracy in cases in which changes do not result in full-fledged democracies or experience subsequent reversals. Previous research has conflated the different effects of democratization on internal and external conflict. Previous research has examined the relationship between democratization and conflict for individual states in isolation, but the regional context turns out to be very important for determining whether democratization improves the prospects for peace or increases the risks of war. The constraints on the chief executives in neighboring states indicate the likely barriers or restraints these states face on intervention in adjacent polities. Such external assistance can be critical in determining whether insurgencies succeed or fail. For both internal and external conflict, I find that the extent of constraints in a country’s regional context strongly decreases the likelihood that conflict will accompany democratization. Do Democracy and Peace Coevolve? If democracy and authority structures covary and changes toward democracy on average reduce the risk of conflict, can we talk of coevolving zones of democracy and zones of peace? There are numerous nontrivial problems involved in constructing indicators of how the risk of conflict persists and decays over time. Despite all these caveats, I demonstrated Page 188 →in chapter 4 some evidence of cointegration between the values over time for the localized clustering in the time at peace and the clustering in democracy for states located in clear zones of peace or turmoil. This lends some support to the idea that authority structures and conflict go together over time or display long-run trending within such zones. The long-run relationship in the empirical data suggests that Western Europe has evolved in ways resembling a transition from a zone of widespread and repeated conflict toward a security community, with increasingly stable peace, as countries have become more consistently democratic or the constraints on executives increase. By contrast, in the Middle East we see evidence that suggests reinforcing dynamics between conflict and autocracy. Integration, Conflict, and Peace The third conceptual component of this study is the notion of integration. According to the research tradition of Deutsch and his associates (Deutsch 1954, 1977; Deutsch et al. 1957, 1967), integration between states and societies leads to expectations of peaceful change under which the use of violence eventually becomes inconceivable. Integration can become self-sustaining over time and can provide a collective security arrangement and a socializing force potentially as strong as protracted conflict. If such dynamics apply, we should expect to see covariation between indicators of integration and regional conflict and peace. In this study, I used the density of regional trade and the extent of cooperation and conflict in regional interactions as measures of underlying integration. As can be seen by the gray arrows in figure 7.1, the empirical analyses in

chapter 5 indicate some evidence that higher levels of the regional density of trade and more cooperative regional interactions are associated with a lower probability of conflict. Changes in the density of trade flows and changes toward more cooperative interactions furthermore appear to yield a lower risk of conflict. These findings lend some support to the idea that integration can provide a feasible path to stable peace. In chapter 5, I also examined the relationship between Deutschian integration and authority structures. Somewhat surprisingly, the relationship between these two elements is not as strong as has been surmised by those positing virtuous cycles between democracy and integration as well as critics holding that authority structures just mask higher levels of Page 189 →integration between liberal states. Although the density of trade and the extent of cooperative interaction are somewhat higher within more democratic regional contexts, only within the most democratic regional interaction contexts is there a consistent association between trade density and levels of cooperative interaction. At the same time, both authority structures and conflict appear to reduce the likelihood of conflict when considered together, and the effects inferred from each of these elements seem to be at least partly independent. The range of combinations in the empirical world is in this sense larger than what has been surmised by both critics and proponents of a broader Kantian peace. These results are, on the one hand, consistent with the hypothesis that zones of high integration and compatible states could enjoy stable peace even when the constituent polities are not liberal democracies. This lends some support to the notion that security communities outside the North Atlantic region based on other forms of similarity may be feasible (Adler and Barnett 1998; Kacowicz 1998; Kivimäki 2001). On the other hand, there are relatively few contemporary and historical examples of extensive integration as assessed by trade and cooperative interactions. Only in Europe – and above all Western Europe – do we find consistent evidence of broader zones of integration in the post-World War II period. Even here, the evidence is strongest toward the end of the period. As such, there is little evidence of anything approaching peaceful “integrated security communities” outside the North Atlantic region at the present. The prospects for such future communities seem to be largely a question of whether European experiences can be replicated elsewhere. In chapter 5, I discussed the prospects for peaceful communities among nondemocratic states and concluded that the changes that would have to come about for such nonliberal communities to emerge do not seem “less implausible” than changes toward democratization. Greater levels of regional democracy are consistently associated with both the absence and presence of conflict. However, the estimated effects of higher trade densities in inhibiting conflict seem to be quite time dependent, as indicated by the dashed arrow in figure 7.1. Although the coefficient estimate retains the correct sign, this effect is no longer consistent or statistically significant once we explicitly include the duration of peace and consider outbreaks of new wars only. One interpretation of this is that much of the difference between levels of integration for cases of war and its absence may stem from subsequent years of Page 190 →war involvement rather than differences in levels of integration at the outset of wars. This temporal dependence, however, does not in itself imply that economic interdependence must be deemed devoid of any importance for the prospects for regional conflict and peace. Leaving all the nontrivial problems of measurement aside, greater economic linkages may still be an important condition of peace that enhance the stability of peace over time. Such feedback mechanisms are broadly consistent with the findings of this study, although they have not been directly examined here. Thinking systematically about distance, interaction, and integration has clarified some aspects of the democratic peace and highlighted its “geographical limits.” I argued that the extent to which democratic public opinion is likely to display vocal preferences in favor of peaceful resolution of “avoidable” conflict is largely a function of the salience of events. We know from the strong distance, integration, and interaction links that such aspects are geographically bounded. Since people are less affected and have few incentives, they are unlikely to display much interest in conflicts that take place in faraway places. When the salience of issues is low, the structure of democratic institutions provides a more open playing field for high demanders with a greater interest in the issue at stake. Numerous examples attest to the fact that high demanders and special interest groups do not always elicit peaceful policies. Although there are insufficient data for a comprehensive test on such aspects, the overall level of information

about groups and events outside a country’s regional context is probably negligible. Social distances would be large and the extent of identification negligible. This role of salience for the influence of democratic constraints outlines how we can reconcile the peace within zones of democracies with the evidence suggesting that democracies have faced relatively few restraints in colonial and imperial wars. When such remote conflict becomes protracted, however, the constraints on the use of force that can be channeled through democratic institutions often become more substantial, as witnessed by the rising opposition to the Vietnam War in the United States. External and Internal Determinants of Democratization The analysis in chapters 4 and 5 essentially treated the distribution of democracy as given or exogenous, and no attempt was made to account Page 191 →for how the distribution of authority structures itself emerges or changes. Research on the causes of democratization has focused almost exclusively on domestic processes and attributes. Both the social requisites tradition and the macrohistorical approaches to democratization assume static and time-invariant causal linkages at the domestic level. Yet there is simply more variation in the international distribution of authority structures over time than can be attributed to variations in domestic factors alone. In chapter 1, I demonstrated that the distribution of democracy clearly displays a nonrandom geographical distribution. I have argued that the regional context influences a country’s prospects for democracy and transitions and that we should not expect the distribution of democracy to be independent between states. In chapter 2, I related the international dimensions of democracy to two principal processes among states, which I labeled the diffusion of authority structures and the diffusion of insecurity. The strong evidence in chapter 6 that the distribution of democracy is highly dependent on aspects of the regional context are reflected in figure 7.1 by the black arrows emanating from regional democracy and the clustering in time at peace to authority structures. Whereas previous studies on the international dimensions of democratization have largely neglected domestic influences, I have compared the relative influences of international and domestic factors directly by including the primary social requisite variable, namely, a country’s per capita GDP. Chapter 6 demonstrated that average per capita income tends to be higher among democracies. However, as can be seen by the dashed black line extending to moments of democratization, there is less evidence that economic growth yields democratization than is often inferred. Even very dramatic changes in a country’s economic wealth over time would yield relatively small and trivial predicted differences over very long time periods. In addition, most of the highlighted social and economic domestic attributes are likely to change only slowly over time. Failure to take such considerations into account has led many previous studies to overstate the substantive effects of social and economic conditions on transitions to democracy. In chapter 3, I suggested that the political processes leading to transitions and regime change often are partly transnational. First, there may be learning processes, where groups and actors take cues about strategies and the realm of feasible opportunities from events and processes elsewhere. Second, the resources that external actors can provide may often be decisive at the margin in tipping the balance between social Page 192 →groups and actors on the domestic scene. The impact of such external influences can be accentuated when transitions are under way in neighboring countries. Chapter 6 indicated a strong relationship between a country’s authority structures and the composition of authority structures prevailing in its regional context. This is consistent with what we would expect if diffusion effects between states underlie regional similarity in authority structures rather than parallel or similar domestic processes within each individual state. Even though democracy and conflict clearly are not fully antithetical, chapter 6 showed that a prior regional history without conflict or stable peace, as measured by the geographical clustering in time at peace, is associated with a somewhat higher propensity toward democracy. Previous research has largely examined relationships between incidents of conflict and subsequent changes in the level of democracy. However, the effects of conflict on the prospects for democracy do not necessarily follow immediately in the wake of individual conflicts. In chapter 2, I argued that it is these more enduring aspects of conflict and peace over time that can affect the prospects for democracy. The empirical results in this study confirm the effect of diffusion in insecurity, making

both conflict more likely and the emergence of democracy less likely over time. These international effects seem in some sense to be substantially more important than internal factors since external conditions are more susceptible to change over time than are most of the domestic attributes emphasized. Transitions, Randomness, and Equilibrium Most work on democratization has examined cross-sectional differences in levels of variables and assumed that the effects on transitions or changes over time probably are similar to the variation across space. However, there is no necessary relationship between the two. Since changes are highly infrequent and the distribution of authority structures is quite persistent over time, many studies may have exaggerated the impact of economic aspects on democracy. Similarly, the evidence on international dimensions of democracy based on comparing levels of variables is consistent with the dynamics of diffusion, but these findings do not in and of themselves prove that such processes condition the likelihood of political transition. Recent work critical of the social requisites tradition has argued Page 193 →that growth in per capita income does not make transitions more likely. Przeworski and Limongi (1997) hold that the association invoked in the social requisites tradition merely reflects a relationship between economic performance and the survival rates of democracies and autocracies. According to them, transitions to democracy are entirely random and simply emerge as a deus ex machina due to the whims of history. Using a first-order Markov model of the likelihood of changes conditional on the regional composition of authority structures, I demonstrate that transitions to autocracy or democracy tend to occur in ways that render countries more similar to their regional contexts. An autocracy located among democracies is considerably less likely to remain an autocracy than one located in a highly autocratic context. Conversely, a spatial context of autocracies provides a hostile climate for democratic experiments, as democracies located among nondemocracies have much lower prospects for survival. In fact, the predicted transition probabilities for autocracies conditional on regional context vary between zeros and ones. The relationship between the regional context and transitions substantially bolsters our confidence in that the external determinants constitute a dynamic element in processes of democratization. When I considered how transition probabilities vary conditional on both regional context and per capita GDP, I find that many of Przeworski and Limongi’s (1997) conclusions follow from the parameterization of their model, which specifies the functional relationship between regimes and development as the level of per capita GDP and its square, and no longer hold up under other plausible alternatives. Despite differences in the data and measurement of democracy, I was essentially able to replicate Przeworski and Limongi’s original findings. Although the prospects for democracy may not be linear in per capita GDP, the authors provide no theoretical rationale for why the functional relationship between per capita GDP and democracy should be nonmonotonic. I considered a simpler alternative model using the natural logarithm of per capita GDP, which yields a monotonic transformation in which subsequent increases beyond some level matter relatively less. Judged by the absolute likelihood, this model provides a better fit to the data than that proposed by Przeworski and Limongi despite having two parameters less. Under the alternative model, the temporal persistence is still so pervasive that autocracies seem unlikely to experience transitions to democracy on the basis of increases in per capita GDP alone, as indicated by the dashed arrow in figure 7.1. However, Przeworski and Page 194 →Limongi’s (1997) claim that autocracies “display a bell-shaped pattern of instability” (160) no longer holds, and the entire notion that there exists some “equilibrium proportions of democracies given level of development” that would “remain stable in the absence of exogenous disturbances” (190) breaks down. These results suggest that a given population of democracies and autocracies essentially could reproduce itself over time and remain stable if not for such exogenous shocks. If authority structures are related to interdependent regional interaction environments, we should not expect to find such magical “equilibrium” or stable shares of democracy and autocracy given social and economic attributes. Exogenous shocks are not irrelevant noise but precisely the dynamic element that leads to democratization. Domestic and international factors may interact over time in mutually supportive ways or countervene the effects

of each other. However, such exogenous shocks are not random and can be systematically incorporated into analyses of democratization processes.

Is All International Politics local? It is commonly recognized that the most interesting and central features of world politics involve interdependence among actors, events, and processes. Once we take this empirical fact seriously, it immediately becomes suspect to examine relationships between domestic attributes and international behavior in isolation or on a unit by unit basis. Despite references to strategic interaction and interdependence, however, much of international relations research has done exactly this. If international relations is defined as the study of relations between actors and the interdependence of events and decisions, very central elements of the field are obviously missing from much of the present research. Since forms of relations between states such as trade, armed conflict, alliances, and interstate cooperation have been studied as nation-state attributes or purely dyadic relations, the field yields at best an incomplete description or partial understanding of the networks or web of relations connecting states. This again implies that we are ill equipped for understanding the consequences of changes in these relations. Much research on interdependence in world politics has been limited Page 195 →to bilateral interactions. At the other extreme, structuralist approaches at the global level abstract away from actors by aggregating attributes and behavior to the global level. This “addresses” the problem of interdependent actors by construction and ignores actors altogether. Many researchers have come to recognize that such structuralist theories are heavily underspecified and devoid of much behavioral content. Although it may be possible to recast structuralist theory at a microlevel with everything related to everything else in the international system, such a model would be analytically intractable. Furthermore, it would probably be as empirically false as assuming that everything is independent. Interdependence does not necessarily mean that everything is equally related to everything else in the international system. This study suggests that much of the interesting dependence in international relations is neither completely dyadic nor multilateral at the systemic level. The linkages between distance, opportunity, and willingness or interest of interaction strongly indicate that interdependence between actors and processes tends to be geographically confined to a localized or regional level. I have shown geographical clustering in attributes and behavior to be consistent with the hypothesized localized dependence. Although the basic hypotheses, focus, and propositions considered in this study are grounded in older research traditions, the empirical analysis itself constitutes a more radical break given the spatial dependence framework. This study shows how a structure of hypothesized dependence can be made explicit and implemented in empirical research and how taking plausible forms of dependence and variation in the interaction context into account changes our inferences and conclusions about many stylized facts in world politics. Whereas interdependence has been broadly recognized, if insufficiently addressed, in international relations research, the very idea that units or observations may not be independent of each other has essentially been ignored in much cross-national research. Bollen, Entwisle, and Alderson’s (1993) meta-analysis of macrocomparative research finds no studies that considered nonindependence among cases systematically. At best, the problem is discussed in passing. Most cross-national research compares the distribution of attributes between states. If these distributions turn out not to be independent among entities but spatially clustered, however, our inferences from such comparisons can be seriously Page 196 →flawed. The analysis of democratization here indicates that the consequences of disregarding dependence among observations may quite dramatically affect the results of comparative analyses. Comparative cross-national research has recently become more alert to the issue of nonindependence. Researchers have rediscovered “Galton’s problem” (Galton 1889), which states that similar phenomena may result from external diffusion rather than functionally similar processes within each unit alone (see Goldthorpe 1994 and Ross

and Homer 1976). Some researchers have drawn extremely pessimistic inferences from Galton’s problem, concluding that comparisons are inherently impossible (Sztompka 1988) or only feasible within clusters of similar entities with similar societal compositions and external influences (Castles 1993). Although dependent observations pose significant challenges, researchers should see the localized context of world politics as good news. Once we can develop operational hypotheses on the structure of dependence between entities, we can take advantage of this information to construct models and measures that will take such forms of dependence explicitly into account. Modeling dependence provides a way to render regional context variation on general variables. In this sense, we can have general theories of contextual variation (e.g., Przeworski and Teune 1970). In this study, I have shown how techniques from spatial statistics can be used to address and illuminate existing research on domestic-international linkages. These methods are attractive on account of being substantively close to the hypothesized nature of how processes of interest play out and need not be technically complicated. Although proper consideration must be taken to assess the appropriate metric for each specific case and problems on theoretical grounds, the spatial dependence approach can easily be extended to alternative “spatial” metrics. This could include “Blau space” (Blau 1964) metrics derived from the density of interactions. Lofdahl (1997), for example, develops a metric based on bilateral trade. Although I have only examined geographical or Euclidean distance metrics in this case, there is clearly room for innovation in future research by exploring such options more systematically. This study has shown that, although problems of nonindependence between cases are real, such problems of dependence between states need not be insuperable in cross-national research. Given clear hypotheses on the nature of interdependence, it is certainly possible to evaluate Page 197 →the relative importance of external and internal causal processes. The challenges of Galton’s problem are primarily theoretical: given a theoretical understanding of the forms of dependence involved, empirical analysis is nonetheless fully possible. Much of the pessimism seems to stem from a desire to extract historically “grounded theory” from forms of comparative induction that presume independent cases (Goldthorpe 1994; Lieberson 1991). In such instances, the problem may lie partly in the eye of the beholder, and no methodological substitute can adequately compensate for theory.

Theory, Data, and Measurement I have argued at various points in this study that there often is a large discrepancy between the theoretical concepts in which scholars are interested and the actual data considered in empirical analysis. In a field in which a classical hypothesis testing framework is used as the ultimate arbiter and theories are rejected if the associated coefficient estimates fail to reach the magical p ≤ 0.05 level (see Cohen 1994; Gill 1999; and King, Wittenberg, and Tomz 2000), we may conceivably reject our hypotheses too often because of flawed data and technical assumptions that are incorrect rather than flaws in the theory itself. Schisms between theory and empirical approaches in this sense may constitute major impediments to cumulation in international relations and comparative research. Basic complaints about the quality of data in international relations are of course not new. My argument, however, is not that the aspects of interest are unmeasurable and existing data of no use. Rather, I have shown on a constructive note that taking theoretical issues systematically into account in data analysis can provide a better handle on many problematic issues. It is fully feasible to undertake large-scale recoding of data, and this study shows there can be great gains from making data more consistent with theoretical concepts. Data are often treated with excessive reverence, as if the pristine raw data were a fully unbiased and accurate arbiter of the analytical value of our theories. Yet, if a researcher believes something is in error or inappropriate to some hypothesis at hand, then surely this should be changed accordingly. In this study, I have reexamined some common data sets in international relations and comparative politics and suggested various revisions. I have demonstrated that there can be large gains by improving Page 198 →approaches to measurement and that we might be able to get more out of our data by more imaginative use of the available data. Our empirical data will never be perfect, but we should strive to do as much as possible within

the limits of what we have at hand. Measurement may not be valued as an end in itself, but it is absolutely essential for cumulation in theoretical and empirical research. This study has clearly indicated large substantive payoffs from attention to such issues.

A Future Safe for Democracy and Conflict? We have two classes of forecasters: Those who don’t know . . . and those who don’t know they don’t know. (John Kenneth Galbraith) In chapter 1, I posited the existence of markedly different zones or regions and suggested that such geographical “zones” in one domain are associated with variation in other domains. This study has corroborated that several such linkages exist and that these relationships are both of substantial magnitude and robust. However, I have also emphasized the interdependence of these linkages. Besides the individual linkages, we are interested in how these linkages work together on a broader basis. Although figure 7.1 is considerably more detailed than its predecessor, figure 2.1, the theoretical structure is still not sufficient to test all linkages as a fully identified system. That the system is not identified in a statistical sense, however, does not mean that we cannot use this to make conditional statements about the probabilities of events and prospects for change over time. Knowing something about the regional interaction context in which a country is located clearly enables us to update or “sharpen” out priors and make more accurate statements about the likelihood of events and outcomes. I have at various points in this study conducted simulations and thought experiments in which I use estimated coefficients to derive predictions given hypothetical values corresponding to different scenarios. Through these exercises, I have shown that these estimated results allow us to generate predictions about conflict, integration, and democratization that match our theoretical expectations and hypotheses about the causal linkages and relationships between these aspects. The results here also correspond reasonably well to observed historical data and trajectories. Page 199 →The ability to generate plausible hypothetical scenarios and outcomes that are consistent with contemporary and historical data can be seen as a measure of the extent to which we can satisfactorily account for the causal processes at work. If the meaning of life depends on the parameter values, there is a lot of good news here insofar as we have found several seemingly robust linkages between zones of certain domestic properties and zones of regional variation in other behavioral patterns. These empirical results allow us to make conditional conjectures that can satisfy the requirements of plausible counterfactual thought experiments (Tetlock and Belkin 1996). However, postdiction is not analogous to ex ante prediction or anticipation of future events. The less good news is that we obviously cannot project or anticipate the values on the right-hand-side variables far beyond the present with much reliability. Although we can make valid counterfactuals or projections based on hypothetical scenarios, it is more questionable whether we can make reliable long-term real world forecasts. By looking at the short run, we may be able to make some extrapolations that are not too far off the mark. However, we cannot necessarily anticipate and predict the influence of exogenous shocks over time. Thus, we are clearly in the second category of Galbraith’s typology of forecasters, though at least we recognize the extent of our ignorance. Whether long-term prediction is a useful ideal or yardstick here is highly questionable, however. Unless we actually believe in historical regularities such as Kondratieff waves, long-run forecasting may remain inherently impossible in complex social systems (e.g., Hechter et al. 1995). Regional interdependence primarily implies that countries within regional interaction clusters are affected by other entities determined by distance and interaction opportunities. Such forms of dependence, however, can play out in a variety of different ways. Reciprocity in interaction over time could lead to both protracted rivalry and integrated security communities. Although much current research has focused on contemporary diffusion of democracy, previous “waves of authoritarianism” illustrate how regional diffusion in transitions can induce regime changes with outcomes other than democracy. Does this indeterminacy mean that the results of this study are devoid of policy implications and that no

conjectures can be made about more or less likely world futures? The answer to this rhetorical question Page 200 →is clearly no. Even though we may not be able to predict exactly how interdependent communities will change without additional information, a focus on interaction clusters provides a clearer understanding of how such regional dynamics unfold and the realm of feasible alternative world futures. Although a variety of alternative world futures are possible, not all are equally probable. In the remainder of this section, I will go out on a limb and try to speculate on policy implications and likely world futures based on inferences from this study. The results here suggest that both the proposal for a foreign policy strategy that promotes democracy on the basis of its presumed pacifying consequences (Allison and Beschel 1992; Lynn-Jones 1998) and its criticisms (Mansfield and Snyder 1995) may be partly misguided. Whether democratization is likely to induce conflicts or improve the prospects for peace depends on the regional context in which democratization takes place. Although the extreme pessimism that some have inferred about the dangers of war stemming from democratization clearly seem exaggerated, the effects of changes within a single country’s level of democracy on the risk of conflict are potentially ambiguous. Democratization may decrease the likelihood of interstate war, but it may not affect ongoing conflicts and can under certain circumstances increase the likelihood of civil wars or internal conflict. Although the benefits of regional democratization for the prospects for peace may be substantial, the ability to manipulate the likelihood of war by promoting democracy appears to be limited. At the end of the day, promoting democratization is probably better justified as an end in itself than asking democracy to serve some instrumental purpose. The prospects for promoting democracy abroad are somewhat ambiguous in light of the findings of this study. On the one hand, these findings suggest that democratization need not be impossible in developing societies in the absence of high per capita income. The international dimensions of democracy can be very important and can potentially compensate for social requisites. External provision of resources and efforts to enhance democratization may thus be important facilitating factors at the margin. On the other hand, this cuts both ways. In regional contexts characterized by autocracies, democratic transitions will be considerably more prone to reversals toward more autocratic rule. Imposing democracy is, for example, unlikely to result in a functional democracy in present-day Iraq without democratization elsewhere in the region. In the realm of peacemaking, these results suggest that a broader Page 201 →regional approach is required to prevent armed conflicts or sustain democracy. Feasible regional orders must be broadly acceptable to most parties within a region, including social groups that are not formally nation-states. The importance of these issues can be clearly seen in the former Yugoslavia, where the distinction between nation-states and nonstate actors are diffuse and highly unclear, and the peacekeeping efforts of NATO face severe challenges in reconciling the contradictory goals of the parties. This is not merely an issue about the willingness to use force. Although states may be coerced into submission, it is virtually impossible to successfully demolish armed insurgencies and “small wars” by the use of force alone. Even small groups with limited resources may exert a great influence on conflict dynamics. Once under way, armed conflict can be sustained over time with a fairly low level of resources. The international community can provide a constructive role, however, when all parties have some interest in burying the hatchets of war but lack sufficient trust to enforce agreements or make credible commitments. The peace process in El Salvador and the UN commission monitoring the implementation of the disarmament effort and the development of a joint civilian police force provides an example of such an instance. The international system has clearly changed considerably over time. Since the observed likelihood of interstate war has not increased linearly with the growth in the number of states over the last two centuries, the likelihood of war cannot be stationary at any given level of analysis and there must be other factors decreasing the likelihood of war over time (e.g., Avenhaus, Brams, and Fichtner 1989). Many of the states in the international system have clearly changed as well. Much of international relations theory displays the history of the Central European subsystem as a case of Hobbesian anarchy or a zone of war. As the twenty-first century begins, however, this seems to be an increasingly inaccurate and misplaced description of relations between the European states. In some ways, Hobbesian anarchy is a more persuasive description of relations in regional subsystems elsewhere in

the world such as the Middle East and Central Africa (see, e.g., Stam and Bennett 1998). Clearly, local changes within the global system are possible. Despite the possibility of change, the international system is unlikely to move consistently toward either a world safe for democracy where war has become obsolete (Mueller 1989b) or, at the other extreme, a coming global anarchy or a return to the turmoil of the interwar Page 202 →period (Kaplan 1997; Mearsheimer 1990). Rather, the world is likely to remain polarized between disparate zones after the end of the Cold War and reduced superpower domination. Although Europe is unlikely to revert to a zone of turmoil with the end of extended nuclear deterrence, widespread conflict and authoritarian rule in all likelihood will persist in much of the developing world. The end of the Cold War has had only a marginal impact on many of the internal conflicts often attributed to East-West confrontation such as those in Afghanistan and Angola. Within the former socialist bloc, there is already some evidence of growing discrepancies between states in East-Central Europe, and most states that were part of the former Soviet Union. Whether the future holds more transitions akin to those of Poland or Belarus can tip the balance in very different directions. At the same time, there are several encouraging trends that promise improved prospects for peace in the post–World War II period. Less superpower “overlay” in regional subsystems implies less external support contributing to the escalation of localized conflicts (e.g., Buzan 1991). Many regions that have experienced limited experiments with democracy, such as Latin America, are for the first time quite consistently democratic. One of the implications of this analysis is that these new democracies are much more likely to endure now since their regional context is more consistently democratic than at any previous point in time. Despite the current economic crisis in Southeast Asia, the prospects for democratization in the region need not be dismal. Somewhat ironically, in light of the emphasis on social and economic correlates of democracy, economic crisis may actually provide the final blow to some of the autocratic influences in the region. Greater democratization and more constrained polities may have substantial consequences for regional dynamics in the long run. The benefits of regional peace can be self-sustaining and substantial over time. Peace was an important force for changes in the international system in the nineteenth and twentieth centuries, but has often been overshadowed by our focus on war and violent conflict. Now that interstate wars are becoming somewhat less salient in the wake of the Cold War we can better appreciate John Milton’s insight, expressed in a letter to Oliver Cromwell: “Peace has its victories too, no less renowned than war.”

Page 203 →

APPENDIX A Independent States since 1816 Table Al contains a revised list of independent states in the international system since 1816. For completeness, this list also includes some countries that disappeared from the international system before 1875 and as such are not included in the study period here. The criteria for identifying independent states are discussed in greater detail in Gleditsch and Ward 1999. For all entries, we suggest a COW-type numeric and three-letter acronym identifiers. TABLE A1. Independent States. 1816–1996 COW Number COW Identifier Name of State 700 AFG Afghanistan Afghanistan 339 ALB Albania 615 ALG Algeria Algeria 540 ANG Angola 160 ARG Argentina 371 ARM Armenia 900 AUL Australia 305 AUS Austria 300 AUH Austria-Hungary 373 AZE Azerbaijan 267 BAD Baden 31 BHM Bahamas 692 BAH Bahrain 771 BNG Bangladesh 53 BAR Barbados 245 BAY Bavaria 370 BLR Belarus (Byelorussia) 211 BEL Belgium

Start End 01.01.1816 30.12.1888 01.05.1919 – 01.01.1913 – 01.01.1816 05.07.1830 05.07.1962 – 11.11.1975 – 09.07.1816 – 23.09.1991 – 01.01.1901 – 14.11.1918 – 01.01.1816 13.11.1918 03.08.1991 – 01.01.1816 17.01.1871 10.07.1973 – 15.08.1971 – 16.12.1972 – 30.11.1966 – 01.01.1816 17.01.1871 25.08.1991 – 04.10.1830 –

80 434 760 145 346 Page 204 →571 140 835 355 439 516 811

21.09.1981 – 01.08.1960 – 01.01.1949 – 06.08.1825 – 01.04.1992 – 30.09.1966 – 07.09.1822 – 01.01.1984 – 03.03.1878 – 05.08.1960 – 01.07.1961 – 01.01.1954 –

BLZ BEN BHU BOL BOS BOT BRA BRU BUL BFO BUI CAM

Belize Benin Bhutan Bolivia Bosnia-Herzegovina Botswana Brazil Brunei Bulgaria Burkina Faso (Upper Volta) Burundi Cambodia (Kampuchea)

471

CAO

Cameroon

01.01.1960 –

20 402 482 483

CAN CAP CEN CHA

Canada Cape Verde Central African Republic Chad

07.01.1867 – 05.07.1975 – 13.08.1960 – 11.08.1960 –

155 710 100

CHL CHN COL

Chile China Colombia

01.04.1818 – 01.01.1816 – 23.09.1830 –

581 484

COM CON

Comoros Congo

06.07.1975 – 15.08.1961 –

490 94 437 344 40 352 316 315 390 522 42 130 651

DRC COS CDI CRO CUB CYP CZR CZE DEN DJ! DOM ECU EGY

92 411 531 366

SAL EQG ERI EST

530 950 375

ETH FJ! FIN

Congo, Democratic Republic of (Zaire) Costa Rica Cote D'Ivoire Croatia Cuba Cyprus Czech Republic Czechoslovakia Denmark Djibouti Dominican Republic Ecuador Egypt Egypt El Salvador Equatorial Guinea Eritrea Estonia Estonia Ethiopia Fiji Finland

30.06.1960 – 01.01.1840 – 07.08.1960 – 25.06.1991 – 20.05.1902 – 16.08.1960 – 01.01.1993 – 01.01.1919 31.12.1992 01.01.1816 – 27.07.1977 – 01.01.1845 – 18.05.1830 – 01.01.1827 31.12.1882 01.01.1922 – 01.01.1840 – 12.10.1960 – 25.05.1993 – 11.11.1918 01.06.1940 06.06.1991 – 11.02.1855 – 10.09.1970 – 06.12.1917 –

220 481 420 372 265 260 255 452 Page 205 →99 350 90 438

FRN GAB GAM GRG GDR GFR GMY GHA GCL GRC GUA GUI

France Gabon Gambia Georgia German Democratic Republic German Federal Republic Germany (Prussia) Ghana Great Colombia Greece Guatemala Guinea

01.01.1816 – 17.08.1960 – 18.02.1965 – 06.09.1991 – 21.09.1949 03.10.1990 07.10.1949 – 01.01.1816 08.05.1945 06.03.1957 – 30.08.1821 22.08.1830 17.05.1827 – 01.01.1840 – 02.10.1958 –

404

GNB

Guinea-Bissau

10.09.1974 –

110 41

GUY HAI

240

HAN

Guyana Haiti Haiti Hanover

26.05.1966 – 01.01.1816 01.01.1915 15.08.1934 – 01.01.1816 17.01.1871

275 273 91

HSD HSE HON

Hesse, Darmstadt (ducal) Hesse, Kassel (electoral) Honduras

01.01.1816 17.01.1871 01.01.1816 17.01.1871 01.01.1840 –

310 395

HUN ICE

Hungary Iceland

03.11.1918 – 17.06.1944 –

750 850 630 645 205 666 325 51 740 663 705 501 730 731 732 690 703 812 367

IND INS IRN IRQ IRE ISR ITA JAM JPN JOR KZK KEN KOR PRK ROK KUW KYR LAO LAT

660 570

LEB LES

India Indonesia Iran (Persia) Iraq Ireland Israel Italy/Sardinia Jamaica Japan Jordan Kazakhstan Kenya Korea Korea, People's Republic of Korea, Republic of Kuwait Kyrgyz Republic Laos Latvia Latvia Lebanon Lesotho

15.08.1947 – 17.08.1945 – 01.01.1816 – 03.10.1932 – 06.12.1921 – 14.05.1948 – 01.01.1816 – 06.08.1962 – 01.01.1816 – 25.05.1946 – 16.12.1991 – 12.12.1963 – 01.01.1816 22.08.1910 10.09.1948 – 15.08.1948 – 19.06.1961 – 31.08.1991 – 01.05.1954 – 01.11.1918 01.06.1940 06.09.1991 – 22.11.1944 – 04.10.1966 –

450 620

LBR LIB

368

LIT

212 343 580

LUX MAC MAG

Liberia Libya Libya Lithuania Lithuania Luxembourg Macedonia Madagascar Madagascar Malawi Malaysia Maldives

26.07.1847 – 01.01.1816 01.01.1835 25.12.1951 – 01.02.1918 01.06.1940 06.09.1991 – 11.05.1867 – 20.11.1991 – 01.01.1816 05.08.1896 26.06.1960 – 06.07.1964 – 31.08.1957 – 26.05.1965 –

553 MAW Page 206 →820 MAL 781 MAD

432

MLI

Mali

22.09.1960 –

338 435 590 280

MLT MAA MAS MEC

Malta Mauritania Mauritius Mecklenburg-Schwerin

21.09.1964 – 28.11.1960 – 12.03.1968 – 01.01.1816 17.01.1871

70 332 359

MEX MOD MLD

Mexico Modena Moldova

01.07.1821 – 01.01.1816 16.03.1861 27.08.1991 –

712 341

MON MNG

Mongolia Montenegro

13.03.1921 – 01.01.1868 01.07.1915

600

MOR

541 775

MZM MYA

565 790 210 920 93 436 475 385 698 564 770 95 327 910 150 335 135

NAM NEP NTH NEW NIC NIR NIG NOR OMA OFS PAK PAN PAP PNG PAR PMA PER

Morocco Morocco Mozambique Myanmar (Burma) Myanmar (Burma) Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Orange Free State Pakistan Panama Papal States Papua New Guinea Paraguay Parma Peru

01.01.1816 01.01.1904 01.03.1956 – 25.06.1975 – 01.01.1816 30.12.1885 04.01.1948 – 21.03.1990 – 01.01.1816 – 01.01.1816 – 01.09.1907 – 01.01.1840 – 03.08.1960 – 01.10.1960 – 26.08.1905 – 01.01.1816 – 28.03.1854 30.05.1910 14.08.1947 – 03.11.1903 – 01.01.1816 1870 16.09.1975 – 01.01.1816 – 01.01.1816 1860 09.12.1824 –

840 290 235 694 360 365 517 670 269 433 340 451

PHI POL POR QAT RUM RUS RWA SAU SAX SEN SER SIE

Philippines Poland Portugal Qatar Romania Russia (Soviet Union) Rwanda Saudia Arabia Saxony Senegal Serbia Sierra Leone

04.07.1946 – 11.11.1918 – 01.01.1816 – 03.09.1971 – 13.07.1878 – 01.01.1816 – 07.01.1962 – 23.09.1932 – 01.01.1816 17.01.1871 14.04.1960 – 13.07.1878 01.10.1915 27.04.1961 –

830

SIN

Singapore

09.08.1965 –

317 Page 207 →349 940 520

SLO SLV SOL SOM

Slovakia Slovenia Solomon Islands Somalia

01.01.1993 – 25.05.1991 – 07.07.1978 – 01.07.1960 –

560 230 780

SAF SPN SRI

South Africa Spain Sri Lanka

31.05.1910 – 01.01.1816 – 04.02.1948 –

625 115

SUD SUR

Sudan Surinam

01.01.1956 – 25.11.1975 –

572 380 225 652 713 702 510 800 711 461 563 52 616

SWA SWD SWZ SYR TAW TAJ TAZ THI TBT TOG TRA TRI TUN

640 701 337 329 500 369 696 200

TUR TKM TUS SIC UGA UKR UAE UK

Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania/Tanganyika Thailand Tibet Togo Transvaal Trinidad and Tobago Tunisia Tunisia Turkey/Ottoman Empire Turkmenistan Tuscany Two Sicilies Uganda Ukraine United Arab Emirates United Kingdom

06.09.1968 – 01.01.1816 – 01.01.1816 – 01.01.1946 – 08.12.1949 – 09.09.1991 – 09.12.1961 – 01.01.1816 – 01.01.1913 01.10.1950 27.04.1960 – 01.01.1852 30.05.1910 31.08.1962 – 01.01.1816 12.05.1881 01.01.1956 – 01.01.1816 – 27.09.1991 – 01.01.1816 16.03.1861 01.01.1816 16.03.1861 09.10.1962 – 01.12.1991 – 02.12.1971 – 01.01.1816 –

89

UPC

2 165 704 101 815 816 817 271 678 680

USA URU UZB VEN VNM DRV RVN WRT YEM YPR

United Provinces of Central 01.07.1823 31.12.1839 America – United States of America 01.01.1816 – Uruguay 26.05.1830 – Uzbekistan 31.08.1991 – Venezuela 01.01.1829 – Vietnam (Annam/Cochin China/Tonkin) 01.01.1816 01.01.1893 Vietnam, Democratic Republic of 01.05.1954 – Vietnam, Republic of 01.05.1954 30.03.1975 WUrttemberg 01.01.1816 17.01.1871 Yemen (Arab Republic of Yemen) 11.11.1918 – Yemen, People's Republic of 30.11.1967 21.05.1990

345

YUG

Yugoslavia (Serbia)

01.12.1918 –

551 511 522

ZAM ZAN ZIM

Zambia Zanzibar Zimbabwe (Rhodesia)

24.10.1964 – 19.12.1963 26.04.1964 11.11.1965 –

Page 208 →

APPENDIX B Armed Conflicts from 1816 to 1996 The tables in appendix B contain in summary form armed conflicts that took place during the study period as well as in the prior period from 1816. The starting point for the data is the Correlates of War International and Civil War data set (1994; Small and Singer 1982). These data have been revised to reflect changes in the delineation of states and updated from 1992–96 with the Uppsala conflict data (Wallensteen and Sollenberg 1998).

ID 001 004 007 010 013 016 019 022 025 028 031 034 037 040 043 046 049 052 055 061

TABLE B1. Interstate Wars, 1816–1996 War Name Franco-Spanish Russo-Turkish Mexican-American Austro-Sardinian First Schleswig-Holstein Roman Republic

064 067 070 072 073 Page 209 →076 079 082 085 088 091 094

La Plata1 Crimean2 Anglo-Persian3 Italian Unification Spanish-Moroccan halo-Roman Italo-Sicilian Franco-Mexican4 Ecuadorian-Colombian Second Schleswig-Holstein Lopez5 Spanish-Chilean6 Seven Weeks Russo-Turkish Pacific Sino-French7 Central American Franco-Thai8 Sino-Japanese Greco-Turkish Spanish-American9 Boxer Rebellion10 Russo-Japanese Central American Central American Spanish-Moroccan

Time Span 1823 1828–29 1846–48 1848–49 1848–49 1849 1851–52 1853–56 1856–57 1859 1859–60 1860 1860–61 1862–67 1863 1864 1864–70 1865–66 1866 1877–78 1879–83 1884–85 1885 1893 1894–95 1897 1898 1900 1904–5 1906 1907 1909–10

097

Italo-Turkish

1911–12

100 103 106 109

First Balkan Second Balkan World War I11 Russo-Polish

1912–13 1913 1914–18 1919–20

110 112 115

Lithuanian-Polish Hungarian-Allies Greco-Turkish

1919–20 1919 1919–22

116 118

Franco-Turkish12 Sino-Soviet

1919–21 1929

121 124 127 130 133 136 139 142 145 148 151 154 157 160 163 166 169 172 175 178 181 184

Manchurian Chaco

1931–33 1932–35 1935–36 1937–41 1938 1939 1939–45 1939–40 1940–41 1948–49 1950–53 1956 1956 1962 1965–75 1965 1967 1969–70 1969 1971 1973 1974

187 189 190 193 199 202 205 208 Page 210 →211 214

Vietnamese-Cambodian

NIW

Yugoslavia26

halo-Ethiopian13 Sino-Japanese Changkufeng Nomohan World War l14 Russo-Finnish Franco-Thai15 Palestine16 Korean17 Russo-Hungarian Sinai18 Sino-Indian Vietnam19 Second Kashmir Six Day Israeli-Egyptian Football Bangladesh Yom Kippur20 Turco-Cypriot Ethiopian-Somalian21 Ugandan-Tanzanian22 Sino-Vietnamese Iran-Iraq Falklands23 Israel-Syria/“Lebanon” 1982 Sino-Vietnamese

1975–79 1977–78 1978–79 1979 1980–88 1982 1985–87 1990–91

Gulf War24 Azeri-Armenian/"Nagorno-Karabakh" 1992–9325 1993

1 Uruguay is considered a system member with the revised criteria and was added as a participant. 2 The United Kingdom. France. and Italy are excluded by the locus criterion. 3 The United Kingdom is excluded by the locus criterion. 4 France is excluded by the locus criterion. 5 Uruguay is considered a system member and was added as a participant since 1865. 6 Spain is excluded given the locus criterion. 7 France is excluded given locus criterion. 8 France is excluded given locus criterion. 9 Spain is excluded given locus criterion. 10 France, Russia. the United Kingdom, and the United States are excluded given locus of conflict. 11 The United States is excluded given locus of conflict. While Australia, Canada, and New Zealand qualify as members with the new criteria, all are excluded given locus criterion. 12 France is excluded given locus criterion. 13 Italy is excluded given locus criterion. 14 Brazil. Canada, New Zealand. South Africa. and the United States are excluded given locus criterion. 15 France is excluded given locus criterion. 16 Iraq is excluded given locus criterion. 17 Australia, Belgium. Canada, Colombia. Ethiopia. France, Greece, the Netherlands, the Philippines, Thailand, Turkey, the United Kingdom, and the United States are excluded by locus criterion. 18 France and the United Kingdom are excluded by locus criterion. 19 Australia. the Philippines. South Korea. and the United States are excluded by locus criterion, 20 Iraq and Saudi Arabia are excluded given locus of conflict. 21 Cuba is excluded given locus of conflict. 22 Libya is excluded given locus of conflict. 23 The United Kingdom is excluded given locus criterion. 24 Canada. France. Italy. Morocco, the United Kingdom, and the United States are excluded given locus criterion. 25 Ending date is based on the Uppsala conflict data. 26 Based on the Uppsala data. Bosnia-Herzegovina, Croatia. and Yugoslavia were added.

ID 601 602 603 604 607 610 613 616 619 622 625 626 Page 211 →628 631 634 636

TABLE B2, Civil Wars, 1816–1996 Time Span Interventionb War Namea Spain 1821–23 Two Sicilies 1820–21 (G) Sardinia 1821 (G) Turkey/Ottoman Empire 1826 Portugal France Mexico Spain Colombia Argentina1 Spain Mexico “Caste War” Two Sicilies France Austria-Hungary France “Royalists”

1829–34 1830 1832 1834–40 1840–42 1841–51 1847–49 1847–55 1848–49 1848 1848 1851

(G)

(G) (0)

637

Chile

1851

640 643 646 649

Peru Peru Mexico Venezuela

1853–55 1856–58 1858–61 1859–63

652 653 654

China2 China China

1860–64 1860–68 1860–72

655 658

Colombia United States of America

1860–62 1861–65

661 664 667 670 673 676 679 681 682 685 688 691 694 697 700 703 706 709 712 715 718 721

Argentina Argentina Venezuela Spain Argentina France Spain United States “Siouxian” Colombia Japan Argentina Colombia Chile Brazil

1863 1866–67 1868–71 1868 1870–71 1871 1872–76 1876 1876–77 1877 1880 1884–85 1891 1893–94 1893–94 1894–95 1896–97 1899–1903 1904 1905–6 1907 1907–8 (G)

724 727 730 733 736 739 742 744 745 746 748 Page 212 →751

Brazil3 Peru Brazil Colombia Uruguay Russia Romania Morocco4 Iran (Persia)5 Mexico Morocco6 Paraguay China China China Austria “Socialist Putsch” Russia/Soviet Union7 Finnish Hungary Honduras

1908–9 1910–20 1911 1911–12 1911 1913 1914 1934 1917–20 1918 1919–20 1924

(G)

(G) (G)

(0)

754

Afghanistan

1924–25

757 760 763 766

China Mexico Afghanistan China

1926–28 1926–30 1928–29 1929–30

769 771 772

China EI Salvador Brazil

1930–35 1932 1932

775 778

Spain

1934 1936–39

781 784 787 788 790 793 796 799 802 805 808 811 814 817 820 823 826 829 832 835 838 841

Greece9 China Paraguay China “Taiwanese Revolt” Yemen Arab Republic Costa Rica Colombia Burma Colombia Indonesia Philippines Bolivia Indonesia Guatemala Argentina Indonesia

844 847 850 853 856 859 862 863 865 868 869 871

Spain8

Lebanon10 Cuba Iraq Vietnam11 Zaire/Kinshasa12 Laos13 Algeria Yemen Arab Republic Laos Sudan Rwanda Dominican Republic14 Uganda Guatemala China Nigeria Burma Kampuchea/Cambodia15

1944–49 1946–50 1947 1947 1948 1948 1948 1948–51 1949–62 1950 1950–52 1952 1953 1954 1955 1956–60 1958 1958–59 1959 1960–65 1960–65 1960–62 1962–63 1962–69 1963–73 1963–72 1963–64 1965 1966 1966–72 1967–68 1967–70 1968–80 1970–75

(G)

(0) (G)

(G)

(G) (G) (G) (G) (G,O)

(G)

(G,O)

874

Jordan

1970

877 880 883 886

Guatemala Pakistan Sri Lanka/Ceylon Burundi

1970–71 1971 1971 1972

Page 213 →889 Philippines “New People's Army”16 892 Zimbabwe/Rhodesia 893 Pakistan

1972–92 1972–79 1973–77

895 898

1975–90 1975–91

900 901 904 907 908 910 913 916 917 919 922 925 928 931 933 934

Lebanon Angola17 Guatemala Afghanistan18 Iran Nicaragua Cambodia El Salvador Mozambique19 Chad20 Nigeria Ugandan Iran Peru21 Nicaragua Somalia22 Burma23 Sri Lanka “Tamil Rebellion”24

1978–84 1978–96 1978–79 1978–79 1979–91 1979–92 1979–92 1980–88 1980–81 1980–88 1981–82 1982–93 1982–90 1982–92 1983–92 1983–93 1995–96 1983–92 1995–96 1984 1984–93 1985–92

937

Sudan25

939 940 941

Nigeria

942 943 944 946 949 950 952 955 961 964 967 970

1985–93 1986 1987–89 1988 1989–90 Liberia29 Romania 1989 1990–92 Rwanda:30 Georgia 1991 Nagorno-Karabakh (during Soviet Union) 1991 Yugoslavia “Croatian Independence” 1991–92 1991–96 Turkey “Kurdish Rebellion”,31 1991–92 Burundi32

Colombia26 Iraq “Kurdish and Shiite Rebellion”27 Indial28 South Yemen Sri Lanka “JVP” Burundi

(0)

(G,O) (G,O)

(G) (G) (G,O)

(neither) (G)

(0)

(0)

973 976 979 982 NCWI NCW2 NCW3 NCW4

Bosnia “Serbian Rebellion”33 Tajikistan34 Liberia35 Angolia36 Abkhasia37 Chechnya38 Yemen Algeria

1992–93 1992–93 1992–96 1992–94 1993

(0) (G)

1995–96 1994 1993–96

Page 214 → a Many civil wars have not been assigned a name by the COW project. In these instances. the name of the country where the civil war took place is used. b (G) indicates outside intervention on the side of the government; (0) indicates intervention on the side of the opposition. 1 France and the United Kingdom intervene on the side of the opposition. 2 The United Kingdom intervenes on the side of the government. 3 This looks like a possible duplicate listing in the codebook (Singer and Small 1994). although the wars with ID numbers 697 and 700 have different starting days. The first is assigned the duration 02.02.94 to 31.08.94. the second 09.06.93 to 03.11.94. 4 France is excluded given locus and since intervention is on the side of the government. 5 Russia is excluded since intervention is on the side of the government and involvement as measured by number of casualties is low. 6 France is excluded given locus and since intervention is on the side of the government. 7 All countries but Russia are excluded from the Russian civil war given locus. Finland and Japan are cases in doubt. given their proximity and since intervention is against the government. 8 Germany and Italy are excluded from the Spanish civil war. Portugal is included since intervention is against the government the number of battle deaths exceed 2.000. and the nationalist junta for a long period of time was based in Lisbon. 9 The United Kingdom is excluded from the Greek civil war given locus and since intervention is on the side of the government. 10 The United States is excluded from the Lebanese civil war given locus and since intervention is on the side of the government. 11 The United States is excluded from the Vietnamese civil war preceding the Vietnam War given locus and since intervention is on the side of the government. 12 Belgium is excluded given locus and since intervention is on the side of the government. 13 The United States is excluded from the Laotian civil war given locus and since intervention is on the side of the government. The Democratic Republic of Vietnam. which intervened on the side of the opposition. is included. 14 The United States is excluded from the Dominican civil war given locus and since intervention is on the side of the government. 15 The United States is excluded from the Cambodian civil war given locus and since intervention is on the side of the government. The Democratic Republic of Vietnam intervened on the side of the opposition and is included. The Republic of Vietnam intervened on the side of the government but suffered extensive battle deaths and is included given locus. 16 Ending date based on the Uppsala conflict data. Note that this conflict is coded as an ongoing civil war in 1992 by COW. whereas the Uppsala data characterize it as an intermediate armed conflict only in 1993 and 1994. 17 Cuba and South Africa are not included given locus of conflict. 18 Ending date based on the Uppsala conflict data. The Soviet Union is not included given locus of conflict and the fact that intervention was on the side of the government. This is a case in doubt. since the Soviet Union suffered extensive battle deaths and intrusions allegedly did occur into neighboring parts of its

territory. 19 Ending date based on the Uppsala conflict data. Note that this civil war is coded as ongoing past 1992 by COW. whereas the Uppsala conflict data characterize it as terminating in 1992. Tanzania and Zimbabwe are not included since they intervened on the side of the government and did not suffer extensive battle deaths. 20 France is not included given locus of conflict. 21 Ending date based on the Uppsala conflict data. 22 The U.S.-led UN peacekeeping effort known as Operation Restore Hope was meant to restore peace with no intention of supporting any of the parties. The intervention is thus not considered on the side of either the opposition or the government (no recognized central government existed in Somalia at the time). Neither the United States. France. Italy. nor Nigeria are included given locus of conflict. Ending date based on the Uppsala conflict data. COW codes the civil war as ongoing past 1992. but the Uppsala conflict data characterize it as an intermediate armed conflict. Page 215 →23 Ending date based on the Uppsala conflict data. 24 Ending date based on the Uppsala conflict data. 25 Ending date based on the Uppsala conflict data. 26 Ending date based on the Uppsala conflict data. 27 The Uppsala conflict data set holds this to be a war only through 1991. whereas COW considers it to be ongoing through 1992. 28 Ending date based on the Uppsala conflict data. 29 Nigeria is not included since it suffered no battle deaths. 30 Rwanda is coded as experiencing ongoing civil war in 1992 by COW, but the war extends only to 1992 in the Uppsala conflict data. Although Rwanda obviously experienced widespread violence after 1992, it is at best unclear whether this has the character of organized violence. 31 Ending date based on the Uppsala conflict data. 32 Note that Burundi is coded as ongoing in 1992 by COW but is a “minor armed conflict” rather than a civil war in the Uppsala conflict data. 33 Ending date based on the Uppsala conflict data. 34 Ending date based on the Uppsala conflict data. 35 Ending date based on the Uppsala conflict data. Nigeria is not included since it suffered no battle deaths. 36 Ending date based on the Uppsala conflict data. 37 Based on the Uppsala data, Georgia was added as a participant. 38 Based on the Uppsala data, Russia was added as a participant. TABLE B3, Extrasystemic Wars within Contiguous National Territory, 1816–1996 ID War Name Time Span 300 Russo-Georgian 1816–25 303 304 312 313 315 316 317 319 322 323 327

Turko-Persian Greek Albanian Russo-Persian1 Belgian First Polish Russo-Circassian First Syrian Texan Bosnian-Turkish Russo-Khivan

1821 1821–28 1830–31 1826–28 1830–31 1831 1829–40 1831–32 1835–36 1836–37 1839

333

Bosnian-Turkish

1841

334 339 340 346

Peruvian-Bolivian2 Cracow Revolt Hungarian First Turco-Montenegran

1841 1846 1848–49 1852–53

352 353 354

Second Turco-Montenegran 1858–59 First Buenos Aires 1859 Second Buenos Aires 1861

355 360

Second Polish First Cretan

365 366 367 Page 216 →368 369 370 374 385 392 394 395 396 401 404 406 408 409 416 417 423 427 430

Algerian Mitre Rebellion Balkan Egypto-Ethiopian Russo-Turkoman Bosnian Russo-Afghan

431 436 439 442 443 445 448 451 454

Sino-Tibetan Tibetan Filipino-Mora Eritrean Kurdish Autonomy East Timor "Fretilin" Western Sahara Ogaden Tigrean

1863–64 1866–67

1871–72 1875 1875–77 1875–76 1878–81 1878 1885 1885 Serbo-Bulgarian3 Second Cretan 1888–89 1895–96 Italo-Ethiopian4 Third Cretan 1896–97 Druze-Turkish 1896 1887 First Italo-Ethiopian5 Russo-Manchurian 1900 Ilinden 1903 Yunnan 1917–18 Russian Nationalities 1917–21 Chinese Muslims 1928 Soviet-Turkistani 1931–34 Tibetan War of Independence 1912–13 First Kashmir 1947–49 Hyderabad 1948 1956–59 1956–59 1972–80 1974–91 1974–75 1974–77 1975–83 1976–83 1978–91

1 Note that with the revised dates of independence for Iran this would be an interstate rather than extrasystemic war.

2 Note that with the revised dates of independence for Bolivia this would be an interstate rather than extrasystemic war. 3 Note that with the revised dates of independence for Bulgaria this would be an interstate rather than extrasystemic war. 4 By the revised system membership criteria. Ethiopia would be an independent state and this would subsequently be an interstate war. Fighting took place in Ethiopia only. and Italy is excluded by the locus criterion. 5 By the revised system membership criteria. Ethiopia would be an independent state and this should subsequently be considered an interstate war. Fighting took place in Ethiopia only. and Italy is excluded by the locus criterion.

Page 217 →

APPENDIX C A Primer on Generalized Additive Models In many cases, there may be strong reasons to doubt whether the relationship or functional form between a set of covariates and the response or dependent variable of interest necessarily is linear. The generalized linear model framework, or GLM (see McCullagh and Neider 1989), extends the basic linear regression model to a variety of nonlinear functional forms to which researchers can resort. These include the well-known logit and probit link functions common for binary dependent variables that have been used in this study. In addition, researchers often impose various kinds of transformations on variables or introduce interaction terms to emulate nonlinear functional forms between right-hand-side variables and the response. These approaches are often unsatisfactory on two counts. First, these methods all impose a given, deterministic shape on the functional forms between the right-hand-side variables and the response. These may be false, inappropriate, or misleading in light of uncertainty about the correct functional form. Second, the solutions proposed are essentially all global and do not take into account potential differences in functional form over the range of values on the right-hand-side variables. To use an example from the present analysis, we have few theoretical insights about the specific functional form for the effect that peace exerts on the likelihood of new outbreaks of conflict. Although we expect the probability of conflict to decline monotonically with greater time periods at peace, we would not necessarily expect this decrease to be gradual or a constant proportion across the entire range of values on the variable. Stated differently, even when the sign of effects can be assumed to be constant, the magnitude of the effects over the entire range of values on the right-hand-side variable is not necessarily a constant proportion or consistent. Similarly, for interactive effects between right-hand-side variables and the response we may not expect the effect of one covariate to be consistent or linear in the other variable across the entire range of values. The effects of a country’s own authority structure Page 218 →on the likelihood of conflict, for example, may vary over different types of regional context. The generalized additive model framework, or GAM (see Hastie and Tibshirani 1990), provides a nonparametric approach to possible nonlinearity in a variable’s effect on the response that does not require us to specify a functional form parametrically. The additive model extends the basic linear model by modeling the effects on a response y of a set of covariates X nonparametrically through locally weighted regression smoother estimates f(t) derived at an arbitrary point t of the values of a covariate of interest. We compute a weighted average of all those observed values yi with predictors xi in some way “close” to the target point t. The estimated smoothing function can be represented as where Sλ denotes the specific weight function. The smoothing parameter λ indicates the degree of smoothing applied to the local estimates or the tradeoff between parsimony and goodness of fit to the observed data. GAM versions can be derived for the entire class of generalized linear models, and GAM models can include combinations of both parametric and nonparametric terms. The smoothing function itself can be of a variety of different types. The two most common forms of scatterplot smoothers are localized regression smoothing or LOESS (Cleveland and Develin 1988; Cleveland, Grosse, and Shyu 1993) and cubic smoothing splines (Hastie and Tibshirani 1990; Hastie 1993). Given some target point x0, the local regression smoother estimates the relationship between x and y by estimating from a set N (x0) of the q “nearest neighbors” observations to x0 determined by a specified “span.” Each element xi in N(x0) is then assigned a weight wi by the tri-cube weight function where

Page 219 →The smoothed values at xo are then taken from the fitted values in a weighted least squares regression using the weights Wi’. The cubic smoothing spline is a function that minimizes the “penalized” residual sum of squares subject to some roughness penalty λ. The cubic smoothing spline function divides the time interval into various subintervals and fits cubic equations for each interval subject to certain constraints. The decision about how much smoothing to apply is a tradeoff between accuracy and parsimony. On the extreme side of parsimony, a linear regression can be seen as a special case of a localized regression that is infinitely smooth. In contrast, overly low spans can lead to very rugged predicted surfaces that are vulnerable to idiosyncrasies of the observed data and yield unwieldy results with little additional theoretical insight. We can test the restriction of linearity by an F-test for continuous variables or a chi-square test based on the difference in deviance. Although assessing the numbers of degrees of freedom consumed by the nonparametric terms is not entirely unambiguous, Hastie and Tibshirani (1990) suggest that this can be approximated by the sum of the trace of the so-called smoother matrix Sλ(xi,xj). Generalized additive models strike a balance between the overly strict linearity assumption of the linear model and the risk of excessive inductivism inherent in flexible models of inference such as neural networks (see Bishop 1995), which are far removed from the regression framework and difficult to interpret for most applied social scientists. Detection of nonlinearities and inspection of the shape of scatterplot smoothers can be used for confirmatory purposes to evaluate hypotheses about nonlinear functional forms or, in a more exploratory fashion, can yield important clues about functional form, which in turn can help improve theory construction. See Hastie and Tibshirani 1990 for further discussion of technical issues or Cleveland et al. 1993 and Hastie 1993 for details on the implementation of GAMs in the statistical package Splus, Beck, and Jackman (1998) provide an overview of GAMs with numerous applications to political science.

Page 220 →

APPENDIX D Polity Democracy Scale and Modifications The redefinition of system membership also required some additional modifications to the Polity data for the purposes of this study. The changes in the definition of system membership will exclude some dubious entries for which data are available in the Polity data such as Norway prior to independence in 1905. The Polity data set contains separate entries for Austria and Hungary prior to 1918. In Gleditsch and Ward (1999), we regard the Austro-Hungarian Empire as one polity. For the purposes of this study, I merged the data for Austria and Hungary between 1875 and 1918. Note that these polities have identical values throughout the period. For a number of countries, one or more additional initial years were added in light of revised dates of independence. These were assigned the values of the first available annual observation. This includes the following cases (with year added in parentheses): Algeria (1962), Baden (1816–17), Belgium (1830), Cameroon (1960), Gabon (1960), Central African Republic (1960), Chad (1960–61), Ghana (1957–59), India (1947–49), Israel (1948), Kenya (1963–64), Kuwait (1961–62), Latvia (1918–19), Laos (1953), Madagascar (1960), Malawi (1964), Mauritania (1960), Mongolia (1921–23), Mozambique (1975), Papua New Guinea (1975), Togo (1960), Tunisia (1956–58), and South Vietnam (1954). While these changes may appear negligible, the initial years for both Israel and India were associated with conflicts that otherwise would have dropped out of the analysis. For the German Democratic Republic, an additional final year (1990) was added by extending the values for 1989. Finally, for two cases — Tunisia and Switzerland — no values were available in the Polity data for the periods 1825–81 and 1816–47, respectively. In the case of Switzerland, I am reasonably confident that the 1848 values can be applied back to 1816. I am more doubtful that the same would hold for the case of Tunisia, but I have applied the 1848 values to 1825 in the Page 221 →absence of other information. This coding, however, should be recognized as tentative. Table D1 details the construction of the combined institutionalized democracy scale from the five different subcomponents or dimensions of authority structures in the Polity data set. See Gurr, Jaggers, and Moore 1989 or Gleditsch and Ward 1997 for further details. TABLE D1. The Construction of the Polity Institutionalized Democracy Scale

Page 222 →

APPENDIX E Symbols and Notation The following table summarizes the notation, definitions, and ranges of possible values for the variables used in this study. The raw data that go into the construction of these measures are discussed in greater detail in chapter 3. The following conventions are used throughout. All matrixes are denoted in boldface. The letter i indexes the principal country of observation, the letter j denotes the J – 1 other countries in the international system (which mayor may not be contiguous with i), and t denotes the time period of observation. TABLE E1. Symbols and Notation Page 223 → Page 224 →

Page 225 →

Notes Chapter 1 1. Ward and Lofdahl (1995) allegedly found this figure on a poster in a Dutch bar. 2. A gravity model between two units i and j can be expressed as where Ii,j denotes the (level of) interaction; Pi refers to the population, mass, or density of unit i; D i,j denotes the distance between units i and j; the terms α1, α2, and β indicate constants, and k denotes a scale coefficient. Assuming equal mass or density among units, this simplifies to Rapoport (1963) provides a useful overview relating gravity or distance decay models to other general models of social interaction. 3. Identifying the “real” issues of conflict is wrought with several difficulties. Territory, for example, is closely related to other contentious issues such as resources and ethnic diasporas. Wars must take place somewhere, hence it is hard to conceive of conflict not involving some territorial aspect. Even though some have attempted to test the relative importance of “territoriality” and “proximity” (e.g., Senese 1997; Vasquez 1995), researchers may interpret the relevant events differently. Disputes may involve more than one issue, and the relative importance of issues may vary among parties. Attempts to distinguish between territorial and nonterritorial disputes typically generate ambiguous cases. For example, Huth (1996) classifies the dispute over Berlin as territorial, despite its obvious relation to the superpower confrontation. By contrast, Finnish territory lost to the Soviet Union does not qualify as a territorial issue since the need for caution in its foreign policy prevented Finland from making public claims on the lost territory. 4. The term institution is sometimes restricted to organizations or formal structures and rules. Here I use the term more generally, including both formal and informal rules that entail stable patterns of social interaction (e.g., Knight 1992). 5. This is simply to illustrate the range of different feasible combinations of hostility and integration and not a literal claim that cooperation and conflict form a single underlying phenomenon in which one is merely the opposite of the Page 226 →other. Conflict and cooperation may be at least partly independent, and many different combinations of the two may coexist. Accordingly, one may conceptualize ranges of possible relations in multidimensional space with separate hostility and integration dimensions (see, e.g., Bond, Jenkins, and Taylor 1997; and Boulding 1978, 1992). 6. Herz (1950) coined the term security dilemma. Whereas traditional realism holds conflict to be inherent to human nature (e.g., Morgenthau and Thompson 1985), structural varieties of realism relate conflict to the unavoidable potential for conflict in an anarchic international system (e.g., Waltz 1979). Jervis (1978) and Snyder (1971) illustrate through a series of simple game-theoretic models how the structural properties of anarchy induce problems of conflict and cooperation even when parties may have largely defensive motives. Powell (1993) contends that it is not so much any structural property of anarchy that creates the potential for conflict between states but the fact that states can resort to violence. 7. Grieco (1988) argues that many studies of the prospects for cooperation neglect the fact that states are concerned about relative gains from cooperation rather than merely absolute gains. Fear that other states will gain larger benefits that can be converted into greater power may impede cooperation even when absolute gains accrue to both sides. Snidal (1991) shows that relative gains can impede cooperation only under quite limited conditions. Powell (1993) shows that the core claims of realism can be expressed as special cases depending on the cost of using force in a model in which states maximize absolute gains, and he questions the utility of assuming that states maximize relative gains (see Grieco, Powell, and Snidal 1993). 8. Some researchers invoke mechanisms outside the international system such as individual actors (e.g., Gilpin 1981), periodic technological change, or economic fluctuations (e.g., Goldstein 1988) to “explain” changes in key elements of the international system. Regardless of whether these assertions are correct or not, they ultimately weaken the case for the primacy of systemic explanations.

9. Recent efforts have made substantial progress in modeling bilateral strategic interaction (see, in particular, Signorino 1999 and Smith 1999). Yet, with a few exceptions, such as Schrodt and Mintz 1988, studies have not modeled multilateral dependence between units. Schrodt and Mintz do not consider linkages between attributes of states and their behavior. 10. Chapter 3 provides a more thorough overview of the foundations for spatial statistical analysis. 11. A spatial connectivity matrix W is similar to an adjacency matrix in graph theory (see Harary, Norman, and Cartright 1965). Bavaud (1998) stresses the resemblance of spatial connectivity matrices and Markov chains and puts forward some important proofs on their properties. 12. These data are described in greater detail in Gleditsch and Ward 2001. 13. By convention, the diagonal of the connectivity matrix is set to zero so that countries are not considered to be contiguous with themselves. 14. The expected value of the variance of Moran’s I depends upon sampling Page 227 →assumptions. Cliff and Ord (1973: 15) show that under a normality assumption, , whereas under randomization

where all variables as defined earlier. To follow established conventions, I only report results based on the normality assumption. I have also calculated standard errors using the randomization assumption, and in most cases the results were very similar. Although the null hypothesis here obviously is spatial independence(i.e., that observations are not correlated across space), these tests can be ambiguous. Since we only represent one potential pattern of spatial dependence, we can only fail to reject a null relative to a specific hypothesized pattern and cannot conclusively rule out whether other patterns of dependence may apply. 15. Several statistical measures of local clustering yield observation-specific values that indicate the similarity among observations around each location i. I discuss these in greater detail in chapter 3. 16. Map 1.1 excludes four states that were coded as “participants” in the civil war in Somalia in the COW data in 1992 but were not included in the Uppsala data – France, Italy, Nigeria, and the United States. The United States might have maintained a substantial presence in Somalia until a total of 18 casualties forced withdrawal, but no acts of war took place on U.S. territory. Any effort to map the geographical distribution of war immediately highlights the distinction between conflict occurring in a country’s core territory (or in the immediate vicinity) and participation in wars elsewhere in the international system. I return to this issue in chapter 3. 17. The expected value depends upon sample size, but the flat nature of the line indicates only minor changes from one year to another and suggests that comparisons across time are not too problematic.

Chapter 2 1. See, for example, Haas 1964, 1968; Etzioni 1965; and Galtung 1973. 2. See, for example, Merritt and Russett 1981 for an overview of this research. 3. See, for example, Alker 1962; Brams 1965, 1966a, 1966b, 1968; Chadwick and Deutsch 1973; Goodman 1963; and Hughes 1972. 4. Some argue that trade under some circumstances may exacerbate conflict (see, e.g., Barbieri 1996 and Choucri and North 1975). The debate on the Page 228 →empirical issues is not settled. Many of the ambiguities appear to stem from variable sum versus constant sum measures, differences in sample selection, and assumptions about missing data (see Gleditsch 2002). The trade and conflict literature also displays many theoretical ambiguities, perhaps most importantly its lack of economic content. Much of this literature cites controversies between liberals and mercantilists in the nineteenth century and is couched in terms largely unrelated to contemporary trade theory. 5. See, for example, Goldstein and Freeman 1990; Goldstein 1991; Goldstein and Pevehouse 1997; Hermann 1973; North et al. 1963; and Rajmaira and Ward 1990. 6. Research on the democratic peace has also been coupled with a renewed interest in Kant’s ([1795] 1991)

Perpetual Peace, which suggests a pacific union between republics (see, e.g., Cederman 2001; Doyle 1986; and Russett, Oneal, and Davis 1998). Kant, however, argues that democracies are inherently more peaceful rather than the dyadic proposition that democracies do not fight each other, and researchers appear to have discovered Kant after uncovering the empirical regularities between democracy and peace. Thus, it is at best questionable that Kant “anticipated the democratic peace” or motivated this research. 7. Bueno de Mesquita and Siverson (1995) also hold that leaders stand to gain little from apparent foreign policy successes. However, many formal models of diversionary conflict assume exactly the opposite, namely, that more capable leaders can extract political gains by demonstrating resolve in handling foreign policy crises and may have incentives to instigate foreign conflict (e.g., Hess and Orphanides 1995; Richards, Morgan, and Wilson 1993; Smith 1996, 1998). There is at best limited evidence for such diversionary uses of force. However, the popularity of these beliefs suggests that it is at least not immediately obvious that war is not always unpopular and raises doubts about whether differences in costs of failure alone can prevent conflict. 8. More cumbersome institutional procedures with various layers of formal ratification may inhibit escalation by inducing delay. The prospects for alternative means of resolution may improve if the sense of crisis or short time for response is weakened. However, executives in democratic systems typically possess ample discretionary powers in foreign policy. It seems unlikely that such procedural hurdles in themselves prevent leaders from escalating conflicts if they expect no significant opposition to the decision. 9. Singer’s (1961) thesis on the “incommensurability between levels of analysis” is often invoked in research on the democratic peace (e.g., Ray 2000). However, this seems a problem with the existing theories rather than an inherent feature of relations between democracy, conflict, or peace. 10. There has recently been a wave of interest in systemic-level implications of democracy and peace. Some studies show that although the marginal probabilities of war proneness for democratic dyads are consistently lower than for other dyads, dyads in which two states are nondemocratic appear to be less war prone than “mixed” dyads with a democracy and a nondemocracy. Gleditsch and Hegre (1997) use these stylized facts to show that, assuming fixed probabilities of war at the dyadic level given regime type, democratization among states could Page 229 →lead to a higher likelihood of war in the system as the number of mixed dyads increase (see also Crescenzi and Enterline 1999). Others have looked at implications for war at the systemic level of other empirical regularities such as the tendencies for democracies to win wars and losing regimes to be replaced in the aftermath of conflict (e.g., Mitchell, Gates, and Hegre 1999; Siverson et al. 1998). Despite commendable efforts to examine the broader implications, these studies simply assume that the dyadic-level generalizations are true and then try to infer system-level implications and are less helpful in clarifying linkages between authority structures and behavior. 11. Elman (1997), for example, holds the declaration of war by some Allied powers on Finland following the entry of the Soviet Union on the Allied side in World War II to “challenge” the democratic peace even though no acts of war occurred between Finland and democracies on the Allied side. The dyadic proposition holds with a fairly lenient definition of liberal democracy as well as a relatively inclusive notion of conflict (e.g., Ray 1993). Few proponents hold that democratic peace theory should be judged according to whether wars have ever occurred between democracies but tend to invoke probabilistic criteria about the frequency of conflict (e.g., Russett 1995). 12. See, for example, Beck and Tucker 1996, Raknerud and Hegre 1997, or Gates and McLaughlin 1996. 13. A standard argument is that since wars are so rare we can learn more about conflict and peace by examining a broader range of hostile disputes from which wars eventually may result (e.g., Bremer and Cusack 1995). Democratic peace research often uses the so-called militarized interstate disputes (MID) as a superset of situations that potentially may lead to wars. I discuss some problems with the MID data in chapter 3. Measurement problems aside, it is not obvious that theories linking democracy to peace suggest that democracies are less likely to be involved in any type of conflict (e.g., Gochman 1996–97). At a dyadic level, democracies could be more likely to engage in limited-scale disputes, as these can be pursued with near impunity if escalation to war is perceived as unlikely (Gartzke 1998a). 14. Possible exceptions include Chinese threats against a democratic Taiwan and the German and Italian support for the nationalist revolt against the Republic in the Spanish civil war. 15. To anticipate the actual empirical analysis in chapter 4, it turns out that the local clustering in time at peace is correlated with the clustering in level of democracy at 0.55 over the entire period 1875 to 1996 and

about 0.8 for years in the 1990s. 16. Zambia is assigned a democracy score of six (the typical threshold for being considered a “democracy”) in the Polity data for the period 1991–96. 17. Gartner et al. (1997) found local relationships between casualties and attitudes toward the Vietnam War within U.S. counties, too. 18. Democracy is measured by the mean level of institutionalized democracy at a 21 point scale ranging from – 10 to 10 and the proportion of democracies with a score of six or above. The values shown in figure 2.2 are based upon the Polity data set. This will be discussed in greater detail in chapter 3. Page 230 →19. Some of the differences may, of course, stem from new states entering the international system (e.g., Doorenspleet 2000). Several of the major breakpoints in figure 3.2 are associated with events changing the composition of the system, notably the two world wars and the process of decolonization. Other measures, such as the mode of the Polity scale, however, suggest that there is no simple relationship between system size and the distribution of democracy. The mode is the minimum value (–10) well through the middle of the nineteenth century and fluctuates between high and low values in the twentieth century after World War I. Only in the latter part of the nineteenth and the earliest part of the twentieth centuries does the distribution display a modal value close to the midpoint. 20. Gelpi (1997) surmises that externalization would be more common in democracies since more constrained polities will face greater difficulties than nondemocracies in repressing political dissent and turmoil directly and thus would be more likely to resort to alternative means. Enterline and Gleditsch (2000) find that constrained leaders do not seem less likely to apply negative sanctions at high levels of domestic conflict but are somewhat less likely to experience domestic conflict in the first place. 21. Mansfield and Snyder (1997) invoke the conflict in Rwanda (which is a civil war) as one of the examples of how democratization increases the likelihood of war. Since Rwanda can hardly be said to have become more democratic, this example begs the question of whether the theory also applies to conflict in the absence of institutions. Snyder (2000) uses the term democratization in a way that includes increased popular contestation, even in the absence of changes in political institutions. This makes it impossible to judge the consequences of changes toward democratic institutions. Many of Snyder’s case studies seem to revolve around weak and unpopular autocratic polities rather than democratizing polities. 22. Exceptions include Krain and Myers (1997), Benson and Kugler (1998), and Hegre et al. (2001), who argue that democracy tends to inhibit civil wars.

Chapter 3 1. Rather than trying to explain the emergence of nationalism itself, I am merely arguing here that nationalism transformed the character of the modern state. For useful reviews of theories of nationalism, see Smith 1971, 1994; and Tamir 1994. 2. Or more specifically, this is the case for studies using explicit criteria. Many studies purport to examine “all states” in the world or international system without putting forward any explicit criteria but upon closer inspection simply let the available data define the population and do not consider the universe explicitly (see Bollen, Entwisle, and Alderson 1993; and Gleditsch and Ward 1999). 3. Prior to 1920, Singer and Small (1972: 20) judge a state to have been Page 231 →independent if it satisfies two criteria: (1) did the entity have a population greater than 500,000 and (2) was the entity “sufficiently unencumbered by legal, military, economic, or political constraints to exercise a fair degree of sovereignty and independence?” The second was in practice assessed by whether a state maintained formal diplomatic relations with Great Britain and France at or above the level of chargé d’affaires in the capital city. After 1920, however, Singer and Small (21) rely on a nation either: (1) being a member of the League of Nations or the United Nations at any time during its existence or (2) meeting the minimum half-million population criterion and receiving diplomatic missions from any two major powers rather than necessarily France and Great Britain. Various updates have introduced additional changes, but the criteria and revisions have not been publicly documented. As the population threshold no longer seems to be in place, several microstates such as Monaco (population 31,900), Liechtenstein (31,400), San Marino (24,700), and St. Kitts and Nevis (41,800) are now included as system members by virtue of their UN membership.

4. The 1867 date is quoted, for example, in the CIA’s “World Factbook” (Central Intelligence Agency 1998). 5. Spatial statistics is a subfield of statistics concerned with any form of dependence among observations, not necessarily limited to spatial patterns. A general introduction to spatial statistics can be found in Anselin 1988; Cliff and Ord 1973, 1981; Cressie 1991; and Ripley 1981. Many expositions assume regularly shaped units or lattices, which are problematic in international relations research. Examples of studies applying spatial statistics to the study of world politics include Anselin and O’Loughlin 1992; Gleditsch and Ward 2000; Kirby and Ward 1987; Ling 1998; Murdoch, Sandler, and Sargent 1997; O’Loughlin 1986; and Ward and Gleditsch 2000. 6. Since national borders change over time, distances between polities must be measured by means of an approach that is sensitive to such changes over time rather than based on present-day boundaries. The minimum distance data set considers the actual territorial units that shift between states, and we can find the minimum distance between entities from the appropriate unions of these parts. 7. A matrix is row standardized by dividing each row element by the row sum so that all entries in each row sum to one. 8. xT is commonly referred to as the “spatial lag” of x. This terminology is unfortunate since the connectivities in W are not necessarily geographical, the row standardization approach is rather arbitrary, and there is no clearly defined lag operator over space. 9. Many potential matrices can be unwieldy to interpret substantively since the resulting metric of the spatial lag will be relative to the number of borders and no longer matches the metric of the original variable. In addition, the analogy to Markov chains will no longer hold for many alternative matrices. 10. This rules out efforts to extend conflict to social relations and structures without active agency such as “general exploitation principles” (e.g., Roemer 1982) or measures of “structural violence” (e.g., Høivik and Galtung 1971) in terms of underachievement, premature death, or other forms of suboptimality. Page 232 →Such phenomena might be widespread and interesting in their own right. However, it is questionable whether lumping together explicit and positional incompatibilities under the same label enhances analytical clarity. 11. Recall, for example, Easton’s (1965: 21) definition of politics as the authoritative allocation of values. 12. Gartzke (1998) points out that willingness and opportunity to use force cannot be sufficient conditions for conflict since willingness to ultimately resort to force need not imply an actual need to exert force to achieve desired outcomes. However, it is difficult to identify the universe of cases that could potentially lead to violent outcomes. 13. This criterion excludes much of contemporary and historic violence. Rummel (1995), for example, points out that democide, or violence exerted by governments on their own populations, has been a far deadlier force in the twentieth century than interstate wars. Much of this would not be considered conflict by the above criteria since the victims did not constitute an identifiable party with effective resistance. 14. The reliability of such proportions is questionable, as coding biases and media exposure probably understate the amount of civil war and conflict outside the Central European state system in earlier time periods. Nonetheless, one would expect the recent increase in sovereign nation-states to expand the opportunities for civil wars to become interstate. 15. New research linking domestic and international politics challenges the sharp separation of conflict between states and conflict within states. Holsti (1996) examines the applicability of international relations theory to contemporary civil wars. Recent work on ethnic conflict stresses security dilemmas reminiscent of those between states (e.g., Fearon and Laitin 1996; Lake and Rothchild 1996; Melander 2000). 16. Adding further to the complexity, extrasystemic wars are further divided into two subtypes:imperial wars, in which system members engage in war against an independent political entity not considered to be a member of the interstate system due to limitations on its independence or lack of recognition from other states, and colonial wars, in which the adversary was a colonized or dependent entity with an “ethnically different population” located at some geographical distance or at least peripheral to the center of government of the system member. 17. The U2 affair is classified a MID, with Norway as a participant, but its hostility level is given as–9 or “missing.” 18. Since the theoretical criteria for war are the same, one would in principle expect the two to yield nearly

identical entries for interstate wars, save for some minor revisions. As noted in Ward and Gleditsch 1998, the two data sets exhibit quite different assignments of involvement in interstate wars. 19. I follow the UN criteria for overseas colonies and interpret a state’s core territory in a relatively strict sense as contiguous territory. Subsequently, the conflicts in Eritrea and East Timor are considered civil wars for Ethiopia and Indonesia, but the war of Algerian independence is not considered a civil war Page 233 →within France even though Algeria formally was considered a part of the French republic. 20. Oneal and Russett (1999), for example, use the generalized estimating equation (GEE) proposed by Liang and Zeger (1986). 21. Beck et al. (1998) develop an alternative related approach that uses a set of dummy variables instead of the nonparametric smoothed term. 22. New actors entering the system create additional problems. Although unfamiliarity and lack of experience may increase the risk of conflict (e.g., Cederman 1997; Majeski 1996), the magnitude is probably not comparable to cases of recent conflict involvement. I have tried to find a middle ground by assigning new actors a value of four years at peace at the time of entry to the system in some of the variables in this study. This value implies a higher than average risk at the time of emergence but yields a rapid rate of decay for states that do not experience conflict after independence. 23. Modern trade theory provides various theorems outlining when trade will enhance welfare (see, e.g., Dixit and Norman 1980). 24. It has been suggested that since the GDP figures in the Penn World Tables are given in fixed prices (i.e., 1985 U.S. dollars) converted to purchasing power parities (PPP) they cannot be used with trade data in current prices (e.g., Barbieri 1998). Although these are “different,” the two are not incomparable provided appropriate corrections for inflation are made. Whereas the numerator of the trade to GDP ratios should be as close as possible to the commercial values of the commodities being transacted, the ideal denominator is some type of indicator based on resources or wealth and there are no inherent problems in having PPP estimates of GDP in the denominator. I am grateful to Keith Maskus for clarifying this point for me. 25. These projects define what constitutes an event somewhat differently. Gerner et al. (1994) point to the fact that researchers rarely define action explicitly. They do not directly observe the activities of interest but examine reports of them. They suggest defining event more generally as “an interaction, associated with a specific point in time, that can be described as a natural language sentence, that has as its subject and object an element of a set of actors and as its verb an element of action, the content of which are transitive verbs.” 26. The Global Event Data System (GEDS) at the University of Maryland was designated under the Data Development for International Research (DDIR) project’s phase 2 (Merritt, Muncaster, and Zinnes 1993) to update the current COPDAB data. These data are currently not publicly available. Previous public releases have covered only 1990 to 1992 for global data. However, as of March 2001 the global data that have been publicly released cover only 1990 to 1992. 27. Human coded events data such as COPDAB and WEIS have to some extent been supplanted by a new generation of event data relying entirely on automated machine coding. The best-known example is the probably the Kansas Event Data System (KEDS). Machine coding allows faster and more extensive processing and minimizes sources of error and coding biases due to human judgments. Although there are many high-quality event data for particular regions Page 234 →and time periods, no comprehensive machine-coded event data set is available at the present time. 28. Note that some researchers, notably McClelland (1983), reject scaling and advocate treating events as strictly nominal categories. 29. Reuveny and Kang (1996) regress the aggregate Azar and Havener weighted scale for COPDAB and the Goldstein (1992) scale for WEIS on one another. The coefficient for each source regressed on the other is highly significant, but the intercepts of these regressions are not significant for most dyads and the error term does not seem to display higher order autocorrelation or heteroskedasticity. 30. I am grateful to William J. Dixon for pointing this out to me. 31. Other studies have explored shorter (five years) and longer (20 years) windows, but the length of the window does not appear to exert a large difference on the result (e.g., Gleditsch and Ward 2000). The 10 year window follows existing research (e.g., Gleditsch and Ward 2000; Mansfield and Snyder 1995, 1998; Ward and Gleditsch 1998). 32. This measure differs in one important respect from that used in Ward and Gleditsch 1998 in that I use

the standard deviation and do not include the observation of the current year in the calculation.

Chapter 4 1. Since the design differs in a number of respects, there is no simple basis for comparing the results found here with dyadic studies in general. As an illustrative example, however, we can compare the above results with the predicted marginal effects in Oneal and Russett 1997. Their findings indicate that the predicted probabilities of a dispute in contiguous dyads decrease from .071 to .054 when the parties are at either the minimum or maximum level of the Polity institutionalized democracy scale, respectively. By contrast, the results in Table 4.1 imply predicted probabilities of conflict of .065 and .014 for autocracies in an autocratic context and democracies in a democratic context, respectively. 2. The number of cases in Table 4.2 decreases with lower distance thresholds since more countries become “islands” with no adjacent neighbors in their regional context the more restricted the threshold. Since the actual observations differ across regressions, the results are strictly speaking not entirely comparable. 3. The actual significance levels for these tests are somewhat tentative, but in either case the linearity restriction is rejected at any conceivable criteria of statistical significance. 4. The deviance residuals are defined as di = sign is the predicted log-odds. These can be standardized to have approximately equal variance by dividing by , where hi is the ith diagonal element of the so-called hat matrix H = X(XTX)-1XT (e.g., Belsley, Kuh, and Welsch 1980). 5. Figure 4.4 displays the impact of time at peace on the likelihood of Page 235 →interstate war. The shape of the effects of time on the other conflict variables is similar and thus not shown. 6. Unlike in Ward and Gleditsch 1998, the current year is not included in the window used to estimate the variance here, as this risks picking up on changes caused by conflict. The seeming effect of instability on the risk of conflict turns out to be quite sensitive to whether or not the current value is included in the window (see Gleditsch and Ward 2000 for further discussion). 7. Even though the variables are functions of one another and the permissible combinations of values are constrained, more than one set of values for the standard error can be consistent with certain values on the change variables. In this sense, these are not always uniquely defined. Note also that the standard deviation in levels depends upon the number of missing values in the 10 year window. Under such interruptions in authority structures, the variance will increase as the valid N of the 10 year window becomes smaller. 8. This corresponds reasonably well to the global sample means. 9. When controlling for time dependence in equation 4.3, the sign of the coefficient estimates tends to remain the same although the statistical significance of many of the coefficient estimates is somewhat reduced. In the case of the effects of democratization on civil war, the coefficient estimate for the sign of change is now negative, though far from statistically significant. As a result, the previous positive effect of democratization on civil war is weakened. One interpretation of this is that in many cases in which democratization is associated with violent conflict, the violent conflict often precedes democratization or political change. In this sense, it may be argued that democratization does not “cause” conflict in and of itself but that conflicts persist in democratizing states and the prospects for peace do not improve with democratization, at least in the short run. 10. See Hamilton 1994 or Freeman et at. 1998 for more extended discussions of cointegration. 11. The critical values for the Dickey-Fuller test differ from the conventional values for the student’s tstatistic. 12. The reverse null has led to a host of criticism against unit root tests. What is, for example, the power of a test that the order of integration is one rather than 0.96? Time-series in which the order of integration is close to, but not exactly, one are said to be “near integrated” (e.g., DeBoef and Granato 1997).

Chapter 5 1. Norway has traditionally exported large amounts of dry cod to Nigeria as well as to former Portuguese colonies. 2. Economic flows are somewhat more susceptible to change than authority structures are, and a shorter

time window seems appropriate here. In addition, a window of 10 years would have reduced the sample drastically, given the limited temporal scope of the data. Page 236 →3. The coefficient values in summary form for the intercept, compatibility, and trade density scores are –2.485 (.075), –.415 (.025), and –5.289 (1.111), respectively, with a likelihood ratio model chisquare of 42.5(df = 2). 4. Conventional measures of democracy essentially define autocracies by what they are not and treat these regimes as a residual category of non-democracies (e.g., Gartzke and Gleditsch 2000). This obviously lumps together a fairly broad and heterogeneous set of nondemocracies. Both the Iranian regime that preceded the Islamic revolution and the regime that followed in its aftermath are “autocratic” with respect to institutions, but these would certainly be considered quite different by several other plausible political criteria. 5. The null model is not equivalent to that in Table 5.3 since that sample also includes the observations with ongoing years of conflict that have been censored here. 6. A regression of ongoing war years retaining the smoothed function of the years at peace lends some support to this interpretation, insofar as the estimates of a country’s own level of democracy and the density of trade attain statistical significance. However, these results are quite tentative and should be interpreted with considerable caution, as the smoothed function of the duration of peace may not be well behaved when the dependent variable is not censored. 7. Oneal and Russett (1999), for example, argue that it is inappropriate to censor ongoing war years since leaders at each stage can evaluate whether to continue conflict or not. 8. Data imputations such as linear interpolation in the trade data also might induce additional time dependence. 9. The two dimensions need not coincide, but this abstraction seems justified as they are generally correlated. 10. Skeptics might wonder whether the skewed nature of the trade density measure underlies the insignificant effects on conflict found here. Excluding all cases with densities above 0.5, however, does not change these results dramatically. Thus, these extreme cases do not in themselves cause trade integration to become insignificant. As discussed in chapter 3, trade may be a theoretically unsatisfactory measure of interdependence on other accounts, but data constraints effectively prevent the use of alternative measures here. 11. Many contend that much of the repression and many of the counter-insurgency strategies imposed in the Southern Cone states would have been inconceivable outside of the Cold War context. There is also some evidence of linkages between external interactions and domestic conflict behavior (e.g., Davis and Ward 1990). 12. This is not to say, however, that much of the civil conflict in Africa has been devoid of international dimensions. Civil wars in Africa have involved intervention by former colonial powers, South Africa, and even Cuba. In addition, many states currently have committed troops in the conflict in the Democratic Republic of Congo. In early 2001, Zimbabwe was estimated to have 12,000 troops involved. The recent clashes between Ethiopia and Eritrea will probably qualify as interstate war in future COW updates. The fact that this Page 237 →grew out of a protracted preceding civil conflict illustrates how difficult it is to impose the interstate and civil war distinction on a messy empirical world. 13. Starr and Most (1983, 1985) and Anselin and O’Loughlin (1992) cite Kende’s (1971) finding that Africa provided the greatest share of nation-years of conflict involvement during the preceding 25 years as evidence of the particularly violent nature of Africa. However, this inference is dubious on two counts. The Kende data set includes both internal and interstate conflicts, including conflicts with zero fatalities. Since Africa includes a large number of nations, the unweighted share of global conflict years is a poor baseline for assessing the “propensity for violence.” 14. According to Deutsch (1977: 4), “the claims that the boundaries among African, Latin American or Asian states are arbitrary, having been determined merely on the whim of colonial administrators, has been erected on a solid basis of ignorance . . . Most people who make these claims have not looked at settlement density maps . . . and why the boundaries between [African settlement clusters] often was not a very serious matter. . . . Between one settlement area and another there were, and still are, areas of very thin settlement; and colonial administrators, who needed many people to tax and to exploit as customers and sources of labor, were usually interested in the densely settled areas and not in the thinly settled ones.”

15. A necessary condition is trivial if its logical or feasible extension clearly is a strict subset of some other concept, which is part of the definition of the condition of interest itself (see, e.g., Braumoeller and Goertz 2000: 854–56).

Chapter 6 1. There are some possible exceptions to this statement, notably studies on whether the extent of external dependence of the domestic economy or a state’s position in the so-called world system influences its prospect for democratic rule (e.g., Bollen 1983; Wallerstein 1979). Leaving doubts about these theories aside (see, e.g., Weede 1996 for a critique), such studies usually consider only forms of dependence between national economies. Furthermore, few draw explicit linkages between world system position and authority structures. Those that do almost exclusively hypothesize that external factors affect domestic conditions, which in turn influence a country’s authority structures or propensity for democracy. Somewhat ironically, the processes by which external dependence is held to impede democratization are actually quite similar to those highlighted by the social requisites school. 2. Some critics, like Tilly (1984), hold that cross-sectional designs in themselves are based on an underlying assumption that history follows general sequences or similar paths. This assertion, however, is highly questionable. Since the values on right-hand-side variables can both decrease and increase, there is no form of “evolution” assumed by a cross-sectional design alone. If the processes over time and space are similar, the variation across units in a cross section Page 238 →might also be more informative about long-run behavior than relatively short individual unit time-series are. 3. In addition, the structural equation with latent variables (LISREL) framework in Bollen’s (1980) work on the measurement of democracy, which dominated much of the earlier research, is not easily extended to longitudinal designs. 4. I will demonstrate later that the temporal autoregressive component of the democracy data approaches one or perfect correlation. Thus, to subtract this from the data to purge the serial correlation of the error essentially renders the analysis a regression of covariates on the first differences. Any change would have to be attributed to the covariates, such as level of per capita income by construction (see Beck and Katz 1995, 1996; and Gleditsch 1996). 5. An identity matrix is a matrix with ones along the diagonal in which all off-diagonal elements are zero. 6. The solution for binary or limited dependent variables suggested by Beck and Tucker (1996), which was implemented in chapters 4 and 5, is not appropriate here. Since the institutionalized democracy scale values here are not seen as discrete categories, the analogy to an event history representation does not hold. 7. The hat matrix is given by H =X(XTX)-IX T. This is often used to assess the influence of individual observations (see, e.g., Belsley, Kuh, and Welsch 1980). 8. The difference between the results using the raw per capita GDP figures and those using the logged figures is actually relatively marginal and does not change the overall qualitative conclusions stated here. The overall fit as measured by an F-test, however, is somewhat better using the logged figures. 9. Cases that lack data on per capita GPD include Afghanistan, Albania, Cambodia, Cuba, Lebanon, Libya, North Korea, South Vietnam, Vietnam/ North Vietnam, Yemen (after unification), and South Yemen. Furthermore, none of the post-Soviet republics – Estonia, Georgia, Kazakhstan, Kirgizhia, Latvia, Lithuania, Moldova, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan – or the former states of the Yugoslav republics – Bosnia, Croatia, Macedonia, and Slovenia – could be included here, as these states all became independent at the end of the sample period. Finally, New Zealand drops out of the analysis as it has no neighboring entities within the 950 kilometer distance span. If threats do impede democracy, there is certainly something to be said for “splendid” isolation for local threats. Such linkages may in part underlie the seeming relationship between democracy and insularity (e.g., Anckar and Anckar 1995). 10. Briefly summarized, a Markov chain model specifies the probability distribution of some discrete variable yi(t) at time t as a function of the state of observation i at previous time periods and a J × J Markov matrix of probabilities P(t) of transition between the various J possible states that the variable yi(t) may acquire. A Markov chain is said to be first-order Markov if the transition probabilities depend only on the state in the preceding time period yi(t – 1) and are independent of the state at previous T time periods yi(t –

2), yi(t – 3), . . ., yi(t – T). All the entries in the P(t) must be nonnegative, and the entries in each row, indicating transitions from a given state at some time period t to the next, must sum to unity. Finally, a Markov chain is said to be stationary if the transition Page 239 →probabilities between states do not depend on time t (see, e.g., Amemyia 1985: 412–17; and Harary, Norman, and Cartright 1965: 371–77). 11. Similar relationships could also be observed if economic performance is partly endogenous to regime type. It was until recently often regarded as self-evident that leaders who were less constrained would be better able to enact policies boosting economic performance than those dependent on popular support (e.g., De Schweinitz 1996; Huntington and Dominguez 1975; Russett 1965). Many scholars currently argue that aspects of democratic institutions such as the rule of law may have important consequences facilitating economic growth (e.g., Alesina and Perotti 1994; Clague et al. 1996; Pourgerami 1992; Scully 1992; Wittman 1989). Przeworski and Limongi (1993) strongly reject the idea that performance may be endogenous to institutions in the sense that regime type may consistently effect economic growth. Although some find evidence of a positive relationship between democracy and growth, these results do not appear to be robust to alternative specifications (see de Haan and Siermann 1995 and Levine and Renelt 1992). Barro (1996) holds that the direction of causality association stems from development leading to democracy. This study, however, examines a cross section with average growth rates and may understate the persistence in authority structures. 12. Whether logit or probit is appropriate depends on whether the error term is expected to follow a logistic or normal distribution. In most settings, the two will for all practical purposes yield identical results (see, e.g., Maddala 1983 for a more comprehensive treatment). 13. Note that conventional goodness of fit measures based on residual deviance to null deviance are meaningless in this setting since equation 6.2 does not include an intercept and there is no clear null alternative for the estimated model. This is also the case for tables 6.2, 6.5, 6.6, and 6.7. 14. I am grateful to José Antonio Cheibub for providing me with a copy of the Alvarez, Cheibub, Limongi, and Przeworski data set. 15. The temporal difference should be irrelevant under the assumption that the transition probabilities P(t) are constant and do not change over time. Estimation of equation 6.3 on a sample restricted to the post-1945 period yielded nearly identical coefficient estimates and did not change the substantive conclusions. 16. In addition, Przeworskí and Limongi (1997: 159) state that their sample “does not include six countries that derive at least half of their income from oil revenues,” but they do not say which countries were excluded or provide a theoretical justification as to why these cases are not pertinent to the study. 17. Alvarez et al. (1996: 3) describe their data set as covering “a classification of political regimes as democracies and dictatorships for a set of 141 countries between 1950 or the year of independence,” but they provide no definition of system membership or states in the international system. Upon closer inspection, their data classify only country-years when data are available in other data sources such as the Penn World Tables. Hence, West Germany is included from 1950 but East Germany is included only after 1970. Various developing and socialist states such as Afghanistan, Albania, Cambodia, Cuba, Lebanon, Libya, Page 240 →North Korea, South Yemen, and Vietnam are simply not in the ACLP data at all. If the likelihood of observing data for a given country is correlated with aspects of interest in other studies (e.g., conflict), these sample selection biases make the ACLP data less useful for general purposes. 18. The Alvarez et al. (1996) data set includes an indicator of observations excluded by “possible type II error.” They suggest that people may include these cases as democracies if they disagree with the retroactive coding rule. However, this includes numerous cases of country-years that would not qualify as democracies on other criteria. One example would be Mexico, at least prior to the 1990s. 19. An addition to the Polity project labeled Polity HID (e.g., McLaughlin et al. 1998) provides the actual timing of changes in the Polity data. 20. To emulate Przeworski and Limongi (1997), I exclude some of the wealthy oil-producing countries in the Middle East – more specifically, Bahrain, Kuwait, Saudi Arabia, and United Arab Emirates – in the analysis shown in table 6.5.

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Index Amalgamation, 33 Babst, Dean, 37–38 Barzel, Yoram, 57 Beck, Nathaniel A., 80, 154 Bueno de Mesquita, Bruce, 40 Burkhart, Ross, 151–52 Clustering, 3–4, 14 Cointegration, 112–16 Conflict, 7–9, 15–16, 42–43, 72–86, 89–118, 182–84 belligerence vs. security, 42–43, 79, 182–86 clustering in conflict and peace, 16–21, 54–58 Correlates of War categories, 75 diffusion in time and space, 79–81, 101–4, 182 dyadic vs. monadic, 41–42 incidents vs. enduring tension, 79–81, 95–96 internal and external, 74–76, 108–11 peace through integration, 32–33 regional conflict and peace, 44–47, 81–83, 112–16 violent vs. latent, 72–74 wars and disputes, 76–78 Cooperation, 7–9, 83–86 Counterfactuals, 139 Democracy. See also Democratization clustering in, 21, 54–55 and conflict/peace, 37–50, 55–58, 89–118, 150, 158–61, 184–88 democratic institutions, 37–41 democratic norms, 39

and development, 147–58 diffusion of, 50–55, 147–78, 158–61, 164–69, 174–78 measuring, 86–87, 220–21 preferences, 45–47 regional, 87, 90–101, 104–12 Democratic peace, 37–42 and integration, 47–50 Democratization. See also Democracy clustering of, 21–25, 54–55 and conflict, 55–58, 104–11, 186–87 democratic transitions, 161–78, 192–94 measuring, 87 transnational diffusion, 50–55, 147–78, 190–92 waves of, 4, 52–54 Deutsch, Karl w., 32–37, 47–50, 138–39, 142–43 Distance, 5–7, 14–15, 45–47, 68–72 Diversionary conflict, 58–59, 111 Dyad, 12–13, 38, 41–42, 44–45, 91–93, 116–17, 184–86 Economic interdependence, 25–28, 83–84, 119–45 Fearon, James, 40 Galton’s problem, 196–97 Generalized Additive Models, 80, 97–101, 217–19 statistic, 81–82 Page 266 →Gleditsch, Kristian Skrede, 59, 67–68, 161 Hegre, Hc1vard, 80 Independent state. See State Integration, 32–37, 47–50, 119–45, 188–90 and the democratic peace, 47–50, 127–38, 143–45, 188–90 Interactive vs. independent effects, 96–101 Interdependence, 4–5

International system, 65–68 Kacowicz, Arie, 140–43 Katz, Jonathon, 154 Kieser, Edgar, 57 Lemke, Douglas, 142 Lewis-Beck, Michael, 151–52 Limongi, Fernando, 164, 169–70, 172–75 Long peace, 2 Mansfield, Edward, 58–62, 110–11 Maoz, Zeev, 39 Markov chain, 161–69, 238–39 Militarized Interstate Disputes, 76–78 Minimum distance. See Distance Monad. See Dyad; Region Moran’s I, 15, 226–27 Opportunity, 5–7 Peace. See Conflict Political conjunctures, 60–62, 111 Political institutions, 37–41 Political similarity, 49–50, 87, 127–35, 138–43, 188–90 Przeworski, Adam, 164, 169–70, 172–75 Raknerud, Arvid, 80 Region, 4–5, 10–11, 68–72, 90–101, 194–97. See also Distance Regional clustering. See Clustering Regional context. See Region Regional democracy. See Democracy Regional integration. See Integration Regional peace. See Conflict Rummel, Rudolph J., 38

Russett, Bruce M., 39 Security communities, 32–33. See also Integration Snyder, Jack, 58–62, 110–11 Spatial statistics measures of association, 15, 81–82 specifying structure, 14–15 variable construction, 68–72 State, 65–68, 203–7 Thompson, William R., 56–57 Trade, 25–28, 83–84 Transitions. See Democratization Tucker, Richard M., 80 War. See also Conflict clustering in, 16–21 definition, 15–16, 74 Ward, Michael D., 59, 67–68, 86–87, 161 Willingness, 6–8 Zones. See Region