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date: 20 August 2017

Diffusion in International Politics

Summary and Keywords

Diffusion with respect to international politics is commonly defined as the tendency for events or behaviors occurring in one spatial unit to influence the likelihood of similar events or behaviors occurring in another spatial unit. General definitions and mechanisms of diffusion that can be thought of as somewhat ubiquitous to the broader literature of diffusion in international politics tend to focus on processes of spillover or learning/emulation. These processes are common to the adoption and diffusion of policy innovations, the spread of democracy and democratic revolutions, and the contagion of civil and international conflicts. While the nomenclatures of these literatures often differ quite significantly, considerable overlap exists in terms of the primary conceptualizations of diffusion mechanisms. Most literatures appear to identify some combination of the following mechanisms: coercion and external pressure; constructivist norm cycles; social networks and linkages; geographic proximity and demonstration effects; learning and emulation. While the study of these phenomena and mechanisms has advanced significantly in recent years, some notable areas of future growth remain. First, differentiating between learning/emulation and spillover processes still presents considerable difficulty. Second, the role of “firewalls” in limiting diffusion processes is not well understood in either general or specific cases. Third, while understanding of social and geographic spaces is now rather nuanced, it remains unclear how best to theorize and model timing in diffusion processes.

Keywords: diffusion, contagion, conflict, democracy, norms, policies, empirical international relations theory

Introduction: Definitions and Mechanisms of Diffusion

The dominant neorealist and neoliberal theoretical approaches in the field of international relations have long assumed that states are unitary and independent actors in the international system. Many scholars have offered compelling critiques of this reification of state sovereignty. John Agnew (1994), for instance, urges scholars in the field not to fall into what he terms “the territorial trap.” One notable body of literature that has long sought to escape this territorial trap is that which theorizes about and attempts to model patterns of international diffusion. Scholars of diffusion have long considered the messiness of events, behaviors, and their consequences that do not conform to formal political boundaries. Under the general umbrella of transnationalism (see, e.g., Nye & Keohane, 1971; Evangelista, 1995), the study of diffusion seeks to explain how a wide variety of conditions/behaviors/actions “spread” from one country to another. This literature commonly defines diffusion as the tendency for events or behaviors that occur in one spatial unit to influence the likelihood of similar events or behaviors that occur in another spatial unit (see, e.g., Soule, 1997; Rogers, 2010; Elkins & Simmons, 2005).

The study of diffusion involves identifying an innovation or artifact that diffuses from a source unit to an adopter or destination unit, as well as the geographic, social, or political context and the mechanism or channel through which the diffusion occurs (Rogers, 2010; Wejnert, 2002). Arguably, the driving force of this literature is the study of innovations (Rogers, 2010), which has tended to emphasize the diffusion of those policies, ideas, and norms that are generally recognized as benefiting society. Elkins and Simmons (2005) offer a critical evaluation of conceptualizations of diffusion, noting that not all artifacts that diffuse can be thought of as innovative or normatively desirable. As a consequence, they propose distinguishing between two broad types of diffusion: (1) adaptation to spillovers and (2) learning/emulation.

The corrective offered by Elkins and Simmons is valuable, for it helps reconcile quite distinct types of diffusion—for example, the spillover of negative externalities (including refugees, militants, and weapons) from conflict zones (see, e.g., Buhaug & Gleditsch, 2008) and the emulation of public policy reforms between regional counterparts (see, e.g., Weyland, 2009a). There remains, however, a rather broad variety of ways in which diffusion occurs. These mechanisms themselves have various names and are far from being mutually exclusive. Accordingly, rather than trying to identify a uniform set of mechanisms, three prominent studies that offer impressive organizing frameworks across quite distinct subject areas are briefly reviewed here: Strang and Sould (1998), Elkins and Simmons (2005), and Braun and Gilardi (2006).

Strang and Sould (1998) provide a review of diffusion processes in their study of organizations and social movements. They emphasize the structural and cultural logic of diffusion processes, arguing for closer theoretical attention to why practices diffuse at different rates and via different pathways across different settings. In summary, Strang and Sould (1998) provide three suggestions for further development: employment of broader comparative research designs; more detailed inspection of the content of social relations between collective actors; and closer attention to diffusion industries run by the media and communities of experts.

Strang and Soule discuss nine sets of mechanisms—both external and internal to an actor—through which behaviors, strategies, technologies, or structures can diffuse.

  1. 1. The mass media’s crucial role in amplifying and editing the diffusion of collective action.

  2. 2. The view of the state and professionals as change agents that spread new practices and facilitate adoption of innovative actions.

  3. 3. The frequency and cohesion of strong ties between members within a network.

  4. 4. The availability of weak ties through which new information may travel.

  5. 5. Competition between structurally equivalent actors.

  6. 6. Spatial proximity between innovator and potential adopters.

  7. 7. Cultural approaches emphasizing that a self-consciously interpretive process underlies most adoption.

  8. 8. External fashion-setting communities that make their living promulgating innovation and commenting on change.

  9. 9. Practices that enjoy alignment with cultural understandings of appropriate and effective action, which are the practices that tend to diffuse most quickly.

As noted, Elkins and Simmons (2005) categorize the process of diffusion into two types: adaptation and learning. In discussing the international diffusion of policies broadly defined, they describe diffusion via adaptation as occurring when “[t]he policy decisions of one government alter the conditions under which other governments base their decisions” (p. 39). They identify three mechanisms through which adaptation might occur. (1) Cultural norms help to ensure that adoption appears more legitimate when a growing majority of other actors have already adopted a practice. (2) Sheer numbers of prior adopters can confer credibility on a practice and can serve as a support group for the refinement and improvement of the practice. (3) Under conditions of competition over scarce resources, adoption can also have a strong effect on an actor’s competitiveness.

Elkins and Simmons maintain that diffusion via learning occurs when another actor’s action provides information about the benefits and drawbacks of adopting. Actors may be influenced to adopt as a result of knowledge accumulated from prior adoptions in what is often referred to as information cascades. The decisions taken by a long sequence of actors may depend largely on the decisions of the first few actors (see, e.g., Lohmann, 1994; Bikhchandani, Hirshleifer, & Welch, 1998). Adoption decisions will be limited to the set of policies or innovations that are accessible due to availability or familiarity. Finally, actors may prefer to emulate models from reference groups of actors with whom they share similar cultural or social attributes.

In their review of theories detailing the interdependence of policy choices, Braun and Gilardi (2006) espouse an expected-utility model of policy change in which the expected utility of a policy depends on both its effectiveness and its payoffs. They suggest that these parameters are systematically affected by six diffusion mechanisms.

First are rational learning processes in which actors choose policies after they have updated their beliefs about the effects of a policy by looking at the experience of others. Fully rational processes involve Bayesian updating of prior beliefs (see, e.g., Meseguer, 2004, 2005). By contrast, bounded learning involves gathering relevant information by observing the behavior of others while relying on “cognitive shortcuts” such as representativeness, availability, and anchoring (see also Tversky & Kahneman, 1975; McDermott, 2001; Weyland, 2009a).

Second is interdependence through which governments adopt policies via strategic competition to attract economic activity (see, e.g., Simmons & Elkins, 2004) or via cooperative practices to ensure their policies are compatible with those of other entities (see, e.g., Lazer, 2001).

Third, coercion is a process involving the imposition of policies on national governments by powerful international organizations or powerful countries.

Fourth, shared socialization and repeated interactions within networks can lead to the emergence of common norms, which define appropriate behavior in given contexts and for actors with a given identity (see, e.g., Finnemore & Sikkink, 1998). Common norms can provide the same evaluations regarding the effectiveness of policy alternatives.

Fifth, taken-for-grantedness implies that over time, some practices may become accepted as the norm in given contexts. Some policies are automatically assigned a very high effectiveness, while other policies are barely considered; that is, they are automatically attributed a very low effectiveness.

Sixth, symbolic imitation is grounded in the idea that decision makers may choose policies to show that they are acting in a proper and adequate manner (see, e.g., Meyer & Rowan, 1977).

The review of these three studies illustrates the primary set of mechanisms that are used to examine diffusion. Presented in the following sections is a small but representative group of three issue areas that are at the core of international politics: the diffusion of (1) government policies and regulations, (2) democratic regimes and revolutions, and (3) civil and international conflicts.

The Diffusion of Government Policies and Regulations

While much of the considerable body of research on the diffusion of policies centers on domestic patterns, such as those between states within the United States (see, e.g., Berry & Berry, 1990, 2007), the focus here is on global patterns of policy diffusion. Of particular concern in this review is the diffusion of economic liberalism, including social welfare reform, taxation policy, and market regulation (for excellent general introductions, see Holzinger & Knill, 2005; Dobbin, Simmons, & Garrett, 2007). Generally speaking, foreign economic policy choices elsewhere can alter the payoffs associated with choosing or maintaining a particular policy at home (Simmons & Elkins, 2004). Once again, a familiar set of mechanisms are discussed.

In theories of constructivism, policy norms are traced to expert epistemic communities and international organizations. According to these logics, governments adopt policies in response to legitimacy pressures emerging from international institutions’ promotion of certain policy models. Henisz et al. (2005), for example, suggest that market-oriented liberalization reforms diffuse as actors embedded in a social structure adopt similar behaviors as they seek to conform to shared norms (DiMaggio & Powell, 1983; Mizruchi & Galaskiewicz, 1993).

Such processes are often viewed as precursors to the emergence of international harmonization, in which countries comply with uniform legal obligations defined in international or supranational law and often required by membership in international institutions (see, e.g., Holzinger & Knill, 2005). For some countries, these legal frameworks provide political cover for governments. International Monetary Fund (IMF) stabilization programs, for example, provide a window of opportunity for governments to initiate costly and unpopular financial reforms. Governments can shift blame for costly reforms onto the IMF, thereby partially shielding themselves against political opposition (Remmer, 1986; Vreeland, 2003; Mukherjee & Singer, 2010).

Coercion or imposition involves powerful nation-states and international financial institutions threatening sanctions or promising aid in return for adoption (Dobbin, Simmons, & Garrett 2007). In this instance, “coercive isomorphism results from both formal and informal pressures exerted on organizations by other organizations upon which they are dependent” (DiMaggio & Powell, 1991, p. 67). Building on the idea that the more powerful or more high-status countries in the international system shape the policies of less powerful or so-called less legitimate countries, Gilpin (1987) and Henisz et al. (2005) argue that international pressures of coercion also strongly influence the domestic adoption of market-oriented reform.

Demonstrating that not all governments are equally vulnerable to external pressures, Way (2005) argues that politically insecure leaders are potent agents of diffusion, mainly because they tend to “learn” the lessons of financial market reform and emulate the liberalizing practices of others. They may also wish to exploit positive economic conditions to buttress their grip on power or, simply, they may be more susceptible to pressure from international organizations or global powers.

Competition, which is often regulatory, involves countries vying to attract investment and to sell exports by reducing the cost of doing business, loosening constraints on investment, or lowering tariff barriers in the hope of encouraging reciprocity. Regulatory competition is expected to lead to cross-national convergence, as countries facing competitive pressure mutually adjust their policies (see, e.g., Holzinger & Knill, 2005). States, engaging in cultural, political, and economic competition with each other, naturally seek to maintain their position and status, frequently by adopting practices that make them isomorphic with their environment. As an example, Polillo and Guillén (2005) cite the global spread of central bank independence. Further, Elkins et al. (2006) show that the spread of bilateral investment treaties is driven by international competition among potential host countries for foreign direct investment (FDI).

Similarly, Cao (2010) emphasizes the role of peer competitive pressure in the diffusion of corporate taxation policies. He maintains that this is more than mere strategic interaction among neighboring countries. Rather, Cao argues, competitors in the global markets are defined by their positions in networks of international markets such as trade, FDI, and foreign portfolio investment. Competition mechanisms induced by similarity of position in the portfolio investment and exports networks causes policy diffusion in corporate taxation.

In discussing the diffusion of pension privatization around the world, Brooks (2005) identifies an important role for peer dynamics: Peers are countries with comparable geopolitical, economic, and cultural landscapes, as well as common economic or political organizations (Berry & Berry, 1990). Peer decisions may spark competitive concerns, leading such nations to trade extensively or contend for investment, while also signaling whether a general reform model is appropriate for their own country.

Finally, informational networks and processes of learning suggest that governments learn from their own experiences or from those of their peers. Governments draw lessons when they rationally utilize available experience elsewhere to solve their own domestic problems. Thus, governments uncertain about an innovation will examine the outcome of previous reforms so that they can gain information about its likely effects. As the number of previous adoptions of an innovation rises, uncertainty is said to decline, increasing the likelihood of subsequent adoptions of the policy innovation (Jordana & Levi-Faur, 2005; Meseguer, 2004; Simmons & Elkins, 2004; Brooks, 2007). For instance, corporate taxation policies sometimes diffuse through socialization or learning mechanisms that are induced by network position proximity in the global networks of intergovernmental organizations (Cao, 2010).

Of course, not all governments are equally likely to embrace learning opportunities. Building on knowledge regarding corporate taxation, Jensen and Lindstädt (2012) demonstrate that the waves of reform in the Organisation for Economic Co-operation and Development (OECD) are largely driven by partisan learning. Tax cuts by right-wing governments provide little information to other countries, whereas a tax cut by a left-wing government allows social learning to take place; leftist governments lead the way on tax cuts. With regard to policies affecting unemployment benefits, Gilardi (2010) shows that right-wing governments will be more likely to learn from other countries’ experiences when the benefit of the policy is compatible with electoral success. By contrast, left-wing governments will more likely imitate the policy if the policy is associated with lower unemployment rates.

When policy convergence is driven by the mere desire for conformity with other countries rather than the search for effective solutions to given problems, emulation can be said to be at work. Weyland (2005) uses a cognitive-heuristics approach to explain the spread of Chilean-style pension reform throughout Latin America in recent decades. Assuming the inferential shortcuts of bounded rationality, he demonstrates that bold innovations attract disproportionate attention from neighboring countries, ensuring that innovations are widely adopted because of their apparent promise rather than their demonstrated success. Research also demonstrates that countries have different motivations to learn or emulate, depending on the responsiveness and accountability of their political regimes and not any demonstrated success. When democracies confront economic crises, for instance, they are more likely to liberalize trade as a result of learning. By contrast, authoritarian regimes are less motivated to learn from the experience of others, even when they embrace policies that fail (Meseguer & Escribà-Folch, 2011).

Marsh and Sharman (2009) provide five valuable suggestions for drawing on the untapped connections between policy diffusion and the literature on policy transfer. First, work in this area can benefit from a greater focus on the changing interactions between the various mechanisms involved in diffusion/transfer. Second, the diffusion literature privileges structure, whereas the transfer literature privileges agency, but an approach that recognizes the dialectical relationship between the two is needed. Third, the diffusion literature concentrates on finding patterns, whereas the transfer literature examines process-tracing, but any full explanation of transfer/diffusion needs to involve both. Fourth, both literatures suffer from skewed case selection, paying too little attention to developing countries. Finally, while both literatures need to be interested in whether diffusion/transfer is likely to be successful or unsuccessful, neither considers any criteria that might be used to establish policy success and failure.

The Diffusion of Democracy and Democratic Revolutions

A burgeoning literature addresses the global diffusion of democratic institutions and revolutions and in some cases identifies a more significant role for external than internal influences (see, e.g., Wejnert, 2005; Gleditsch & Ward, 2006). This literature spans traditional subfields of comparative politics and international relations. Beginning with the end of the Cold War (Huntington, 1991; Starr, 1991; Karklins & Petersen, 1993; Lohmann, 1994) and continuing through the Color Revolutions across former Soviet states in the early to- mid-2000s (Beissinger, 2007), these studies have been motivated by apparent waves of democratization across regions. . Huntington’s ambitious study (1991) set out to explain the emergence and diffusion of the so-called third wave of democratization globally between 1974 and 1990. As Huntington suggests, three sets of external factors contributed to these ostensibly domestic processes; these three items are used as a framework for our broader review.

First, between the 1960s and 1990s, authoritarian regimes faced deepening legitimacy problems at a time when democratic norms and values were widely being accepted globally. As an example, a shift in the doctrine and activities of the Catholic Church in the mid-1960s was central to many democratization processes, especially in Central and Eastern Europe and Latin America. During the Second Vatican Council (1962–1965), the church transitioned to become an opponent of authoritarianism. More generally, Brinks and Coppedge (2006) show that countries tend to change their regimes to match the average degree of democracy among their contiguous neighbors. Although Brinks and Coppedge do not highlight the precise mechanism through which the pattern emerges, they do show that the greater the gap in the level of democracy between a country and its neighbors, the greater the pressure will be for convergence toward the local norm. They also show that major powers (most notably the United States) can play a role that is subsequently emulated by smaller powers (see also Leeson & Dean, 2009).

Second, changing foci in the foreign policies of major powers and the membership requirements of economic communities have motivated a significant number of transitions globally (see, e.g., Leeson & Dean, 2009). This statement aligns with Wejnert’s (2005) conclusion that actors positioned at the core of highly centralized networks employ coercive pressures to achieve conformity among their member states. This results in homogeneity and increasing adoption of democracy. Gleditsch and Ward (2006) maintain that coercion is an important form of external influence on domestic transitions. In other words, foreign-imposed regime change and external support have altered the relative power of actors and groups in domestic politics, providing the context for democratization.

Third, Huntington identifies a “snowballing” or demonstration effect in which earlier transitions provided models for subsequent democratization efforts. This general demonstration effect lies at the heart of many studies of the diffusion of democracy. Starr (1991), for example, conceptualizes the spread of democratic transitions through an analogy to dominoes. Kopstein and Reilly (2000) demonstrate that geographic proximity is crucial to spatial diffusion of influence, institutions, norms, and expectations across borders. It is this diffusion, they maintain, that has led to the variance in political and economic outcome among the postcommunist countries. Simply stated, the closer countries are to each other, the greater the number of possible linkages through which democracy can be promoted or spread (Wejnert, 2005).

Instead of this predominant reliance on geographic proximity, Beck et al. (2006) suggest that trade, joint membership in international organizations, and similar forms of social connectivity also play an important role in facilitating the global diffusion of democracy. Levitsky and Way (2005) demonstrate, for example, that the more subtle and diffuse effects of linkage to Western countries, rather than the western countries’ direct leverage over authoritarian states, contributed more consistently to democratization. Linkage serves to increase the costs associated with maintaining authoritarian rule.

Learning also influences democratic transition (see, e.g., Leeson & Dean, 2009). Gleditsch and Ward (2006) contend that the evaluation of other countries’ democracy (which involved less cost than expected and accrual of substantial benefits such as economic growth) encourages some countries to adopt democracy. In other words, spreading media communications (Wejnert, 2005) and providing information across borders can be central to increasing rates of democratization. Furthermore, the active promotion of democracy by democratic regimes across country borders, as well as informal communication between citizens of countries, are crucial to influencing patterns of temporal and spatial clustering of democratic regimes (Elkink, 2011).

Weyland (2009b, 2010), using his cognitive-heuristic approach, demonstrates that processes of bounded rational learning also most likely explain the diffusion of democratic revolutions. He finds considerable support for his theory that cognitive-psychological insights explain the spread of protests and revolutions in Europe and Latin America in 1848, and, more broadly, explain patterns of democratic diffusion across Europe between 1830 and 1940. Most simply, foreign precedents inspired protestors. However, rather than engaging in a full cost-benefit analysis of the tactic’s likely usefulness in their own pursuit of democracy, protestors relied on cognitive heuristics—or shortcuts—that enabled them to process information in simple, yet potentially distorted, ways. First, they relied on the availability heuristic, which made them focus disproportionately on dramatic, vivid, remarkable events and attribute unusual evidentiary weight to them. Second, they were affected by the representativeness heuristic, which distorted the inferences drawn from this information, causing them to see too much regularity and too little chance underlying the success of events.

Each of the studies reviewed in this section characterizes the diffusion of democratic regimes in terms of the flow of democracy from one country to the next. A meaningful approach to explain the diffusion of democratic revolutions highlights a parallel set of diffusive processes at the local level that are fundamental to the success of these efforts at transition. These examples are presented as a reminder that international processes often mask deep and important local mechanisms.

Local or individual-level models of the diffusion of democratic protests and revolutions tend to build upon Granovetter’s (1978) threshold models of collective action. According to his models, the decisions of individual actors to participate in collective actions are contingent on what other actors do when at least two alternatives present themselves and the costs and/or benefits of each depend on how many other actors have chosen each alternative. The threshold refers to the number or proportion of other actors who must make one decision before a given actor does similarly; it is at this point that benefits exceed costs in the calculation of that actor.

Following this tradition, Lohmann (1994) interprets the Monday demonstrations in East Germany over the period 1981–1991 as an informational cascade that publicly revealed some of the previously hidden information about the evils of the East German communist regime. According to this model, regular citizens engaged in costly political action to express their dissatisfaction with the government. Other members of the public observed these behaviors and took informational cues from changes in the size of the protest movement over time. As a consequence, the regime lost public support and ultimately collapsed.

Karklins and Petersen (1993) distinguished their assurance and deassurance games from predominant models of political diffusion (Bartholomew, 1982). They suggested that, in order to explain changes in behaviors, traditional models require variation in information flows. However, they noted that, in the case of demonstrations, residents in a single city typically already have similar information. Instead, Karklins and Petersen maintained that the decisions of individual protestors concerning participation in protest activity are influenced by a set of assurance games that involve their own and other social groups. The ruling regime’s reactions undergo the reverse process of a “deassurance game” as their instruments of coercion are undermined.

Beissinger (2007) builds on each of these studies to posit two elite-based models for the diffusion of democratic revolutions. He suggests that elite defection and elite learning are fundamental to the emulation of prior successful examples. According to the defection model, once examples gain momentum and cross the tipping point where modular behavior accelerates across groups, a general expectation about the direction in which events are flowing demoralizes those representing established institutions, potentially promoting defections among them and encouraging band-wagoning behavior. In turn, according to the learning model, the elites opposing modular change learn the critical lessons of the model from its repeated successes and failures and thus impose additional institutional constraints on actors to prevent the model from succeeding further.

The spread of democratic governments in the late 20th century is just one of many examples of the global diffusion of norms of state behavior (Finnemore & Sikkink, 1998). Perhaps the most well-developed accounts of the international diffusion of norms derive from the path-defining work of Keck and Sikkink (1998) on transnational advocacy networks. At the heart of their work is their suggestion that complex transnational connections between nongovernmental and governmental organizations and individuals globally can help to identify and diffuse norms of behavior. A similar process underlies Ramirez et al.’s (1997) explanation for the cross-national acquisition and diffusion of women’s suffrage rights. They argue that throughout the 20th century the influence of national political and organizational factors declined and international links and influences became increasingly important.

In a similar vein, a series of studies have explored the role of third-party observers and monitors in executing democratic practices, including free and fair elections. Kelley (2008) claims that the rise of election monitoring has been driven by an interaction of instrumentalism, emergent norms, and fundamental power shifts in the international system. In line with arguments that norm entrepreneurs often connect new norms to existing norms, more than 20 proponents framed election monitoring in the context of human rights and democratic rights and essentially “grafted” election monitoring onto the new principle of periodic and genuine elections. In 1990, election monitoring passed the critical tipping point for the subgroup of nonestablished democracies with a jump from 28% in 1989 to 44% in 1990. After monitoring began to increase around 1990, in just eight more years it had risen to nearly 70 % of all nonestablished democracies. By 2004, monitoring reached a high of 81.5%. Kelley argues that incumbents’ motivations for inviting monitors were both normative and instrumental.

Hyde (2011) takes a slightly different approach, contending that international norms—including adherence to free and fair elections—can be generated through a diffusely motivated signaling process. Responding to the increased benefits associated with being democratic, democratizing governments initiated international observation of elections as a sign of a government’s commitment to democracy. Increased democracy-contingent benefits gave other “true democrats” the incentive to invite observers; the result was a widespread belief that all true-democrats invite election monitors. Consequently, not inviting observers became an unambiguous signal that a government was not democratizing, giving even pseudo-democrats reason to invite observers and risk a negative report.

The Diffusion of Civil and International Conflict

The onset of civil conflict is commonly explained by structural factors within the state, including poverty, the absence of democracy, and ethnic fractionalization (see, e.g., Fearon & Laitin, 2003; Collier & Hoeffler, 2004). Two relatively recent innovations discussed in the literature reflect a seed change. First, scholars have focused on the actors engaged in conflict and on their incompatibilities. Bargaining frameworks acknowledge the strategic interaction between government and rebels that lies at the heart of conflicts (for a detailed review of this perspective, see, e.g., Walter, 2009).

Second, scholars have focused on the role of factors external to the state in contributing to the onset of conflict (e.g., Hill, Rothchild, & Cameron, 1998; Gleditsch, 2007; Checkel, 2013).There appears to be strong evidence of neighborhood effects in the causes of civil conflicts (see, e.g., Sambanis, 2001; Hegre & Sambanis, 2006; Gleditsch, 2007). Gleditsch (2007), for instance, shows that transnational and regional economic, political, and social linkages between states strongly influence the risk of civil conflict.

A growing body of research demonstrates that dependent relationships appear to result in conflicts clustering spatially and identifies an important role, in particular, for contagion and diffusion effects in determining these patterns in both violent (see, e.g., Lake & Rothchild, 1998; Salehyan & Gleditsch, 2006; Buhaug & Gleditsch, 2008; Braithwaite, 2010; Forsberg, 2014) and nonviolent civil conflicts (Sutton, Bitcher, & Svensson, 2014; Braithwaite, Braithwaite, & Kucik, 2015; Gleditsch & Rivera, 2015).

Conflicts might be contagious because of spillover or emulation, or both (Elkins & Simmons, 2005). First, research has demonstrated that externalities from conflict—including refugees, rebels, and economic shocks—tend to spill over across international boundaries (Salehyan & Gleditsch, 2006; Salehyan, 2008; Krcmaric, 2014). Second, studies show that conflict tends to spread through emulation (Hill, Rothchild, & Cameron, 1998; Kuran, 1998). Emulation effects rest on the idea that information about conflicts occurring elsewhere can cause opposition actors to revise their beliefs that they will likely achieve their goals (Hill, Rothchild, & Cameron, 1998). This notion is comparable to that of learning but is bounded with respect to rationality (Weyland, 2009b).

In a similar vein, Koopmans (1993) and Tarrow (1994) suggested that demonstration effects are also central to the spread of popular dissent. In the case of nonviolent movements in the mid-1980s: “One may be certain,” noted an editorial in the New York Times, “that events in the Philippines were closely watched in Pretoria. Scenes of nuns stopping tanks with rosaries were worth a million words to the democratic forces. Officials in South Korea saw those pictures; citizens in Taiwan saw them; bankers in New York saw them” (cited in Hill & Rothchild, 1986, pp. 716–717).

An important reason for the spatial and temporal clustering of civil conflicts is that observing individuals and groups elsewhere taking to the streets captures attention and amplifies feelings of grievance. The literature speaks to a number of plausible mechanisms through which emulation may occur; however, no study has been able to demonstrate empirically which mechanisms are the most influential.

There are competing explanations of the role of geographic proximity in emulation processes. The conventional wisdom is that close proximity to existing conflict abroad increases the prospects of conflict at home (Buhaug & Gleditsch, 2008; Gleditsch & Rivera, 2015). Ample evidence suggests, however, that learning and emulation processes, specifically, operate on a larger geographic scale and may even be global. Linebarger (2015), for instance, shows that many rebels mobilize in response to global events. The Cuban Revolution inspired the formation of Uruguayan Tupamoros, Argentine Montoneros, and Nicaraguan Sandanistas.

The homophily of actors is intuitively key to the process of emulation (Soule, 1997; Elkins & Simmons, 2005). Close social proximity facilitates communication and information-sharing (Rogers, 2010). In terms of the spread of conflict, learning might be expected to occur between ethnic kin separated by international borders or countries with shared language and cultural backgrounds (Kuran, 1998; Forsberg, 2014).

The structural equivalence of the contexts in which opposition campaigns are being fought might also be expected to determine lines of information and communication. Maves and Braithwaite (2013) demonstrate a strong contagion effect for violent civil conflicts between pairs of similarly autocratic states. Braithwaite, Braithwaite, and Kucik (2015) and Gleditsch and Rivera (2015) find evidence for such an effect between pairs of autocratic states within the context of nonviolent mobilizations. For example, the OTPOR resistance movement in Serbia, which was integral to the removal of Slobodan Milosevic from office in 2000, is said to have inspired several similar movements around the world, including the Bolga movement in Uzbekistan opposing the dictator Islam Karimov, and the Eritrean Movement for Democracy and Human Rights (Beissinger, 2007; Sharp, 1973). In addition to the similarity of actors and contexts, learning is also theorized to occur between groups that are seeking to achieve similar goals (McAdam, 1988; Beissinger, 2007; Strang & Sould, 1998). In particular, groups will tend to expand their actions upon observation of their use in similar campaigns elsewhere (Tilly, 1978).

Tactical successes achieved by opposition groups in conflicts appear to incentivize imitation and adoption by actors elsewhere (Kuran, 1998). Thus, successfully concluded campaigns, campaigns making progress, or simply those that display collective action and mobilization may be sources of inspiration (Maves & Braithwaite, 2013). At the heart of these logics lies Granovetter’s (1978) threshold model, which is predicated on the notion that participation in antigovernment mobilizations depends, in part, on observation of others’ participation. For example, Croatia’s and Bosnia’s eventually successful use of force to extricate themselves from the control of the Serbian-led Federal Republic of Yugoslavia, confirmed by the Dayton Peace Accords in November 1995, was the inspiration for the militant Kosovo Liberation Army (KLA)’s subsequent bid for Kosovan independence in 1996.

Imitation or emulation also underlies the diffusion of terrorist tactics by left-leaning violent organizations. Midlarsky et al. (1980) proposed the regional hierarchies theory in which the violent behavior of countries with high status is more likely to be emulated by other countries. In the 1950s and 1960s, events demonstrated a random diffusion effect, probably conditioned by anti-imperialist responses to the United States. By the 1970s, a hierarchical routinization of violence developed, in which groups in Latin America appeared to learn from tactics employed previously in western Europe.

Heyman and Micholus (1980), disagreeing with Midlarsky et al. (1980), suggested that, rather than regional hierarchies, a noncontagious diffusion explains the empirical record. Intergroup cooperation between terrorist groups enables them to exchange ideas, intelligence, training, funds, and support. This process appears to lie at the heart of Horowitz’s (2010) organizational-level account of the adoption of suicide terrorist tactics. Moreover, the displacement of terrorism likely occurs when terrorists decide to move to a location where their victims are weakest or where they can maximize the impact of an incident. For example, Enders and Sandler (2006) demonstrated that anti-U.S. terrorism was displaced from western Europe and North America to the Middle East and other parts of Asia. They explain this displacement in terms of changing global patterns of counterterrorism expenditure.

The research of Benjamin Most and Harvey Starr (1980, 1990) laid the groundwork for analysis of the likely causes of the diffusion of disputes and wars between countries. They initially claimed that international conflicts may spread from one nation to another, employing patterns similar to those followed by contagious diseases. This conflict–disease analogy is a hallmark of subsequent analyses of the spatial clustering of conflict (see, e.g., Houweling & Siccama, 1985; Gleditsch, 2009; Braithwaite, 2010). Most and Starr (1980) conceived of diffusion as involving both positive and negative reinforcement (local) and diffusion (international) processes.

Siverson and Starr (1990, 1991) developed the opportunity and willingness pretheoretical framework to further explain how the perceptions of foreign policy decision makers increase the chances that nations become involved in an ongoing war. This framework views international borders and alliances as mechanisms through which participation in war spreads internationally. Siverson and Starr contend that borders represent the “opportunity” for war to spread between territories, with the number of borders a state has reflecting the number of risks and opportunities confronting the nation. By contrast, alliances reflect a “willingness” to see wars diffuse. Alliance membership, as a conscious choice, implies that member states have made a similar policy preference, and accordingly, alliance commitments could be responsible for the diffusion of wars.

Subsequent studies have demonstrated that this opportunity and willingness framework might be conditioned by additional state and dyad characteristics. First, Joyce and Braithwaite (2013) demonstrate that states are more likely to join conflicts that occur close to their territories than conflicts that are located at a greater distance. In other words, proximity to the location of an ongoing conflict affects the opportunity for a state to join (by decreasing costs), while also affecting the state’s willingness to join (by increasing the potential threat to the state’s security). Second, democracy might serve as a “firewall” against the diffusion of war. While Gleditsch and Ward (2000) do not find such a role for general levels of democratization, they do demonstrate that uneven transitions toward democracy can increase the probability that the state will experience a war. Hence, processes of diffusion may condition both democracy and war.

Conclusion: Areas for Future Investigation

While the nomenclatures of the literatures accounting for the diffusion of policies and regulations, democracy and democratic revolutions, civil and international conflicts, and norms of state behaviors differ significantly, it is clear that the primary conceptualizations of diffusion mechanisms overlap considerably. Most literatures appear to identify some combination of the following mechanisms: coercion and external pressure; constructivist norm cycles; social networks and linkages; geographic proximity and demonstration effects; learning and emulation.

There remain (at least) three areas in which each of these literatures could benefit from additional thought and exploration. First, despite the best efforts of Elkins and Simmons (2005), there remains some difficulty in differentiating between processes of learning and those of the spillover of negative externalities. In simple terms, this may reflect a distinction between the diffusion of normatively positive and normatively negative behaviors. This problem may be most relevant to the literature on political violence, especially given that most instances of conflict contagion occur in border regions, where it is especially tricky to distinguish between these two mechanisms (see, e.g., Buhaug & Gleditsch, 2008). As Table 1 demonstrates, the dividing lines between these two broad types are far from clear. This table summarizes the most common terms employed across relevant literatures in international politics. A considerable number of concepts relay information regarding some hybrid process that straddles notions of spillover and learning/emulation.

Table 1. Summary of Key Concepts

Spillover

Mixed/Hybrid

Learning/Emulation

  • Conflict–disease analogy

  • Contagion

  • Imposition

  • Coercion

  • Competition

  • (De)Assurance games

  • Demonstration effect

  • Geographic proximity

  • Informational cascades

  • Interdependence

  • Linkage

  • Mass media

  • Opportunity and willingness

  • Regional hierarchies

  • Signaling

  • Spatial proximity

  • Structural equivalence

  • Strong ties

  • Threshold models

  • Transnational advocacy networks

  • Alignment

  • Availability

  • Bounded rational learning

  • Change agents

  • Common norms

  • Cultural norms

  • Democratic norms

  • Elite defection and learning

  • Fashion-setting communities

  • Homophily

  • Imitation

  • International harmonization

  • Information networks

  • Interpretive process

  • Lesson-drawing

  • Noncontagious diffusion

  • Norm entrepreneurs

  • Peer dynamics

  • Rational learning

  • Reference groups

  • Support group

  • Similar goals

  • Symbolic imitation

  • Taken-for-grantedness

  • Weak ties

Second, and related to the first area, notions of “firewalls” limiting diffusion are underdeveloped (Solingen, 2012). Solingen and Börzel (2014) edited a special issue of International Studies Review on diffusion in international politics. Only one of the contributions prioritized the study of firewalls—in that case exploring the case of nuclear weapons (Wan, 2014). There do exist a few examples of research that speaks to the possibility of developing firewalls against diffusion processes; however, there is little consistency across these studies. Collectively, they seem to suggest that democracy (Gleditsch & Ward, 2000), state capacity (Braithwaite, 2010), peacekeeping (Beardsley, 2011), third-party interventions (Kathman, 2010), state repression (Danneman & Ritter, 2014), and distribution of ethnic groups (Metternich et al., 2015) may serve as firewalls limiting the contagion of violent conflict processes or achieving their containment. However, these initial findings have not been robustly confirmed.

Third, and finally, all of the literature reviewed herein identifies a fairly prominent role for space in diffusion processes. This is intuitive and reasonable. However, few studies appear to take time as seriously as they do geographic or social spaces. What are the appropriate timeframes in which researchers can analyze and attempt to observe the occurrence of diffusion processes? The answer to this question will help to determine the future course of this intriguing field of research.

References

Agnew, J. (1994). The territorial trap: The geographical assumptions of international relations theory. Review of International Political Economy, 1(1), 53–80.Find this resource:

Bartholomew, C. H. (1982). Carbon deposition in steam eforming and methanation. Catalysis Reviews Science and Engineering, 24(1), 67–112.Find this resource:

Beardsley, K. (2011). Peacekeeping and the contagion of armed conflict 1. Journal of Politics, 73(4), 1051–1064.Find this resource:

Beck, N., Gleditsch, K. Skrede, & Beardsley, K. (2006). Space is more than geography: Using spatial econometrics in the study of political economy. International Studies Quarterly, 50(1), 27–44.Find this resource:

Beissinger, M. R. (2007). Structure and example in modular political phenomena: The diffusion of bulldozer/rose/orange/tulip revolutions. Perspectives on Politics, 5(2), 259–276.Find this resource:

Berry, F. S., & Berry, W. D. (1990). State lottery adoptions as policy innovations: An event history analysis. American Political Science Review, 84(2), 395–415.Find this resource:

Berry, F. S., & Berry, W. D. (2007). Innovation and diffusion models in policy research. In F. S. Berry, W. D. Berry, & P. A. Sabatier (Eds.), Theories of the policy process (2d ed., pp. 223–260). Boulder, CO: Westview Press.Find this resource:

Bikhchandani, S., Hirshleifer, D., & Welch, I. (1998). Learning from the behavior of others: Conformity, fads, and informational cascades. The Journal of Economic Perspectives, 12(3), 151–170.Find this resource:

Braithwaite, A. (2010). Resisting infection: How state capacity conditions conflict contagion. Journal of Peace Research, 47(3), 311–319.Find this resource:

Braithwaite, A., Braithwaite, J. M., & Kucik, J. (2015). The conditioning effect of protest history on the emulation of nonviolent conflict. Journal of Peace Research, 52(6), 697–711.Find this resource:

Braun, D., & Gilardi, F. (2006). Taking “Galton’s problem”seriously: Towards a theory of policy diffusion. Journal of Theoretical Politics, 18(3), 298–322.Find this resource:

Brinks, D., & Coppedge, M. (2006). Diffusion is no illusion: Neighbor emulation in the third wave of democracy. Comparative Political Studies, 39(4), 463–489.Find this resource:

Brooks, S. M. (2005). Interdependent and domestic foundations of policy change: The diffusion of pension privatization around the world. International Studies Quarterly, 49(2), 273–294.Find this resource:

Brooks, S. M. (2007). When does diffusion matter? Explaining the spread of structural pension reforms across nations. Journal of Politics, 69(3), 701–715.Find this resource:

Buhaug, H., & Gleditsch, K. S. (2008). Contagion or confusion? Why conflicts cluster in space. International Studies Quarterly, 52(2), 215–233.Find this resource:

Cao, X. (2010). Networks as channels of policy diffusion: Explaining worldwide changes in capital taxation, 1998–2006. International Studies Quarterly, 54(3), 823–854.Find this resource:

Checkel, J. T. (2013). Transnational dynamics of civil war. Cambridge, U.K.: Cambridge University Press.Find this resource:

Collier, P., & Hoeffler, A. (2004). Greed and grievance in civil war. Oxford Economic Papers, 56(4), 563–595.Find this resource:

Danneman, N., & Ritter, E. H. (2014). Contagious rebellion and preemptive repression. Journal of Conflict Resolution, 58(2), 254–279.Find this resource:

DiMaggio, P., & Powell, W. W. (1983). The iron cage revisited: Collective rationality and institutional isomorphism in organizational fields. American Sociological Review, 48(2), 147–160.Find this resource:

DiMaggio, P. J., & Powell, W. W. (1991). The new institutionalism in organizational analysis. Vol. 17. Chicago: University of Chicago Press.Find this resource:

Dobbin, F., Simmons, B., & Garrett, G. (2007). The global diffusion of public policies: Social construction, coercion, competition, or learning? Annual Review of Sociology, 33, 449–472.Find this resource:

Elkink, J. A. (2011). The international diffusion of democracy. Comparative Political Studies, 44(12), 1651–1674.Find this resource:

Elkins, Z., Guzman, A. T., & Simmons, B. A. (2006). Competing for capital: The diffusion of bilateral investment treaties, 1960–2000. International Organization, 60(4), 811–846.Find this resource:

Elkins, Z., & Simmons, B. (2005). On waves, clusters, and diffusion: A conceptual framework. Annals of the American Academy of Political and Social Science, 598(1), 33–51.Find this resource:

Enders, W., & Sandler, T. (2006). Distribution of transnational terrorism among countries by income class and geography after 9/11. International Studies Quarterly, 50(2), 367–393.Find this resource:

Evangelista, M. (1995). The paradox of state strength: Transnational relations, domestic structures, and security policy in Russia and the Soviet Union. International Organization, 49(1), 1–38.Find this resource:

Fearon, J. D., & Laitin, D. D. (2003). Ethnicity, insurgency, and civil war. American Political Science Review, 97(1), 75–90.Find this resource:

Finnemore, M., & Sikkink, K. (1998). International norm dynamics and political change. International Organization, 52(4), 887–917.Find this resource:

Forsberg, E. (2014). Diffusion in the study of civil wars: A cautionary tale. International Studies Review, 16(2), 188–198.Find this resource:

Gilardi, F. (2010). Who learns from what in policy diffusion processes? American Journal of Political Science, 54(3), 650–666.Find this resource:

Gilpin, R. (1987). The Political Economy of International Relations. Princeton, NJ: Princeton University Press.Find this resource:

Gleditsch, K. S. (2007). Transnational dimensions of civil war. Journal of Peace Research, 44(3), 293–309.Find this resource:

Gleditsch, K. S. (2009). All international politics is local: The diffusion of conflict, integration, and democratization. Ann Arbor: University of Michigan Press.Find this resource:

Gleditsch, K. S., & Rivera, M. (2015). The diffusion of nonviolent campaigns. Journal of Conflict Resolution.Find this resource:

Gleditsch, K. S., & Ward, M. D. (2000). War and peace in space and time: The role of democratization. International Studies Quarterly, 44(1), 1–29.Find this resource:

Gleditsch, K. S., & Ward, M. D. (2006). Diffusion and the international context of democratization. International Organization, 60(4), 911–933.Find this resource:

Granovetter, M. (1978). Threshold models of collective behavior. American Journal of Sociology, 83(6), 1420–1443.Find this resource:

Hegre, H., & Sambanis, N. (2006). Sensitivity analysis of empirical results on civil war onset. Journal of Conflict Resolution, 50(4), 508–535.Find this resource:

Henisz, W. J., Zelner, B. A., & Guillén, M. F. (2005). The worldwide diffusion of market-oriented infrastructure reform, 1977–1999. American Sociological Review, 70(6), 871–897.Find this resource:

Heyman, E., & Micholus, E. (1980). Observations on “why violence spreads.” International Studies Quarterly, 24(2), 299–305.Find this resource:

Hill, S., & Rothchild, D. (1986). The contagion of political conflict in Africa and the world. Journal of Conflict Resolution, 30(4), 716–735.Find this resource:

Hill, S., Rothchild, D., & Cameron, C. (1998). Tactical information and the diffusion of peaceful protests. In D. A. Lake & D. S. Rothchild (Eds.), The international spread of ethnic conflict: Fear, diffusion, and escalation (pp. 61–88). Princeton, NJ: Princeton University Press.Find this resource:

Holzinger, K., & Knill, C. (2005). Causes and conditions of cross-national policy convergence. Journal of European Public Policy, 12(5), 775–796.Find this resource:

Horowitz, M. C. (2010). Nonstate actors and the diffusion of innovations: The case of suicide terrorism. International Organization, 64(1), 33–64.Find this resource:

Houweling, H. W., & Siccama, J. G. (1985). The epidemiology of war, 1816–1980. Journal of Conflict Resolution, 29(4), 641–663.Find this resource:

Huntington, S. P. (1991). Democracy’s third wave. Journal of Democracy, 2(2), 12–34.Find this resource:

Hyde, S. D. (2011). Catch us if you can: election monitoring and international norm diffusion. American Journal of Political Science, 55(2), 356–369.Find this resource:

Jensen, N. M., & Lindstädt, R. (2012). Leaning right and learning from the left: Diffusion of corporate tax policy across borders. Comparative Political Studies, 45(3), 283–311.Find this resource:

Jordana, J., & Levi-Faur, D. (2005). The diffusion of regulatory capitalism in Latin America: Sectoral and national channels in the making of a new order. Annals of the American Academy of Political and Social Science, 598(1), 102–124.Find this resource:

Joyce, K. A., & Braithwaite, A. (2013). Geographic proximity and third-party joiners in militarized interstate disputes. Journal of Peace Research, 50(5), 595–608.Find this resource:

Karklins, R., & Petersen, R. (1993). Decision calculus of protesters and regimes: Eastern Europe 1989. Journal of Politics, 55(3), 588–614.Find this resource:

Kathman, J. D. (2010). Civil war contagion and neighboring interventions. International Studies Quarterly, 54(4), 989–1012.Find this resource:

Keck, M. E., & Sikkink, K. (1998). Activists beyond borders: Advocacy network in international politics. Ithaca, NY: Cornell University Press.Find this resource:

Kelley, J. (2008). Assessing the complex evolution of norms: The rise of international election monitoring. International Organization, 62(2), 221–255.Find this resource:

Koopmans, R. (1993). The dynamics of protest waves: West Germany, 1965 to 1989. American Sociological Review, 58(5), 637–658.Find this resource:

Kopstein, J. S., & Reilly, D. A. (2000). Geographic diffusion and the transformation of the postcommunist world. World Politics, 53(1), 1–37.Find this resource:

Krcmaric, D. (2014). Refugee flows, ethnic power relations, and the spread of conflict. Security Studies, 23(1), 182–216.Find this resource:

Kuran, T. (1998). Ethnic norms and their transformation through reputational cascades. Journal of Legal Studies, 27(S2), 623–659.Find this resource:

Lake, D. A., & Rothchild, D. S. (1998). The international spread of ethnic conflict: Fear, diffusion, and escalation. Princeton, NJ: Princeton University Press.Find this resource:

Lazer, D. (2001). Regulatory interdependence and international governance. Journal of European Public Policy, 8(3), 474–492.Find this resource:

Leeson, P. T., & Dean, A. M. (2009). The democratic domino theory: An empirical investigation. American Journal of Political Science, 53(3), 533–551.Find this resource:

Levitsky, S., & Way, L. (2005). International linkage and democratization. Journal of Democracy, 16(3), 20–34.Find this resource:

Linebarger, C. (2015). Civil war diffusion and the emergence of militant groups, 1960–2001. International Interactions, 41(3), 583–600.Find this resource:

Lohmann, S. (1994). The dynamics of informational cascades: The Monday demonstrations in Leipzig, East Germany, 1989–91. World Politics, 47(1), 42–101.Find this resource:

Marsh, D., & Sharman, J. C. (2009). Policy diffusion and policy transfer. Policy Studies, 30(3), 269–288.Find this resource:

Maves, J., & Braithwaite, A. (2013). Autocratic institutions and civil conflict contagion. Journal of Politics, 75(2), 478–490.Find this resource:

McAdam, D. (1988). Micromobilization contexts and recruitment to activism. International Social Movement Research, 1(1), 125–154.Find this resource:

McDermott, R. (2001). Risk-taking in international politics: Prospect theory in American foreign policy. Ann Arbor: University of Michigan Press.Find this resource:

Meseguer, C. (2004). What role for learning? The diffusion of privatisation in OECD and Latin American countries. Journal of Public Policy, 24(3), 299–325.Find this resource:

Meseguer, C. (2005). Policy learning, policy diffusion, and the making of a new order. Annals of the American Academy of Political and Social Science, 598(1), 67–82.Find this resource:

Meseguer, C., & Escribà-Folch, A. (2011). Learning, political regimes and the liberalisation of trade. European Journal of Political Research, 50(6), 775–810.Find this resource:

Metternich, N. W., Minhas, S., & Ward, M. D. (2015). Firewall? Or wall on fire? A unified framework of conflict contagion and the role of ethnic exclusion. Journal of Conflict Resolution.Find this resource:

Meyer, J. W., & Rowan, B. (1977). Institutionalized organizations: Formal structure as myth and ceremony. American Journal of Sociology, 83(2), 340–363.Find this resource:

Midlarsky, M. I., Crenshaw, M., & Yoshida, F. (1980). Why violence spreads. International Studies Quarterly, 24(2), 262–298.Find this resource:

Mizruchi, M. S., & Galaskiewicz, J. (1993). Networks of interorganizational relations. Sociological Methods and Research, 22(1), 46–70.Find this resource:

Most, B. A., & Starr, H. (1980). Diffusion, reinforcement, geopolitics, and the spread of war. American Political Science Review, 74(4), 932–946.Find this resource:

Most, B. A., & Starr, H. (1990). Theoretical and logical issues in the study of international diffusion. Journal of Theoretical Politics, 2(4), 391–412.Find this resource:

Mukherjee, B., & Singer, D. A. (2010). International institutions and domestic compensation: The IMF and the politics of capital account liberalization. American Journal of Political Science, 54(1), 45–60.Find this resource:

Nye, J. S., & Keohane, R. O. (1971). Transnational relations and world politics: An introduction. International Organization, 25(3), 329–349.Find this resource:

Polillo, S., & Guillén, M. F. (2005). Globalization pressures and the state: The worldwide spread of central bank independence. American Journal of Sociology, 110(6), 1764–1802.Find this resource:

Ramirez, F. O., Soysal, Y., & Shanahan, S. (1997). The changing logic of political citizenship: Cross-national acquisition of women’s suffrage rights, 1890 to 1990. American Sociological Review, 62(5), 735–745.Find this resource:

Remmer, K. L. (1986). The politics of economic stabilization: IMF standby Programs in Latin America, 1954–1984. Comparative Politics, 19(1), 1–24.Find this resource:

Rogers, E. M. (2010). Diffusion of innovations. New York: Simon and Schuster.Find this resource:

Salehyan, I. (2008). The externalities of civil strife: Refugees as a source of international conflict. American Journal of Political Science, 52(4), 787–801.Find this resource:

Salehyan, I., & Gleditsch, K. S. (2006). Refugees and the spread of civil war. International Organization, 60(2), 335–366.Find this resource:

Sambanis, N. (2001). Do ethnic and nonethnic civil wars have the same causes? A theoretical and empirical inquiry (Part 1). Journal of Conflict Resolution, 45(3), 259–282.Find this resource:

Sharp, G. (1973). The Politics of Nonviolent Action. Boston: P. Sargent.Find this resource:

Simmons, B. A., & Elkins, Z. (2004). The globalization of liberalization: Policy diffusion in the international political economy. American Political Science Review, 98(1), 171–189.Find this resource:

Siverson, R. M., & Starr, H. (1990). Opportunity, willingness, and the diffusion of war. American Political Science Review, 84(1), 47–67.Find this resource:

Siverson, R. M., & Starr, H. (1991). The diffusion of war: A study of opportunity and willingness. Ann Arbor: University of Michigan Press.Find this resource:

Solingen, E. (2012). Of dominoes and firewalls: The domestic, regional, and global politics of international diffusion. International Studies Quarterly, 56(4), 631–644.Find this resource:

Solingen, E., & Börzel, T. A. (2014). Introduction to presidential issue: The politics of international diffusion—A symposium. International Studies Review, 16(2), 173–187.Find this resource:

Soule, S. A. (1997). The student divestment movement in the United States and tactical diffusion: The Shantytown protest. Social Forces, 75(3), 855–882.Find this resource:

Starr, H. (1991). Democratic dominoes diffusion approaches to the spread of democracy in the international system. Journal of Conflict Resolution, 35(2), 356–381.Find this resource:

Strang, D., & Sould, S. A. (1998). Diffusion in organizations and social movements: From hybrid corn to poison pills. Annual Review of Sociology, 24(1), 265–290.Find this resource:

Sutton, J., Bitcher, C. R., & Svensson, I. (2014). Explaining political jiu-jitsu institution-building and the outcomes of regime violence against unarmed protests. Journal of Peace Research.Find this resource:

Tarrow, S. (1994). Power in movement: Social movements, collective action and mass politics in the modern state. New York: Cambridge University Press.Find this resource:

Tilly, C. (1978). From mobilization to revolution. Reading, MA: Addison-Wesley.Find this resource:

Tversky, A., & Kahneman, D. (1975). Judgment under uncertainty: Heuristics and biases. In Utility, Probability, and Human Decision Making (pp. 141–162). Amsterdam: Springer.Find this resource:

Vreeland, J. R. (2003). The IMF and economic development. Cambridge, U.K.: Cambridge University Press.Find this resource:

Vreeland, J. R. (2003). Why do governments and the IMF enter into agreements? Statistically selected cases. International Political Science Review, 24(3), 321–343.Find this resource:

Walter, B. F. (2009). Bargaining failures and civil war. Annual Review of Political Science, 12, 243–261.Find this resource:

Wan, W. (2014). “Firewalling Nuclear Diffusion.” International Studies Review, 16(2), 217–228.Find this resource:

Way, C. R. (2005). Political insecurity and the diffusion of financial market regulation. Annals of the American Academy of Political and Social Science, 598(1), 125–144.Find this resource:

Wejnert, B. (2002). Integrating models of diffusion of innovations: A conceptual framework. Annual Review of Sociology, 28(1), 297–326.Find this resource:

Wejnert, B. (2005). Diffusion, development, and democracy, 1800–1999. American Sociological Review, 70(1), 53–81.Find this resource:

Weyland, K. (2005). Theories of policy diffusion lessons from Latin American pension reform. World Politics, 57(2), 262–295.Find this resource:

Weyland, K. (2009a). Bounded rationality and policy diffusion: Social sector reform in Latin America. Princeton, NJ: Princeton University Press.Find this resource:

Weyland, K. (2009b). The diffusion of revolution:”1848”in Europe and Latin America. International Organization, 63(3), 391–423.Find this resource:

Weyland, K. (2010). The diffusion of regime contention in European democratization, 1830–1940. Comparative Political Studies, 43(8–9), 1148–1176.Find this resource: