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Electronic copy available at: http://ssrn.com/abstract=1913981
War, Trade, and Distrust:
Why Trade Agreements Don’t Always Keep the Peace
Emilie M. Hafner-Burton
Associate Professor of Political Science
University of California, San Diego
9500 Gilman Drive
La Jolla CA 92093-0521
ehafner@ucsd.edu
Alexander H. Montgomery
Assistant Professor of Political Science
Reed College
3203 SE Woodstock Blvd
Portland OR 97214
ahm@reed.edu
NOTE: DRAFT 2011-08-21; please do not quote without permission. The authors share equal
responsibility for this paper and their names appear in alphabetical order. Please direct
correspondence to both authors.
The authors thank Zeev Maoz, Charles Boehmer, and two anonymous reviewers for valuable
comments on earlier drafts of this article as well as Jon Pevehouse and Edward Mansfield
for sharing their data.
Forthcoming in Conflict Management and Peace Science 29(3), July 2012.
Electronic copy available at: http://ssrn.com/abstract=1913981
1
Title:
War, Trade, and Distrust: Why Trade Agreements Don’t Always Keep the Peace
Abstract:
There is growing evidence that preferential trade agreements (PTAs) provide strong
institutional incentives to prevent international conflict among member states, often creating the
conditions of trust that can help prevent militarized aggression. We provide an approach to the
study of how international institutions influence conflict behavior that considers how PTAs
exclude as well as include members and create asymmetrical relationships among members that
could exacerbate conflict. PTAs do more than create expectations of economic gains and reduce
opportunism; they also create hierarchical relations between states, which can encourage conflict
under different conditions due to distrust. We theorize these conditions for militarized
international disputes (MIDs), develop appropriate measures using social network analysis, and
test our expectations on new PTA data during the period 1950 to 2000.
2
Does trade interdependence promote peace among states? A long intellectual tradition suggests
as much, as liberals have argued that the formation of global trade ties and institutions creates
incentives to settle disputes before they come to violence (Angell, 1913; Doyle, 1997; Mitrany,
1966; Nye, 1971; Russett and Oneal, 2001). Trade with foreign nations fosters economic
interdependence among governments, generates expectations about wealth gains, now and into
the future, and may even create a sense of community among nations (Deutsch, 1957; Gartzke,
1998; Haas, 1960; Polachek, 1980; Russett et al., 1998). International institutions like
preferential trade arrangements (PTAs) or the World Trade Organization (WTO) that organize
trade ties reinforce these peace-making processes. They provide a formal institutional
mechanism through which states lengthen the shadow of future trade relations, credibly commit
to economic interdependence, and cooperate to overcome coordination problems. In the process,
trade institutions increase trust through creating strong expectations of future gains, enhancing
political relations and preserving peace among trade partners (Fernandéz and Portes, 1998;
Mansfield and Pevehouse, 2000; Mansfield et al., 1999; Schiff and Winters, 1998).
Various scholars have contested this liberal argument (Baldwin, 1980; Barbieri, 1996;
Buzan, 1984; Gilpin, 1981; Hirschman, 1945), yet most of the evidence available today suggests
that the liberals might be right: economic interdependence can promote collective security
among trade partners and trade institutions are central to the peacekeeping process. Studies
illustrate that trade partners are systematically less likely to resort to military conflict than states
that do not trade (Gartzke et al., 2001; Maoz, 2009; Oneal et al., 1996; Oneal et al., 2003). Others
show that when trade becomes institutionalized through PTAs, members of the same
arrangement are even less likely to go to war than are other states and that PTAs are most
3
effective in preventing conflict as trade between members grows (Dembinski et al., 2004;
Mansfield and Pevehouse, 2000; 2003; Mansfield et al., 1999).
However, we have reason to be skeptical that mutual membership in trade institutions
always or primarily dampens conflict. While it is possible that institutional interactions reveal or
alter states’ interests to create trust among members, which may in turn inhibit conflict, we
suggest that this trust-building property only holds under conditions of symmetrical relationships
between states in institutions. Large asymmetries in these relationships, by contrast, can actually
undermine trust between states and thereby lead to additional militarized conflict in the
international system. More specifically, we argue that the distribution of ties in the network
formed through preferential trade agreements (PTAs) can lead to large asymmetries in
dependence and influence, thus undermining trust and promoting conflict.
Hafner-Burton and Montgomery have shown that neither international governmental
organizations (IGOs) nor preferential trade agreements (PTAs) simply provide a benign forum
for state interaction (Hafner-Burton and Montgomery, 2006; 2008; 2009). They also create social
networks that define hierarchies of social order in which states hold relative positions of power
over each other. Like military power (Waltz, 1979), states’ social power in this network of
institutional memberships creates expectations for behavior and gives states the ability to coerce,
bribe, reward, or punish others, defining the conditions under which acts of military aggression
or cooperation are rational strategies of action. These positions are emergent properties of the
overall pattern of institutional memberships that define the social network among states, and can
just as easily provide incentives for conflict as for cooperation.
4
In this article, we draw upon the insights of social network analysis
1
to investigate how
states in the international system form relationships through their membership in international
trade institutions, like PTAs and the WTO, and how these relationships in turn create an
international structure that can shape violent conflict. In the realist view, mutual memberships in
international institutions—in social network analysis terms, ties—are epiphenomenal: they have
no impact on states’ propensity for conflict, which is only characterized by relative disparities in
military capabilities or trade gains (Mearsheimer, 1994). In the liberal view, ties bind states
positively: trade institutions produce symmetrical relationships of amity that solve problems of
relative gains that can lead to war through multiple mechanisms. Neither assumption, however,
accurately describes how trade institutions create incentives for conflict. Institutional ties
between actors shape conflict, but they do not necessarily have positive effects.
Rather, ties place states into particular positions of power within a social network. Social
network analysis allows for conceptualization and measurement of the emergent properties of
networks such as institutions. As a conceptual framework, network analysis moves from the
individualist perspective in which institutional membership is considered to affect state behavior
simply through membership in individual institutions to a perspective that emphasizes the
emergent properties of networks of institutions, whether from the perspective of the direct
network of states or from both direct and indirect ties as well. Rather than measuring the effects
of institutions through totaling up the number that a country joins or the characteristics of
1
For a general primer on social network analysis, see (Scott, 2000); for a technical primer, see
(Wasserman and Faust, 1994); on social network analysis (SNA) in international relations, see
(Hafner-Burton et al., 2009). For some prominent examples of SNA in IR, see (Dorussen and
Ward, 2008; Elkins, 2009; Elkins et al., 2006; Hafner-Burton and Montgomery, 2006; 2008;
Ingram et al., 2005; Manger et al., 2008; Maoz, 2009; 2010; Maoz et al., 2005; 2007; Ward and
Hoff, 2007; Ward et al., 2007).
5
individual institutions, network analysis measures the collective effects of direct and indirect ties
through institutions on state behavior.
Here, we focus on two particular social positions—states' direct sensitivity dependence
(hereafter dependence) on each other and their relative access centrality due to both direct and
indirect ties in the social network formed by PTAs.
2
Conceptually, for any pair of states, the
relative dependence of one state on another increases with the number of joint memberships and
decreases with the number of non-joint memberships. States that have a great deal of ties to other
states have high access centrality; this quality increases further for states that have ties to other
well-connected states. We define and describe both terms in detail in the pages to come. We
hypothesize that asymmetries in dependence or access centrality increase conflict since they
undermine trust between states.
In the following pages, we position our argument within the broader context of debates
over the effects of international organizations and economic interdependence on conflict through
trust and develop our core propositions. We introduce new data on state membership in trade
institutions from 1950 to 2000 and derive our principal indicators using social network tools. We
use these tools to empirically identify and describe states’ structural positions within the social
network created by ties, and systematically test our argument using cross-national data on
interstate military disputes. In the process, we take great care to replicate previous work where
possible and to build on existing scholarship.
2
On different forms of dependence, see (Maoz, 2009; 2010). On access centrality, see Hafner-
Burton, Kahler, and Montgomery, 2009.
6
How Institutions Can Lead to Trust
Since the time of Immanuel Kant, scholars of international politics have proposed that peace is
possible through the forging of an international social structure based on liberal principles of
rights, obligations, and law (Kant, [1795] (1991) ). In the modern world, international institutions
and economic interdependence create this social structure through the establishment of authority,
providing a foundation for the building of trust among nations in an anarchic world and the
diffusion of the value of cooperation (Angell, 1913; Zimmern, 1936). Europe has been an
important example. Looking to Europe, integration theorists have argued that economic
integration between nations can, over time, create a communal understanding and interest in
collective security, as learned forms of cooperation in markets spill over into areas of higher
security politics (Haas, 1971; Mitrany, 1966; 1976; Nye, 1971). PTAs, like the European
Community, can merge the interests of age-old rivals by establishing a community of states and
peoples long divided (Wallace, 1994).
While integration theorists looked toward the experience of Europe, Karl Deutsch
proposed the more general concept of a security community, where economic integration among
liberal states could create a sense of community based on trust and reciprocity (Deutsch, 1957).
A pluralistic security community forms among members that hold similar core values grounded
in common institutions and mutual responsiveness, creating a shared identity, loyalty, and sense
of ‘we-ness’ among states (Adler and Crawford, 2002). Building from Deutsch, Adler and
Barnett argued many years later that this sense of community among states is not simply a
European phenomenon, but can and does exist internationally (Adler and Barnett, 1998). States
within this community have the ability to cultivate peaceful methods of interacting, although
they do not always succeed or choose to do so.
7
The underlying theme of both theoretical traditions has been adopted by scholars seeking
to provide evidence that international institutions in general and trade institutions in particular
assuage conflict by generating trust and mutual identification and proffering norms of peace-
making among states with common institutional ties. In their influential work on the democratic
or “Kantian” peace, Russett and Oneal argue that shared memberships in intergovernmental
organizations (IGOs) increase cooperation among nations and reduce their propensity to go to
war (Oneal and Russett, 1999; Russett and Oneal, 2001). Among the various means through
which IGOs can have a pacifying effect is the generation of narratives of mutual identification
through the construction of mutual identity, and the legitimation of norms developed within the
organizations that facilitate cooperation and create common interests. Bearce extends this line of
argument to commercial institutions and suggests that the key to generating trust is improved
contact between potential rivals (Bearce, 2003). Trade institutions, accordingly, can promote
peace by bringing government decision makers together in repeated interactions that can
generate bonds of trust
3
among potential adversaries and reduce problems of misperception.
Mansfield and Pevehouse correspondingly suggest that PTAs can produce focal points around
which states shape their expectations for acceptable behavior, preventing breakdowns in
cooperation that might otherwise lead to violence (Garrett and Weingast, 1993; Mansfield and
Pevehouse, 2000).
Why Trade Institutions Don’t Always Keep The Peace
Many before us have been skeptical of the claim that interdependence promotes peace among
states. It is well understood that international institutions can have adverse effects on conflicts
3
(Schiff and Winters, 1998) similarly assume that trade between neighboring states creates trust
and reduces the likelihood of conflict and that international organizations can serve a trust-
building function. See also (Schiff and Winters, 2002).
8
among member states, mismanaging crisis situations and worsening conflict intensity (Gallarotti,
1991), or producing rivalry among states due to their relative social positions (Hafner-Burton and
Montgomery, 2006). We are nevertheless among the first to directly tackle the principal claims
supporting the liberal thesis that trade institutions dampen conflict, and to propose an explanation
for why conflict often characterizes outcomes.
This is important because we observe significant instances of violent conflict
4
between
PTA members: the 1990s alone included border clashes between Armenia and Azerbaijan,
members of the Commonwealth of Independent States (CIS); the outbreak of war in the Great
Lakes, with foreign involvement in the Democratic Republic of Congo from Angola, Namibia,
Rwanda, Uganda, and Zimbabwe, all members of the Common Market for Eastern and Southern
Africa (COMESA); the Iraqi invasion of Kuwait and violent border clashes between Egypt and
Sudan, all members of the Council of Arab Economic Unity (CAEU); and fighting between India
and Pakistan, members of the South Asian Association for Regional Cooperation (SAARC).
North and South Korea frequently are involved in violent incidents; both are members of the
Global System of Trade Preferences Among Developing Countries (GSTP). A majority of these
disputants are also members of the WTO. Powers contends that in Africa, 16% of all militarized
international disputes registered by the Correlates of War data from 1950 to 1992 occurred
between PTA members (Powers, 2003; 2004). These examples show clearly that members of the
same trade institution can and do conflict, that conflict often breaks out into violence, and that
commerce is frequently not enough to keep the peace. They stand in sharp contrast to the liberal
expectation that trade institutions dampen conflict through an increase in trust.
4
As per the usual convention, we define “violent” MIDs to be any MID in which at least one
death occurred.
9
Trade institutions do increase repeated contact between members; however, contact does
not necessarily build trust or a sense of community. The lessons of European integration theory
suggest that building community through upgrading the common interest between PTA members
requires a minimum level of homogeneity: a pluralist social structure, a high level of economic
and industrial development, and ideological similarity (Haas, 1960). Security communities are
also most likely to develop through economic relations among western nations, as even the most
institutionalized forms of integration in the developing world cannot be said to create the mutual
identification at the core of the concept (Bearce, 2003). Although evidence suggests that
economic integration has led to the formation of a collective identity and trust among member
states of the European Union over time, it is well understood that “democratic features of liberal
democracies enable the community in the first place.” (Russett and Oneal, 2001, p. 166) The
liberal argument that trade institutions dampen conflict by building trust among leaders to
overcome commitment problems consequently chiefly applies to the Western world of advanced
democratic nations. Yet the overwhelming majority of trade institutions manage trade between
partners that include at least one developing or nondemocratic state, and there is no evidence to
show that these institutions build trust over asymmetrical distribution of gains. Boehmer,
Gartzke, and Nordstrom cogently argue that states that belong to many different international
institutions may have a greater number of international interests to competitively defend and a
greater array of opportunities to enact aggressive behavior in defense of those perceived interests
(Boehmer et al., 2002). We extend this argument one step further; trade institutions create and
shape states’ interests, affecting not only the number of potential issues for dispute, but also
establishing conditions that can lead to distrust. Institutions do this by placing states in social
positions of power within international relations, which shape expectations for behavior by
10
defining which issues are legitimate for contestation via military means and enable states to
coerce, bribe, reward, or punish each other. We address this possibility in the next section.
How Trade Institutions Undermine Trust and Fuel Conflict
Although we do not share the liberal view that trade institutions necessarily or regularly promote
peace among members, we are equally skeptical of critics’ arguments maintaining that they have
no relationship to war or a negative relationship. Rather, we argue that trade institutions are
neither inherently likely nor unlikely to keep the peace among member states. States form social
networks through membership in these institutions. Mutual memberships create ties between
states and, although the strength of these ties increases with additional joint memberships, they
do not necessarily create positive or negative bonds between states. These ties define states’
relative positions in social hierarchies in the international political economy. Like the balance of
military power, these positions are state characteristics that are measured (and have their effects)
relative to other states, shaping the conditions under which conflict or cooperation become
rational strategies of action.
We are concerned with two particular types of relative social positions: dependence and
access centrality. Take two states, A and B; state A's dependence on state B is proportional to the
number of trade institutions both belong to and is inversely proportional to the total number of
trade institutions state A belongs to. In other words, A's dependence on B increases if A and B
join additional trade institutions together, but A's dependence on B decreases if A joins
additional trade institutions without B. Like differences in military capabilities, different levels
of dependence create structural motives for peace among trading partners in some circumstances,
and conflict under others (Hafner-Burton and Montgomery, 2006). Here, we focus on one
particular type of dependence: direct dyadic sensitivity dependence due to the PTA network. It is
11
direct because the measure relates primarily to direct links to each of the two actors in question;
dyadic because it looks at the strength of the link between the two actors, and sensitivity because
it measures how sensitive each actor is to the other due to the link rather than the potential
opportunity cost of breaking it. Although multiple different kinds of dependence (direct and
indirect; monadic, dyadic, and systemic; sensitivity and vulnerability; single and multi-
dimensional) are relevant to relations between states (Maoz, 2009; 2010), we are focusing on
this particular type and measuring it in this way in this paper because it provides for a direct
contrast between the mechanism of trust through interdependence, typically also measured as
direct dyadic sensitivity interdependence (i.e., the strength of a tie between two states, the
number of PTAs that both belong to), and the mechanism of distrust through dependence, which
can be measured by dividing the liberal measure by the total number of PTAs that each state
belongs to.
Specifically, we expect that distrust will characterize conditions of asymmetrical
dependence. We consequently expect the liberal prediction to be most robust when states hold
positions of dependence vis-à-vis each other that are relatively equal; under these conditions,
mutual memberships in trade institutions are most likely to produce trust, and therefore, to create
conditions favorable to conflict avoidance. However, we expect that states will be more likely to
conflict with members of their trade institutions when one state is much more dependent on the
other; under these conditions, disparity in dependence is more likely to lead to envy than trust,
and therefore, provide incentives for the envious state to conflict.
Hypothesis 1. Dyads characterized by greater relative disparity in dependence
will be more likely to engage in militarized disputes than dyads characterized by
relative equality in dependence.
12
While the (direct dyadic sensitivity) dependence of two states on each other can be
derived from their direct membership ties alone, access centrality is an emergent property of the
ties between all states in the entire system. There are three (major) classes of centrality measures,
access, brokerage, and efficiency, which measure the extent to which an actor is generally well-
connected to others, can act as a broker between actors, and can reach other actors quickly
(Hafner-Burton et al., 2009). Here, we use access centrality measure since this family of
measures has been shown to be important in the relationship between international institutions
and conflict in general and PTAs in particular (Hafner-Burton and Montgomery, 2006; 2008;
2009). Conceptually, a state’s access centrality in a network is proportional to the ties received
from other states. A state with high access centrality—that is, one with a large number of strong
ties to other important states—is particularly socially powerful and important in the network of
trade institutions. Further, we believe that a large number of ties to other important states will
increase that state’s capabilities further, and so we use a measure of access centrality
(eigenvector centrality) that reflects this. With large disparities in centrality, we expect that
(similar to our predictions on dependence) trust will be more likely to form among states that
have equal access centrality, while distrust and therefore conflict will characterize relationships
between pairs of states with large disparities in access centrality.
5
Disparities in social power
thus operate opposite to disparities in material power; where (according to realist arguments)
equality leads to increased conflict and a preponderance of power suppresses it.
Hypothesis 2. Dyads characterized by greater relative disparity in access
centrality will be more likely to engage in militarized disputes than dyads
5
Dependence is inherently a directed dyadic quantity that defines a relative hierarchy between
two states, whereas access centrality is a monadic quantity that defines an absolute hierarchy
among all states. We reduce both quantities to undirected dyadic quantities, since we argue that it
is the relative position of two states with respect to each other that affects conflict.
13
characterized by relative equality in access centrality.
Large disparities in dependence and access centrality create asymmetries in states’
abilities to socially coerce, bribe, reward, or sanction each other; more influential and access
central states simply have more social capital to expend. These states will distrust marginal
countries that are not well-integrated into their networks and will be more likely to escalate
conflict rather than resolve disputes peacefully. Conversely, less influential states have little
ability to respond to social coercion and so may choose to respond in a material way through
military or economic action. Disparities thus produce incentives for forum-switching for such
states. Highly dependent or peripheral states are excluded from communities and fear domination
within economic forums, and thus rather than attempting to compete in the socioeconomic sphere
where disparities are large, countries have incentives to enter militarized conflicts instead.
Expectations and abilities combine to undermine trust across these dyads.
Research Design
We test our two hypotheses using pooled cross-national time-series data on state dyad-years. Our
attention is focused on all dyads
6
from the period 1950 to 2000, although we replicate our results
on politically relevant dyads in order to facilitate comparison across studies that consider only
the latter sample.
7
In order to ensure comparison with studies supporting the liberal thesis that
international institutions dampen conflict, we base our analysis on Mansfield and Pevehouse,
who consider the effects of PTAs on conflict (Mansfield and Pevehouse, 2000); we also draw
6
We choose to use all dyads instead of politically relevant dyads since the effects captured by
taking only a subset of states (power projection capabilities, distance between dyads) are already
included in our model.
7
In order to facilitate replication of our findings we have made our data, including our PTA and
state samples, available at the following locations: <censored for review>.
14
insights from Oneal and Russett’s analysis of the effects of IGOs on conflict.
8
We incorporate
their data and update them in several ways. In order to examine the post-Cold War period, we
rely on an alternative trade institution data set, since Mansfield and Pevehouse’s data only
consider PTA membership from 1950 to 1985. We consider membership in a greater number of
PTAs and observe membership from 1950 to 2000.
9
In our sample, we include membership in
the General Agreement on Trade and Tariffs (GATT) and the WTO because these trade
institutions are just as likely as PTAs to offer a basis for mutual trust. We base our GDP and
trade data on Gleditsch’s expanded set (Gleditsch, 2002), our measures of regime type from
Polity IV (Marshall and Jaggers, 2003), and generate the remainder of our data using EUGene
(Bennett and Stam, 2000; 2005). We employ Beck, Katz and Tucker’s splines to correct for
temporal dependence in the dependent variable (Beck et al., 1998; Tucker, 1999), and calculate
our social network variables using the sna package in R (Butts, 2007; R Development Core
Team, 2007). Regression analysis was done in STATA (Stata Corporation, 2005).
Trade institutions exhibit a great deal of institutional variation. Ideally, any study
comparing the effects of relative institutional ties on conflict against the effects of mutual ties
would also include information about varying institutional qualities, such as dispute settlement
mechanisms or security aims. Unfortunately, these data are simply not available for most trade
institutions. Following both Mansfield and Pevehouse (2000) and Oneal and Russett (1999), we
consequently adopt the simplifying assumption that trade institutions can be analyzed as if they
supply homogenous institutional qualities across agreements. We thus assume that social
8
Oneal and Russett’s 1999 study gives full details of their model specification and their results;
both manuscript and data are available online at http://www.yale.edu/unsy/democ/democ1.htm.
9
Data were collected by Emilie Hafner-Burton using sources from the WTO, (McCall Smith,
2000; Schott, 2003). We would like to thank Ed Mansfield, Jon Pevehouse, Bruce Russett and
John Oneal for generously sharing their data.
15
network properties that emerge through a given institution (such as NAFTA) create equivalent
types of social ties to those created by another institution (such as ASEAN).
The liberal perspective suggests that increased information through organizational
mechanisms as well as social interaction itself and a feeling of sameness and mutual
identification decreases conflict. Consequently, both components of the liberal argument suggest
that the conflict-decreasing properties of trade institutions should be proportional to membership,
not simply dichotomous; more arrangements mean more information, and similarly more
common identification. In order to test our social network hypotheses, we thus create a count
measure of mutual membership in institutions. This is important because Mansfield and
Pevehouse rely on a binary measure of mutual PTA ties between dyads (Mansfield and
Pevehouse, 2000). This measure allowed them to test whether two states with mutual
membership in any PTA are less likely to dispute than two states without membership. Our count
measure of mutual membership better fits both the liberal hypotheses and our social network
hypotheses.
We start by deriving a general measure of mutual membership in trade institutions. We
incorporate all trade institutions in the sample, including non-preferential institutions such as
GATT, PTAs composed of other PTAs such as the EU-Gulf Cooperation Council, and non-
reciprocal arrangements such as the Cotonou arrangement and the numerous EU arrangements
with individual states outside of the EU. We treat all memberships as symmetrical and equal for
the purposes of calculating liberal and social network variables, since co-membership in any of
these institutions is a mutual affiliation that could transmit information or increase affinity.
16
For each year, we observe the n states and k trade institutions that exist for that year,
forming an n by k affiliation matrix A.
10
Each entry is either 1 (if a state is a member of an
institution) or 0 (if not). We then convert the affiliation matrix A into a sociomatrix S by
multiplying the matrix by its transpose (S = A'A). Each off-diagonal entry s
ij
is equal to the
number of trade institution that states i and j have in common (our variable PTASAME
ij
), while
the diagonal s
ii
is equal to the total number of trade institutions country i belongs to. The
diagonal elements are the total number of PTAs a given country belongs to; the off-diagonal
elements indicate the number of PTAs two countries share.
We then define the dependence of state i on state j as the number of shared memberships
of i and j divided by the total number of trade institution memberships of state i, producing a
dependence matrix Š.
DEPENDENCE
ij
=š
ij
=s
ij
/s
ii
An actor with high access centrality is the recipient of many ties. If we believed that only
direct ties mattered, we would use a simple form of access centrality, degree centrality,
computing by summing over an actor’s incoming ties. However, according to our hypothesis, it
is not simply the incoming ties that matter, but also the importance of the actors sending those
ties. Consequently, we define the access centrality of a state as the sum of the state’s ties to the
other actors in the system, weighted by the access centrality of the actors sending ties to that
state. In practice, we compute the eigenvector centrality
11
of the dependence matrix Š.
12
10
An affiliation matrix is a social network term for a special case of a two-mode matrix. A two-
mode matrix has two distinct types of entities; an affiliation matrix is a two-mode matrix with
only one set of actors. See Wasserman and Faust (1994, pp. 29-30)
11
Bonacich power centrality (a generalization of eigenvector centrality, see Bonacich, 1987) is a
frequently-used measure in the access centrality family of measures (Hafner-Burton et al., 2009)
that takes into account through the parameter β how much access comes from being connected to
other well-connected nodes (β>0) or to more isolated nodes (β<0). The latter happens in
17
We then convert these measures into undirected dyadic form by computing the difference
for each quantity: DEPENDENCE
D
=|DEPENDENCE
ij
-DEPENDENCE
ji
| and ACCESS
CENTRALITY
D
=|ACCESS CENTRALITY
i
-ACCESS CENTRALITY
j
|
Statistical Analyses
We begin by replicating the core findings presented in Mansfield and Pevehouse (2000) using
our new trade institution data. In order to do so, we estimate the following model:
(1)
€
MID
ij
=
β
0
€
+
β
1
PTA
ij
+
β
2
(TRADE
ij
× PTA
ij
) +
β
3
(GDP
L
× PTA
ij
) +
β
4
(GDP
H
× PTA
ij
)
+
β
5
DEM
L
+
β
6
DEM
H
+
β
7
GROWTH
L
+
β
8
TRADE
ij
+
β
9
GDP
L
+
β
10
GDP
H
+
β
11
CAPRATIO
ij
+
β
12
ALLIES
ij
+
β
13
HEGEMONY
+
β
14
CONTIG
ij
+
ε
ij
A militarized international dispute (MID
ij
) occurs when a state threatens or enacts
military force against another state. The observed value of the dependent variable is binary,
equaling 1 if a dyad ij begins a MID in a given year t, and 0 if no MID is observed. This variable
is often termed MID onset, in contrast to DISPUTE
ij
, which equals 1 for each year of a MID
rather than just the first year. We include MID joiners as experiencing a MID onset in the year
that they join.
To replicate, we employ independent variables consistent with Mansfield and Pevehouse
exchange networks (Cook et al., 1983). Since our network is not an exchange network and our
theoretical expectation is that social influence comes from being connected to others who are
well-connected in institutional networks, we choose β>0. There is little guidance in the literature
as to how to choose β, and so consequently we default to the simpler eigenvector measure, which
occurs when the parameter β approaches the reciprocal of the largest eigenvalue of the
sociomatrix.
12
Using the directed dependence matrix Š instead of the symmetrical raw sociomatrix S can be
problematic in cases where a network contains unreciprocated ties. In these cases, alternate,
eigenvector-like measures should be used. However, in the dependence matrix, every outgoing
tie has an incoming tie as well. Consequently, eigenvector approaches are equally valid
(Bonacich and Lloyd, 2001).
18
and effectively lagged by one year. The core of their analysis rests on the results of PTA
membership on conflict. The authors measure whether a pair of states ij share membership in any
PTA during a given year t, drawing upon their sample of institutions from 1950 to 1985. They
call this binary variable PTA
ij
and expect that dyads sharing any mutual memberships will be less
likely to conflict. We replicate this variable in our new and updated sample including more
institutions and covering the period 1950 to 2000. Since Mansfield and Pevehouse’s sample
appeared to exclude general trade institutions that were not agreements (e.g. GATT), for the
purposes of initial replication in Table 1 we exclude these institutions and compute PTA
ij
;
13
using
PTA
ij
, we re-create several interaction terms with GDP and trade variables, described below.
However, for the reasons stated above, we use a continuous measure that includes these
institutions for our extensions of the model in Table 2, PTASAME
ij
.
Four additional variables are used to discriminate between the effects of PTAs and the
effects of other liberal forces influencing conflict. Mansfield and Pevehouse test a ‘weak link’
hypothesis about the dependence of democracy. DEM
L
measures the political character of the
less democratic state in a dyad, which they expect to be the stronger determinant of conflict
behavior. Because a MID can result from the actions of a single state, they argue that MID
likelihood mainly depends on the level of political constraint experienced by the weak link—the
less constrained state in each dyad (or the less democratic state). The variable ranges from -10
for a state characterized by extremely autocratic political institutions, to 10 for a state
characterized by extremely democratic political institutions. Following Mansfield and
Pevehouse, our second model also includes the regime type of the more democratic state in the
dyad, DEM
H
. This weak link theory extends to economic growth as well. Since states with
13
For the subset of overlapping dyads between our samples, our PTA
ij
is highly correlated with
their variable (~0.84).
19
lagging growth may have incentives to launch wars to divert the public’s attention from poor
economic conditions, both studies include a measure of economic growth. GROWTH
L
measures
the percentage change in GDP per capita during the previous three years for the state in each
dyad that has experienced the smallest change. TRADE
ij
measures the sum of i's exports to and
imports from j in year t.
The authors consider additional variables to control for realist expectations about the
causes of conflict. GDP
H
and GDP
L
measure the real Gross Domestic Product of the state with
the highest and lowest national income in 1996 US dollars, respectively. CAPRATIO
ij
is the ratio
of the stronger state’s military capability—measured by averaging its share of world population,
urban population, military expenditures, military personnel, iron and steel production, and
energy consumption—to that of the weaker dyad member. This may increase conflict (if the
stronger state is tempted to take over the weaker one) or decrease it (if the stronger state deters
the weaker state from attacking). ALLIES
ij
equals 1 if the dyad members were linked by formal
mutual defense treaties, neutrality pacts, or entente, and equals 0 otherwise. This variable is
important to control for the common wisdom that allies are generally less likely to fight each
other less than non-allied states because they share a common security interest. The authors also
include the variable HEGEMONY in order to control for the strength of the most powerful state
relative to other states in the international system. This variable is computed by the percentage of
total global GDP generated by the state with the largest GDP in the previous year (the United
States for every year in our sample). Finally, CONTIG
ij
controls for the potential that MIDs
result when at least one member of a dyad can reach the other member with effective military
force. The variable equals 0 if two states are not directly or indirectly contiguous and 1 if they
20
share a territorial boundary.
14
[Insert Table 1 here]
In the first column of Table 1, we report estimates of our replication of Mansfield and
Pevehouse, Model (1), using our measure, PTA
ij
. In order to be as consistent as possible with
their analysis, in this column we limit our time span from 1950 through 1985
15
and our sample to
politically relevant dyads. In the second column, we expand the replication through 2000 and in
the third column we replicate this second model on an expanded sample of states that include all
dyads.
When using the same variable construction as Mansfield and Pevehouse (binary PTA
ij
,
excluding organizations composed of PTAs and general trade institutions), the same timespan
(1950-1985), and the same dyads (politically relevant) we find very similar results. The
coefficient on PTA
ij
does switch signs from their results, but as both are small and highly
insignificant, this is a consistent finding. Our coefficients on the three interaction terms are in the
same direction as their results, although at lower levels of significance. The remaining variables
also have similar results, except for HEGEMONY, which is insignificant in our tests. However,
when we expand our timespan through 2000, we find that none of the PTA-related variables are
significant; moreover, when we move to all dyads, we find that PTA
ij
is highly significant and
positive, indicating that states that shared membership in a PTA overall actually leads
systematically to increased conflict.
Using these results, we build a base model, Model (2), from which we compute all
subsequent models. For the reasons stated previously, we believe that a count measure that
14
See Mansfield and Pevehouse (2000) for complete descriptions of their variable codings.
15
Due to limits on the temporal span of the GDP variables (1950-2000), where we include this
variable our first year is 1951.
21
includes all trade institutions is more compatible with both version of the liberal hypothesis (as
well as a better measure for construction of social network variables); the anomalous finding that
PTAs seem to increase conflict in some models adds empirical support for our argument that a
binary measure is inadequate. Consequently, we include our continuous measure PTASAME
ij
that
includes all trade institutions in all remaining regressions instead of PTA
ij
. Because the
interaction terms between membership in trade institutions and trade and GDP are insignificant
when we expand the time horizon of the study either with all dyads or politically relevant ones,
we exclude them from Model (2). We also introduce two additional control variables used by
Oneal and Russett in their studies of the effects of IGOs on MIDs: LOGDIST
ij
controls for the
natural logarithm of mileage between the two capitals (or major ports for the superpowers) of
dyad partners, while MAJPOWER
ij
controls for the effects of great powers.
16
The variable takes
on a value of 0 if a dyad is made up of minor powers and 1 if it contains at least one great power.
Both are important to control for realist explanations of war.
(2)
€
MID
ij
=
β
0
€
+
β
1
PTASAME
ij
+
β
2
DEM
L
+
β
3
DEM
H
+
β
4
GROWTH
L
+
β
5
TRADE
ij
+
β
6
GDP
L
+
β
7
GDP
H
+
β
8
CAPRATIO
ij
+
β
9
ALLIES
ij
+
β
10
HEGEMONY
+
β
11
CONTIG
ij
+
β
12
MAJPOWER
ij
+
β
13
LOGDIST
ij
+
ε
ij
Using Model (2) as our base, we add DEPENDENCE
D
and ACCESS CENTRALITY
D
in
Model (3) to test our social network hypotheses about dependence and access centrality. We
report estimates of the parameters from Model (3) in the final column of Table 1. Our results
show that membership in trade institutions can both increase and decrease conflict among
members. Consistent with the liberal expectation, dyads linked by more ties to trade institutions
16
Oneal and Russett have a slightly different set of countries as major powers; we use the COW2
dataset to determine major power status.
22
are less likely to go to war. However, in contrast with the liberal expectation, we find two
circumstances under which memberships in trade institutions can significantly increase the
likelihood of conflict among members. When dyads are characterized by relative disparities in
dependence or access centrality within the network of trade ties that characterize the structure of
the international political economy, states are more likely to fight. When dyads are characterized
by relative equality in dependence or access centrality, states are less likely to engage in
militarized disputes, controlling for the number of overall memberships.
We also test the empirical import of our findings. Using CLARIFY(Tomz et al., 2003),
we set all variables at their median levels, then increase each variable of interest separately to its
95 percent level. Increasing PTASAME
ij
in this way decreases MID onset by 7 percent. By
contrast, increasing DEPENDENCE
D
and ACCESS CENTRALITY
D
to the same level increases
MID onset by 17 percent and 10 percent respectively. To think of this a different way, suppose
that two states A and B at the median in all other variables belong to just one joint PTA in total,
so PTASAME
ij
is 1 and DEPENDENCE
D
is 0. Now suppose that state A joins a PTA with state C
as well. DEPENDENCE
D
then becomes 0.5, while PTASAME
ij
remains at 1. The chance of
militarized dispute onset increases by 10 percent as a result. If state A and state B joined a
second PTA together, by contrast, PTASAME
ij
would become 2, while DEPENDENCE
D
would
stay at 0, decreasing militarized dispute onset by 3.5 percent. While these are not enormous, in
terms of the influence that states’ individual choices can have, they are quite important.
Our findings, moreover, are robust. We have taken a number of steps to provide results
that are as consistent with as many different sample and variable specifications as possible.
Although we cannot report all of those steps here, we do address some of the more important
issues. Table 2 offers estimates across four new models. In Model (4), we test a minimalist
23
model by eliminating all realist and liberal variables while retaining geographic variables, social
variables, and PTASAME
ij
. In Model (5), we test whether our results are consistent when we
truncate our sample to politically relevant dyads. In Model (6), we consider an alternative
specification of the dependent variable that takes on a value of 1 throughout the entire dispute
rather than just the onset. Finally, Model (7) offers a different specifications of the relationship
between trade, GDP, and conflict: instead of three separate components, we include Oneal and
Russett’s measure of trade dependence TRADEDEP
L
, equal to the lower ratio of bilateral trade to
GDP in a given dyad. We also substituted in Zeev Maoz’s dependence balance measure (Maoz,
2009; 2010), which has a 0.97 correlation with our own, in all models; the results were
substantively unchanged.
[Insert Table 2 here]
Our results are quite stable across models, with some variation. In the minimal model, all
three remaining variables (PTASAME
ij
, DEPENDENCE
D
, and ACCESS CENTRALITY
D
) have a
greater effect at the same or better significance levels. When we restrict our sample to only
politically relevant dyads, the coefficient on DEPENDENCE
D
becomes insignificant. This is an
interesting finding, since it could indicate that the effects of PTA dependence (but not access
centrality) are limited to countries that fall outside of traditional definitions of “politically
relevant” states. We are conducting further research to investigate the causes of this particular
finding, although we strongly prefer measuring political relevance through the inclusion of
variables rather than through the exclusion of cases. When using DISPUTE as the dependent
variable instead of dispute onset (MID), PTASAME
ij
becomes insignificant, while the coefficent
on DEPENDENCE
D
increases significantly and the coefficient on ACCESS CENTRALITY
D
decreases slightly. When including the effects of trade dependence, we find that while trade
24
dependence itself is insignificant, the parameter estimates for ACCESS CENTRALITY
D
and
PTASAME
ij
increase, while DEPENDENCE
D
decreases slightly.
Conclusion
PTAs are not inherently trust-building or rivalry-inducing institutions and membership does not
automatically reveal previously hidden information about military capacity, build trust, or ensure
commitment to peace. Instead, there is significant variation in the effects of trade institution
membership across states in the international system. While there are a group of states that fulfill
the conditions for the liberal peace, for many states at the fringes, membership can actually
increase conflict by defining hierarchies of access centrality and dependence that are resented by
those at the bottom of those hierarchies.
Our findings therefore strongly confirm the liberal belief that trade institutions can keep
the peace under some circumstances—when they create ties among states with relatively equal
social positions within the international political economy, facilitating trust and reciprocity. Yet
trade institutions do not always keep the peace, and the liberal mechanisms are not universally
applicable. We show that trade institutions can also create relative disparities in social status
among members and that these disparities increase the likelihood of militarized conflict. Far
from being vehicles of peace, trade institutions generate inequalities of social power that can lead
to distrust, and ultimately, to conflict among nations.
Social network analysis gives us a way to conceptualize and tools to measure the effects
of international institutions beyond simple membership effects. In particular, it allows us to think
about asymmetries created by the uneven distribution of ties across the international system.
Here, we have identified two important asymmetries in the international trade institution network
that lead to increased militarized conflict: PTA access centrality and direct dyadic PTA
25
sensitivity dependence. Without the use of network analysis, such results would be difficult to
conceive of and impossible to measure. These two measures do not exhaust the possible effects
of the network of PTAs on conflict. Other centrality measures related to the brokerage and
efficiency families could have significant effects on conflict through different mechanisms, while
the network also creates potentially important dependencies at the monadic, dyadic, and systemic
levels through direct and indirect effects and through both sensitivity and vulnerability.
Measuring these effects will be important for the future agenda of network analysis in
international relations.
26
Table 1. Estimates of the Effects of PTAs on MIDs, 1950 to 2000: Replications and Core Models
Variable
PTA
ij
3.98E-02
(1.33E-01)
4.76E-02
(8.91E-02)
0.35
(0.09)
***
PTA
ij
x TRADE
ij
-2.14E-04
(1.13E-04)
+
-3.50E-06
(8.44E-06)
9.17E-06
(1.23E-05)
PTA
ij
x GDP
L
3.17E-06
(1.32E-06)
*
8.52E-08
(3.37E-07)
-2.41E-07
(4.85E-07)
PTA
ij
x GDP
H
-7.64E-07
(3.62E-07)
*
4.65E-10
(7.76E-08)
-6.56E-08
(8.05E-08)
PTASAME
ij
-2.82E-02
(1.18E-02)
*
-2.99E-02
(1.30E-02)
*
DEPENDENCE
D
0.22
(0.10)
*
ACCESS
CENTRALITY
D
2.46
(0.83)
**
DEM
L
-4.57E-02
(1.04E-02)
***
-6.33E-02
(8.56E-03)
***
-7.58E-02
(8.62E-03)
***
-7.93E-02
(9.60E-03)
***
-7.65E-02
(9.52E-03)
***
DEM
H
3.23E-02
(9.81E-03)
**
3.70E-02
(8.30E-03)
***
4.36E-02
(7.49E-03)
***
4.53E-02
(7.82E-03)
***
4.00E-02
(7.38E-03)
***
GROWTH
L
1.77E-03
(4.66E-03)
-2.81E-03
(3.84E-03)
-2.10E-03
(3.84E-03)
-7.70E-03
(3.57E-03)
*
-7.71E-03
(3.54E-03)
*
TRADE
ij
-2.77E-05
(1.68E-05)
+
-5.73E-06
(1.52E-05)
-2.64E-05
(1.79E-05)
-1.75E-05
(7.12E-06)
*
-1.65E-05
(6.79E-06)
*
GDP
L
1.05E-06
(2.28E-07)
***
6.50E-07
(1.95E-07)
**
1.26E-06
(3.24E-07)
***
6.34E-07
(3.05E-07)
*
5.86E-07
(2.90E-07)
*
GDP
H
2.61E-07
(5.54E-08)
***
1.32E-07
(3.03E-08)
***
4.45E-07
(2.32E-08)
***
3.34E-07
(4.16E-08)
***
3.28E-07
(4.37E-08)
***
CAPRATIO
ij
-2.91E-03
(6.61E-04)
***
-3.25E-03
(7.08E-04)
***
-1.81E-03
(5.50E-04)
**
-2.91E-03
(9.20E-04)
**
-2.91E-03
(9.15E-04)
**
ALLIES
ij
-0.15
(0.13)
-4.76E-02
(1.07E-01)
0.22
(0.11)
+
3.79E-02
(1.26E-01)
3.57E-02
(1.27E-01)
HEGEMONY
1.08E-02
(2.12E00)
1.81
(1.90)
4.90
(1.97)
*
1.23 (1.91)
-0.40
(1.89)
CONTIG
ij
1.32
(0.16)
***
1.27
(0.15)
***
2.94
(0.13)
***
-4.98 (0.51)
***
-5.07
(0.49)
***
MAJPOWER
ij
1.17 (0.15)
*** 1.19
(0.16)
***
LOGDIST
ij
-1.04 (0.07)
***
-1.05
(0.07)
***
N
25209 42320 407209 407209 407209
+ p<.10; * p<.05; ** p<.01; *** p<.001
all dyads
all dyads
all dyads
Note: All models are estimated using logit and include a natural spline function with three knots, omitted
from the table due to space considerations. Numbers in parentheses are panel corrected standard errors. Pr
dyads are politically relevant dyads.
pr dyads
pr dyads
(3)
Network
Model
1950-2000
1950-2000
(1)
Replications of M&P (2000)
1950 - 1985
1950-2000
(2)
Base Model
27
Table 2. Robustness Checks of the Estimates of the Effects of PTAs on MIDs, 1950 to 2000
Variable
PTASAME
ij
-2.99E-02
(1.30E-
*
-6.72E-02
(1.29E-02)
***
-6.16E-02
(1.97E-
**
-6.47E-03
(1.14E-
-4.57E-02
(1.24E-
***
DEPENDENCE
D
0.22
(0.10)
*
0.37
(0.16)
*
3.90E-02
(8.92E-
0.22
(0.09)
* 0.30
(0.09)
**
ACCESS
CENTRALITY
D
2.46
(0.83)
**
3.49
(0.90)
*** 2.24
(0.78)
** 2.10
(0.71)
** 2.87
(0.91)
**
DEM
L
-7.65E-02
(9.52E-
***
-6.12E-02
(8.79E-
***
-8.90E-02
(9.34E-
***
-7.98E-02
(1.01E-
***
DEM
H
4.00E-02
(7.38E-
***
3.26E-02
(7.75E-
***
3.79E-02
(7.44E-
***
4.72E-02
(7.58E-
***
GROWTH
L
-7.71E-03
(3.54E-
*
-4.43E-03
(3.63E-
-5.59E-03
(3.20E-
+
-3.51E-03
(3.61E-
TRADE
ij
-1.65E-05
(6.79E-
*
-5.80E-06
(4.40E-
-1.60E-05
(5.53E-
**
TRADEDEP
L
-6.71
(8.60)
GDP
L
5.86E-07
(2.90E-
*
5.60E-07
(1.55E-
***
4.25E-07
(2.46E-
+
GDP
H
3.28E-07
(4.37E-
***
2.00E-07
(3.22E-
***
2.88E-07
(4.45E-
***
CAPRATIO
ij
-2.91E-03
(9.15E-
**
-2.93E-03
(6.94E-
***
-3.28E-03
(8.42E-
***
-2.76E-03
(9.92E-
**
ALLIES
ij
3.57E-02
(1.27E-
-7.20E-02
(1.10E-
5.56E-02
(1.17E-
0.12
(0.13)
HEGEMONY
-0.40
(1.89)
0.42
(1.91)
2.73
(1.78)
-5.73
(1.81)
**
CONTIG
ij
-5.07
(0.49)
***
-4.15
(0.52)
***
-3.29
(0.64)
***
-4.24
(0.52)
***
-4.55
(0.62)
***
MAJPOWER
ij
1.19
(0.16)
***
1.69
(0.15)
***
-0.28
(0.15)
+ 1.31
(0.16)
*** 1.82
(0.16)
***
LOGDIST
ij
-1.05
(0.07)
***
-0.96
(0.07)
***
-0.57
(0.08)
***
-0.90
(0.07)
***
-0.98
(0.09)
***
N
407209
534407 42320 407209 407209
+ p<.10; * p<.05; ** p<.01; *** p<.001
(4)
(5)
(6)
Note: All models are estimated using logit and include a natural spline function with three
knots, omitted from the table due to space considerations. Numbers in parentheses are
panel corrected standard errors. Pr dyads are politically relevant dyads.
(7)
Networks
Minimal Model
PR dyads
DISPUTE
Trade Dep
(3)
28
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