THE LIMITS OF THE LIBERAL PEACE
Håvard Hegre
International Peace Research Institute, Oslo (PRIO)
Cand.polit. thesis
Department of Political Science
University of Oslo
June 1999
iii
Table of Contents
Table of Contents............................................................................................................................... iii
List of Figures and Tables ............................................................................................................... iv
Preface
.................................................................................................................................. v
Chapter 1
Introduction ............................................................................................................ 1
Chapter 2
Theoretical Background ........................................................................................ 5
2.1
Three Schools of Thought: Realism, Liberalism, and Structuralism ............... 5
2.2
The Liberal Peace ................................................................................................... 7
2.3
How May Trade Lead to Peace? ........................................................................ 10
2.4
Realist Objections to the Liberal Peace .............................................................. 13
2.5
Structuralist Objections to the Liberal Peace .................................................... 15
2.6
Levels of Analysis ................................................................................................ 16
2.7
Summary ............................................................................................................... 16
Chapter 3
Peace through Interdependence?....................................................................... 19
3.1
Peace through Interdependence......................................................................... 19
3.2
Modeling ‘Peace through Interdependence’ as a Deterrence Game ............. 24
3.3
Objection: Causality Runs from Peace to Trade, not Vice Versa ................... 34
Chapter 4
Development and Asymmetry ........................................................................... 43
4.1
Development and the Liberal Peace .................................................................. 43
4.2
Asymmetrical Relationships and the Liberal Peace ........................................ 49
1.3
Asymmetric Development .................................................................................. 62
Chapter 5
Research Design ................................................................................................... 67
5.1
Statistical Problems and Methods...................................................................... 67
5.2
Temporal-Spatial Domain................................................................................... 73
5.3
Operationalizing Interdependence .................................................................... 74
5.4
Operationalizing Development.......................................................................... 78
5.5
Operationalizing Regime Type .......................................................................... 78
5.6
Operationalizing Asymmetry............................................................................. 79
5.7
The Dependent Variable: Fatal Dispute ............................................................ 82
5.8
Control Variables ................................................................................................. 82
Chapter 6
Testing the Hypotheses ....................................................................................... 85
6.1
Hypothesis 1: Peace through Interdependence................................................ 85
6.2
Hypotheses 2 and 3: The Direction of Causation............................................. 95
6.3
Hypotheses 4 and 5: Development .................................................................... 98
6.4
Hypotheses 6 and 7: Power Asymmetry......................................................... 107
6.5
Hypotheses 8 and 9: Asymmetry in the Gains from Trade .......................... 109
6.6
Hypothesis 10: Development Asymmetry...................................................... 113
6.7
Summary of Results ........................................................................................... 113
Chapter 7
Conclusion........................................................................................................... 115
Appendices
.............................................................................................................................. 121
Appendix 1: Results of Gravity Model Regressions.............................................................. 121
Appendix 2: Descriptive Statistics........................................................................................... 122
References
.............................................................................................................................. 124
iv
List of Figures and Tables
Figures
Figure 3-1. The Prisoners’ Dilemma ..................................................................................................... 21
Figure 3-2. The Threat Game ................................................................................................................. 26
Figure 3-3. Subgame-perfect Equilibrium Strategies and Payoffs in the Threat Game for
Various Intervals of Ti Relative to bD and bA, for Fixed Values for ki and ri ......................... 28
Figure 3-4. Expected Utility in Equilibrium to Aggressia and Deterristan, as a Function of
Ti, the Symmetric Case, for Fixed bA, bD, p, and ki.................................................................... 32
Figure 3-5. Payoff Matrix Incorporating Relative-gains Considerations......................................... 36
Figure 4-1. Effects of Asymmetry for Equilibrium Outcomes for Various Intervals of Ti
Relative to bD and bA, Relevant Areas Only............................................................................... 54
Figure 6-1 Relationship between Lowest GDP per capita, Gravity Model Measure of
Interdependence, and Estimated Relative Risk of Fatal Dispute, 1950–92 .......................... 102
Figure 6-2 Relationship between Energy Consumption per Capita, ln(Salience) Measure of
Interdependence, and Relative Risk of Fatal Dispute, 1950–92............................................. 104
Figure 6-3 Estimated Baseline Hazard of Fatal Disputes, 1950–92................................................. 106
Tables
Table 6-1 Test of Hypothesis 1: Estimated Effect of Interdependence on the Risk of Fatal
Dispute, 1950–92............................................................................................................................ 89
Table 6-2 Test of Hypothesis 1: Estimated Effect of Interdependence on the Risk of Fatal
Dispute, 1950–19, Alternative Specifications ............................................................................. 92
Table 6-3 Test of Hypotheses 4 and 5: Estimated Effect of Interdependence and
Development on the Risk of Fatal Dispute, 1950–92............................................................... 100
Table 6-4 Test of Hypothesis 6: Estimated Effect of Power Asymmetry on the Risk of Fatal
Dispute, 1950–92.......................................................................................................................... 108
Table 6-5 Test of Hypothesis 8: Estimated Effect of Trade Asymmetry on the Risk of Fatal
Dispute, 1950–92.......................................................................................................................... 111
Table 6-6 Test of Hypothesis 10: Estimated Effect of Development Asymmetry on the
Risk of Fatal Dispute, 1950–92 ................................................................................................... 114
v
Preface
E
arly drafts of material in this thesis were presented to the 32nd Meeting
of the Peace Science Society (International), East Brunswick, NJ, 16–18
October 1998, to the 7th Norwegian National Conference in Political
Science, Røros, 11–13 January 1999, and to the 40th Convention of the International Studies Association, Washington, DC, 16–20 February 1999.
I have benefitted greatly from generous comments from the many people
who have read various versions of the manuscript. Firstly, I wish to thank my
thesis advisor, Jon Hovi. His careful advice and thoughtful and constructive
comments have substantially improved the presentation and argument.
The thesis was written at the International Peace Research Institute, Oslo
(PRIO) as part of the project on methodological issues in the study of democracy and peace, and is an off-shoot of my work on democracy and peace. I am
grateful to PRIO for providing a stimulating and pleasant social environment. I
am especially thankful to Nils Petter Gleditsch – for his continuous support and
encouragement through several years, for arranging excellent working conditions at PRIO for me, and for giving me the opportunity to present my work at
international conferences. The members of the Conditions of War and Peace
Program at PRIO, in particular Gleditsch, Scott Gates, and Indra de Soysa, have
provided very useful feedback. Finally, I wish to thank Katherine Barbieri, Kristian S. Gleditsch, Leif Helland, Soo Yeon Kim, Michael Mousseau, John Oneal,
Arvid Raknerud, Bruce Russett, Gerald Schneider, Richard Tucker, and Michael
D. Ward for comments on the conference papers. Thanks to Susan Høivik for
language-editing parts of the manuscript. Finally, thanks to Toril, Maria,
Aurora, Gabriel, and Kaspar for tolerating the several years of studies this thesis completes, which for them implied low income and frequent absences on my
part.
vi
The process of writing this thesis has been facilitated by a generous grant
from the Ryoichi Sasakawa Young Leaders Fellowship Fund, for which I am
grateful.
Section 5.1 draws heavily on an article I wrote together with Arvid Raknerud (Raknerud & Hegre, 1997). The analysis in Chapter 6 applies the method
developed in that article. The section describing the Cox regression model was
mostly Raknerud’s work, although I have commented on and influenced the
presentation. The rest of that article was written jointly.
Chapter 1
Introduction
F
or the past fifty years, the Western states have enjoyed a continuous
peace among themselves. Never before in the history of the nation-state
has a large group of countries managed to keep peace for such a long
period (Mueller, 1989). How can this be explained? According to the proponents of the ‘liberal peace’, the Western peace rests on the pacifying effects of
democratic regimes and commercial links between the states. In this thesis, I
will investigate this claim theoretically and empirically, with emphasis on the
‘trade promotes peace’ aspect of the liberal peace proposition.
The liberal peace argument has been attacked from several sides. Scholars
of the realist school emphasize the primacy of security to economic factors, and
question the liberal assumption that causation goes from trade (and democracy)
to peace, and not vice versa. Other scholars, among them many of radical or
‘structuralist’ leanings, question whether the pacifying effects of trade are confined to symmetrical relationships. I also look into other theoretical arguments
stressing the importance of socio-economic development for the liberal peace.
To see whether there are limits to the liberal peace, I study four core questions in this thesis. Firstly, I investigate the trade promotes peace hypothesis itself: Is the extent of the trade bonds between two states positively correlated
with peace between them? Secondly, if there is a relationship, are trade bonds
causally prior to the peace they are supposed to explain? Thirdly, can we expect
pacifying effects of highly asymmetrical trade relationships? And finally, does
the liberal peace require a certain amount of socio-economic development in the
states that take part in it?
I discuss the theoretical arguments in the literature and seek to model them
in a game-theoretical model. I derive a set of hypotheses from the theoretical
discussion, and survey a set of large-N quantitative studies to see how these
fare when confronted with historical data. Finally, I test some of the hypotheses
2
The Limits of the Liberal Peace
using Cox regression, a method that in several aspects improves on the method
employed in comparable earlier studies. As these studies do, I employ the data
on militarized interstate disputes, alliances, military capabilities, and development made available by the Correlates of War Project at the University of
Michigan. Data on trade, political regime type, and GNP were taken from the
IMF, the Polity Project, and Penn World Tables, respectively.
Representing the arguments in a formal model has certain advantages.
Modeling helps ensuring logic consistency, enforces explicitness about assumptions, enables a more concentrated exposition of an idea than is possible with
verbal arguments, and eases the extension of the argument.1 Here, I am interested in the limits of the liberal peace. Game-theoretical models have shown
themselves useful for clarifying the conditions under which a hypothesis is
valid. For example, Powell (1991) demonstrated that some arguments concerning relative gains (e.g., Snidal 1991a; 1991b) do not apply if a state has the opportunity to alter the rules of the game by the use of force, e.g. by eradicating
the opponent as an independent actor. I use the model to investigate whether
my model of the ‘peace through interdependence’ hypothesis yields the same
conclusions in situations of asymmetry in the gains from trade, and whether we
can expect the same conclusion for any level of socio-economic development.
The formal modeling allows me to extend the argument, to investigate under
which conditions the liberal peace hypothesis applies. The model also sheds
some light on the question of direction of causation.
Harsanyi has defined game theory as ‘the theory of rational behavior by
two or more interacting rational individuals, each of them determined to maximize his own interests, whether selfish or unselfish, as specified by his own
utility function’ (1986: 89, emphasis in original). A common criticism of gametheoretical arguments in international relations literature is that these assumptions are unrealistic. First of all, states are not individual actors, and may therefore have inconsistent and intransitive preferences due to weaknesses in the
mechanisms of preference aggregation. Decisions may be the unintended consequences of group interactions and bureaucratic politics. Moreover, even if
1
This discussion of advantages and disadvantages of game theory is based on Hovi & Rasch
(1993: 28–33; 1996: 74–84, 96–99) and Hollis & Smith (1991: 135–141).
Chapter 1: Introduction
3
states may usefully be conceived of as unitary actors, the strategic situations
they face are often so complex that it is impossible to expect them to have all the
information required to act rationally.
However, game theorists still defend these assumptions by pointing to the
fact that in practice one single person will normally have decision-making
authority when it comes to foreign policy. Furthermore, they argue that the advantages of game-theoretical modeling outweigh the disadvantages of such
drastic simplifications. Moreover, even if decisions in individual situations may
not be characterized as rational, rationality may still be seen as a ‘regulative
idea’ (Elster, quoted in Hovi & Rasch, 1996: 75). Rational models, then, predict
how actors will act under ideal conditions.
I formulate the hypotheses as probabilistic ‘laws’. These are tested using
quantitative methods to analyze data for a large number of countries. Such hypothesis testing has several advantages relative to confronting the propositions
with verbal information for a handful of case-studies. Using a large-N research
design facilitates abstracting from particular instances, and avoids the accusation of selecting cases that fit the theory. With more observations of a phenomenon, we may be more certain that confirming (or disconfirming/invalidating) observations were not just coincidences. On the negative side,
quantitative studies over-simplify complex phenomena. For example, in the
analysis reported in Chapters 5 and 6 I will treat the militarized dispute between Greece and Turkey in 1986 as the same thing as the Iran-Iraq 1980–88 war
– they are both an instance of a fatal dispute. Still, I intend here to test general
hypotheses, presumed to be valid for all countries at all times. For the present
purpose, the advantages of a quantitative study outweigh the disadvantages.
The thesis is organized as follows: In Chapter 2, I summarize the theoretical
background for the liberal peace debate. In Chapter 3, I go more into detail with
the ‘trade through interdependence’ argument, and presents a formal model. I
then go through the direction of causation objection to the argument, and discuss it in light of the model. The counter-arguments concerning asymmetry and
development are presented and confronted with the formal model in Chapter 4.
In Chapter 5, I defend my choice of statistical method, discuss the operationalization of the theoretical variables, and specify the data sources. The results of
4
The Limits of the Liberal Peace
the analysis are reported in Chapter 6. Then, in Chapter 7, I try to connect the
numerous threads.
My overall conclusion is that interdependent pairs of states – dyads – really
are more peaceful than non-interdependent pairs, but that this does not apply
to dyads involving less-developed countries. For dyads of developed countries,
on the other hand, trade is an important factor for peace. Furthermore, I argue
that the direction of causation counter-argument applies only below a certain
interdependence threshold. Finally, I find no support for the idea that the
‘peace through interdependence’ hypothesis requires a symmetrical relationship.
Chapter 2
Theoretical Background
T
he inquiry into the relationship between trade and conflict brings us
into the heart of the debate between the three schools of thought on
international relations: realism, liberalism, and structuralism.2
2.1
Three Schools of Thought: Realism, Liberalism, and
Structuralism
The realist school may be traced back to Machiavelli and Hobbes – some even
count Thucydides among the realists. Although the term ‘realists’ subsumes a
wide variety of scholars, they share a set of assumptions of the conditions for
international interaction (see Holsti, 1995: 36–37; Mearsheimer, 1995: 10): The
most important feature of the international system is seen as the mode of organization: anarchy, or the absence of any authority above the individual, sovereign states. Without such an authority, enforcement of international laws and
regulations is impossible. Given these structural conditions, the most basic interest of states becomes survival, since all other interests are dependent on the
existence of the state. At the same time, all states have a potential to hurt or destroy each other – there exists no means to ensure survival that cannot be used
for attack. This is the ‘security dilemma’: if one state increases its security, the
security of other states will decrease (see, e.g., Snyder, 1984) . They, in turn, will
arm to regain their relative loss, such that in the end the first state is as insecure
as at the onset. States may never be sure of each other‘s intentions, since occupying another state is one way to increase security. War will always be a possibility in the relationship between states. For realists, non-state actors play only
subordinate parts on the world stage.
2
See Viotti (1987) and Wight (1991) for a similar classification. Viotti uses the terms realism,
pluralism, and globalism, whereas Wight calls the writer in these categories realists, rationalists,
and revolutionists.
6
The Limits of the Liberal Peace
Liberal theory counts numerous strands, and the tracing of its intellectual
history is even more difficult than for realism. Locke and Grotius emphasize
individual rights and the existence of natural law. Thus, right from the start, liberalism has challenged two realist assumptions: The nation-state is not the only
important actor in international politics (cf. Holsti, 1995: 40),3 and the question
of war and peace does not dominate all other issues. According to Zacher &
Matthews (1995: 118–19), liberal thinkers share this set of assumptions:
Liberals regard individual human beings as the primary international actors. Liberals view states
as the most important collective actors in our present era, but they are seen as pluralistic actors whose interests and policies are determined by bargaining among groups and elections. … Liberals believe that human and state interests are shaped by a wide variety of domestic
and international conditions. Ultimately they are determined by bargaining power among
interest groups, but these groups’ definition of their interests are affected by a host of factors. [Emphasis in original]
Liberal economic and political theory have been closely related since the
18th century. The liberal concern for the individual was emphasized by Adam
Smith and David Ricardo in their work in economics. Kant, Paine, Bentham,
James Mill, and John Stuart Mill all argued for free trade, liberty for individuals
and for republican or democratic government. These ideas were linked up in the
liberal opposition to mercantilism: Mercantilism saw the wealth in the world as
constant. Trade, then, was a zero-sum game. Moreover, accumulating gold was
seen by mercantilists as equivalent to increasing state power, since war was financed largely through the state’s gold reserves and through loans. Given these
assumptions, all economic and individual interests were necessarily subordinated to the pursuit of state power. The liberal opposition to the traditional political systems then automatically meant an opposition to its economic doctrine:
‘Mercantilism was seen to arise from the nature of aristocratic states, and therefore the political priority of liberals was to topple the interventionist, powerseeking state structures that were the legacy of the eighteenth century’ (Buzan,
1984: 600).
The assumption behind economic theories of states’ interests is that states
will act so as to maximize the welfare of their citizens. However, many liberal
3
Due to its view on actors, this group of theories is also called pluralism (Hollis & Smith, 1991;
Viotti & Kauppi, 1987).
Chapter 2: Theoretical Background
7
thinkers (among them Kant, 1795/1991; Keohane, 1984) also recognize structural factors: Liberal states are not merely aggregations of individual preferences, they are also systems and guarantors for such aggregation. To the extent
that this very system is threatened, the main interest of a state will be survival,
as realism predicts.
Finally, the eclectic set of ideas labeled ‘structuralism’ emphasizes the importance of global structures. Many of these, but not all, draw on the writings of
Karl Marx. Structural theories typically disagree with the realist focus on states
as the primary actors: Marxist strands see states only as tools for the capitalist
class (although like other organizations, they may have their own dynamics, cf.
Wallerstein, 1974: 402). The structure and dynamics of the entire world system
are seen as more fundamental driving forces than the individual states. Structural theories conflict with liberal theories as to whether all economic exchange
is mutually beneficial. The structure of the system, structuralists argue, ensures
that this exchange is unequal, such that some parts of the system will exploit
other parts. Marxist versions of this argument also see the exchange in itself as
nothing but exploitation of the proletariat by the capitalist class.
2.2
The Liberal Peace
With ‘the liberal peace’, I refer to the two ideas that states with democratic government will keep peace with each other, and that states that trade extensively
will do likewise. These ideas are rooted in the liberal focus on individuals as the
primary actors. To place the modern exponents into a broader historical perspective, I will look more closely into Immanuel Kant’s vision of a perpetual
peace based on these two mechanisms. Kant’s thinking on this point was reintroduced to the field of international relations by Michael W. Doyle (1983a;
1983b; 1986), and has since been the primary philosophical reference for the
democratic peace literature.4 Then, I will define interdependence more precisely, and proceed to show how modern liberal reasoning on the relationship
4
Kant was by no means the first to forward these ideas, though. Enlightenment theorists such as
Rousseau, Montesquieu, Paine, and Godwin all precede him in arguing that states founded on
democratic principles must also be against war (Flessen, 1999: 13–17; Gates, Knutsen & Moses,
1996: 6–7).
8
The Limits of the Liberal Peace
between interdependence and peace may be divided into four categories, with
partly overlapping explanations for why trade should promote peace. The first
two identify causal processes between two interacting states (at the dyadic level),
whereas the two other concentrate on processes within the interacting states. 5
2.2.1 Kant’s Perpetual Peace
Kant’s vision of a perpetual peace is found in Zum Ewigen Frieden (Kant,
1795/1991). It rests on three ‘definitive articles’ of peace:
First Definitive Article of a Perpetual Peace: The Civil Constitution of Every State
shall be Republican. Kant defines the republican constitution as ‘founded upon
three principles: firstly, the principle of freedom for all members of a society (as
men); secondly, the principle of the dependence of everyone upon a single common legislation (as subjects); and thirdly, the principle of legal equality for everyone (as citizens)’ (p. 99, emphasis in original). Republics are peaceful since
‘the consent of the citizens is required to decide whether or not war is to be declared’ (p. 100).6 Kant’s explanation of the pacifying mechanism deserves being
quoted in full:
[I]t is very natural that they will have great hesitation in embarking on so dangerous an
enterprise. For this would mean calling down on themselves all the miseries of war, such
as doing the fighting themselves, supplying the costs of the war from their own resources,
painfully making good the ensuing devastation, and, as the crowning evil, having to take
upon themselves a burden of debt which will embitter peace itself and which can never be
paid off on account of the constant threat of new wars. But under a constitution where the
subject is not a citizen, and which is therefore not republican, it is the simplest thing in the
world to go to war. For the head of state is not a fellow citizen, but the owner of the state,
and a war will not force him to make the slightest sacrifice so far as his banquets, hunts,
pleasure palaces and court festivals are concerned. He can thus decide on war, without any
5
See McMillan (1997) for an excellent introduction to the literature on interdependence and con-
flict.
6
Kant takes pain to distinguish his republic constitution from the democratic one (Kant,
1795/1991: 100–102). This has been used to argue that Kant’s peace was not democratic at all
(Gates, Knutsen & Moses, 1996: 6). However, Kant’s classification of regime types follows Aristotle’s. Here, democracy means direct democracy. This ‘is necessarily a despotism, because it establishes an executive power through which all the citizens may make decisions about (and indeed against) the single individual against his consent’ (Kant, 1795/1991: 101, emphasis in
original). What is required for the perpetual peace is a constitution where the executive power is
separated from the legislative power. To ensure this, the government necessarily must be representative, he argues (p. 101). This definition of a republic is not inconsistent with modern, representative democracies.
Chapter 2: Theoretical Background
9
significant reason, as a kind of amusement, and unconcernedly leave it to the diplomatic
corps (who are always ready for such purposes) to justify the war for the sake of propriety.
(p. 100)
Second Definitive Article of a Perpetual Peace: The Right of Nations shall be based on a
Federation of Free States: ‘Each nation, for the sake of its own security, can and
ought to demand of the others that they should enter along with it into a constitution, similar to the civil one, within which the rights of each could be secured’
(p. 102). With this Article, Kant ‘appears to have in mind a mutual nonaggression pact, perhaps a collective security agreement, and the cosmopolitan
law set forth in the Third Definitive Article’ (Doyle, 1986: 1158).
Third Definitive Article of a Perpetual Peace: Cosmopolitan Right shall be limited
to Conditions of Universal Hospitality. This article is fundamental to the perpetual
peace since it is necessary for ‘continents distant from each other to enter into
peaceful mutual relations which may eventually be regulated by public laws,
thus bringing the human race nearer and nearer to a cosmopolitan constitution’
(p. 102). This natural right of hospitality ‘does not extend beyond those conditions which make it possible for them to attempt to enter into relations with the
native inhabitants’ (p. 106, emphasis in original). Thus, Kant uses this Article to
denounce the imperial powers’ conquest of the peoples of Africa and America.
Kant argues that the perpetual peace is guaranteed by nature, and even by
war itself (pp. 108–114). Nature has made it possible for people to make a living
all over the world. War is nature’s means of scattering the peoples of the world
to everywhere on earth. Moreover, the threat of war with a neighboring people
has forced each people to ‘form itself internally into a state in order to encounter
the other as an armed power’ (p. 112, emphasis in original). Kant further argues
that republics will emerge from this state formation because ‘the republic constitution is the only one which does complete justice to the rights of man’ (p.
112).
Although nature separates the nations, it also unites them. And this is
where the economic aspect of the liberal peace enters Kant’s argument: 7
7
In fact, this quotation is the only reference to the ‘trade promotes peace’ thesis in Perpetual
Peace.
10
The Limits of the Liberal Peace
On the other hand, nature also unites nations which the concept of cosmopolitan right
would not have protected from violence and war, and does so by means of their mutual
self-interest. For the spirit of commerce sooner or later takes hold of every people, and it
cannot exist side by side with war. And of all the powers (or means) at the disposal of the
power of the state, financial power can probably be relied on most. Thus states find themselves compelled to promote the noble cause of peace, though not exactly from motives of
morality. And wherever in the world there is a threat of war breaking out, they will try to
prevent it by mediation, just as if they had entered into a permanent league for this purpose … (p. 114, emphasis in original)
It is important to note that Kant’s argument rests on individual self-interest, not
on idealistic moral concepts: ‘the problem of setting up a [republican] state can
be solved even by a nation of devils (so long they possess understanding)’ (p.
112). For Kant’s state of nature is a state of war, just as is Hobbes’ (Kant,
1975/1991: 98).
Kant’s idea of a democratic peace has been the focus for a large number of
studies in the past fifteen years, studies with theoretical as well as empirical focus.8 Key empirical works are Doyle (1986), Bremer (1992), and Maoz & Russett
(1992; 1993). Much of the present work on the liberal peace build on the framework laid out in these articles, this thesis being no exception. Moreover, some of
the same writers are now working with questions of trade and conflict (Barbieri
& Bremer, 1999; Oneal et al., 1996; Oneal & Russett, 1997; 1999).
Through its foundation in individual self-interest, Kant’s vision of a peaceful federation of free republics is fully consistent with the Enlightenment idea of
peace through trade. These ideas were well established by the time of Kant: in
the early 17th century Emeric Crucé and Hugo Grotius had argued that the interaction of enlightened and rational economic actors in different nations would
stimulate mutual dependence and consequently peace (Thomassen, 1998).
2.3
How May Trade Lead to Peace?
The modern literature has proposed several mechanisms for trade to promote
peace. Below is a brief review of these. In the remainder of the thesis, I will concentrate on the first and the last of these mechanisms.
8
See Gleditsch (1992) and Chan (1997) for reviews of the literature.
Chapter 2: Theoretical Background
11
2.3.1 Trade leads to interdependence, which inhibits war
Modern exponents of the first mechanism have hardly changed Montesquieu’s
250-year old wording: ‘The natural effect of commerce is to bring about peace.
Two nations which trade together, render themselves reciprocally dependent: if
the one has an interest in buying the other has an interest in selling; and all unions are based upon mutual needs’ (De l’esprit des lois, Book XX, ch. II, 1748,
quoted in Hirschman, 1945/1980: 10). Mutual dependence acts as a form of economic deterrence.
This reciprocal dependence is usually called interdependence. Interdependence, according to Keohane & Nye (1977: 8–12), is mutual dependence between
states, meaning that situations and events in one state affect other states, and
vice versa. Interdependence may be cultural, technological, political, or economic. The more costs and benefits the relationship entails, the more interdependent will the states be. Such relations may also have varying degrees of
symmetry. If a relation between two states is entirely asymmetric, it is a relation
of dependence. Moreover, Keohane & Nye (pp. 12–13) distinguish between sensitivity and vulnerability: ‘Sensitivity involves degrees of responsiveness within a
policy framework – how quickly do changes in one country bring costly
changes in another, and how great are the costly effects?’ For example, most oilimporting countries are sensitive to an oil embargo, since this will entail higher
oil prices, costs of reallocation, etc. Country a’s vulnerability concerns the extent
to which it may counter the costs (in the long run) by political measures. Vulnerability rests on the relative availability and costliness of the alternatives that
various actors face. If state a cuts off its oil exports to country b, b is more vulnerable the more costly it is to replace this oil import with domestic production
or imports from other countries, or to replace oil with other sources of energy.
The greater the mutual dependence, the less the risk of war. For the deterrence to work, it is required that both states are ‘vulnerable’ and not only ‘sensitive’, and that the relationship is symmetrical.
2.3.2 Trade stimulates the formation of international regimes, which inhibit war
Another mechanism between trade and peace is that trade leads to cooperation
on mutual elimination of trade restrictions (Keohane, 1984: 75–78). Such coop-
12
The Limits of the Liberal Peace
eration may be formalized into an international regime. According to liberal
theorists, these regimes dampen conflicts in themselves. They serve as the fora
for negotiations, highlight the states’ common interests, broaden the involved
states’ repertoire of non-military means of force through issue-linking, and ease
the inclusion of third-party mediators to conflicts. Thus, trade helps to put into
practice Kant’s second and third definitive articles of a perpetual peace: the federation of free states, and the conditions of unlimited hospitality (Kant,
1795/1991: 102–108).
2.3.3 Trade increases wealth, which paves the way for democracy, which inhibits war
According to Erich Weede (1995), international trade leads to peace through
changes within the states: Free trade increases the wealth of countries. Greater
wealth, in turn, tends to reduce class conflict and to invite domestic compromises, and consequently leads to democracy (cf. Lipset, 1960. See also section
4.1.3 below). Democracies, in turn, do not wage war with each other, according
to the democratic peace thesis. This forms a strong causal chain, where trade
primarily affects the monadic (nation) level, but reinforces a dyadic effect
through wealth and democracy.
2.3.4 Territory and trade: Antithetical routes to wealth
As Kant noted in the passage quoted (p. 10 above), liberals assume that trade
cannot exist side by side with war. In The Great Illusion (1910; 1938), Norman
Angell depicts territorial expansion and expansion through trade as contrasting
objectives for nations. As formulated by Richard Rosecrance (1986), states are
forced to make a choice between expanding territory or increasing trade as a
basis for increasing wealth, power, and welfare. Naturally, all states are concerned with territory, since
[…] nations are themselves territorial organizations. Unchecked expansion by one state
will impinge upon the territory controlled by others. Second, power, an objective of state
policy, was historically defined in territorial terms. The state with the greatest land mass
would have the largest population, the greatest stock of natural resources, and presumably
as well the largest wealth’ (1986: 6–7).
Chapter 2: Theoretical Background
13
Consequently, making war is a means to increasing territory and wealth.
One alternative way to wealth is international trade. But war and trade are antithetical routes to wealth:
If national policies of economic growth depend upon an expanding world market, one
country can hardly expect to rely primarily upon territorial aggression and aggrandizement. To attack one’s best customers is to undermine the commercial faith and reciprocity
in which exchange takes place. Thus, while the territorial and military-political means to
national improvement causes inevitable conflict with other nations, the trading method is
consistent with international cooperation. (Rosecrance, 1986: 13–14)
This view is not a contradiction or opposition to the classical ‘peace
through interdependence’ hypothesis, but an extension of it:
While trading states try to improve their position and their own domestic allocation of resources, they do so within a context of accepted interdependence. They recognize that the
attempt to provide every service and fulfill every function of statehood on an independent
and autonomous basis is extremely inefficient, and they prefer a situation which provides
for specialization and division of labor among nations. One nation’s attempt to improve its
own access to products and resources, therefore, does not conflict with another state’s attempt to do the same (p. 24).
Changing their orientation from the military-political world to the trading
world does not imply that trading states relieve themselves of security concerns. On the contrary, economic interdependence has to be accompanied by
military interdependence: ‘Trading states will also normally form alliances as a
precaution against sudden intrusion by military-political nations’ (p. 24).
2.4
Realist Objections to the Liberal Peace
Realists focus on the state as actor, stressing the primacy of security issues.
Consequently, they question the direction of causation assumed in many expositions of the liberal argument. Moreover, since power has always been highly
concentrated in a small number of nations, realists have tended to focus on
these powers. Many realists therefore argues for studying these questions at the
systemic level, in terms of polarity and hegemony.
2.4.1 Direction of causation
Realists stress the dominance of security issues over economic issues. Not seeing this, they claim, is to violate the assumption that the international system is
anarchical. As a logical consequence, then, the most important realist counter-
14
The Limits of the Liberal Peace
arguments question the direction of causation in the liberal reasoning. Anticipating the costs of broken trade ties in wartime, a state will have an incentive to
limit its trade with other states if it perceives the probability of war with them
in the near future to be high. This is a classic realistic argument, found in Waltz
(1986) and perhaps most explicitly in Copeland (1996).
Realists argue that interdependence is a double-edged sword. If a country
is dependent on resources in another country, it may be tempted to secure access to the resources by occupying the other country, thereby unilaterally solving its ‘dependency problem’ (Copeland, 1996: 10; Liberman, 1996: 148;
Mearsheimer, 1990: 45). A rupture of international trade may also create losses
beyond the loss of the gains from trade. The economy has to readjust, it will
lose productivity, and social problems may emerge from the ensuing unemployment. All in all, the country may be worse off than if the trade ties never
had existed (see also Buzan, 1984: 620–621; Hirschman, 1945/1980: 26–29). This
argument is especially valid if the trade relation is asymmetrical (see section
4.2.3 below).
Another aspect of this point is the relative-gains argument. According to
realists, states care more about relative gains than about absolute gains: Economic gains may be converted to military force. This is what Hirschman
(1945/1980: 14) refers to as the supply effect of foreign trade: ‘By providing a
more plentiful supply of goods or by replacing goods wanted less by goods
wanted more (from the power standpoint), foreign trade enhances the potential
military force of a country’. The security dilemma therefore dictates that states
should care more about relative gains and losses than absolute gains.
2.4.2 Hegemony and the Cold War
Another realist objection is that a liberal zone of peace requires a hegemon to
blossom. According to hegemonic stability theory (see Keohane, 1984), order in
world politics is typically created by a single dominant power – a hegemon.
Without this hegemon, the order will collapse. The liberal peace requires adhesion to the rules of a liberal international economic power. The only way this
can be enforced, the argument goes, is through an economically and militarily
superior power.
Chapter 2: Theoretical Background
15
Hegemony is defined ‘as preponderance of material resources…
Hegemonic powers must have control over raw materials, control over sources
of capital, control of markets, and competitive advantages in the production of
highly valued goods’ (Keohane, 1984: 32). Of course, the hegemon must also be
willing to use its power to enforce the rules. Although the USA had superior
power in the interwar years, its isolationist policies kept it from using it.
Military power is crucial to the hegemonic stability theory, since economic
issues may become military-security issues if they are crucial enough to basic
national interests. ‘A hegemonic power must possess enough military power to
protect the international political economy it dominates from incursion by hostile adversaries’ (Keohane, 1984: 39). In fact, the hegemonic stability theory is
the systemic variant of the argument in the previous section. Just as bilateral
trade requires the expectation of stable, peaceful relations between the two
states, a liberal economy requires a stable, regulated system – a liberal international regime, as it is often labeled (Keohane, 1984: 49ff.) Just as domestic economic activity will be restrained if private property rights are not protected by
the state, economic activity between countries will be difficult if there is no hegemon with economic and military power to enforce the rules. A liberal economy is dependent on, as a pre-existing condition, the peace and stability it is
supposed to explain (Buzan 1984: 607).
Related to this is the argument that the liberal peace is an artifact of the
Cold War. The Western states have had high levels of trade and an unprecedented period of peace in the 50 years following World War II, but this cannot
be seen independently of the fact that the same states were on the same side in
the global contest with the Soviet Union (Farber & Gowa, 1995).
2.5
Structuralist Objections to the Liberal Peace
The fact that the liberal peace as of today applies mostly to the Western world
makes it also vulnerable to critique from structuralists. The Western countries
enjoy a preponderance of military superiority and economic power. Against the
rosy liberal vision of world peace and mutually beneficial relations everywhere
is the argument that the powerful nations have established the structure of the
16
The Limits of the Liberal Peace
system in order to benefit from it. Although the use of military power is seldom
necessary, it is the final guarantee for maintenance of the status quo.
The works of Baran, Bornschier, Cardoso, Chase-Dunn, Galtung, Prebisch,
Wallerstein and the dependencia school are important modern contributions to
this general class of arguments. This school also stresses the inequality in the
exchange between the developed and the developing world. In an unequal exchange, trade and investment are not necessarily mutually beneficial, as implied
by classic economic theory. On the contrary, trade and investment may remove
capital from the South. Recently, these views have been restated more formally
by economists, with Paul Krugman as the prime exponent. Some of Krugman’s
models (1979; 1981) refer explicitly to the dependencia theorists, and may also be
seen as consistent with the ideas of Galtung (1971).
2.6
Levels of Analysis
Whether interdependence affects the probability of militarized interstate conflict may be studied at three different levels: systemic, nation, or dyadic (see
Gleditsch & Hegre, 1997). At the systemic level, we may ask whether changes in
the level of world trade affect the calculations of individual states. Rosecrance’s
trading world and realist theories of hegemony are located at this level. At the
nation level, we may ask whether a state’s level of economic openness affects its
international behavior. At the dyadic level, we may ask whether the level of
trade between two specific countries affects their mutual relations.
I will restrict this analysis to the dyadic level in this thesis. Although all
three levels are interesting for the study of the liberal peace, the dyadic seems to
provides the closest focus on the core concept: interdependence, defined as mutual dependence between two countries.
2.7
Summary
The liberal argument that trade and democracy promotes peace has been contested by realists and structuralists alike. Realists question the direction of causation, and the tenability of seeing dyadic trade relationships as independent of
global structures of power, defined in terms of hegemony and polarity. Struc-
Chapter 2: Theoretical Background
17
turalists also emphasize the role of global structures, but have the division between developed and non-developed countries in mind. Even liberal scholars
(e.g., Angell and Rosecrance) stress the importance of socio-economic development for the liberal peace proposition.
In the next two chapters I discuss the theoretical debate on the ‘peace
through interdependence’ hypothesis. The survey in this chapter of the theoretical background indicates it should be confronted with three main objections:
The question of the direction of causation, the importance of socio-economic
development, and the role of asymmetries within the dyad.
18
The Limits of the Liberal Peace
Chapter 3
Peace through Interdependence?
T
he liberal peace proposition has been heavily contested and a focus for
a lively debate in recent years. However, this discussion easily degenerates into an unresolvable debate between realism and liberalism
(and, to a lesser degree, structuralism). The arguments have been uncompromising and seemingly founded on totally divergent assumptions. Criticizing
the interdependence hypothesis very often means a complete rejection of the
liberal assumptions. Many researchers have lamented this situation,9 and have
sought to build bridges between the two. One effort (perhaps the most fruitful)
proceeds by means of a rational-actor formulation of the realist and liberal positions.
In this chapter, I investigate the arguments for and against the liberal peace
in far greater detail, focusing on the first and the last mechanisms introduced
above (sections 2.3.1 and 2.3.4). I will discuss some formal models of the relationship that have been proposed, and introduce my own game-theoretical
model of the mechanism. The various positions will be formulated in terms of
probabilistic hypotheses. Translating from game-theoretical results to probabilistic hypotheses is a difficult task, however, and this part of the argument is
more intuitive than formally precise.
3.1
Peace through Interdependence
3.1.1 Trade theory
According to Ethier (1995: 3), there are three fundamental reasons why nations
trade. The classical explanation is that nations trade to benefit from comparative
9
‘Let’s halt the phony realist-liberal debate (or, can there be more to IR theory than mutual as-
sured destruction?)’ (Snidal, 1993: 740).
20
The Limits of the Liberal Peace
advantage.10 In addition, more recent economic theory describes how economies of scale and imperfect competition give incentives to trade. Classic economic theory shows that the free-trade solution is an efficient allocation of the
production resources of any two given countries.
If one of the countries levies a tariff, this will cause the domestic relative
price of imports in terms of exports to exceed the foreign relative price. This
will give the domestic firm an incentive to reallocate its production to a mix
which is worth less at international prices than the country is capable of producing. If the tariff does not change the international price, the production and
consumption loss is always larger than the income from the tariff itself. The
country’s trading partner will also lose from the tariff, since decreases in the
demand for good 2 and in the supply of good 1 force it to reallocate its production and consumption. The tariff causes a reduction of trade between the states.
Generally, tariffs always harm the world as a whole.
On the other hand, a tariff may improve the terms of trade of the levying
country if that country is large enough in world markets. Thus, with a moderate
tariff, the favorable terms-of-trade effect could outweigh the unfavorable costs
of consumption and production (Ethier, 1995: 222). Such a tariff – one that
maximizes this gain – is called an optimum tariff.
3.1.2 Polachek’s model
Solomon Polachek’s (1980) model of the relationship between trade and conflict
is based on the standard trade model. He assumes that conflict makes trade
more difficult through retaliatory tariffs, embargoes, and other barriers to trade.
Conflict thus reduces trade, and the ‘implicit price of being hostile is the diminution of welfare associated with potential trade losses’ (Polachek, 1980: 60). In
his mathematical model (pp. 75–77), conflict is related to trade through inclusion of conflict in the welfare function w=w(c,z), where w is welfare, c is consumption, and z is net conflict, and through the assumption that conflict in10
A state has a comparative advantage over another in good 1 relative to good 2 if, in autarky,
the relative price of good 1 in terms of good 2 would be lower in one state than in the other. Under free trade, each state will increase the production of the good in which it has a comparative
advantage at the expense of the other to the point where the relative prices are equalized, and
both states would be better off than under autarky.
Chapter 3: Peace through Interdependence?
21
creases import prices and decreases export prices. Any increase in welfare with
increasing conflict is offset by the increased economic costs associated with the
conflict. The model also shows that the marginal utility of conflict decreases
with increasing trade, just as classic interdependence theory claims.
3.1.3 Cooperation in repeated Prisoners’ Dilemma games
The previous section demonstrated that in some cases countries may have an
incentive to impose a tariff. Given this, the other party may prefer to retaliate
with a counter-tariff. Both states will benefit, however, if they cooperate on
eliminating the tariffs. Such a situation may be modeled as a Prisoners’ Dilemma game.
Also the security dilemma may be formulated as a Prisoners’ Dilemma. If a
country increases its military spending, its rival will feel compelled to do the
same to re-establish a balance. Both countries will then be worse off: The level
of security remains unchanged, but military spending is higher. The security
dilemma is also relevant for Rosecrance’s depiction of a choice between a trading world and a military-political world: In order to rely on trade as an alternative to military means for increasing welfare, a state needs to be confident that
the trade flow will not be cut off. All in all, this makes the work on cooperation
in iterated Prisoners’ Dilemma games highly relevant for the liberal peace.
Figure 3-1. The Prisoners’ Dilemma
Cooperate
(No tariff)
Defect
(Impose tariff)
M
F
Cooperate
M
U
(No tariff)
U
P
Defect
F
P
(Impose tariff)
M denotes mutual cooperation, U unilateral cooperation, F free-riding, and P no cooperation. The game is a
Prisoners’ Dilemma if F > M > P > U. (Adapted from Snidal, 1991b: 706)
The equilibrium outcome of the one-shot Prisoners’ Dilemma is mutual defection: that both sides impose a tariff is dominant strategy for both players.
This outcome is Pareto sub-optimal: Both players would be better off if they had
cooperated. Cooperation seems impossible in such if a body that can enforce
cooperation is lacking. However, Shubik (1970), Taylor (1976), and Axelrod
(1981; 1984) have shown that cooperation may be an equilibrium outcome if the
22
The Limits of the Liberal Peace
Prisoners’ Dilemma is repeated an infinite number of times, and if the players
value future payoffs to a sufficient extent. When the game is repeated infinitely,
two players that defect in each move both receive a discounted payoff of
1
P,
1−φ
where φ is the discount factor (the value in present payoff units of one payoff
unit to be received one period from the present). The strategy of always defecting is called ‘All D’. Two players who always cooperate (‘All C’) get the mutual
cooperation payoff
1
M
1−φ
. As in the one-shot Prisoners’ Dilemma this strategy
combination Pareto-dominates the ‘All D’ combination. But the players still
have an incentive to defect when encountering an ‘All C’ player, so as to harvest the free-riders’ payoff
1
F
1−φ
.
Repetition of the game gives the players the opportunity to punish defections and reward cooperation. The ‘Tit for Tat’ strategy is ‘the policy of cooperating on the first move and then doing whatever the other player did on the
previous move’ (Axelrod, 1984: 13). A player who follows this strategy will obtain
1
M
1−φ
when playing against an ‘All C’ or another ‘Tit for Tat’ player. If an
‘All D’ player plays against a ‘Tit for Tat’ player, he will get the temptation
payoff T in the first round and P in all subsequent rounds, totaling F +
φP
1−φ
. If a
player who follows an ‘alternation between D and C’ strategy meets a ‘Tit for
Tat’ player, he will obtain the payoff
F + φU
. Given this, playing ‘Tit for Tat’ is
1−φ 2
one of several equilibrium strategies if
1
φP
F−M
and
M >= F +
⇔ φ >=
1−φ
1−φ
F−P
1
F + φU
F −M
M >=
⇔ φ >=
(Axelrod, 1984: 208). This combined threshold
2
1−φ
M −U
1−φ
value for φ is called ‘the minimum discount factor’ for cooperation to be selfmaintaining.
However, reciprocal ‘Tit for Tat’ is not the only equilibrium in repeated
Prisoners’ Dilemma games. In The Evolution of Cooperation (1984), Axelrod demonstrated that states may adopt cooperative – ‘trading state’ – strategies in an
initially hostile environment. In a series of computer tournaments, the ‘Tit for
Chapter 3: Peace through Interdependence?
23
Tat’ strategy obtained higher scores (i.e. payoffs) than any other strategies. In
the computer tournaments, each strategy was paired with itself and all other
strategies, and each strategy’s payoff for each encounter was summed for all the
iterations. Furthermore, Axelrod demonstrated the possibility of an ‘evolution
of cooperation’ in an extension of the tournament. Here, ‘the number of copies
(or offspring) of a given entry will be proportional to that entry’s tournament
score’ (p. 49). The strategies that perform badly would then gradually disappear
from the tournament. Here also the ‘Tit for Tat’ strategy was found to have performed the best (p. 51).
3.1.4 Morrow’s model
Morrow (1999) takes a model of crises as contests of relative resolve as his point
of departure for discussing the importance of trade to conflict. Resolve is the
value of going to war, and determines its willingness to make concessions to
avoid war. Resolve is partly observable and partly unobservable. Having the
unobservable resolve in the model is important, Morrow claims, since this is
what makes war possible. If the resolve of both parties were fully known, both
states would know who would win the contest, and the loser would give in before the crisis had begun to minimize costs. War is the outcome if the following
two inequalities are satisfied:
βX ij + ε ij − β ′X ji − αε ji > µ ′
β ′X ji + ε ji − βX ij − αε ij > µ ′
where βXij is i’s observable resolve and εij is i’s unobservable resolve, and
β’Xji and εji are the corresponding terms for j. α denotes the extent to which the
parties are able to signal their resolve to the opponents, and µ’ the threshold
over which i or j will want to escalate the crisis to war. War results if both
states think the difference between their own resolve, observable as unobservable, and the opponent’s resolve, observable and signaled, exceeds a threshold
value. Then both states think they will prevail in the conflict. The unobservable
components of the model allow the formulation of probabilistic hypotheses
from this model.
Morrow enters trade into this model by assuming that it affects the states’
resolve. Trade is observable, and thus enters the βX terms. The fear of breaking
24
The Limits of the Liberal Peace
trade bonds will decrease their value of going to war. But since the trade bond
reduces the resolve of both states, it will not necessarily reduce the relative resolve – if trade decreases both states’ resolve by the same amount, the difference that determines the war outcome remains unchanged.
Morrow mentions some qualifications to this argument: if a trade bond has
an asymmetric impact on the states’ resolve, it may increase or decrease the
states’ relative resolve, and thereby change the probability of war. Moreover,
‘very high levels of trade could reduce resolve so much that even the most
resolute type of prospective initiator prefers the status quo to war’ (Morrow,
1999: 486). Morrow also notes that trade may decrease the likelihood of war by
acting as a costly signal (p. 487): The better states are able to convey how resolute they really are (i.e. increasing α in the equation above), the higher is the
likelihood that the least resolute will back down before escalating. But since
states have an incentive to bluff, it is important that the signal is credible. The
signal will be more credible the more costly it is, since leaders will be more
punished for failed politics the more costly they are. Morrow then suggests that
‘states with higher trade flows may have more signals of their resolve available
than dyads with little trade’. This might explain the liberal peace in the same
way as Fearon (1994) explains the democratic peace: by claiming that audience
costs for failed policies are higher in democracies than in non-democracies.
3.2
Modeling ‘Peace through Interdependence’ as a
Deterrence Game
In this section, I introduce a deterrence game as a model of the ‘peace through
interdependence’ argument. The model will provide a common framework for
the discussion of the competing and seemingly contradictory hypotheses. The
basic model is quite simple, although the discussion of the different thresholds
rapidly becomes very complicated. Its simplicity is an advantage over Bueno de
Mesquita & Lalman’s (1992) international interaction game, although that
model is more general. The proposed model also has an advantage over Polachek’s model in explaining why the expectation of conflict leads states to reduce their trade. Polachek’s model merely assumes this to be the case.
Chapter 3: Peace through Interdependence?
25
3.2.1 Specifications
My point of departure is a threat game based on the game used by Hovi (1998:
34 and elsewhere). The game models the interaction of two states, for convenience called Aggressia and Deterristan. Aggressia considers using military force
to alter the status quo. The precise form of this use of force or of the claim is not
important here. It may be a blockade, a seizure, the occupation of a territory
that is contested between the two states, or the occupation of a third country.
Aggressia knows that Deterristan has threatened to start a war if Aggressia
makes use of military force. In the case that it deems Aggressia’s transgression
too minor to warrant a full war, Deterristan has also issued a threat to impose
economic sanctions if that is more appropriate. In this way, Deterristan hopes to
increase its credibility.
The game is sequential, has complete and perfect information, and is represented in Figure 3–2. The first move in the game is Aggressia’s choice to use
military force to alter the status quo or not. Deterristan may react by carrying
out its war threat, its sanctions threat, or by accepting the change. If Deterristan
starts a war or accepts, the game ends. If Deterristan imposes economic sanctions, Aggressia may withdraw its forces and re-establish the status quo ante,
continue the use of force while escalating the conflict to full war with Deterristan, or continue the use of force without escalating. If Aggressia withdraws, Deterristan lifts the sanctions.
The payoff for maintaining status quo is (TA, TD), where Ti is the discounted
value to state i of future trade between the two states. For simplicity I assume
that all trade ends in the case of war or economic sanctions.11 The economic cost
of rupture of the trade bonds is then equal to Ti.
If Aggressia chooses to withdraw its forces as a response to economic sanctions, each state i suffers the costs riTi of a short sanctioning episode, yielding a
11
Arguably, this is a rather strong assumption. Barbieri & Levy (1999) argue that war between
two countries need not necessarily reduce trade very much. We will see later that this finding is
not wholly inconsistent with this model, as states will adjust their trade level to the perceived
conflict level before hostilities take place. In any case, however, the objection does not completely
invalidate the model. T may then represent the value of the trade that is lost in case of war or
economic sanctions.
26
The Limits of the Liberal Peace
total payoff of Ti − ri Ti = Ti (1 − ri ) . ri denotes the share of Ti that is lost in case of
short-term sanctions, such that riTi is the total loss.
Figure 3-2. The Threat Game
War
( pbA − k A ,− pbD − k D )
Aggressia
War
( pbA − k A ,− pbD − k D )
Deterristan
Aggressia
Start war
Use force
to alter
status quo
Do not challenge
SQ
(TA,TD)
Start war
Impose economic
sanctions
Accept change
in status quo
uncontested
Uncontested change of status quo
(TA + bA , TD − bD )
Continue
use of force
Withdraw forces,
reestablish status quo
Longterm
sanctions
& change
of status
quo
(bA,–bD)
Short-term sanctions &
withdrawal
(TA (1 − rA ), TD (1 − rD ))
Payoffs: (Aggressia, Deterristan)
Symbols:
Ti:
Discounted utility for state i of continued trade relations in the future
bA:
Gain in utility for Aggressia of change in status quo
bD:
Loss in utility for Deterristan of change in status quo
ki:
Cost of war for state i
p:
Probability that Agressia wins the war
ri:
Share of Ti that is lost in case of short-term sanctions
A successful change of status quo increases Aggressia’s payoff by bA and
Deterristan’s by –bD. As in Bueno de Mesquita & Lalman’s domestic variant of
their game (1992: 41), the magnitudes of these utilities (or demand, as they call
the bA term) are determined outside the game itself. If Deterristan accepts the
change of status quo without contesting it, this is added to the status quo payoff, giving a total of TA + bA for Aggressia and TD − bD for Deterristan. If the
outcome of the game is that Aggressia continues the use of force while Deterristan maintains economic sanctions, the payoffs are (bA,–bD).
If one of the states opt for war, both states will have to bear the costs of war
ki (e.g., costs of mobilization, loss of life and property), in addition to the disutility of breaking off the trading relationship. The payoff depends on who wins
the war: If Aggressia wins the war, it obtains the payoff bA, but will have to bear
the cost of war kA. Deterristan then gets the payoff − bD − k D . If Deterristan wins
the war, status quo is re-established, but without trade. Both states will have to
bear the cost of war –ki independently of the outcome of the war. The probability of Aggressia winning the contest is p. The expected utility is then
Chapter 3: Peace through Interdependence?
27
p(bA − k A ) + (1 − p )(− k A ) = pbA − k A for Aggressia. The probability of Deterristan
winning
is
(1–p).
The
corresponding
expected
utility
is
[ p(− bD − k D ) + (1 − p )(− k D )] = − pbD − k D for Deterristan.
Throughout, I assume that the utility Ti of trade is positive for both states,
and that the cost of war ki is positive (i.e. that –ki is negative). Moreover, the
uncontested use of force has always positive utility for Aggressia, and negative
for Deterristan.
3.2.2 Solution of the game
The game is solved by backward induction. The outcome changes with changing values for the parameters. Figure 3–3 summarizes the equilibria of the game
for different levels of trade relative to bA and bD, holding ki fixed. The horizontal axis represents the joint value of TA and kA relative to bA. The vertical axis
represents the joint value of TD and kD relative to bD. The combinations of intervals form areas in the figure denoted by Roman numerals I–VII. Within each,
the equilibrium strategies and their associated payoffs are given. The solution
of the game depends on whether Deterristan’s war and sanctions threats are effective. In order to be effective, they will have to be both credible and sufficiently serious (cf. Hovi, 1998). Below, I will identify the thresholds for credibility and sufficient seriousness for Deterristan’s two threats, and show how the
different combinations of intervals on the two axes yield the different equilibrium outcomes.
In the last node in the game tree in Figure 3–2, Aggressia will never escalate
a conflict to war in this game: Aggressia will always prefer maintaining the
change of status quo to starting a war since it is always true that
b A > pb A − k A (–ki is negative by definition, and p<=1). There is no reason to
escalate a conflict if the objective already has been achieved. Aggressia’s choice
then, is between maintaining the change in status quo and withdrawal. It will
choose the latter if Deterristan’s threat of continued sanctions is sufficiently serious. This is the case if Aggressia prefers short-term sanctions and withdrawal
to long-term sanctions and continued use of force:
28
The Limits of the Liberal Peace
Figure 3-3. Subgame-perfect Equilibrium Strategies and Payoffs in the Threat Game for
Various Intervals of Ti Relative to bD and bA, for Fixed Values for ki and ri
TD relative to
[Sanctions are not sufficiently serious]
bD
[Neither threat
VI: Uncontested use of force
is credible]
A: (Use force to change status quo, continue use of force
if sanctions are imposed)
D: (Accept change of status quo)
[Sanctions are
sufficiently serious]
VII: Uncontested use of force
A: (Use force to change status quo, continue use of force if sanctions are imposed)
D: (Accept change of status quo)
(TA + bA , TD − bD )
(TA + bA , TD − bD )
Thr 2 :
bD
rD
[Only the
threat of sanctions is credible]
V: Status quo
IV: Uncontested use of force
A: (Do not challenge status quo, withdraw forces if sanctions are imposed)
D: (Impose sanctions if Aggressia uses
force
A: (Use force to change status, continue use of force if
sanctions are imposed)
D: (Accept change of status quo)
(TA , TD )
(TA + bA , TD − bD )
Thr 3 : (1 − p )bD − k D
[Both threats
are credible]
II: Status quo
I: War
A: (Use force to change
status quo, continue use of
force if sanctions are imposed)
D: (Start war if Aggressia
uses force)
Thr 4 : pb
A: (Do not challenge status quo, withdraw forces if sanctions are imposed)
D: (Impose sanctions if Aggressia uses
force
− kA
bA
1 − rA
(TA , TD )
( pbA − k A ,− pbD − k D )
A
III: Status quo
A: (Do not challenge status
quo, continue use of force if
sanctions are imposed)
D: (Start war if Aggressia
uses force)
Thr 1 :
(TA , TD )
TA relative
to bA
Payoffs: (Aggressia, Deterristan)
Threshold 1: Deterristan’s threat of sanctions is sufficiently serious at node 3 if
T A (1 − rA ) > bA ⇔ T A >
bA
1 − rA
The inequality is satisfied in areas III, V, and VII in Figure 3–3. If the threat
of sanctions is not sufficiently serious, Aggressia will continue the use of force
in order to maintain the change in status quo if it reaches node 3 (area IV).
At node 2, Deterristan will choose between starting a war, imposing sanctions, and accepting the change in status quo. If Deterristan knows that the
sanctions threat is sufficiently serious, it will impose them if that yields a higher
utility than withdrawal. Otherwise, the threat of sanctions is not credible:
Chapter 3: Peace through Interdependence?
29
Threshold 2: Deterristan’s threat of sanctions is not credible if
T D − bD > TD (1 − rD ) ⇔ −bD > − rD TD ⇔ T D >
bD
rD
The inequality is satisfied in areas VI and VII in Figure 3–3. Knowing that
Deterristan will accept the change of status quo in node 2 in Figure 3–2, Aggressia will always use force to alter status quo in this situation.
Threshold 2 implies that a very high level of trade (as perceived by Deterristan) leads to the uncontested use of force. This is counterintuitive, as it suggests that the risk of lower-level militarized conflict may increase with a higher
level of trade.12 The results get more reasonable if we allow Deterristan to select, within the game, the magnitude of rD that maximizes its utility. Deterristan
will then keep rD as low as possible, to ensure credibility. The lower rD is, the
larger is
bD
, and the less likely it is that the value to Deterristan of the trade
rD
(TD) is above this threshold.13 Henceforth, I will assume that Deterristan may
choose the magnitude of rD, and completely disregard the outcomes where the
sanctions threat is not credible.
In areas III and V, the sanctions threat is both credible and sufficiently serious. Thus, Deterristan knows that Aggressia’s dependence on their bilateral
trade is so high that sanctions will work, and it would not be rational for Deterristan to accept the challenge uncontested in node 2 in Figure 3–2. Deterristanwill always prefer short-term sanctions to war, since the payoff from short-term
sanctions T A (1 − rA ) is always positive and the utility of war − pbD − k D is always negative. Knowing that sanctions will be imposed, Aggressia will refrain
from challenging the status quo in node 1 in Figure 3–2 (areas III and V in Figure 3–3).
If Deterristan is expected to impose economic sanctions, Aggressia will use
force only if the costs of sanctions are lower than the utility of the use of force;
12
This is also noted by Morrow (1999: 485, see section 3.1.4 above).
13
In other words, the threat of sanctions should go along with the promise that the sanctions
will be lifted swiftly if Aggressia withdraws. As Threshold 1 implies, it is also in Deterristan’s
interest to keep rA as low as possible, since this increases the range where the sanctions are sufficiently serious.
30
The Limits of the Liberal Peace
TA < bA .14 If Deterristan is expected to accept it uncontested, Aggressia will
change the status quo by force since bA is positive by definition (areas IV and
VI).
If the threat of sanctions fails, Deterristan will have to rely on its threat of
war. This threat may also fail to meet the credibility and seriousness criteria. To
take credibility first, Deterristan will opt for full war only if the expected payoff
for this is higher than the payoff for accepting the change in status quo without
contest:
Threshold 3: Deterristan’s threat of war is credible if
− pbD − k D > TD − bD ⇔ TD < (1 − p )bD − k D
This inequality is satisfied in areas I, II, and III in Figure 3–3.15 It is not satisfied in the other areas. In area V, the threat of sanctions is effective, keeping
Aggressia from challenging status quo. In area IV, the outcome of the game is
the same as in areas VI and VII: Aggressia gets what it wants without contest.
Aggressia prefers the use of force to withdrawal – the value of the bilateral
trade to Aggressia is lower than Threshold 1. Note that the trade relationship is
unaffected in this case: If the contested territory (or whatever is contested) will
be lost in any case, Deterristan will prefer to keep up the trade relationship.16
If the threat of war is credible, it still has to be sufficiently serious to be effective. If Deterristan opts for war, Aggressia will still use force if T A < pbA − k A ,
leading to the war outcome (area I). In that case, the war threat failed to be sufficiently serious. If the combined costs from trade loss and war exceed this
threshold, Aggressia will prefer the status quo (area II). This is the fourth
threshold of the game:
14
Assuming perfect information, Aggressia will never use force to alter the status quo if it
knows that it will be forced to withdraw in node 3, since T > T(1–rA)
15
The expected utility of starting war has to be higher than for continued sanctions, too;
− pbD − k D > −bD ⇔ (1 − p )bD > k D . Since TD > 0 by definition, Threshold 3 may be rewritten to read
16
(1 − p )bD > k D . Consequently, this criterion is always fulfilled if the other is.
The model thus predicts that governments may allow their citizens limited trade with their
enemies (cf. Barbieri & Levy, 1999).
Chapter 3: Peace through Interdependence?
31
Threshold 4: Deterristan’s threat of war is sufficiently serious if
TA > pbA − k A
The inequality is satisfied in area II. In area I, neither the loss of trade nor
the costs of war can keep the two states from going to war – the war threat is
credible, but not sufficiently serious.
Figure 3–3 illustrates how the tenets of the liberal argument are captured by
the game: An increase in TA relative to bA makes the use of force less attractive
for Aggressia, relative to keeping up the trading relationship. In the three areas
forming the south-east corner of the table (areas II, III, and V), Aggressia will
refrain from challenging the status quo. The figure also demonstrates how Aggressia’s choice is contingent on how Deterristan values trade relative to the
disutility of Aggressia’s use of force: If Deterristan considers its trade with Aggressia to be much more important than the disputed claim (top line of figure),
its threats of economic sanctions will not be credible, and Aggressia may freely
do what it wants. If Deterristan considers altering the status quo to be highly
undesirable (bottom line of figure), the threat of war will be effective for intervals of TA relative to bA where the threat of sanctions does not work.
Figure 3–4 provides another representation of these results for the symmetric case, where the value of trade is equal for both parties; TA=TD, they have
equal probability of winning, p = (1 − p ) = 0.5 , they will suffer the same war
costs, kA=kD, and the two states are equally capable of inflicting pain through
economic sanctions: rA=rD. The figure plots the expected utility for Aggressia
and Deterristan as a function of the level of trade Ti for fixed values for the remaining parameters. The only asymmetry in this relationship concerns how the
two states assess the change in status quo: the disutility to Deterristan is in this
case twice as large as the utility to Aggressia. The utilities relate to TA according
to the sets of strategies that are equilibrium solutions, as summarized in Figure
3–3. For the sample values, Threshold 3 > Threshold 1 , and area III never applies.
Figure 3–4 allows tracing the outcomes as the level of trade increases from
0. Firstly, war is the outcome (area I). When the trade level crosses Threshold 4,
the war threat is sufficiently serious to maintain the status quo, and both states’
32
The Limits of the Liberal Peace
utilities are equal to the gains from trade. Between Threshold 3 and Threshold 1
neither threat is effective, allowing Aggressia to change the status quo
uncontested. This means a drop in utility for Deterristan, and an increase for
Aggressia. Over Threshold 1, the sanctions threat is effective, such that both
states’ utility equals the gains from trade.
In sum, war is the outcome if trade is low, T D < (1 − p )bD − k D and
T A < pbA − k A . Uncontested use of force is the outcome if the value of the trade
to Deterristan is very high: T >
T D > (1 − p )bD − k D and T A <
bD
, or if the value of trade to Aggressia is low:
rD
bA
.
1 − rA
Figure 3-4. Expected Utility in Equilibrium to Aggressia and Deterristan, as a Function
of Ti, the Symmetric Case, for Fixed bA, bD, p, and ki.
Area I: War
Area II:
Status quo
Area IV: Uncontested
use of force
Area V: Status quo
100
80
60
Utility
40
20
0
-20
0.00
0.60
1.20
Threshold 4
Threshold 3
1.80
Utility for Aggressia
2.40
Threshold 1
Utility for Deterristan
Utility for Deterristan
3.00
Level of Trade
3.60
Threshold 5
Utility for Aggressia
bA = 25, bD = 50, ki = 5, ri = 0.1, p = 0.5.
3.2.3 Translating into probabilistic hypotheses
How can this result be translated to hypotheses in terms of the probability of
war? War is often defined as the reciprocal use of force between two states that
Chapter 3: Peace through Interdependence?
33
involve a minimum number of battle-related deaths. If two states find themselves in a situation corresponding to area I in Figure 3–3, war is a certain outcome. The status of area IV, uncontested use of force, is less certain. Since I take
into consideration a wide range of contested issues, Aggressia’s use of force will
only lead to fatalities in relatively few cases. Consequently, if two states find
themselves in area IV, they will have a small but non-zero probability of being
defined as a war. The translation from game to hypothesis, then, requires an
idea of the probability of being in the different areas in the figure.17
I assume that the costs of war ki, the probability of winning p, the impact of
short-term sanctions ri, and the level of trade Ti are known variables. The utilities of the change in status quo bi, however, are random variables. If their probability distributions are known or assumed (e.g., the normal distribution), it is
possible to compute the probability of being on either side of the thresholds in
the propositions, e.g.
T + kA 

P (T A < pb A − k A ) = P b A > A

p 

and
T + kD

P (T D < (1 − p )bD − k D ) = P bD > D
1− p


 .

If the probability distributions are known, it is also possible to compute the
probabilities that both bA and bD are on the war outcome side of the thresholds.
If the probability distribution is unknown, this model still allows us to assume
T + kA 

that P b A > A
 is a monotonically decreasing function of TA.
p 

The probability of being in area I, then, is the product of two probabilities:
T + kA 

T + kD

P b A > A
 and P bD > D
p 
1− p



 . Since these probabilities are decreasing

functions of TA and TD, respectively, the product also has to be a monotonically
decreasing function of these parameters. In the symmetric case where TA =TD,
17
Admittedly, the translation I propose is loosely based. Until recently, good methods to express
game theoretical models as statistically testable probabilistic hypotheses have been lacking (but
see Signorino, 1998a; 1998b; Smith, 1996).
34
The Limits of the Liberal Peace
the probability of being in area I decreases monotonically with increase in the
level of trade.
As Figure 3–4 demonstrates, an increase in trade over Threshold 3 leads to
Aggressia’s use of force. Depending on to what extent this will take the form of
a war, this may violate the monotonic relationship between trade and war.
However, a further increase in trade takes the states into area V. If the difference between Threshold 3 and Threshold 1 is not too large, the game (as presented so far) would appear to support the liberal hypothesis:
Hypothesis 1: The more two states trade, the lower the probability of war between them
The model presented here corresponds in many respects to that of Morrow
(1999). The pbi − k i terms are analogous to resolve in that model. As in his model,
the effect of trade in the contestants’ resolve is indeterminate. Morrow’s general
conclusion is that the effect of trade on the probability of conflict is indeterminate, except as a tool for signaling. He notes some qualifications to this result,
however. More specifically: ‘higher trade could lower a prospective initiator’s
resolve to a level where the target does not believe that the initiator has a credible threat. … very high levels of trade could reduce resolve so much that even
the most resolute type of prospective initiator prefers the status quo to war’ (p.
486). It is precisely this qualification which is the focus of my model.
3.3
Objection: Causality Runs from Peace to Trade, not
Vice Versa
3.3.1 Expectation of future trade
As noted above, realists question the direction of causation stated in Hypothesis
1: If a country is dependent on resources in another country, it may want to reduce this dependence by securing access to the resources by force. Moreover, a
rupture of international trade brings about severe adjustment costs, such that
the total loss is larger than merely the loss of the gains from trade.
Copeland (1996) argues for introducing the expectations of future trade as a
new causal variable. He argues that this will reconcile the liberal and realist
views on interdependence:
Chapter 3: Peace through Interdependence?
35
High interdependence can be peace-inducing, as liberals maintain, as long as states expect
future trade levels to be high in the future: positive expectations for future trade will lead
dependent states to assign a high expected value to a continuation of peaceful trade, making war the less appealing option. If, however, a highly dependent state expects future
trade to be low due to the policy decisions of the other side, then realists are likely to be
correct: the state will attach a low or even negative expected value to continued peace
without trade, making war an attractive alternative if its expected value is greater than
peace. Moreover, since a negative expected value of trade implies a long-term decline in
power, even if war is not profitable per se, it may be chosen as the lesser evil (Copeland,
1996: 17).
3.3.2 Relative gains
The direction-of-causation problem has also been seen as a concern for relative
gains and losses. Gowa (1989) phrases this in terms of ‘security externalities’:
Gains from trade will free resources that may be used for military purposes. She
argues that trade with an enemy has a social cost that is proportional to the enemy’s gain from trade. The lower this cost is, the higher is the relative gain. If,
on the other hand, the trading partner is an ally, then the partner’s gain is also
a gain for the trading state. Consequently, states will use tariffs and other
means of trade restriction to limit trade with potential enemies, thereby directing trade to their allies and political ‘friends’. The expectation of future conflict
determines in part the level of trade.
Grieco (1988), Snidal (1991a; 1991b), and Gowa & Mansfield (1993) incorporate the relative-gains argument into the iterated Prisoners’ Dilemma model. A
state’s payoff consists of its absolute gain minus a fraction of the opponent’s absolute gain. For the (Cooperate, Cooperate) outcome, state i’s payoff then is
M i − rij M j , where the subscripts i and j denote the two states. The rij parameter
denotes the extent to which the gain of state j is considered a relative loss to
state i. For two states that are enemies, rij ranges from 0 to 1, where 1 denotes a
relationship where only relative gains matter and 0 a relationship where only
absolute gains matter. The model may also be extended to incorporate allies, in
which case rij ranges from –1 to 0 (cf. Gowa & Mansfield, 1993: 411). The payoff
matrix for the one-shot game represented in Figure 3–1 is reproduced for the
relative-gains model in Figure 3–5.
36
The Limits of the Liberal Peace
Figure 3-5. Payoff Matrix Incorporating Relative-gains Considerations
Cooperate
(No tariff)
Defect
(Impose tariff)
Cooperate
(No tariff)
M i − rij M j , M j − r ji U i − rij F j , F j − r jiU j
Defect
(Impose tariff)
Fi − rijU j ,U j − r ji F j Pi − rij P j , P j − r ji P j
Adapted from Snidal (1991b: 706) and Gowa & Mansfield (1993: 410).
Snidal (1991b: 706–709) has shown how relative-gains concerns transform
the one-shot game. No matter what the original values for M, U, F, and P are,
the game is transformed to a Prisoners’ Dilemma if rij is sufficiently large. If the
original game is a Prisoners’ Dilemma, it is transformed to a more severe dilemma, i.e. one in which the minimum discount factor for cooperation to be
self-enforcing (φ) is higher.
However, Snidal proceeds to show that the impact of relative-gains considerations in each dyadic relationship decreases considerably with an increasing
number of actors. In a tripolar setting, where each state’s concern with relative
gains is equally divided among the two others, the impact of relative-gains considerations on the minimum discount factor is only one half of the bipolar setting. The reasoning behind this is simple: The absolute gains from A’s cooperation with B may be almost fully countered by the relative loss respective to B,
but will always mean a relative gain respective to C. If A and B cooperate and C
does not, C will lose both absolutely and relatively. Snidal therefore concludes:
Thus, the relative gains argument cannot provide a decisive response to the institutionalist
claim that decentralized cooperation is possible under anarchy. Relative gains can save the
realist case only in the two-actor world and perhaps demonstrate that institutionalists under-estimate the difficulty of cooperation in other very-small-n cases. But these are much
weaker claims than realists have made in uncritically transferring relative gains arguments
from the two-actor world to international politics more generally (Snidal, 1991b: 719).
Powell (1991) argues that the use of the iterated prisoners’ dilemma model
is inappropriate to model the relative-gains problem, since it does not reflect
how one party’s use of military force may change the structure of the game – it
may even exterminate the opponent as an actor. To ameliorate this deficiency,
Powell suggests a model where a state takes advantage of a relative gain to
Chapter 3: Peace through Interdependence?
37
launch a military attack. As a result, the opponent receives a utility level for the
rest of the game that is even lower than that of unilateral cooperation.
Relative-gains considerations are relevant for the ‘peace through interdependence’ hypothesis, because they explicitly link the utility of trade to calculations on war and peace. Snidal’s argument that this applies only to systems
with very few actors, however, is a reminder that the dyadic construction is an
artifact, and that states have many more options when including third-parties
in their calculations. However, Snidal’s argument suggests that the dyad
framework employed here provides the hardest case for the liberal theory.
The essence of realist counter-arguments to the ‘peace through interdependence‘ hypothesis is to question the direction of causation in the trade and
conflict relationship. Knowing that economic interdependence may be used by
the other part to influence its decisions, a state will take measures to limit this
interdependence. Trade is correlated with conflict because the expectation of
conflict induces states to reduce trade, rather than vice versa (Gowa, 1989;
Gowa & Mansfield, 1993), and because the expectation of a reduction in trade
induces states to initiate conflict (Copeland, 1996; 1998). This we may formulate
as a hypothesis,
Hypothesis 2: The higher the probability of war between two states, the less they trade.
Evidently, Hypothesis 1 loses most of its explanatory power if Hypothesis 2
is equally true. The explanation of any correlation between trade and peace
found in empirical studies will have to be sought in more fundamental causes,
e.g. in realist power-based theories. It is therefore vital to come to terms with
this problem. In the next section, I will see what light my deterrence model
might shed on the issue.
3.3.3 Direction of causation in the deterrence model
Figure 3–3 demonstrated that high levels of trade could induce Aggressia to refrain from aggression. But may this give Aggressia an incentive to maintain
trade with Deterristan on a low level if Aggressia is deliberating a militarized
challenge to the status quo? What are the incentives for Deterristan to alter its
trade level with Aggressia?
38
The Limits of the Liberal Peace
States can affect the bilateral trade level, as they may use tariffs, embargoes,
subsidies of trade with third parties, and other means to reduce trade. In the
above model, Ti denotes the discounted value of all future trade between states
i and j to state i,. Over time, most states will be able to reduce trade with one
partner appreciably, such that the reduction in the discounted value of future
trade is considerable. In the passage quoted above, Copeland (1996) even suggests that severe adjustment costs may render Ti negative – a state may perhaps
find itself in a situation where it would have been better off if there had been no
trade relationship whatsoever between i and j.
It is much harder for a state to increase its trade with a partner in the short
run. Apart from reducing any existing trade restrictions, states do not have
many means to achieve this. Besides, there are limits to how much their economies may produce for export, how much their markets may absorb, and the
amount of goods that may be shipped between the countries.18
I will not look into the effects of any relative-gains considerations. Below,
the consequences of different choices of trade levels are discussed explicitly.
This I consider more appropriate than simply assuming that states care about
relative gains when deciding to cooperate or not, as in the studies discussed
above. However, one could imagine repeated iterations of this game as well,
where relative gains and losses would affect the probability of winning a war,
consequently affecting the parties’ calculations. Exploring the consequences of
iterated games is, however, beyond the framework of this thesis.
The level of trade is given exogenously in my model. I will not extend the
model to allow states to choose their trade levels endogenously. However, it is
possible to identify situations where the parties’ payoffs would have been different at the end of the game if the level of trade had been different. Investigating when this is the case provide some suggestions for the trade levels they
would have chosen if they had had the chance. I will refer to Figure 3–4 (p. 32)
when doing this for the symmetric case where TA = TD. If the initial trade level
18
The symmetry assumption disallows any side-payments and altering of the terms of trade in
either’s favor. Increasing Aggressia’s gains from trade so as to exceed the threshold may pay off
for Deterristan. Deterristan then may have an incentive to alter the terms of trade in Aggressia’s
favor. This again may be exploited by Aggressia (cf. Hirschman, 1945/1980). These issues will
be treated in section 4.2.4 below.
Chapter 3: Peace through Interdependence?
39
had been below Threshold 4, war would follow. Deterristan, then, would have
preferred a higher initial level of trade, so as to avoid the war. Aggressia would
have been indifferent to the trade level for this initial level, or would have preferred more trade since it obtains a higher utility for levels over Threshold 4.
Between Threshold 4 and Threshold 3, Deterristan would be happy with
the outcome. It would definitely not been better off if its trade with Aggressia
were below the war threshold, Threshold 4. Up to the Threshold 3, Deterristan’s
utility will increase with increased trade. However, it would have been worse
off if the initial level of trade were higher than Threshold 3, since its threat of
war would then have been non-credible. Above Threshold 3, Deterristan’s utility would have been higher the higher its trade with Aggressia. This is especially true in the range just below Threshold 1, above which the sanctions threat
is effective. Here, a slightly higher level of trade would have brought about the
status-quo outcome.
A similar logic applies to Aggressia: If the initial level of trade were lower
than Threshold 1, Aggressia would have preferred it to be higher. However, its
utility would have been reduced markedly to the status quo payoff if the trade
level had passed this threshold. Finally, if the initial level of trade were above
Threshold 1, Aggressia would have good reasons to regret that it were not just
below the threshold. Here, Deterristan’s threats of war and/or sanctions would
not have been carried out, and Aggressia might have enjoyed both the gains
from trade and the freedom to change the status quo by force.
But Figure 3–4 also demonstrates that Aggressia’s regretting the high level
of trade applies to a limited range only. Far to the right in the figure, the gains
from extensive trade alone exceed the gains from middle trade levels combined
with the change of status quo. This identifies the fifth threshold of the game:
Threshold 5: Aggressia would not have been better off with a lower trade level if
TA > bA +
bA
b (2 − rA )
⇔ Ta > A
1 − rA
1 − rA
Knowing what the two states would have preferred in retrospect, we may
now infer what trade levels the two states would have chosen to maximize their
payoffs if they knew a crisis was brewing (i.e. bA was likely to attain a peak
40
The Limits of the Liberal Peace
level). However, note that this reasoning is outside the model as formulated in
Figure 3–2. All in all, the expectation of conflicts does not hinder increase in
trade at a low initial level; it has an indeterminate impact in an intermediate
range, and does not hinder an increase for high initial levels. Three caveats to
this conclusion should be noted, however:
Firstly, Figure 3–4 suggests that Threshold 3 is roughly mid-way between
Thresholds 1 and 4. This depends on the particular choice of ratio between bD
and bA (the disutility and utility of changing the status quo). In fact, in the
symmetric case, Threshold 3 will be between the two other thresholds only if
bD > b A and bD <
2b A
+ k D . Above this range, the area IV outcome will never
1 − rA
be reached in the symmetric case since the threat of war will always be credible.
Both states, then, will always have an incentive to increase bilateral trade even
when expecting war between them. If bD < b A , area II will never be reached. In
this situation, Deterristan will always want to increase its bilateral trade. Aggressia, on the other hand, will face the same incentive to keep trade just below
Threshold 1, so as to stay within area IV.
The second caveat is that there are limits to how much states may manipulate the level of trade, especially upwards. The incentives to reduce trade seem
more important than those to increase trade. However, trade flows tend to increase steadily over time, reflecting the economic growth most countries enjoy.
For a non-myopic leader, it may then be rational to let this trade unfold at the
expense of short-term military gains. I will return to this point when discussing
development and the liberal peace below (section 4.1).
Thirdly, Copeland (1996) suggests that changes in TA may affect the magnitude of bA: By denying Aggressia access to important resources through trade,
steps taken by Deterristan to limit trade may increase Aggressia’s incentives to
use force to change the status quo. This argument might justify direct modeling
of the relationship between TA and bA, but I would hold that the reasoning
above covers the essence of his argument: If a reduction in TA tends to increase
bA, this will merely mean that the
TA
ratio – the unit along the x-axis in Figure
bA
3–4 – is reduced more than I have assumed. Assuming the relationship between
Chapter 3: Peace through Interdependence?
41
TA and bA is common knowledge, this will enter into Deterristan’s calculations.
If the levelof trade is above the war threshold (Threshold 4), it will still not pay
off for either state to reduce its trade to a level under this threshold.
Does the game model support the realist Hypothesis 2? Only to a limited
extent. Over a certain threshold of trade relative to contested issues, there are
no incentives to reduce trade to avoid loss in case of war. The same is the case
below another, lower, threshold. In the intermediate range, both states have
mixed incentives, and these may be sufficiently strong to hinder any increase in
trade in this range. However, neither state has any incentive to reduce trade to
the below-Threshold 4 level in which war is a possibility (area I).
All in all, the model seems to support Hypothesis 1 more than it supports
Hypothesis 2. This warrants the formulation of a new hypothesis:
Hypothesis 3: There is a two-way causal relationship between the probability of war and
extent of trade between two states, but such that the causal effect from trade to peace
is considerably stronger than the opposite.
42
The Limits of the Liberal Peace
Chapter 4
Development and Asymmetry
S
o far, I have discussed the theoretical arguments for the idea that inter-
dependence fosters peace, as well as the realist objection concerning the
direction of causation. In this chapter, I turn to the significance of
asymmetry and economic development for the relationship between trade and
conflict.
4.1
Development and the Liberal Peace
4.1.1 Development as a requirement for shifting from the military-political world to
the trading world
Some liberal thinkers limit the liberal peace hypothesis in that they see the trade
and conflict relationship as partly dependent on the structure of the states’
economies. For instance, Norman Angell’s The Great Illusion (1910; 1938), frequently considered the modern ancestor of interdependence theory, stresses
that things have changed in the modern world. Nations’ fears of their neighbors
‘are based on the universal assumption that a nation, in order to find outlets for
expanding population and increasing industry are pushed to territorial expansion and the exercise of political force against others’. In his book, Angell ‘…
attempts to show that it [this assumption] belongs to a stage of development
out of which we have passed’ (1938: 115). Modernization and industrializing
has fundamentally changed to what extent war is profitable.
Richard Rosecrance (1986) argues that the incentives for states to choose between the trading world and the military-political world (see section 2.3.4)
changes with economic development. The two worlds have always co-existed,
but the historical development has made the trading world increasingly more
attractive to states. Rosecrance points out that development alters four variables
that are crucial to the calculations of the leader of a state: it increases the poten-
44
The Limits of the Liberal Peace
tial gains from trade, the economic costs of war, and the political costs of war,
as well as decreasing the utility of occupying territories relative to the pursuit of
trade policies.
Firstly, development directly affects the possibility for and the gains from
trade:
Industrial and population growth strengthen interdependence and make it harder to
achieve national objectives autonomously. When technology was rudimentary and population sparse, states had little contact with one another and did not generally get in each
other’s way. With the commercial and industrial revolutions, however, they were brought
into closer proximity. As the Industrial Revolution demanded energy resources – great
quantities of food, coal, iron, water power and petroleum – the number of states that could
be fully independent declined (Rosecrance, 1986: 25).
Likewise, development furnishes states with access to better transport and
communications technology and infrastructure – within and between states –
which in turn increases the utility of trade by reducing its transaction costs.
Rosecrance’s argument is to some extent systemic, since the spread of technology and industrialization is quicker than the initial development of it. However, sizeable differences in the level of development persist. Rosecrance’s argument then applies at the nation-state and dyadic level as well.
Further arguments for development to increase trade may be found in the
“new growth theory” in economics. If there are economies of scale in the production of a good and a large market for it, firms will specialize (see Ethier,
1995: 52–58). However, to run manufacturing plants sufficiently large to benefit
from economies of scale, firms need capital, skilled labor, and a developed infrastructure. Thus, developed countries are in a better position to enjoy the
gains from trade due to economies of scale (cf. Krugman, 1981). Accordingly, it
may be hypothesized that the more developed countries will trade more, relative to their GDP, than less developed ones.
The choice between the trading world and the military-political world is
also related to how easy it is to conquer territory, and to govern it once it has
been taken. Rosecrance (1986: 32–38, 155–162) holds that the costs of war have
increased enormously with the industrialization of warfare. The price of producing one tank or one fighter has become far higher, but such items do not last
correspondingly longer in the battlefield (in confrontation with an opponent
Chapter 4: Development and Asymmetry
45
with the same technological level). In addition, the accelerating technological
change renders weapons and units obsolete more and more quickly. Modern
weapons are also more destructive, and sophisticated factories and elaborate
infrastructure in the target state take more time to reconstruct if damaged. In
addition, Rosecrance argues, the political costs of warfare are higher in industrialized societies.
On the other hand, Liberman (1993) argues that industrialized countries are
more valuable prizes for an expansionist country. He also counters Rosecrance’s
argument that the political costs of occupation are higher in developed countries by pointing to the relative ease with which Nazi Germany could make the
manufacturing sectors in the occupied countries – each of them fairly developed
even by modern standards – contribute to its own war economy.
Likewise, advanced weapons may cause less collateral damage. This is
most evident when a technologically superior power fights a lesser state (e.g.,
the USA vs. Iraq), but may also apply to a war between two developed states.
Economic development further means that states, through improved organization and a larger tax base, have more resources to spend on the military. This
tends to reduce the relative costs of war.
Rosecrance also points out (p. 159) that development affects the costs of
holding the occupied territory by force and the likelihood of making it profitable. Illegitimate governments will face stiffer opposition from the population
and have a hard time taxing them. He argues that these problems will increase,
the higher the level of education is in the occupied territory. Furthermore, the
more developed a country is, the easier it is for the inhabitants to take their assets with them when fleeing the country. If this is so, it is not certain that increased wealth in a society makes it a richer prize. Arguably, military force may
secure the access to raw materials in the occupied territory as easily in a developed area as in a underdeveloped area. This is counter-balanced, however, by
the reduction in transport costs brought about by development and technological improvements, making trade a more attractive means of obtaining access to
raw materials. Moreover, complex economies rely on the access to a broad
range of raw materials. The occupation of a single country cannot ensure access
46
The Limits of the Liberal Peace
to more than a few different goods, which decreases the utility of conquest for
developed states compared to simpler economies.
A certain level of development may thus be a prerequisite for the liberal
peace to work.
4.1.2 Development in the deterrence model
As argued in the previous section, development increases the value of trade Ti,
the costs of war ki, and reduces the value for Aggressia of altering the status quo
bA. What is the impact on the expected outcome of these changes? In this section, I assume that both states have an equal level of development. This assumption will be relaxed in section 4.3.
Given this discussion on how development relates to trade and war costs,
Figure 4–1 may be used to show how the incentives change for the two states
with increasing development. TA is hypothesized to increase relative to bA with
increased development, as the value of trade increases and the utility of occupation decreases. The same happens to TD relative to bD. This will move the location of the two states upwards and to the right in the figure, parallel to the diagonal, and will at some point take it over Threshold 3 and Threshold 4. In Rosecrance’s terms, these thresholds are where Aggressia and Deterristan opt for
the trading world at the expense of the military-political world. Development
lowers these thresholds, such that states will more often choose commerce
rather than conquest.
If development reduces the utility of occupation more than the costs of war,
the costs of war relative to bA will increase. This will push Threshold 3 downwards, and Threshold 4 to the left, and cause area I to shrink.
The effect of both these two processes is to reduce the likelihood that Aggressia and Deterristan will find themselves in a strategic situation where war is
an outcome, for fixed values for p, ri and Ti (cf. section 3.2.3). Stated as a probabilistic hypothesis,
Hypothesis 4: Assuming symmetry, the more developed two states are, the lower the
probability of war between them
Chapter 4: Development and Asymmetry
47
To the extent that development reduces the utility of occupation, it pushes
Threshold 1 to the left. This increases the probability of ending up in area III
and V. Moreover, it also pushes Threshold 5 to the left, changing the strategic
situation to one where neither state has an incentive to reduce trade. In other
words, development changes the strategic situation to one where it is more certain that trade promotes peace – development reinforces the effect of trade.
In contrast to the trade variable, development may be assumed to be an exogenous variable in the model. Aggressia may have an incentive to limit its
trade with Deterristan in order to retain freedom of action. However, for security reasons, it will not want to hamper its own economic growth. After all, its
military power relies largely on its economic power. This means that with increased development, Aggressia may more easily find itself above Threshold 5.
The change in the utility of using force to gain access to resources is outside
Aggressia’s control, as a side-effect of economic development. Even if it intends
to keepits trade level under Threshold 1, there is a chance that it may find itself
over Threshold 5 as a result of this unintended change in incentives. This gives
the model more dynamic potential, and reinforces the interaction between trade
and development. However, the fact that trade increases economic growth
weakens the exogeneity of this variable.
Above, I argued that development increases states’ ability to trade. This indirect effect of development also serves to reinforce the ‘peace through interdependence’ hypothesis:
Hypothesis 5: Assuming symmetry, the more developed two states are, the stronger is
the peace-conducive effect of trade
4.1.3 Development and democracy
The relationship between development and democracy has been widely debated.19 This question was at the core in the controversy around ‘modernization
theory’, a controversy set off by a 1959 article by Seymour Martin Lipset. Lipset
saw development as leading to democracy:
19
This section draws in part on Diamond (1992: 475–485).
48
The Limits of the Liberal Peace
Perhaps the most common generalization linking political systems to other aspects of society has been that democracy is related to the state of economic development. The more
well-to-do a nation, the greater the chances that it will sustain democracy. From Aristotle
down to the present, men have argued that only in a wealthy society in which relatively
few citizens lived at the level of real poverty could there be a situation in which the mass of
the population could intelligently participate in politics and develop the self-restraint necessary to avoid succumbing to the appeals of irresponsible demagogues (Lipset, 1960: 49–
50)
Lipset clearly saw economic development as giving rise to a more democratic political culture, partly through improved education. He also argued that
increased wealth reduces objective inequality, weakens status distinctions and
increases the size of the middle class. Lipset quotes de Tocqueville’s point that
‘only those who have nothing to lose ever revolt’, and goes on to say that a
‘large middle class tempers conflict by rewarding moderate and democratic
parties and penalizing extremist groups’. Moreover, ‘if there is enough wealth
in the country so that it does not make too much difference whether some redistribution takes place, it is easier to accept the idea that it does not matter greatly
which side is in power’ (Lipset, 1960: 66). Wealth also generates income and career alternatives to positions in the state. This reduces the incentives for nepotism, which is a severe hindrance to the development of the efficient bureaucracy a modern democratic state requires. Finally, Lipset argued that the intermediary organizations that form de Tocqueville’s civil society are associated
with national wealth. These organizations are important for the development of
democracy as they stimulate political interests, enhance their members’ political
and organizational skills, and check and balance the power of the state.
Lipset demonstrated that there was empirical foundation for this hypothesis – a finding that has been corroborated in a series of studies (see Diamond,
1992 for a comprehensive review). The correlation between democracy and development seems well confirmed. The most rigorous test of the ‘development
gives rise to democracy’ hypothesis has been provided by Burkhart & LewisBeck (1994). They analyzed annual observations of 131 nations in the period
1972–89. Controlling for ‘world system position’ (cf. Wallerstein, 1974) and past
values for democracy, they concluded that development is related to democracy. The substantial importance of this finding may have been overstated,
Chapter 4: Development and Asymmetry
49
however, since the variation over time in regime type within countries is very
small (Gleditsch, 1999; Przeworski & Limongi, 1997). In fact, Gleditsch (1999: ch.
7) argues that geographical diffusion is of substantially greater importance than
economic development.
However, many have questioned the direction of causation: does economic
development lead to democratic political regime, or is it that democratic political regimes are conducive to economic development? Burkhart & Lewis-Beck
(1994) tested this counter-argument using Granger’s causality tests and concluded that ‘the causal arrow most probably runs from economic development
to democracy, rather than vice versa’. Londregan & Poole (1996: 28) reached the
same conclusion, although with the caveat that ‘the democratizing effects of income are modest’.
In sum, there is considerable support for the idea that economic development is a ‘requisite to democracy’, as Lipset has termed it. It is then necessary to
ask whether development is a ‘requisite’ to the democratic peace, just as I have
pointed out for the trade and peace hypothesis.
4.2
Asymmetrical Relationships and the Liberal Peace
If symmetric dependence is a double-edged sword, may asymmetric dependence be a sword in the hands of the stronger party? At the very least, some argue, asymmetric dependence will not reduce the probability of war. Others argue that uneven market power and unilateral vulnerability may create conflictuous situations if the strong power exploits this relation (see Barbieri, 1996a).
Asymmetry may be in terms of (military) power, the gains from trade, and level
of development. I will investigate these three aspects of asymmetry in the following sections.
4.2.1 Asymmetry in power
The symmetry of the trade relation involving two states is inextricably linked to
the power symmetry between them. If the asymmetry is due to one state being
much larger than the other, that state will normally also have a larger army and
superior military power. If the asymmetry is due to one state being richer than
the other, the developed state will usually have a military-technological edge
50
The Limits of the Liberal Peace
on the other. It is therefore necessary to inform the discussion of asymmetric
trade and conflict with a look at the debate on power symmetry.
The classic view on power symmetry is the balance-of-power theory, represented by scholars such as Morgenthau, Gulick, and Waltz.20 It states that if no
nation is allowed to acquire preponderant strength, the international system
will be peaceful, since this will maximize the joint uncertainty about the outcome and consequently make both sides unwilling to initiate conflict. If there
are more than two major powers in the system, they will tend to form alliances
such that the blocs are balanced in power. In this view, war is a result of a
power transition from the dominant nation in a system to a rising challenger. If
war is not the result, such power transitions tend to cause a rearrangement of
alliances that re-establishes the balance.
On the other hand, power-preponderance or hegemonic-stability theorists –
among them Organski, Kugler, Keohane, Kennedy, and Gilpin – stress that the
chances of a state misperceiving its power relative to the adversary’s are the
greatest if power is roughly equal. Power transition is crucial for the explanation of war for these theories as well: the probability of a system-transforming
war is highest when a challenger who is dissatisfied with the existing status quo
gains power relative to the dominant power(s) or hegemon. However, both
these theories are to some extent systemic – or at least restricted to major powers – and therefore not directly applicable to the dyadic hypotheses explored
here.
The balance-of-power theory is essentially realist in seeing the quest for
power (which is equal to security) both as the motive for action and the determinant of success. The ‘expected utility framework’ developed by Bruce Bueno
de Mesquita and David Lalman (Bueno de Mesquita, 1981; Bueno de Mesquita
& Lalman, 1992) allows evaluating balance-of-power and power preponderance
theories while also accounting for motives other than power on the part of the
nation. Their framework is also useful since it applies to bilateral and minorpower wars as well as to large-scale wars.
20
See de Soysa, Oneal, & Park (1997: 511) and Bueno de Mesquita & Lalman (1992: 182–188) for
short introductions to these theories.
Chapter 4: Development and Asymmetry
51
Since leaders invariably face uncertainties when deliberating whether to go
to war, they will have to compare the utility they expect to gain from war to the
utility they expect from not initiating a war. Bueno de Mesquita & Lalman place
the choice of initiating war within an ‘international interaction game’ (1992: 30).
This sequential game starts with nation A (the challenger) choosing to make a
demand or not. Nation B (the defender) chooses between acquiescing to the
demand or making a counter-demand. If both nations make demands, the game
reaches the crisis subgame. Here, both nations have the option to use force to
back their claims or not. War is the outcome if both choose to use force, capitulation the outcome if only one uses force, and negotiation the outcome if neither
uses force. The expected utility maximization, then, will take the form of
choosing the strategy with the greatest expected utility, given that they are
playing subgame perfect strategies (p. 40). The expected utility from a war is a
function of the utility of the demands, the probability of winning the war, and a
set of costs associated with the use of force. The probability of winning the war
is a function of the power ratio between the two states.21
An important finding in this book is their ‘negotiation/status quo theorem’
(Bueno de Mesquita & Lalman, 1992: 60–64): ‘Under full-information conditions
and with demands being endogenous to the international interaction game,
only negotiation or the status quo can be an equilibrium outcome of the realpolitik variant of the game’. If the states are free to choose a demand that
maximizes expected utility, war will be an equilibrium outcomeonly if the
states are uncertain of the probabilities of winning the war. Moreover, Bueno de
Mesquita & Lalman proceed to show that under uncertainty conditions, both
states’ subjective probability of winning has to be larger than 0.5 for war to be
an equilibrium outcome. This is consistent with the realist balance-of-power
theory. However, they find that these conclusions lack empirical support: Wars
do occur when the subjective probability of winning is less than 0.5 (p. 70), and
when there should be little uncertainty (p. 66). They had to change their model
to reconcile it with the empirical observations: war may be explained only if one
21
Distance between the states also affects the probability of winning a war. This is discussed in
Bueno de Mesquita (1981: 40–44), but plays no role in War and Reason.
52
The Limits of the Liberal Peace
assumes that demands are made exogenously to the international interactions
game.
In their ‘domestic politics’ games, Bueno de Mesquita & Lalman assume
that the magnitude of state i’s demand is determined by domestic political processes, possibly without any foreign policy considerations. Their domestic-basic
war theorem suggests a more nuanced picture of the relationship between
power symmetry and war:
For any probability of success for A or B, there is a feasible mix of costs and benefits such
that war is possible. There are situations, such as those involving large stakes and small
expected costs, in which A, the challenger, can initiate the use of force even though it expects to lose (Bueno de Mesquita & Lalman, 1992: 199).
As an example, Bueno de Mesquita & Lalman (1992: 200–202) mention the
dispute between India and China over the McMahon Line in 1962. Even though
India was militarily inferior, Nehru dismissed China’s offer to negotiate, and
tried to force China to acquiesce. In the eyes of the Indian government, the conflict had high stakes and low expected costs, since they expected China to back
down rather than using its military strength to settle the issue. After a series of
Indian military advances, however, China struck back and won a decisive victory.
However, Bueno de Mesquita & Lalman find that war is most likely when
there is power symmetry, especially if the wars are expected to be costly: ‘In
disputes in which sides A and B each believe that its probability of success is
greater than 0.5, there is a disproportionate tendency for the dispute to end in
warfare’ (p. 204). Bueno de Mesquita & Lalman test this proposition and find it
to hold very well, even when controlling for systemic power variables (pp. 205–
212).
All in all, Bueno de Mesquita & Lalman’s model suggests that asymmetric
dyads should be less prone to escalate conflicts to war since the outcome of
such a war is so evident. When there is little uncertainty, states should prefer
negotiation. In the next section, I will investigate whether the same conclusion
is warranted in my model.
Chapter 4: Development and Asymmetry
53
4.2.2 Power asymmetry in the deterrence model
Power asymmetry affects the probability of winning a war and the costs borne
in such a war. If one of the two states is larger than the other in terms of population and resources, it will have greater chances of winning a military contest.
Likewise, a state that is technologically more advanced and better organized
will also be likely to prevail. Finally, a state that is more militarized than the
other, or that can draw on a more powerful military alliance, will also have the
upper hand in a conflict.
In contrast to Bueno de Mesquita & Lalman (1992), I see the cost of war as
independent of the probability of winning.22 In many cases, a state may win a
war because it suffers less costs than its opponent. This implies that the costs of
war are inversely related to the probability of winning. In other cases, however,
one state may win precisely because it is willing to suffer more costs than its
opponent. This implies that the probability of winning may be proportional to
the costs of fighting. In the absence of an unambiguous theoretical idea for the
relationship between the two variables, I will treat the cost term as a separate
variable.23
The impact of power asymmetry for the outcome of the game may be read
out of Figure 4–1, which is a simplification of Figure 3–3.24 An increase in p (the
probability that Aggressia will win) moves the pbA − k A threshold to the right
on the horizontal axis, while moving the (1 − p )bD − k D threshold downwards.
22
Bueno de Mesquita & Lalman weight their cost terms by the subjective probability of gaining
welfare (i.e. of winning). For instance,
α i (1 − Pi ) is the expected cost borne by the attacker for
fighting away from home in a war. (Bueno de Mesquita & Lalman, 1992: 40–41)
23
As shown below, the effect of asymmetry in the costs of war is similar to that of power asym-
metry.
24
Using Figure 4-1 to solve the asymmetric game is valid if the orderings of the threshold values
along the two axes are similar, e.g. that
Both these always hold.
b
bD
> pbD − k D and A > pbA − kA for all values of p.
rD
1− rA
bD
is always larger than bD since 0 < rD < 1, and pbD − k D is always
rD
smaller than bD since p < 1 and –kD always is negative . Both –bD and –kD are negative, such that
54
The Limits of the Liberal Peace
With increasing p, Area I changes to a lower and wider shape. Just as this may
or may not increase this area, it may or may not increase the probability of war.
Increasing asymmetry in terms of the costs of war in Aggressia’s favor (i.e. increasing kD and decreasing kA) causes the thresholds to move in the same manner. Area I changes shape correspondingly.
Figure 4-1. Effects of Asymmetry for Equilibrium Outcomes for Various Intervals of Ti
Relative to bD and bA, Relevant Areas Only
TD relative to bD
[Sanctions are not sufficiently
serious]
[Sanctions are
sufficiently serious]
IV: Uncontested use of force
(TA + bA , TD − bD )
V: Status quo
(TA , TD )
I: War II: Status quo
(TA , TD )
 pbA − k A , 


 − pbD − k D 
III: Status quo
(TA , TD )
[Only the threat of
sanctions is credible]
Thr 3 : (1 − p )bD − k D
[Both threats are
credible]
Thr 4 : pb
A
− kA
Thr 1 :
bA
1 − rA
TA relative
to bA
Payoffs: (Aggressia, Deterristan)
The probability of the war outcome is highest when the war area is largest,
that is when it is quadratic. If bA=bD and kA =kD, the area is quadratic when
p = (1–p), and this is the value for p with the highest probability of war. This is
consistent with Bueno de Mesquita & Lalman’s conclusion that war is most
likely under power parity (see section 4.2.1). War is actually not a possible outcome of the model if either Threshold 3 or Threshold 4 is less than zero, i.e. if
the first inequality holds. The second inequality also holds, since
pbA − kA < bA since p < 1 and –kA is negative.
bA
> bA as long as rA < 1, and
1− rA
Chapter 4: Development and Asymmetry
(1 − p )bD − k D < 0 ⇔ p > bD − k D
bD
or pbA − kA < 0 ⇔ p <
55
kA
. This argument is reflected
bA
in the following hypothesis:
Hypothesis 6: The more asymmetric a pair of states is in terms of power, the lower is the
probability of war
The probability of winning also affects the probability of ending up in area
IV in Figure 4–1. The higher p is, the lower will Threshold 3: The stronger Aggressia is, the higher is the probability that it will bully Deterristan. As noted
above, there is a risk that this outcome will be counted as a war. This probability depends on the nature of the contested issue. Note that increasing the trade
level when in this range can do nothing to reduce this probability. A similar
reasoning applies if p is so low that Threshold 4 is close to or less than zero. If
Deterristan is sufficiently strong, Aggressia will never challenge the status quo,
and neither war nor uncontested use of force will be an outcome. The level of
trade is then irrelevant. This allows me to formulate another hypothesis on the
relationship between power asymmetry, trade, and war:
Hypothesis 7: The more asymmetric a pair of states is in terms of power and/or the costs
of war, the weaker is the relationship between trade and war
4.2.3 Asymmetry in the value of bilateral trade
Investigating asymmetry in the value of the dyadic trade relationship is even
more pertinent to the general question in this thesis. Albert Hirschman’s National Power and the Structure of Foreign Trade (1945/1980) provides a useful
starting-point for handling the question of trade asymmetry. In order to illustrate Nazi Germany’s use of trade as a means of power, he provided a recipe for
using foreign trade as an instrument of national power (pp. 13–35). In addition
to the supply effect (see section 2.4.1 above, p. 14), foreign trade may become a
direct source of power through its influence effect. A country A has a large potential for influence when it is difficult for B to dispense entirely with its trade with
A, or to replace A as a market and a source of supply with other countries (p.
17). This difficulty depends on the total net gain to B of its trade with A, the
length and the painfulness of the adjustment process which A may impose
56
The Limits of the Liberal Peace
upon B by interrupting trade, and the strength of the vested interests which A
has created by its trade within the economies of B (p. 18). As for all power, influence through trade is a relative power: A has potential power over B if A suffers less from these difficulties.
The total net gain of the bilateral trade to B will be higher, the larger its
share of B’s total trade. It is also larger, the more inelastic B’s demand for A’s
goods is. To maximize its influence, A might have an interest in altering the
terms of trade in B’s favor, since a ‘country which gains much from the exchange … may be maneuvered more easily into concessions … than a country
for which trade is only barely profitable under existing conditions’ (pp. 20–23).
Ceteris paribus, large countries have economic power relative to small countries because bilateral trade makes up a larger share of the small country’s trade
than the large country’s. This tends to make it more difficult for the small country to dispense with such trade, since the net gain is larger. Moreover, shortterm adjustment costs are higher because it takes longer to divert a large fraction of a state’s total trade to other markets than is the case for a small fraction
(pp. 30–31).
Likewise, rich countries have economic power relative to poor countries.
According to Hirschman, Alfred Marshall applied the law of the diminishing
marginal utility of income to argue this:
The rich country can with little effort supply a poor country with implements for agriculture or the chase [sic] which doubled the effectiveness of her labor, and which she could
not make for herself; while the rich country could without great trouble make for herself
most of the things which she purchased from the poor nation or at all events could get
fairly good substitutes for them. A stoppage of the trade would therefore generally cause
much more real loss to the poor than to the rich nation. ( quoted in Hirschman, 1945/1980:
24; Marshall, 1923: 168)
Moreover, adjustment is more difficult the more concentrated the production of exports is in certain products or in certain regions: ‘If most of the exports
are made up of one particular product, there is very little probability that any
great part of it can be consumed at home if the foreign outlet fails; if the exports
all come from certain specialized regions within the country, there will be ‘distressed areas’ and a need for large-scale relief and resettlement’ (p. 28).
Chapter 4: Development and Asymmetry
57
On the basis of this theory of economic power relationships, Hirschman
summarizes policies that will increase national power (pp. 34–35). He then goes
on to show how Nazi Germany used such policies in the late 1930s. Many of
Hirschman’s points have been taken up by the dependencia school. I will return
to a few representatives of this school below.
What does Hirschman’s argument imply for the probability of militarized
conflict in dyads with an asymmetric trade relationship? It does not follow from
Hirschman’s discussion that the potential for use of economic power in an
asymmetrical relationship changes the likelihood of militarized conflict in the
pair of states. While referring to the idea that trade may supersede war since it
is an alternative way of gaining access to resources, Hirschman points out that
‘commerce can become an alternative to war also … by providing a method of
coercion of its own in the relations between sovereign nations’ (p. 15).
Polachek, Robst & Chang (1999) extend Polachek’s (1980) model to show
that ‘an increase in the price of exports to a larger country decreases conflict
more than an increase in the price of exports to a smaller country’ (p. 415). This
reflects Hirschman’s argument, and leads Polachek, Robst & Chang to conclude:
Since relatively small targets have less of an influence on domestic consumption in a large
actor, increased trade gains result in a greater reduction in conflict for a small actor than a
large actor trading with a small target. The model predicts that a country’s ability to influence domestic consumption in a trading partner is an important determinant of conflict
(1999: 416)
Wagner (1988) dismisses Hirschman’s (and, by extension, Polachek’s) idea
that political influence in a pair of states is related to the degree of symmetry.
Clearly, the asymmetry described by Hirschman affects the terms of trade.
Wagner uses a simplified example to illustrate his point (pp. 468–469): Two individuals are bargaining over how to divide a sum of money between them.
Both have declining marginal utility for money. Bargainer 2 is poor, meaning
that the utility of one unit of money is higher for him than for Bargainer 1. This
is analogous to Hirschman’s saying that the net gain of bilateral trade is higher
for the poor or small country. In addition, Bargainer 2 has a more urgent need
for the money. Since the money will not be available to any of them before they
58
The Limits of the Liberal Peace
have reached agreement, the most patient bargainer has an advantage. This is
analogous to the adjustment costs discussed above.
In this asymmetric relationship, the poor bargainer will settle for less than
half of the money. The degree of symmetry affects the terms of trade, as
Hirschman implies. But Wagner does not agree that this leads to political influence. If the stronger bargainer (Bargainer 1) demands that the other party must
agree to support him on some political issue, this ‘decreases the utility gain to
Bargainer 2 from agreement rather than increases it, while it increases the utility
gain to Bargainer 1’ (p. 469, emphasis in original). The political demand changes
the division of money in Bargainer 2’s favor. Bargainer 1 cannot force Bargainer
2 to change his behavior without fully compensating him for the resulting loss
in his utility (pp. 470–471). Bargainer 1 will be willing to do this only if he places
a higher monetary value on this change than Bargainer 2. If Bargainer 1 place a
lower monetary value on the change, he will not be willing to offer the other
party a payment that is sufficient for Bargainer 2 to agree to a change in his behavior. Of course, if one party has refrained from exploiting its bargaining
power, this may be used as a threat to induce the other party to change its behavior. But this is in fact just a threat of withdrawing a subsidy and does not
require an asymmetrical relationship to work. Wagner concludes that
… asymmetrical economic interdependence does not imply that the less dependent actor
will be able to exercise political influence over the other. […] The use of economic interdependence for political influence requires, instead, that the exchange of economic resources
for political concessions make both parties to a relationship better off than they would be if
they bargained over the distribution of the gains from the economic relationship alone.
Whether this is true is entirely independent of the degree of asymmetry in the economic
relationship, or its direction (Wagner, : 481)
As mentioned above, such a bargain will result only if Bargainer 1 places a
higher monetary value on this change than Bargainer 2.
Snidal (1991b) further undermines the hypothesis that ‘asymmetric relationships are conflictive’ when extending his relative gains model (see section
3.3.2) to analyze cooperation between states of different size (there is nothing to
prevent us from equating cooperation with trade here). He argues that the absolute cooperative gains are equally distributed between states independently
of their relative size (pp. 714–715). He demonstrates this by means of a formal-
Chapter 4: Development and Asymmetry
59
ized argument based on the assumption of constant returns to scale. Then, even
though the USA is much larger than Canada, the value of their trade is equal:
‘On the one hand, the United States is 10 times the size of Canada, so each Canadian unit benefits from cooperation with 10 times as many U.S. units as does
each U.S. unit with Canadian units. On the other hand, 10 times as many U.S.
units benefit from cooperation’ (p. 715). Snidal stresses the difference between
absolute gains and gains relative to the domestic production, and consequently
acknowledges the differences in bargaining power pointed out by Hirschman:
‘In absolute terms, states have the same interest in cooperation regardless of
their respective sizes. Because the potential benefits of international versus domestic cooperation are proportionately greater for small states, asymmetric interdependence places them in a more vulnerable bargaining position’ (p. 715, my
emphasis).
Snidal assumes that the sum of states’ relative-gains concerns Σr is independent of the number of states n in the system, such that the average value for
the parameter is r/n (p. 716). Snidal then shows that the minimum discount factor for cooperation φ in a dyad is a function of the costs and benefits of cooperation, the actor’s overall concern for relative gains and its weighting of relativegains concerns in relation to the other state in the dyad. His model shows ‘that
neither the absolute nor relative sizes of two interacting states directly affect
their propensity to cooperate’ (p. 717).
However, size may affect relative gains weights: Large states may be more
concerned about relative gains when dealing with large states than with small
states, since the larger states pose larger threats than do the smaller. Likewise,
the relative gains concerns may be asymmetric also in asymmetric dyads, but in
the opposite direction of what one might expect: a small state may pay more
attention to relative gains in such interactions than the larger state. Snidal only
assumes that the sum of states’ relative-gains concerns Σr is independent of the
number of states in the system (and this assumption is perhaps not satisfactorily
justified), but the asymmetry in relative-gains concerns justifies the assumption.
If large states direct all their relative-gains concerns towards the remaining
large states, they will have to cooperate with the small ones.
60
The Limits of the Liberal Peace
If this argument holds, then the relative-gains argument is a reason for a
large state to forgo its bargaining strength and offer the small state more than
an equal share of the benefits. Snidal uses this to hold out the relative-gains argument as an alternative explanation for why hegemonic powers act benevolently (p. 720).
All in all, Wagner’s & Snidal’s arguments suggest that Hirschman’s conclusion – that asymmetric dyads are more conflictive than symmetric dyads – does
not hold up to scrutiny.
4.2.4 Gains from trade asymmetry in the deterrence model
According to Hirschman (1945/1980) and many of the structuralist school, the
state that is the least dependent on the bilateral trade may exploit this (see section 4.2.3 above). On average, the larger and/or the richer countries in a dyad
are the least dependent, he claims. Wagner (1988), however, argues that the
gains from trade are independent of their relative size. Bargaining over the
terms of trade will level out these differences before the conflict game starts.
Any asymmetry in the gains from trade is then due to one state refraining from
using its bargaining power. Asymmetries may also stem from differing expectations of trade in the future: one state may fear the other will cut off trade in the
near future, while the other state may be quite confident that the trade relationship will continue (cf. Copeland, 1996).
Disregarding the source of asymmetries in the gains from trade, what impact on the outcome of the game do such asymmetries have? To answer this, it
is useful to discuss the implications of altering the ratio of the gains from trade;
TD
. The relationship between Aggressia and Deterristan is asymmetric if this
TA
ratio is either high or low. Increasing
TD
from an initial trade level (where TD =
TA
TA) is equivalent to increasing TD and decreasing TA.
The effect of increasing asymmetry such that Deterristan becomes more dependent on bilateral trade than Aggressia is quite similar to the effect of increasing the probability that Aggressia wins the war. Consider Figure 4–1. The
diagonal line represents a perfectly symmetric case, where all parameters are
Chapter 4: Development and Asymmetry
similar for both states. Increasing
61
TD
will move the location of the two counTA
tries to the right and upwards. Such movements are suggested by arrows, perpendicular to the diagonal and pointing upwards. If they initially are located in
the area I (war), this will at some point lead them into the area IV (use of force).
If their initial position is in area II (status quo), increasing the ratio will either
lead them into area I or area IV. A further increase will take them from area I to
area IV. If area III (status quo) is the initial location, the increase in
TD
will take
TA
the states to area IV, either through area II or area V (status quo). The increase
in asymmetry in this direction will have a slight tendency to reduce the probability of being in the war area, but increase the probability of being in the
‘uncontested use of force’ area.25
Likewise, a decrease in this ratio – such that Aggressia becomes more dependent on the bilateral trade relative to Deterristan – will change the strategic
situation from area IV to area III through areas I or V, from area I and II to area
III, and from area V to area III. Such movements are represented by downward
pointing arrows in Figure 4–1. In terms of probabilities, this means a slight reduction in the probability of being in the war area, and a considerable probability of being in one of the status quo areas.
The overall effect of asymmetry, then, is indeterminate. The increase in the
probability of uncontested use of force when increasing
TD
is fully offset by the
TA
increase in the probability of continued status quo when decreasing the ratio.
The net effect of asymmetry on the probability of war is the slight decrease in
the probability of being in the war area in Figure 4–1. The trade-asymmetry hypothesis, then, closely resembles the correspondinghypothesis for power
asymmetry:
Hypothesis 8: The more asymmetric a pair of states is in terms of gains from trade, the
lower is the probability of war. This relationship is weaker than the corresponding
for power asymmetry.
25
As noted in section 3.2.3 above, this discussionis sorely lacking a secure method for translat-
62
The Limits of the Liberal Peace
To the extent that an increase in asymmetry increases the likelihood of being in areas IV and III, the probability of war becomes less dependent on the
trade level. For a highly asymmetrical relationship, the gains from to trade are
likely to be greater than Threshold 3 even for very low levels of bilateral trade
(defined as the sum of the gains from trade for the two countries). Asymmetry,
then, weakens the liberal hypothesis:
Hypothesis 9: The more asymmetric a pair of states is in terms of the gains from trade,
the weaker is the relationship between trade and war
4.3
Asymmetric Development
The arguments in the preceding section assume that the relationship is symmetric. In asymmetric relationships, the effect of development may be different. The
volume of trade in a dyad will probably increase with increasing development
in one of the countries, even if the other is not developing. As argued above
(section 4.2.3), there is no secure foundation for Hirschman’s hypothesis that
asymmetric trade dyads are more conflict-prone than symmetric dyads. The
game-theoretical argument in that section implied that asymmetric trade dyads,
on average, have fewer wars than symmetric ones. At the same time, trade
might be a less important variable for explaining variance in conflict behavior
for these dyads. Do similar mechanisms apply for development asymmetry?
4.3.1 Rosecrance’s argument and asymmetry
Rosecrance’s ‘development increases the cost of war’ argument requires that
both states are developed: If increased costs of war are to restrain states from
going to war, both states have to be restrained. If a technologically advanced
state faces a less developed country, it will not be as constrained by the expected costs of the war as when facing another developed state. Moreover, the
economic costs of war are related to the political costs: citizens of developed
states may be unwilling to risk their lives and property in military adventures.
This concern is much weaker if the state is sufficiently powerful to ensure that
ing from game-theoretic results to probabilistic hypotheses, and thus remains partly intuitive.
Chapter 4: Development and Asymmetry
63
the war is fought out on the territory of the adversary. Moreover, an asymmetric access to advanced weapons systems significantly decreases the risk of dying on the battlefield. With superior technology, the horrors of war remain
somewhat abstract for the stronger side.
Thus, development in only one of the two countries will not constrain the
dyad as an entity from going to war. However, the fact that asymmetric development means asymmetric military power may influence the probability of
war. Above (see section 4.2.2), I concluded that the probability of war decreases
with increasing asymmetry, since the uncontested use of force or negotiations
(Bueno de Mesquita & Lalman, 1992) is clearly preferable to both parties if the
outcome of the contest is more predictable.
4.3.2 Structuralism, asymmetry, and war
Theories of structuralism also deal with asymmetric relationships. Wallerstein
(1974: 400–401) sees three structural positions in a world economy: core, periphery, and semi-periphery. To some extent through a series of accidents,
northwest Europe was the first to diversify its production and develop strong
state mechanisms. The region thus became the core of the modern world economy. In other regions, the interests of local groups did not converge in a way
that allowed the development of efficient states. This led to a self-reinforcing
structure of core and periphery: ‘Once we get a difference in the strength of the
state-machineries, we get the operation of ‘unequal exchange’ which is enforced
by strong states on weak ones, by core states on peripheral areas. Thus capitalism involves not only appropriation of surplus of the whole world-economy by
an owner from a laborer, but an appropriation of surplus of the whole worldeconomy by core areas’ (p. 401).
Wallerstein thus sees the relationship between developed (core) states and
underdeveloped (periphery) states as highly conflictive. To what extent will this
conflict assume a militarized form? It is inherent in the capitalist structure that
the state machineries of the periphery decline, he claims:
In peripheral countries, the interests of the capitalist landowners lie in an opposite direction from those of the local commercial bourgeoisie. Their interests lie in maintaining an
open economy to maximize their profit from world-market trade […] and in elimination of
the commercial bourgeoisie in favor of outside merchants who pose no local political
64
The Limits of the Liberal Peace
threat. [Secondly,] the strength of the state-machinery in core states is a function of the
weakness of other state-machineries. Hence intervention of outsiders via war, subversion,
and diplomacy is the lot of peripheral states (p. 403).
However, if the capitalist landowners secure the power in peripheral states,
war and subversion is not necessary. This is a central point in Galtung’s concept
of structural imperialism (1971). Structural imperialism ‘is a relation between a
Center and a Periphery nation so that (1) there is harmony of interest between the
center in the Center nation and the center in the Periphery nation, (2) there is more
disharmony of interest within the Periphery nations than within the Center nations, (3) there is disharmony of interest between the periphery in the Center nation
and the periphery in the Periphery nation’ (p. 83, emphasis in original). This allows the Center nation to exploit the Periphery nation without military means:
‘Only imperfect, amateurish imperialism needs weapons; professional imperialism is based on structural rather than direct violence’ (p. 91, emphasis removed). It is not certain, then, that development asymmetry is connected to
higher probability of militarized conflict.
A more serious challenge to the liberal hypothesis is posed by the structuralist argument of ‘unequal exchange’. Wallerstein sees this as a result of differential state power. Galtung’s more sophisticated conception is directly relevant to differences in development. Unequal exchange (or exploitation) is due
to asymmetry in intra-actor effects. When manufactured goods are exchanged
for raw materials, the producer of manufactured goods obtains far more
spinoffs than the raw materials exporter: In the developed center nation, new
means of productions may be developed, the central political position is reinforced, military capabilities are enhanced through increased industrial capability, the development of skills, education, and research is enhanced, etc. In the
periphery nation very little is developed; for instance, Galtung argues that ‘just
a hole in the ground’ is needed to extract oil, (1971: 87).
Krugman (1981) paints a similar picture in an economic model of how
wealth is accumulated in the larger, richer party to a trading relationship if
there are increasing returns to scale: Investment will flow to the developed state
since it is more profitable there, more investment will in turn lower the cost of
producing manufactures and depresses the international price of manufactures,
Chapter 4: Development and Asymmetry
65
and the end-point of this accumulation process is that nearly all the manufacturing will take place in the rich world (see also Krugman & Venables, 1995).
If the logic of unequal exchange holds, trade between rich and poor states
will benefit the rich country disproportionally. Trade should then have little restraining effect on the poor country’s propensity for military action. This, however, is offset by the structuralist idea that it is the elite in the periphery nations
who actually profits from the trade relationship, and at the same time control
the military apparatus of the periphery nation. The conclusion to draw from
this for my purposes is again very uncertain, but there seems reason to believe
that the beneficial effects of trade are very slight in rich–poor dyads.
4.3.3 Asymmetric development in the light of the deterrence model
The discussion above implies that asymmetry in development affects all the
following parameters in the game-theoretical model. Development asymmetry
increases the probability that the more developed state wins – p is larger if Aggressia is the more developed, p is smaller if Deterristan is the more developed.
Development asymmetry increases the costs of war ki for the less developed,
and decreases them for the other. In the symmetric case, I argued that increased
development tends to increase the gains from trade Ti and to reduce the utility
of using force bA for Aggressia. If only one of the states develops, this change
will affect only that state, and not the other one.
The effect of these changes may be explored with the help of Figure 4–1: Increased development in Aggressia will affect Threshold 4 by increasing p and
decreasing kA and bA. The sum of these changes is indeterminate since they shift
the threshold in opposite directions. The increased development will lower
Threshold 1 through the reduction of bA, and unambiguously lower Threshold 3
since (1–p) and –kD come closer to zero. The net effect of this is indeterminate,
since area IV becomes higher but more narrow, and area I becomes lower but
may become either wider or more narrow.
Increased development in Deterristan will have the opposite effect on
Threshold 3, moving it upwards. Threshold 4 will move to the right, since both
p and –kA will be reduced. Threshold 1 will remain unchanged. Area I will become more narrow, but higher. The net effect of this on the probability of being
66
The Limits of the Liberal Peace
within the area will depend on the initial shape of area I – if it was quadratic,
the probability will decrease; if not, it will increase.
All in all, the conclusions drawn from this are far less clear than in the
symmetric case. There will still be a point where trade relative to the utility to
Aggressia of using force is so high that it will not pay to challenge the status
quo. But the increased probability of winning the war, and the lower costs attached to this, will make it harder to pass that threshold. However, that aggression will be likely to take the form of uncontested use of force, which I have assumed have a low, constant probability of being classified as war. All in all, the
following hypothesis seems warranted:
Hypothesis 10: The relationship between development and the probability of war is
weaker the more asymmetric the dyad is in terms of development, but is never negative
Chapter 5
Research Design
I
n Chapter 3, I argued that it is tenable to assume that trade causes peace,
and not vice versa. Consequently, the research design here involves a single-equation statistical method. I begin this chapter by discussing the
most appropriate method to use.26 The remainder of the chapter focuses on the
operationalization of the variables described in Chapters 3 and 4.
5.1
Statistical Problems and Methods
5.1.1 Dependency between units and inconsistent censoring
Oneal & Russett (e.g., 1997; 1999) and Barbieri (1996a) follow the lead of the
‘dyad-year tradition’, common in the study of international relations since
Bremer (1992) and Maoz & Russett (1993). In this tradition, the basic idea is to
count the number of dyad-years in dispute and in peace. It is assumed that all
dyad-years are independent (when we condition on the explanatory variables).
If this is tenable, the dispute status of the dyad-years become conditionally independent random variables. Bremer points out two problems with this assumption. Firstly, when a dyad is at dispute for more than one year, the counts
of ‘dispute’ in the subsequent years are dependent on the first. Secondly, once
an interstate dispute has started, other states may join it. Hence, one dyad dispute can cause other dyad disputes, and the latter will be dependent on the
first.
Here I will ignore the problem of ‘joining dependence’, even though I earlier (Raknerud & Hegre, 1997) demonstrated that this is a severe problem for
studies of large-scale, multi-party wars. The dependent variable in the present
study includes disputes with a low number of fatalities (see section 5.7), and is
restricted to the post-World War II period. Consequently, the share of disputes
26
Section 5.1 is adapted from Raknerud & Hegre (1997: 386–390).
68
The Limits of the Liberal Peace
that do not involve joining is much higher than was the case in Raknerud &
Hegre (1997), so the problem of joining dependence is correspondingly reduced. The standard errors and significance probabilities reported in Chapter 6
is therefore slightly under-estimated. To counter this bias, I will report twosided tests although one-sided tests would be appropriate for all hypotheses.
Bremer and Maoz & Russett diverge on the issue of including the dyadyears of conflict that follow the first if a dyad dispute continues over several
years. Bremer (followed by Barbieri, 1996a; 1996b) count only the first year;
subsequent dyad-years of dispute are removed from the dataset. Maoz & Russett (1993) count all dyad-years of disputes as independent observations, and
continue to do so in some of their studies of the liberal peace (e.g., Oneal et al.,
1996; Oneal & Russett, 1997).
Neither solution is satisfactory. Not only will an ongoing dispute lead to
dependent counts of ‘dispute’, but a continuing peace will lead to dependent
counts of ‘peace’ as well. If we are to censor continuing disputes, why should
we not censor continuing peace? Maoz & Russett (1993: 631) are aware of this
problem, and choose to count all dyad-years of the disputes, even if the responses are clearly dependent. They realize that the root of the problem is that
the ‘true’ model is one of dependent response, no matter whether that response
is ‘dispute’ or ‘peace’. It is difficult to assess how this dependence will bias the
estimates, but it will certainly lead to deflated p-values when statistical hypotheses are to be tested. This situation is similar to distributing a questionnaire
to a sample of N individuals twice and then treating the responses as coming
from 2N different individuals. My answer to these problems is to model dispute
origination and dispute-joining simultaneously – as causally related events in a
statistical event-history model.
The problems with the dyad-year tradition fundamentally derive from
statistical dependence: a dispute in another dyad or in the same dyad in the
past may alter the probability of dispute in other dyads. To some extent these
problems can be handled within the framework of the dyad-year approach. One
option is to include explanatory variables containing information about ongoing disputes. In general we may condition on all relevant historical information,
i.e. information known prior to year t, and this would fit naturally into the
Chapter 5: Research Design
69
dyad-year framework. This is also recognized by Beck & Tucker (1997), who
propose modeling the probability of outbreak of dispute as a function of the
duration of peace.
Since the start and end of wars and disputes are identified by date in the
Correlates of War data, Raknerud & Hegre (1997) suggest using a continuoustime model. Of course, all time measures are discrete, but with a finer scale a
continuous-time model becomes more realistic. In ‘continuous’ time, the history
contains all information up until day t. We will then be able to observe the succession of dispute outbreaks accurately, and the problem of dependence
through causality can be more adequately accounted for.27
In a continuous-time model, the dyadic observations at t could become conditionally independent – and thus amenable to statistical analysis – and still remain highly interrelated (through dependence on a common history). Furthermore, information about ongoing disputes as well as other circumstantial evidence relevant for classifying a dispute (like starting or joining) can be incorporated into the empirical model.
Some of the time-dependent variables are measured by year. In these cases,
we follow common practice in event-history analysis and treat them as step
functions, i.e. constant through the year. This does not invalidate our argument
for a continuous-time model. The reason is that, if we employ a coarser grid,
with e.g. the year as (a discrete) time unit, we are unable to make use of relevant information. On the other hand, when we treat variables observed annually as constant through the year, no information is lost; the available information may just be less than desirable.
5.1.2 An alternative model: Cox regression
Thus, the approaches of Barbieri (1996a; 1996b) and Oneal & Russett (1997) suffer from serious inadequacies and inconsistencies. An ‘ideal’ model should have
the following features:
27
However, this does not hold if a state declares war against several states on the same day,
which is an example of a ‘tie’ – a truly simultaneous event. A ‘solution’ to the ties problem is
discussed in the Appendix of Raknerud & Hegre (1997); that is also the solution used here.
70
•
The Limits of the Liberal Peace
observations on dyads should be recorded on the finest possible time-scale
to keep track of the succession of events,
•
the dispute probabilities of low-relevance dyads should depend on the
number of states in the international system,
•
the model should allow for non-stationarity due to changes in latent variables at the system level.
Below, I will argue that a Cox regression model addresses these three concerns.
In this section I present the general idea of Cox regression, and relate the parameters of the model to logistic regression to facilitate comparison with the
existing literature. The Cox regression model was proposed by Cox (1972);
good introductory descriptions can be found in McCullagh & Nelder (1989) and
Collett (1994).
In Cox regression, the dependent variable is the transition between ‘states
of nature’ – the transition from peace to dispute (or vice versa) being of this
type. A central concept is the hazard function, λ (t ) , which is closely related to
the concept of transition probability: λ (t )∆t is approximately the probability of
a transition in the ‘small’ time interval (t , t + ∆t ) given that the subject under
study is at risk of transition at t. In our case, the subjects under study are all the
different interstate dyads, and t is calendar time. We study the transition from
peace to dispute; a dyad that risks transition has a non-zero probability of dispute – i.e. it is a system member28 and not already at dispute. Basic to Cox regression is the assumption that the hazard of dispute λd (t ) for dyad d can be
factorized into a parametric function of (time-dependent) variables and a nonparametric function of time itself (the baseline hazard):
p
(1)
λ d (t ) = α (t ) exp( ∑ β k X kd (t ))
k =1
In (1) α (t ) is the baseline hazard: an arbitrary function of calendar time reflecting unobserved variables at the system level. X k d (t ) is a (possibly timedependent) explanatory variable for dyad d; β k is the corresponding regression
coefficient; and p is the number of explanatory variables. All legitimate explana28
That is, the dyad is formed by two states that are both system members at time t.
Chapter 5: Research Design
71
tory variables are known prior to t – they must be a part of the history up until
immediately before t.
Estimating this model involves both estimation of the regression coefficients β = ( β 1 ,..., β p ) and estimation of the baseline hazard of dispute α (t ) .
These two tasks are quite different, since the latter is an unknown function – not
a parameter. However, for the specific purpose of inference about the democratic peace, we are mainly interested in the ‘structural’ parameters β . Inferences about β can efficiently be made by conditioning on the time-points of
outbreaks of dispute, {t1 ,...., t n } . This means that we can consider {t1 ,...., t n } as
fixed rather than stochastic, without losing any information about the parameters.
Given that there is an outbreak of dyad dispute at time tw, the probability
that this dispute outbreak will happen in dyad d is:
p
(2)
Pr( war in dyad d | a war breaks out at t w ) =
exp( ∑ β k X kd (t w ))
k =1
∑
i∈Rt w
p
exp( ∑ β k X ki (t w ))
k =1
where Rtw is the risk set at tw: the set of dyads that are at peace immediately before tw. The parameters β can be interpreted in terms of a relative probability of
dispute. Assume that dyad i and j have the same values on all explanatory variables, except for X k (t ) . Then, from (1), the ratio between the hazard of dispute
of dyad i and dyad j becomes
(3)
λ i (t )
= exp( β k ( X ki (t ) − X kj (t ))) .
λ j (t )
Hence we have
ln
λ i (t )
= β k ( Xki (t ) − Xkj (t )) .
λ j (t )
We may therefore interpret the parameter β k as follows: β k is the log of the
relative risk between two dyads which are identical, except for the variable Xk (t )
which differs with one unit. This interpretation may be compared to the interpretation of the parameters in the logistic model. Let p i (t ) be the probability of
dispute at time t assigned by the logistic model for dyad i:
72
The Limits of the Liberal Peace
p i (t ) =
1
p
~
~
1 + exp( − β 0 − ∑ β k X kd (t ))
k =1
Then, for the two dyads of the previous example, it follows by a standard
deduction that
 p i ( t ) 1 − p j (t )  ~
 = βk
ln j ×
i

−
p
(
t
)
1
p
(
t
)


~
i.e. β k is the log-odds ratio between dyad i and j – not the log-relative risk.
However, the probabilities of dispute p i (t ) and p j (t ) are typically both very
small when dyad-years are the observational units. Hence the term
1 − p j (t )
≈1
1 − p i (t )
and the log-relative risk is almost identical to the log-odds ratio. The conclusion
is that, for rare events like disputes, the parameters of the Cox model and the
logistic model have almost identical interpretations.
To perform an analysis with this model, we need a data file constructed in
the following way: For each tw – i.e. each day a dyad dispute breaks out somewhere – we take a ‘snapshot’ of the international system; we note, for all dyads
that are system members and not already at dispute, the values of the explanatory variables at that particular day. As is seen from expression (2), the dyad
that did erupt in dispute at tw is compared to all dyads that were at risk of doing
so. Thus, all information for the time between different tw’s is ignored. From the
combined information about all outbreaks in the period under study, we can
estimate β and hence the relative hazard (3).
The non-parametric part of the model, the baseline hazard α (t ) , contains
information about the distribution of the outbreak of disputes in the time dimension and may be of interest for some purposes. Efficient estimation of the
baseline hazard requires non-parametric estimation tools and smoothing techniques. However, we will not go into detail on this here.
5.1.3 Modeling temporal dependence: ‘Time in peace’ and ‘Past dispute’
The probability of peace between two states in the next period is durationdependent: The longer the peace has lasted, the greater the chances that it will
continue. Time is required to heal wounds and re-establish normal relations af-
Chapter 5: Research Design
73
ter an interstate conflict, and the creation of new states is often followed by tensions in the first period due to uncertainties in defining borders, etc. In the
‘Time in Peace’ variable I have recorded the number of days since the current
peace began (recall that all disputing dyads are excluded from the dataset). This
variable was transformed into a decaying function using the formula
 Days in peace 
Exp  −
 . γ was set to 3,162 to model the assumption that the hazγ


ard of a fatal dispute is halved every six years. The variable was coded from the
Correlates of War datasets on militarized disputes (Jones, Bremer & Singer,
1996) and on system membership (taken from the Peace Science Society website). When coding the variable, I made use of information from 1816 and onwards. This is in contrast to Beck, Katz & Tucker (1998) who only coded peaceyears from 1950 onwards. This is not a trivial difference, as information on the
alliance alignment of World War II is ignored in their analysis, as well as the
entry of new states in the system in the two decades before 1950 (e.g., India and
Pakistan).
If the peace was preceded by a fatal dispute between the states, we expect
the hazard of new dispute to be higher than if the peace started with one of the
countries gaining system membership. I include a variable called ‘Past Dispute’
to distinguish the two types from each other.
5.2
Temporal-Spatial Domain
The study covers the period 1950–92. The analysis is limited to an extension of
Maoz & Russett’s (1992) ‘high-relevance dyads’. All dyads that are two major
powers, allied, contiguous, or have inter-capital distance less than 3,000 km
were included.29
29
The inclusion of ‘low-relevance’ dyads with inter-capital distance up to 3,000 km means a sig-
nificantly larger spatial domain than the ‘high-relevance’ dyads. Still, only a quarter of all dyads
were included. The reasons for the limitation are purely technical. A dataset with 500,000 cases
is much more manageable than one with 2,000,000.
74
The Limits of the Liberal Peace
5.3
Operationalizing Interdependence
5.3.1 ‘Least dependent’ and ‘Salience’
Katherine Barbieri (1996a) argues for the use of dyadic trade flow (imports +
exports) between two states relative to total trade – ‘trade share’ – as a measure
of one state’s dependence on another. She combines the two trade share figures
into a measure of size of a trading relationship called Salience, defined as
Salienceij = TradeSharei * TradeShare j . Oneal & Russett (1997) suggest using the
dyadic trade flow relative to Gross Domestic Product as a measure of one
state’s dependence on the other. They use the value for the least dependent
state (i.e. the one with the lowest trade-to-GDP ratio) as their dyadic measure.
Their choice is based on the ‘weak-link assumption’ (Dixon, 1994). These two
measures are highly correlated, and yield comparable results when my trade
dataset is used (see Hegre, 1998 for a comparison).
Both measures vary with the size of the country’s economy. A given
amount of trade is less significant for a country with a large GDP than for one
with a small GDP. Since the amount of trade for any country is highly dependent on the size of its economy, the level of dependence is also dependent on the
size of the economy. Moreover, when we create a dyadic measure, the size of
the smaller state’s economy will set a ceiling on the larger country’s dependence. When Oneal & Russett’s ‘weak link’ formula is used, the larger country’s
dependence will, in most cases, be coded as the level of interdependence. The
same thing will tend to happen with Barbieri’s measure, although to a lesser
degree. This is potentially problematic, since the interdependence measure will
easily come to function as a proxy for country size. To see this problem, consider the USA: in the entire period studied here, it was by far the largest economy in the world. In all the dyads of which it is part (except for US–Japan, US–
Canada, and US–Germany), the value for ‘least dependent’ is extremely low.
The USA has made use of its military power in a large number of militarized
disputes. Is this because it is economically independent, or because it is a military superpower? Disputes with the USA form a large portion of the MID dataset. To what extent does this affect the study of the trade and conflict relationship?
Chapter 5: Research Design
75
Another problem with the two measures is that their distributions are extremely skewed to the right (cf. the summary statistics in Appendix 2). This creates difficulties in interpreting the results from a generalized linear model
analysis. To minimize this problem, I log-transformed the Salience measure. Zeros were handled by adding 0.02 to all values. The interpretation of the parameter estimates for the variable then changes. Rather than estimating the effect on
the dependent variable when adding one unit to the interdependence variable, it
estimates the effect of multiplying the variable by the natural number e ≈ 2.7. In
other words, the parameter estimates the change in the relative risk of fatal dispute if the bilateral trade is increased by the factor 2.7.
To ensure comparability with previous studies, I compiled Oneal & Russett’s trade-to-GDP ratio and Barbieri’s Salience measure on the basis of my
own trade dataset. These variables were scaled to range from 0 to 100, and
should be interpreted as the value of the dyadic trade as a percentage of GDP.
5.3.2 Level of interdependence as deviation from ‘expected trade’: The gravity model
The contamination of relative size in the interdependence variable is partly
solved by entering a control for relative size in the model. Still, it would be useful to have a measure of interdependence which was independent of the sizes of
the states in the dyad, absolutely as well as relative to each other. In the spirit of
Russett (1967: 123–125), this may be obtained by assessing how much trade we
might ‘expect’ in the dyad, and then measuring the deviation of the observed
trade level from this predicted level.
Once we have such a measure, the question of symmetry may be treated
through a measure of relative capabilities or relative size. This is more appropriate, since it is extremely difficult to disentangle the contribution of military
and political power preponderance from economic preponderance. With such a
measure of interdependence, a measure of relative size, and the interaction term
of these two variables, we may obtain more precise answers.
I will take an economic model of international trade as the point of departure for formulating a realistic zero model of trade in a dyad: How much trade
is to be expected in the dyad if political factors are not accounted for? The gravity model is an old model of human interaction, used extensively in geography
76
The Limits of the Liberal Peace
and regional science.30 One of the early applications of this model to study trade
flows was Linneman (1966), who modeled trade in a dyad ij as
tradeij =
GDPi * GDP j
dist ij
. Distij is usually measured as the geographical distance
between the capitals of the states. The model reflects that, ceteris paribus, states
will trade more with states with a large GDP than with smaller economies.
Likewise, states will trade more with neighboring states than with distant ones.
I will add contiguity to this model, since large countries may share a long border with extensive trade opportunities, although their capitals are located far
from each other.
The multiplicative gravity model is rendered linear when taking the logarithms
of
all
terms.
The
model
may
thus
be
formulated
as
ln (tradeij ) = α + β 1 ln (GDPi ) + β 2 ln (GDP j ) + β 3 ln (dist ij ) + β 4 contiguity ij + ε . This I
estimate by means of separate OLS regressions for each year, as the dependent
variable is at the interval level and probably assumes a normal distribution. The
data on bilateral trade, distance, and GDP are described below. Since the gravity model was estimated separately for each year, trade and GDP figures in current dollars were used. A summary of these analyses is reported in Appendix 3.
The residuals – the differences between the observed values minus the predicted values – from the OLS estimation of the gravity model of trade were
used as my measure of interdependence, henceforth called the ‘Gravity model
measure’ or GMM. Since the model is logarithmic, the measure is equivalent to
the natural logarithm of the trade observed in the dyad divided by the trade
predicted from the gravity model. The interpretation of the parameter estimate
for the GMM is similar to that for ln(‘Salience’) when it comes to comparing different trade levels for similar dyads: it estimates the change in the relative risk
of fatal dispute if the bilateral trade in the dyad are increased by the factor 2.7.
However, the two variables compare different dyads differently: Two distant
countries that trade just a little is regarded as non-interdependent by the ‘Salience’ measure, but may have a high score for the GMM.
30
The gravity model, originally developed in geography, has also been employed to study other
forms of international interaction (Gleditsch, 1968). Earlier applications of the gravity model to
study the trade/conflict issue are found in Gowa & Mansfield (1993), and Pollins (1989a).
Chapter 5: Research Design
77
The correlation with the other interdependence measures is r = 0.26 with
‘Salience’, r = 0.22 with Oneal & Russett’s ‘Least Dependent’ measure. The correlation with ln(‘Salience’) is higher, r = 0.63, which reflects the skewness in the
‘Salience’ variable. ‘Salience’ and ‘Least Dependent’ are correlated by r = 0.65 in
my compilation of the data.
5.3.3 Data sources for the interdependence measures
Like Oneal & Russett (1997) I use the International Monetary Fund’s Direction of
Trade (1997) data. This source was supplemented with Faber & Nierop’s World
Export Data, 1948–83 (1989, subsequently called WED), which has more comprehensive information on non-IMF members. The IMF dataset contains information on exports from state 1 to state 2 as well as imports to state 2 from 1,
whereas the WED data report exports only. There are considerable discrepancies between these three figures. To minimize errors, I calculated the average
between the three figures where all were available and reported as larger than
0.31 If one of three figures was missing or reported to be 0, I calculated the average of the remaining two. If two were missing or 0, the third was used. Finally,
if both sources reported 0 or missing data, I followed Oneal & Russett’s example in treating this as an instance of negligible trade. The smallest unit in the
IMF dataset is US $0.1 million. Any exports or imports less than $0.05 million
would be rounded down to 0. Consequently, I recoded all cases reported as
having zero trade to $0.02 million for the gravity model estimation, which is
approximately the average of all the rounded-down figures. When computing
the ‘Salience’ and ‘Least Dependent’ measures, I employed the original coding
of 0.
The information on trade level was lagged with one year to minimize
problems in assessing the direction of causality. Thus, for dispute outbreaks in
1950, the interdependence measures were calculated on the basis of trade figures for 1949.
31
The figures for imports were weighted down by the factor 0.96, the average exports/imports
ratio in the DOT dataset. This discrepancy is due to the reporting of imports as c.i.f. and exports
as f.o.b.
78
The Limits of the Liberal Peace
Data on GDP were taken from Penn World Table (Mark 5.6) (see Summers
& Heston, 1991). For the gravity model, the current dollar value of the GDP per
capita was used (the Penn CGDP variable). GDP was calculated by multiplying
the GDP per capita variable by the population variable.
Dyadic distance is defined as the beeline distance between the capitals of
the two states. I used the data computed for Gleditsch (1995).
5.4
Operationalizing Development
5.4.1 Development
I ran the analysis using two different indicators of economic development:
Gross Domestic Product per capita, and energy consumption per capita. Both
indicators were log-transformed, reflecting the view that the marginal effect of
development on conflict behavior is diminishing. As was the case for ‘Salience’,
the parameter estimates the effect of multiplying development by the natural
number e ≈ 2.7, or the change in the relative risk of fatal dispute if the bilateral
trade is increased by the factor 2.7. To create a dyadic measure I used the value
for the poorest country in the dyad. This follows the lead of Oneal & Russett
(1997: 275–276) who argue that the likelihood of conflict primarily is a function
of the degree of political constraint experienced by the least constrained state in
the dyad. They consequently use the trade dependence value for the state for
which the dyadic trade poses the lowest economy dependence, based on the
‘weak-link assumption’ (Dixon, 1994).
The source for GDP per capita is the same as above. Energy Consumption
data were taken from the Correlates of War Project.32
5.5
Operationalizing Regime Type
The regime-type variable denotes whether the dyad consists of two democracies, two non-democracies, or one democracy and one non-democracy (here
32
Data on energy consumption were taken from Eugene’s version of the Correlates of War Proj-
ect
dataset
on
national
capabilities,
found
on
the
EUGene
home
page:
http:
//wizard.ucr.edu/cps/eugene/eugene.html. Several missing cases in this dataset were filled in
by means of linear interpolation.
Chapter 5: Research Design
79
called ‘politically mixed dyads’), or whether one or both countries have missing
regime data or are coded as being ‘in transition’. Regime data were taken from
Polity IIId (Gurr, Jaggers & Moore, 1989; Jaggers & Gurr, 1995; McLaughlin et
al., 1998). A ‘democracy’ is defined as a country that receives a score of 6 or
higher on the Institutionalized Democracy index in Polity.
Oneal & Russett employ the lower score of the two countries in the dyad as
the corresponding control variable. I choose the categorical variable described
above instead, for several reasons. First, in the politically mixed dyads we find
higher dispute-proneness than in the non-democratic dyads (Beck & Jackman,
1998; Gleditsch & Hegre, 1997; Raknerud & Hegre, 1997). Oneal & Russett’s
measure does not account for this. The bimodal distribution of the democracy
variable allows this simplification without much loss of information. Moreover,
the categorical variable allows the inclusion of dyads where information on regime type is missing; these were omitted by Oneal & Russett.
5.6
Operationalizing Asymmetry
5.6.1 Power asymmetry
The ratio of the ‘military capabilities’ of two states may be employed as a measure of power asymmetry (or power preponderance). The most commonly used
index for capabilities is the Correlates of War Project’s military capabilities index (Singer, Bremer & Stuckey, 1972). This index gives equal weight to the
states’ total population, urban population, energy consumption, iron and steel
production, military expenditures, and size of the armed forces. I log-transform
this variable, too, to reflect the decreasing marginal effect of power preponderance, and call it ‘Capability Asymmetry’. The source for this variable is the
same as for Energy Consumption per capita.
To minimize the loss of information due to missing data, I also compiled a
measure of relative capabilities on the basis of the Penn World Tables (Mark 5.6)
(see Summers & Heston, 1991). This variable, which I call ‘Size Asymmetry’, is
based on the two countries’ population and GNP. The variable is calculated by
a formula that computes the geometric average between the ratios:
80
The Limits of the Liberal Peace
 GDPcountry _ 1 Populationcountry _ 1
Size Asymmetry = ln 
*
 GDPcountry _ 2 Populationcountry _ 2


 . The log transformation


reduces problems caused by outliers.
5.6.2 Asymmetry in the gains from trade
Barbieri (1995; 1996a; 1996b) define interdependence, or salience, as
Salienceij = TradeSharei * TradeShare j . The trade shares are the value of the bi-
lateral trade divided by state i and j’s total trade. This measure automatically
accounts for some asymmetry, since the product of a given sum of trade shares
is the highest when these are equal. In addition, Barbieri includes a measure of
symmetry: Symmetry ij = 1 − TradeSharei − TradeShare j . This measure has a severe
weakness, however, since the largest possible value for this measure depends
on the magnitude of the trade shares. The difference between them will be
larger, the larger TradeSharei is. To see this, consider a dyad where the bilateral
trade makes up 0.40 and 0.50 of the two countries’ total trade – both are heavily
dependent on each other. Barbieri’s symmetry measure is then 0.90. Then take a
situation where the bilateral trade as share of total trade is 0.01 and 0.10 – two
countries that are not very dependent on other, but the bilateral trade for one of
the countries forms a 10 times larger share of the total trade than for the other.
In this case, the symmetry measure will be 0.91 – more symmetric than the first
case!
In addition, Barbieri has constructed the interaction term between Salience
and Symmetry. Since the Symmetry variable varies between 0.85 and 1 and is
negatively correlated with Salience, the interaction term introduces collinearity
in the model. These weaknesses create difficulties in interpreting her results;
indeed, it is not possible to draw any conclusions on asymmetry from these results.
A measure that uses the ratio of the trade shares of the two countries rather
than the difference between these avoids the dependence between the magnitude and asymmetry of the trade relationship. But this is equivalent to using the
ratio of the two countries’ total trade, since
Chapter 5: Research Design
81
Dyadic Trade
Total Trade1
Total Trade2
Trade Share1
=
=
.
Trade Share2 Dyadic Trade Total Trade1
Total Trade2
 Total Tradel arg est
I consequently define Trade Asymmetry = ln
 Total Tradesmallest

 . Placing the

largest total trade on top in the fraction ensures that the measure increases
monotonically with increased asymmetry. Log-transforming the measure helps
to avoid outliers.
Likewise, we could construct a measure of trade asymmetry based on
Oneal & Russett’s ‘trade as share of GDP’ measure. This takes the form of the
ratio of the GDPs of two countries, and is highly correlated with the Size
Asymmetry measure. There is consequently no point in constructing this measure.
The ‘Trade Asymmetry’ measure is also positively correlated with the
power asymmetry measures (0.68 with the Size Asymmetry measure, 0.12 with
Capability Asymmetry). It would be useful to have a measure of trade asymmetry that was easier to distinguish from the power dimension. Export partner
concentration is a good candidate here. Hirschman (1945/1980: 98–101) constructed an index for export (or commodity) partner concentration:
2
 Exports to Country i 
 . I computed this index
Export Partner Concentration = ∑ 
Total Exports 
i =1 
n
on the basis of my trade dataset, and created a dyadic measure by using the
value for the country in the dyad with the lowest concentration (following the
‘weak link’ principle). I constructed an ‘Concentration Asymmetry’ measure by
log-transforming the ratio of the two countries’ export concentration indexes.
5.6.3 Development asymmetry
The third dimension of asymmetry is the difference in level of economic development. As with the other asymmetry measures, I use the log of the ratio for
the development variables. Since ln(GDP per capita) and ln(Energy Consumption per Capita) are already log-transformed, this simplifies the difference be-
82
The Limits of the Liberal Peace
tween the two measures. The asymmetry measures for the two development
measures, then, are:
GDP per capita Asymmetry = ln (GDP per capital arg est ) − ln (GDP per capita smallest )
Energy Cons. per capita Asymmetry = ln (En. Cons . per cap l arg est ) − ln (En. Cons . per cap smallest )
5.7
The Dependent Variable: Fatal Dispute
The dependent variable is a subset of the Militarized Interstate Disputes compiled by the Correlates of War Project (Jones, Bremer & Singer, 1996). Only disputes where at least one of the two states in the dyad experienced at least one
fatality resulting from the dispute were included here. Although limiting the
number of disputes in itself will reduce the power of the analysis, I expect only
slight reduction in significance for the regime and interdependence variables.33
Disputes which involve battle-deaths are more clearcut examples of militarized
disputes, which requires a much more difficult decision to take than those not
involving fatalities. Moreover, there is reason to suspect that militarized disputes between rich democracies are over-reported in the MID dataset (cf. the
Gasiorowski quote at p. 86 above). Hereafter, I will refer to such outbreaks as
‘fatal disputes’.
5.8
Control Variables
Are there any variables that might confound the relationship between interdependence and militarized conflict? The set of control variables chosen here
builds on Raknerud & Hegre (1997).
5.8.1 Contiguity
Contiguity is defined as the situation when two countries share a land border or
where there is less than 25 nautical miles of sea between them. Contiguity
through colonies is not counted as contiguity here. A contiguous dyad is defined as a high-relevance dyad.
33
In a trial run with Oneal & Russett’s (1997) dataset, I replaced their dependent variable with
mine. This in fact resulted in a higher level of significance for their interdependence variable,
despite the loss of cases.
Chapter 5: Research Design
83
5.8.2 Major powers
By definition, major powers have the means of and interest in interacting with a
large proportion of the states in the system. They are therefore expected to participate in more militarized disputes than other states. For the same reason,
Oneal & Russett include dyads containing major powers in their set of ‘relevant’ dyads. We have coded each dyad as consisting of zero, one or two major
powers. The information on power status is taken from the Correlates of War
Project (Small & Singer, 1982).
Dyads consisting of two major powers are defined as high-relevance dyads
and are included in the dataset. Dyads involving only one major power, on the
other hand, are not included. This is a different choice than Maoz & Russett’s
(1992). My justification for this is that the number of dyads containing one major power is dependent on the number of states in the system. It is, then, in line
with the discussion on the relevance of dyads in Raknerud & Hegre (1997), necessary to treat them together with the low-relevance dyads. The category ‘One
major power’ distinguishes these dyads from the rest of the low-relevance dyads.
5.8.3 Alliance
Dyads related through alliances have a lower probability of dispute, ceteris paribus (Bremer, 1992). I used an update34 to 1992 of the COW alliance dataset
(Singer & Small, 1966; Small & Singer, 1969), to code this variable and added
some alliances from Oren (1990). The ‘Non-aggression pact’ category was excluded, since this usually applies to potential enemies rather than potential allies in war (see Raknerud & Hegre, 1997: 394 for an empirical validation of this
choice).
34
This dataset was obtained from the COW project in 1995 through personal communication
with J. David Singer.
84
The Limits of the Liberal Peace
Chapter 6
Testing the Hypotheses
T
his chapter reports the empirical analysis of the various hypotheses described and developed in Chapters 3 and 4. I will proceed hypothesis
by hypothesis, in the same order as above. Each section will be intro-
duced by a survey of the comparable existing studies of the hypotheses. I will
place special emphasis on the work by Oneal & Russett and by Barbieri, since
these occupy a prominent place in the debate, and since they employ research
designs which are close to mine. There exists also, of course, a large number of
case studies of the relationship between trade and conflict, but I will not discuss
these here. I will then proceed to the presentation and discussion of the relevant
part of my own empirical analysis.
6.1
Hypothesis 1: Peace through Interdependence
Hypothesis 1 stated that the more two states trade, the lower is the probability
of war between them.
6.1.1 Previous studies
The first large-N quantitative study of the hypothesis is Solomon Polachek’s
(1980). His conflict measure is taken from the Azar Conflict and Peace data
bank, COPDAB (Azar, 1980), a longitudinal collection of events reported by
dyad from a large number of newspaper sources. These events are classified as
different kinds of conflict and cooperation. Polachek’s conflict measure is the
frequency of cooperative events minus the frequency of conflictive events. Using ordinary least-square regression (henceforth called OLS) and pooled OLS,
he finds that the dollar value of trade is positively associated with this index in
the dyads formed by 30 countries, for the period 1958–67. The same conclusion
is reached in later work with various specifications of Polachek and associates
(Gasiorowski & Polachek, 1982; Polachek & McDonald, 1992).
86
The Limits of the Liberal Peace
However, Mark J. Gasiorowski (1986) criticizes Polachek’s use of the
COPDAB events data. In the dataset, there is a weighting scheme that gives war
actions more weight than actions of ‘mild verbal dismay’. Polachek does not
make use of these intensity weights (although he does report regressions for
each of the individual types of interaction). Moreover, Gasiorowski notes that
many more events are reported for countries such as the Western developed nations than
for others. This is due in part to the greater role these countries play in the international
system. However, it may also reflect a kind of source coverage bias: certain countries are
viewed as more newsworthy than others and hence receive more coverage in the news
media. In either case the additional events reported tend to be less dramatic. … His conflict
measure is thus likely to be biased away from 0 for country pairs showing many events
(Gasiorowski, 1986: 28)
Gasiorowski also criticizes Polachek’s use of the dollar value of the trade to
measure interdependence, and argues that trade as a ratio of GDP is a better
measure. Polachek’s findings may thus ‘simply reflect a correlation between the
size of a country’s economy and the number of events that are reported for it in
the news media (p. 28). Gasiorowski then gives a set of bivariate correlations
between various measures of trade and conflict that suggests that correcting the
measures may reverse the sign of the coefficients, such that trade increases conflict and not vice versa.
Gasiorowski’s own OLS model (1986: 32) consequently uses the weighted
measure of net conflict from the COPDAB data set, and the trade/GDP ratio as
the trade dependence measure. His analysis is at the nation level, however. The
dependent variable is ‘the conflict directed by country A toward all of its trade
partners’ (p. 34), and the trade variable the average trade/GDP. He adds longterm and short-term capital flows as percent of GDP as measures of interdependence, and controls for GDP per capita, import price elasticity and partner
and commodity concentration indexes. His analysis includes 130 countries for
the 1948–77 period – a substantial extension of Polachek’s domain, spatially as
well as temporally. He finds a negative parameter estimate for the trade variable, implying that trade reduces conflict. However, he obtains positive estimates for the capital flow and export partner concentration measures. This
makes him conclude that ‘trade interconnectedness is associated with a decline
in conflict only when its costly effects have been controlled for’ (p. 36). How-
Chapter 6: Testing the Hypotheses
87
ever, it is not easy to compare this nation-level analysis with the other studies,
which are mostly dyadic. Nation-level studies of the ‘peace through interdependence’ hypothesis are inferior to dyadic-level studies, since they may hide
that economies that are open on average may have little trade and much conflict with individual countries.
In a series of articles, John R. Oneal, Bruce M. Russett, and associates (Oneal
et al., 1996; Oneal & Ray, 1997; Oneal & Russett, 1997; 1998a; 1998b; Oneal &
Russett, 1999; Russett, Oneal & Davis, 1998) have explored the liberal hypothesis with a setup that differs from both Polachek’s and Gasiorowski’s. They use
the occurrence of a militarized interstate dispute (see section 5.7 for details) as
their dependent variable, and relate this to their set of explanatory variables by
means of logistic regression. This allows them to relate the ‘peace through interdependence’ hypothesis directly to their seminal work on the democratic
peace (Maoz & Russett, 1993). They operationalize interdependence in the dyad
as the ‘least dependent’ – the lowest trade/GDP ratio of the two states in the
dyad. Their first analyses covered the 1950–85 period and only dyads that are
contiguous or include at least one major power (‘high-relevance dyads’). In
their later work, this has been extended to cover the 1885–1992 period and all
dyads. Throughout, they find a clear support for Hypothesis 1, even when controlling for the effect of democracy. In their various articles, they control for a
wide range of other possibly confounding variables, including alliance ties, contiguity, economic growth rate, and military capability ratio.
Katherine Barbieri (1995; 1996a), however, comes to the opposite conclusion
using the same method, corresponding time-frames, a similar setup, and to a
large extent the same data sources: High levels of trade seem related to a higher
likelihood of militarized conflict between states. She defines interdependence as
the geometric mean of the two states’ trade/total trade ratio, and not as the
trade/GDP ratio. In an attempt to find out why her results differ from Oneal &
Russett’s (Barbieri, 1996b; 1998), she concludes that this has to be sought in the
different samples employed rather than the varying interdependence variable.
Her study includes all dyads with data, whereas Oneal & Russett’s earlier
studies were restricted to high-relevance dyads (dyads consisting of two contiguous countries or at least one major power). The source of the inconsistency
88
The Limits of the Liberal Peace
between the results might then be due to erroneously assuming that the relationship between trade and conflict is linear – it might be A-shaped
(Thomassen, 1998). In high-relevance dyads, the trade level is typically high
and has a peace-conducive effect. In low-relevance dyads, the trade level is
typically low and has no particular effect on the likelihood of militarized conflict. However, in these dyads, the trade variable may function as a proxy for
interaction – friendly as well as unfriendly – since the criteria for defining relevance are very crude. If this holds, studies of all dyads (where the highrelevance dyads make up only a small fraction) are likely to be dominated by
the ‘interaction proxy’ effect of low-relevance dyads, rather than the ‘true interdependence’ effect of high-relevance dyads. In studies of high-relevance dyads
only, the opposite will happen. However, Oneal & Russett include lowrelevance dyads in their latest study (1999), and still find trade to reduce conflict. In an analysis including all dyads (Hegre, 1998: 20), I find the inclusion of
low-relevance dyads to weaken the negative relationship between trade and
conflict, but not to reverse it. In sum, the controversy between Barbieri and
Oneal & Russett remains unresolved.
As discussed above, Oneal & Russett’s earlier studies suffer from not controlling for temporal dependence. Beck, Katz & Tucker (1998) reanalyze the
simplest model in Oneal & Russett (1997) with a model that controls for temporal dependence by using a function of the years of peace in the dyad as an explanatory variable. With this correction, the interdependence variable is rendered insignificant. Oneal & Russett use Beck et al.’s correction for temporal
dependence in their latest study (1999). Analyzing all dyads (not only the set of
‘politically relevant’ dyads), they still find trade to reduce conflict.
Chapter 6: Testing the Hypotheses
89
Table 6-1 Test of Hypothesis 1: Estimated Effect of Interdependence on the Risk of Fatal
Dispute, 1950–92
Variable
Interdependence Measure
Interdependence
Category
Model 1 A
GMM
-0.119
0.037
0.001
Regime Type
Two
-0.082
Democracies
0.393
0.835
Two
0.092
Autocracies
0.240
0.700
Missing
-0.630
Regime Data
0.758
0.406
Relevance
Contiguity
3.072
0.367
<0.0005
Alliance
-0.134
0.242
0.579
One Major
-0.220
Power
0.369
0.551
Two Major
0.200
Powers
0.509
0.695
Peace History
Time in Peace
3.059
(exp(–Days in
0.329
<0.0005
Peace/3,162))
Past Dispute
1.647
0.264
<0.0005
Log likelihood
-466.7
No. of disputes (failures)
104
No. of observations
272,279
The figures in each cell are:
Parameter estimate
Robust standard error
p-value (two-sided test)
Model 1 B
Salience
-0.042
0.024
0.082
-0.363
0.347
0.295
-0.138
0.176
0.435
-0.396
0.474
0.404
2.563
0.244
<0.0005
-0.285
0.191
0.136
0.235
0.251
0.351
0.987
0.381
0.010
2.937
0.259
<0.0005
1.834
0.200
<0.0005
–824.7
160
360,302
Model 1 C
Least Dependent
-0.847
0.519
0.103
-0.098
0.390
0.802
-0.064
0.227
0.778
-1.363
1.044
0.192
3.216
0.367
<0.0005
-0.089
0.244
0.714
0.053
0.365
0.886
-0.122
0.704
0.862
3.275
0.327
<0.0005
1.713
0.247
<0.0005
–446.0
99
267,617
6.1.2 Results from the Cox regression analysis
Results from the Cox regression estimation using the gravity model measure of
interdependence are reported in Table 6–1. In the column labeled ‘Model 1A’,
Hypothesis 1 is tested using the gravity model measure of interdependence.
The parameter estimate (top row in each cell) is more than three times the size
90
The Limits of the Liberal Peace
of the estimated standard error (second row in each cell), meaning that the variable is statistically significant. The p-value (bottom row in each cell) is 0.001.35
The substantial significance may be evaluated from another viewpoint. The
GMM variable ranges from –13.5 to + 8.5. The 10th percentile36 is –2.43 and the
90th is 2.14 (see Appendix 2 for descriptive statistics) – the difference between
these two values is 4.57. The estimated hazard of fatal dispute of the 90th percentile is exp(–0.119(4.57)) = 0.58 relative to the 10th percentile – highly interdependent dyads are just above half as likely to experience fatal disputes as highly
non-dependent dyads. Although reducing the risk of dispute with 42% is considerable, it is not enough to claim a liberal peace.
For the sake of comparison, I also estimated the models using Barbieri’s
and Oneal & Russett’s measure of interdependence. These measures were computed from my trade data set using their formulae (see section 5.3.1). The results are reported in Models 1B and 1C in Table 6–1. Both estimates are negative, but with considerably lower p-values than is the case for the GMM: 0.082
and 0.103. The difference in significance is not due to smaller sample sizes: The
bottom row in the table shows that the number of disputes and observations is
roughly the same for the ‘Least dependent’ variable, and considerably higher
for the ‘Salience’ variable.
The sign of the estimated coefficients is consistent with the GMM model
and with Oneal & Russett’s results (1997; 1999), but not with Barbieri’s (1995;
1996a). The results in Oneal & Russett (1997: 278) results are statistically significant at a much higher level than I find. This is explained by this study’s prob35
The p-value (also called the significance probability) is the probability under H0 of the occur-
rence of the particular observed value (i.e., the parameter estimate) or more extreme values (see
Bhattacharyya & Johnson, 1977: 175). The smaller the magnitude of the p-value, the stronger the
evidence against H0 (H0 is here the hypothesis that there is no relationship between trade and
militarized conflict). I prefer reporting the p-values to comparing the results with pre-defined
significance thresholds, e.g. p<0.05, since statistical significance is a continuous variable, and
reporting the p-value retains more information. Obtaining a p-value of less than 0.05 is equivalent to ‘being significant at the 0.05 level’. The estimated standard errors are probably underestimated since spatial dependence is not modeled here. To counter this bias, I report p-values
for two-sided tests, although all hypotheses are one-sided (cf. section 5.1.1).
36
The sample 10th percentile is a value such that after the data are ordered from smallest to larg-
est, at least 10% of the observations are at or to the left of (below) this value and at least
100-10=90% are at or to the right of (above) this value (Bhattacharyya & Johnson, 1977: 29).
Chapter 6: Testing the Hypotheses
91
lems with dependence between observations discussed in section 5.1.1: they
count each consecutive year of a dispute as an independent instance, and fail to
account for the dependence on the dyad’s history of dispute and peace. In their
most recent study (Oneal & Russett, 1999), they correct for this by omitting consecutive years of dispute and including the ‘Peace years correction’ suggested
by Beck & Tucker (1997). This correction is a semi-parametric modeling of the
effect of the time in peace in the dyad before the observation, and corresponds
closely to the ‘Time in Peace’ variable in my model. With this correction, Oneal
& Russett obtain a p-value of 0.15 for the analysis of all dyads, and 0.03 for relevant dyads only. The magnitude of their parameter estimates (i.e., the substantial significance) is lower than what I obtain here.37
The substantial significance of my estimates for ‘Salience’ and ‘Least Dependent’ is even smaller than for the GMM. The risks of fatal dispute for the
90th percentile dyad relative to the 10th are 0.88 and 0.73, respectively. However,
as may be seen from the distribution statistics of these two variables in Appendix 2, their distribution is extremely skewed. More than a quarter of the observations are zero – the dyad has no or negligible trade. Less than a quarter have
values larger than the mean. Extremely skewed variables often perform badly
in linear models (Kleinbaum, Kupper & Muller, 1988: 220). I consequently logtransformed the ‘Salience’ variable to improve the results.38
The results for the model with the transformed variable is reported in Table
6–2, Model 1D. The p-value is unchanged, but the substantial significance of the
variable is now much larger: The 90th percentile dyad is now estimated to have
a hazard of dispute of 0.45 relative to the 10th percentile dyad.
37
I have rescaled Oneal & Russett’s and Barbieri’s variables by dividing them by 100.
38
More precisely, ln(Salience) was defined as ln(Salience + 0.02). Adding a small number to the
original variable is necessary since ln(0) is not defined. The choice of 0.02 is arbitrary. I tried out
other figures, but they yielded almost identical results.
92
The Limits of the Liberal Peace
Table 6-2 Test of Hypothesis 1: Estimated Effect of Interdependence on the Risk of Fatal
Dispute, 1950–19, Alternative Specifications
Variable
Category
Interdependence Measure
Interdependence
Model 1 D
Ln(Salience)
-0.124
0.072
0.088
Regime Type
Two
-0.327
Democracies
0.348
0.348
Two
-0.150
Autocracies
0.176
0.395
Missing
-0.408
Regime Data
0.472
0.395
Relevance
Contiguity
2.583
0.254
<0.0005
Alliance
-0.307
0.189
0.106
One Major
0.174
Power
0.249
0.484
Two Major
0.976
Powers
0.391
0.013
Peace History
Time in Peace
2.867
(exp(–Days in
0.273
<0.0005
Peace/3,162))
Past Dispute
1.843
0.202
<0.0005
Log likelihood
–824.7
No. of disputes (failures)
160
No. of observations
360,302
The figures in each cell are:
Parameter estimate
Robust standard error
p-value (two-sided test)
Model 1 E
Model 1 F
Correction for
Correction for
temporal
temporal
dependence
dependence
omitted
omitted
Ln(Salience)
GMM
-0.279
-0.309
0.089
0.035
0.002
<0.0005
-0.592
-0.265
0.354
0.367
0.094
0.471
-0.207
0.033
0.172
0.207
0.228
0.875
-0.849
-0.684
0.470
0.703
0.071
0.331
3.706
4.103
0.249
0.334
<0.0005
<0.0005
-0.798
-0.499
0.176
0.211
<0.0005
0.018
0.067
-0.635
0.257
0.379
0.794
0.094
1.575
0.529
0.381
0.532
<0.0005
0.320
–945.3
160
360,302
-541.3
104
272,279
6.1.3 Control variables
Among the control variables, only ‘Contiguity’, ‘Time in Peace’, and ‘Past Dispute’ are significant in the models reported in Table 6–1. They are in return
strong and very significant. The contiguous dyads have a hazard of dispute 13–
Chapter 6: Testing the Hypotheses
93
25 times higher than the baseline39. The ‘Time in Peace’ variable is as important
for the hazard of dispute in a dyad as contiguity. The parameter estimate implies that the risk of dispute is approximately 15 times higher in the first year
after a dispute than after some 40 years in peace.40 The idea that there is temporal dependence in the data, receives considerable support. This temporal dependence is further strengthened by the ‘Past Dispute’ variable. Naturally,
whether the dyad has been enemies in a dispute earlier is important for the risk
of a new dispute: The estimated hazard is five to six times higher for such dyads. This is in addition to the increase in risk modeled by the ‘Time in Peace’
variable. The first year after a fatal dispute, the estimated risk of military hostilities is almost 100 times higher than that of a dyad that has never had a dispute
and have coexisted peacefully for many years. The substantial significance of
these variables is large, indeed.
The estimate for ‘Two Major Powers’ is positive but significant only in
Model 1b, whereas the ‘One Major Power’ and ‘Alliance variables never are
significant. This is at odds with the results in most comparable studies (Barbieri,
1996a; Bremer, 1992; Maoz & Russett, 1992; 1993; Oneal & Russett, 1997; 1999;
Raknerud & Hegre, 1997). The same applies to the regime variable: It never
reaches statistical significance, in spite of the many studies finding support for
the democratic peace (e.g., Bremer, 1992; Doyle, 1986; Maoz & Russett, 1993;
Raknerud & Hegre, 1997).
The discrepancy between these results and previous studies are in part due
to the correction for temporal dependence. Models 1E and 1F (Table 6–2) are
estimated without the ‘Time in Peace’ and ‘Past Dispute’ variables. The parameter estimates for ‘Two Democracies’, ‘Alliance’, and ‘Two Major Powers’ show
39
The estimated relative hazard of ’13 times higher than the baseline’ is arrived at by computing
the exponential of the parameter estimate; exp(2.563) = 13.0.
40
Recall from section 5.1.3 that the γ parameter was set to model a half-life of six years. After
one year, the impact of time is then assumed to be 89% of the first day’s impact. After 40 year,
only 1% remains. The estimated change in hazard from year one to year 40 is then
exp(3.059*0.88) = 14.8.
94
The Limits of the Liberal Peace
that the loss in significance is to a large extent due to the correction for temporal
dependence.41
Without the correction for temporal dependence, both ln(Salience) and the
GMM interdependence variable are far more significant, both statistically and
substantially. Neither ‘Two Democracies’ nor ‘Two Major Powers’ is significant
when estimated jointly with the GMM. This is not so surprising: the democratic
states tend to be interdependent.42 Which of these variables that have causal
priority is uncertain, but the fact that the democracy variable is insignificant
when estimated together with the interdependence variable suggests that
‘peace through interdependence’ is a more general finding than the democratic
peace. Likewise, major powers are less dependent on trade than minor powers
since they have larger internal markets.43 These results may suggest that the
dispute-proneness of major powers is partly due to the weakness of the constraints that trade considerations force upon them.
It may be debated how the two temporal dependence variables should be
interpreted. The principle of conditioning on all events that precede the event
we analyze to avoid temporal dependence is a strong argument for including
them. However, with ‘Time in Peace’ and ‘Interdependence’ as the exceptions,
the variables in the model are dyad attributes that change slowly. When estimating the models without the two history variables (Model 1E), we see that a
contiguous, politically mixed dyad of two major powers are among the most
likely to wage a first dispute. Using the peace history variable to predict later
disputes may mean partly subsuming these explanations under this variable.
A closer look at the data will throw some more light on the puzzle. For 55%
of the cases with dispute outbreaks in the dataset we find that the two countries
are previous enemies in disputes, as compared to 2.7% for the non-dispute observations. Contrary to what one would expect, the double democratic dyads in
41
In our study of the outbreak of war for the 1840–1992 period (Raknerud & Hegre, 1997: 394),
we found these variables to be statistically significant with similar control for temporal dependence. This seeming puzzle is probably due to the larger sample size (343 outbreaks compared to
100–160), and perhaps also to the fact that the dependent variable in that study was large-scale
war.
42
The mean value for GMM is 0.80 for two democracies, –0.43 for two democracies, and –0.24
for politically mixed dyads.
Chapter 6: Testing the Hypotheses
95
the dataset have had past disputes more frequently than any other regime combinations; 5.6% in contrast to 1.8% for the double autocratic dyads and 2.9% for
the politically mixed ones. The reason for this is that double democratic dyads
on average have existed for a longer time, but is also due to the regime changes
in Germany, Italy, and Japan after World War II.44 In 10 of the 12 double democratic disputes (83%) there had been a past dispute. This is high, but not that far
from the baseline of 55%. A trivariate analysis of the relationship between Regime Type, Past Dispute, and Dispute Outbreak shows that regime type does
make less of a difference for dyads with a past dispute than for dyads with a
peaceful history: For the group with past dispute, the probabilities for politically mixed dyads and double autocratic dyads are 2.5 and 5 times higher than
for double democratic dyads, respectively. The corresponding figures for the
group with no past disputes are 5 and 6.5. This change is sufficient for the parameter estimates to drop considerably in terms of statistical significance.
6.2
Hypotheses 2 and 3: The Direction of Causation
Hypothesis 2 state that ‘the higher the probability of dispute between two
states, the less they trade’. This is based on the realist assumption that security
issues have primacy over economic issues (see section 3.3). Brian Pollins (1989b)
tests whether ‘trade follows the flag’ by adding political variables to a gravity
model of trade. The nominal value of total imports is the dependent variable in
these two studies. The specification differs somewhat in the two studies, but
both include a measure based on the COPDAB dataset to measure ‘weighted
cooperation sent’. Pollins (1989a) estimate an OLS regression model separately
for each year in the period 1955–78, covering the dyads formed by 25 nations.
Pollins (1989b) analyze the trade flows between six importers and 25 exporter in
the 1960–75 period, using cross-section pooled time-series analysis. Both studies
43
The mean for GMM is –0.88 for two major powers, and –0.08 for one major power dyads.
44
The democratization of the losing powers in World War II may be a case of a more general
pattern of democratization in the wake of war (see Bueno de Mesquita et al., 1998; Bueno de
Mesquita, Siverson & Woller, 1992; Mitchell, Gates & Hegre, 1998), implying that doubledemocratic dyads frequently have a violent past, prior to one or both of the countries becoming
democratic.
96
The Limits of the Liberal Peace
use lagged values for the conflict variable. Pollins conclude that political conflict
between two countries clearly decreases the amount of trade.
Joanne Gowa & Edward D. Mansfield (1993) also employ the gravity model
to test Hypothesis 2 for a set of seven major powers for nine selected years in
the 1905–85 period. They replace the COPDAB measure of conflict/cooperation
with dummy variables for common membership in alliances and for being belligerents in war. These variables were coded on the basis of the Correlates of
War datasets (see sections 5.7 and 5.8.3). They find alliances to significantly and
strongly increase the level of trade, but only in the period of bipolarity in their
sample (1955–85). In the period of multipolarity in their sample (1905–38), the
alliance variable showed no consistent relationship with trade. Their war variable yielded no clear results, mainly because of the sparseness of war between
the countries in their sample.
Similar results are obtained in Morrow, Siverson, & Tabares (1998). The
more similar two states are in their international relations (defined as the Tau
correlation of their alliance portfolios), the more they trade. This measure is a
more general measure of the idea of joint security interests than using alliances
alone as done by Gowa & Mansfield, and this probably explains why Morrow,
Siverson & Tabares obtain considerably more robust results. They also find joint
democracy in the dyad to considerably increase trade.
However, the direction of causation in these realist studies are no more securely founded than in the liberal studies they counter. None of the studies discussed so far establish anything but a correlation between the two variables. To
say anything conclusively on the direction of causation, a simultaneousequation approach is necessary. In such studies, both trade and conflict appear
as dependent variables in two separate equations. Past (lagged) values for both
variables are included in both equations. An investigation of the parameter estimates for the lagged variables yields information on which of the two dependent variables are best at predicting later values for both variables.
Polachek (1980) employs two-stage least-squares regression, and Gasiorowski & Polachek (1982) perform Granger causality tests to control for the possible
reverse causality of their ‘trade promotes peace’ hypothesis. They find this only
to reinforce their main hypothesis: Past values for the trade variable are much
Chapter 6: Testing the Hypotheses
97
better at predicting present values of cooperation and conflict than past values
for the conflict variable are for predicting present values of trade. Their studies
thus contradict Hypothesis 2 and strongly supports Hypothesis 3.
Rafael Reuveny & Heejoon Kang (1996: 949–50) point out some weaknesses
in the test for direction of causation in Gasiorowski & Polachek (1982). Most
important is the objection that it only covers one dyad for a limited time-frame,
and that the dollar value of exports and imports is rather a measure of country
size than an indicator of interdependence, as pointed out by Gasiorowski. On a
more technical note, Reuveny & Kang point out that the study lacks a test for
unit roots in their data, a control for seasonal fluctuations in trade flows, and
controls for exchange rate fluctuations.
In their own analysis of Granger causality, they sample 16 dyads quarterly
in the 1960–92 period (some of the dyads have shorter time-series). The
COPDAB events dataset was augmented with corresponding data from WEIS.
As a measure of interdependence, they use the trade/total trade ratio which
they argue is insensitive to inflation, exchange rates, and business cycles. They
conclude that the causal relationship between trade and conflict/cooperation is
dyad-dependent, but largely reciprocal. Hypothesis 1 and 2 are equally supported. Hypothesis 3 is supported except that the causal effect from conflict to
trade is as strong as the effect from trade to conflict.
Reuveny & Kang (1998) investigate the direction of causation for the trade
in different goods. They find reciprocal causality for some goods, and that the
causality from conflict to trade is more pronounced in ‘strategic’ goods as minerals, iron and steel, fuels, basic manufactures, and control and scientific
equipment, reinforcing the realist argument.
Soo Yeon Kim (1998; 1999) also investigates the direction of causation in the
relationship between trade and conflict. Her conflict variable is the outbreak of
militarized disputes. Since this variable is dichotomous, she uses a combination
of OLS and probit analysis, with two-stage procedures to estimate the reciprocal effects. Her analysis includes all high-relevance dyads for the 1950–92 period, and tries out three different operationalizations of interdependence: Oneal
& Russett’s ‘least dependent’ index, Barbieri’s interaction term, and log(trade
flow) in a gravity model formulation. She finds reciprocal effects between in-
98
The Limits of the Liberal Peace
terdependence and conflict, but, in contrast to Reuveny & Kang, she concludes
that trade has a stronger impact on conflict than vice versa.
The issue of direction of causation is not settled with these studies, and remains a very important question. However, I will use Kim’s results and my
theoretical argument (see section 3.3.3) as a justification of my choice to assume
that causation flows mainly from trade to conflict – that Hypothesis 3 holds. To
the extent that this holds, I may investigate the remaining hypotheses in a single-equation framework where conflict is the dependent variable.
6.3
Hypotheses 4 and 5: Development
Hypothesis 4 states that assuming symmetry, the probability of dispute between two states is lower the more developed they are. Hypothesis 5 states that
the more developed two states are, the stronger is the peace-conducive effect of
trade.
6.3.1 Previous studies
There are not many cross-national quantitative studies that have tested this hypothesis. At the nation level, Gasiorowski (1986) finds a statistically significant,
negative relationship between development – defined as GDP per capita – and
the amount of COPDAB conflict. Rich countries direct less conflictive actions to
other nations. This result seems stronger than his result for trade, since it is not
offset by other variables. On the contrary, it is strengthened by the positive and
significant parameter estimates for the trade partner and commodity concentration indexes: Countries that are heavily dependent on a small number of goods
or partners, engage more in conflict. This reinforces the result for development,
since dependence on a small number of goods is more common in countries
with limited industrialization and low GDP per capita. Although Gasiorowski’s
study is at the nation level, this is largely consistent with my Hypotheses 9 and
10.
Bremer (1992: 334–335) finds dyads where both states are ‘more advanced’
to be significantly less war-prone than other dyads when controlling for regime
type and other possibly confounding variables. ‘More advanced’ is defined as
‘possessing a share of system-wide economic capability that is greater than its
Chapter 6: Testing the Hypotheses
99
share of system-wide demographic capability’ (pp. 324–325). The effect of development is strong: controlling for other factors, less advanced states are more
than four times as likely to be involved in wars than more advanced states (p.
336).
Maoz & Russett (1992: 256–257) presented a cross-tabulation of MID disputes and different dyadic combinations of regime type and wealth categories.
They conclude that ‘the notion that democracies do not fight one another because they are rich is flatly rejected’. Disregarding regime type, some support
for Hypothesis 4 may be inferred from the table: Dyads with two rich countries
have considerably less conflict than expected from a zero hypothesis of no relationship, and dyads with two poor countries have considerably more.
Michael Mousseau (1997; 1998; 1999) relates the MID dispute dataset to the
Polity dataset and energy consumption per capita in a study of all (directional)
dyads in the 1920–92 period. He finds that the difference in war behavior is
much more marked between more developed democracies and developed nondemocracies than between their less developed counterparts: The democratic
peace seems restricted to the developed world in his analysis. However, he also
finds that the probability of engaging in militarized disputes increases with increasing development. This is contrary to Gasiorowski’s results, and to my Hypothesis 4 .
Oneal et al. (1996: 18), however, report that ‘[d]yadic wealth is not included
in the analyses we will report, however, because it never proved significant
when [the interdependence measure] was in the equation’.45
6.3.2 Results from the Cox regression analysis
Table 6–3 reports the test of the two hypotheses. Model 4A is similar to Model
1A, except that the lowest GDP per capita in the dyad is added as a measure of
development. The estimate for the development variable is negative: Development is associated with less militarized conflict. The result is clearly significant,
the p-value being 0.001. The inclusion of the development variable changed the
interdependence variable by virtually nothing. One change caused by this in45
I tried adding my development variable and the interaction term to the dataset used in Oneal
& Russett (1997). This exercise reproduced results quite similar to those reported in Table 6-3.
100
The Limits of the Liberal Peace
clusion should be noted, however: The ‘Two Democracies’ variable changed
from weakly negative to weakly positive. This change is not that surprising, as
democracy and development are highly correlated (see section 4.1.3).
Table 6-3 Test of Hypotheses 4 and 5: Estimated Effect of Interdependence and Development on the Risk of Fatal Dispute, 1950–92
Variable
Category
Interdependence Measure
Development Measure
Interdependence
Development
Interdependence
* Development
Interaction
Regime Type
Two
Democracies
Two
Autocracies
Missing
Regime Data
Relevance
Contiguity
Alliance
One Major
Power
Two Major
Powers
Peace History
Time in Peace
(exp(–Days in
Peace/3,162))
Past Dispute
Log likelihood
No. of disputes
No. of obs.
The figures in each cell are:
Model 4 A
GMM
GDP
-0.126
0.038
0.001
-0.466
0.188
0.013
Model 4 B
Ln(Salience)
En. Cons.
-0.099
0.076
0.195
-0.251
0.060
<0.0005
0.322
0.414
0.438
-0.031
0.262
0.907
-0.848
0.771
0.271
2.984
0.368
<0.0005
-0.018
0.243
0.942
-0.192
0.382
0.615
0.297
0.508
0.558
2.772
0.395
<0.0005
1.794
0.271
<0.0005
–453.2
103
266,095
Parameter estimate
Robust standard error
p-value (two-sided test)
-0.144
0.364
0.693
-0.331
0.179
0.068
-0.684
0.456
0.136
2.455
0.258
<0.0005
-0.340
0.192
0.077
0.305
0.251
0.224
1.225
0.401
0.002
2.546
0.291
<0.0005
2.032
0.212
<0.0005
–799.7
158
356,679
Model 5 A
GMM
GDP
0.932
0.284
0.001
-0.706
0.166
<0.0005
-0.154
0.040
<0.0005
0.394
0.397
0.321
-0.094
0.253
0.711
-0.730
0.756
0.334
2.974
0.357
<0.0005
-0.077
0.242
0.749
-0.017
0.367
0.962
0.272
0.505
0.591
2.603
0.359
<0.0005
1.854
0.278
<0.0005
–448.3
103
266,095
Model 5 B
Ln(Salience)
En. Cons.
-0.445
0.118
<0.0005
-0.646
0.106
<0.0005
-0.180
0.041
<0.0005
0.035
0.359
0.923
-0.279
0.185
0.132
-0.508
0.462
0.272
2.482
0.261
<0.0005
-0.152
0.205
0.459
0.534
0.258
0.039
1.515
0.411
<0.0005
2.438
0.293
<0.0005
1.980
0.207
<0.0005
–790.7
158
356,679
Chapter 6: Testing the Hypotheses
101
Model 4B tests Hypothesis 4 using ln(Salience) as an indicator of interdependence, and the lowest ln(Energy Consumption per capita) in the dyad as the
measure of development.46 This development variable is estimated to be even
more significant than the GDP-based one, and of roughly the same substantial
importance.47 Note that the ln(Salience) variable is more affected by the inclusion of the development variable than is the GMM – the p-value drops from
0.088 to 0.195.
In Models 5A and 5B, I test Hypothesis 5 by including an interaction term
between development and interdependence. The parameter estimates for the
interaction term is negative and clearly significant, strongly suggesting that development and interdependence reinforce each other’s peace-conducive effects,
as hypothesized. Moreover, they greatly improve the goodness-of-fit of the
model. The increase in –log likelihood is 4.9 for the GMM/GDP model, and 9.0
for the ln(Salience)/Energy consumption model. The improvement in goodness-of-fit is clearly significant; the likelihood ratio statistic yields p-values of
0.027 and 0.003, respectively.48
The empirical results are consistent with the results of Bremer (1992: 334–
335). The negative estimate for the interaction term reflects the results of Mousseau (1997; 1998; 1999), who finds the democratic peace to be restricted to the
developed world. However, he finds developed non-democratic dyads to en-
46
I do not report the estimation of models where GMM is combined with the Energy consump-
tion measure of development, and Salience with GDP per capita. These models gave very similar results, but with slightly poorer levels of significance since these combinations yield the largest loss of cases due to missing data. I also estimated a model using the geometric average of the
two countries’ GDP per capita as a dyadic measure of development. This did not change results
substantially.
47
The range of the Energy Consumption per capita variable is about twice as large as that of
GDP per capita (cf. Appendix 2).
48
The likelihood ratio statistic is widely used to compare two models where the observations
are the same and one model is a special case of the other. This is the case here, since the number
of observations are identical in Models 4A and 5A and in Model 4B and 5B, and since Models
4A and 4B are simpler than Models 5A and 5B. Assuming that the simpler model holds, the difference in log likelihood is a test statistic of the hypothesis that the more complicated model fits
the data better than the simpler, and has an asymptotic chi-squared distribution with degrees of
freedom equal to the number of parameters added in the more complicated model (Agresti,
1990: 211–212).
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The Limits of the Liberal Peace
gage in more conflicts than non-developed non-democratic dyads. Furthermore, my results are at odds with those reported by Oneal & Russett.
In Model 5A, the parameter estimate for Interdependence is positive. With
an interaction term (and ensuing collinearity) in the model, this does not necessarily mean that interdependence increases the likelihood of fatal disputes. To
ease the interpretation of the results, I visualize the parameter estimates in
Model 5A in Figure 6–1 for actual ranges for the two variables.
Figure 6-1 Relationship between Lowest GDP per capita, Gravity Model Measure of
Interdependence, and Estimated Relative Risk of Fatal Dispute, 1950–92
Relative risk of fatal dispute
10
1
-4
-3
-2
-1 Interdependence:
0
Gravity model
1
measure
2
3
0.1
0.01
5.7
6
6.3 6.6 6.9 7.2
7.5 7.8 8.1 8.4
8.7
4
9
9.3
9.6
9.9
Development: GDP per capita
The figure is based on the estimates in Model 5A in Table 6–3. Relative risk is relative to a dyad with mean
value for lowest ln(GDP per Capita) (7.33) and Interdependence = 0
The vertical axis in the figure denotes the estimated risk of fatal disputes
relative to a baseline dyad. The baseline dyad is defined as a dyad with mean
value for development (7.33) and 0 for interdependence. The two curved lines
in the figure connect points where the estimated relative risk is similar. The areas between these lines have been given different shades. The dark area in the
middle of the surface includes the combinations of values for the development
and interdependence that have lower risks of fatal dispute than the baseline,
but higher than one tenth of it.
Chapter 6: Testing the Hypotheses
103
In the upper right corner we find dyads consisting of two rich states – 9.9 is
somewhat higher than the US income in 1990 (18,000 US $ per capita, logtransformed to 9.8) and that have negligible trade bonds. This dyad is estimated
to be 74% more dispute-prone than the baseline. The interdependence measure
is the natural logarithm of the ratio between observed and expected trade. Multiplying trade by e = 2.7 is equivalent with increasing the interdependence
measure with one unit. For the rich dyad, this reduces the risk of dispute with
45%. This decrease is reflected by the descending line along the right side of the
coordinate space.
In the lower left corner we find a highly interdependent dyad where the
poorest state is very poor (5.7 corresponds to $300 per capita, e.g., Chad and
Ethiopia in the mid-1980s). Interdependence for such a dyad is estimated to
have the opposite effect: Increasing interdependence by one unit increases the
risk of dispute with 6%. The figure demonstrates clearly that interdependence
works best for developed economies, as my theoretical discussion implied.
However, interdependence is estimated to reduce the likelihood of fatal disputes for development levels above 6.05 ($425 per capita, or about the level of
Tanzania and Zaire in the 1980s). This threshold is very low. The estimated
positive effect under it does not have much practical importance.
The median score for development is 7.23. If the dyadic trade level is increased by a factor of e = 2.7 for a dyad with lowest GDP per capita corresponding to this value, the estimated hazard of dispute is reduced with 17% .
The same estimates for the 25th and the 75th percentile are 8% and 26%, respectively.
These estimates suggest that the development variable is of great substantial importance. For a dyad with 0 on the interdependence variable, an increase
in development by the factor 2.7 reduces the hazard of dispute to one half. The
most well-to-do dyads are estimated to be 16 times less likely to experience
militarized conflict than the dyads that contains Chad or Ethiopia. This relationship is illustrated by the descending lines from left to right in the figure.
The descent is much steeper for the interdependent dyads at the front of the coordinate space than for the non-interdependent dyads at the back of the space.
104
The Limits of the Liberal Peace
In Model 5B, this analysis is done using energy consumption per capita and
ln(Salience). Although the parameter estimates seem very different, the results
are quite similar to those of Model 5A, as witnessed by the plot in Figure 6–2.
Model 5B yields a very similar picture to Model 5A. A difference is a more
marked tendency for interdependence to increase the risk of dispute for extremely under-developed dyads. The threshold under which interdependence
is estimated to increase the likelihood of conflict in this model is –2.47, which is
the value for Guinea, Angola, and Bangladesh in the 1990s. For dyads where
the least developed state has ln(Energy Consumption per Capita) = –5, one
unit’s increase in interdependence is estimated to increase the risk of dispute by
57%. Some countries have had energy consumption per capita in this range
during the 1950–92 period; most recently, Bhutan and Kampuchea in the 1980s.
Figure 6-2 Relationship between Energy Consumption per Capita, ln(Salience) Measure
of Interdependence, and Relative Risk of Fatal Dispute, 1950–92
1000
Relative risk of fatal dispute
100
10
1
-4
-2.4
-0.8
0.1
0.01
0.8
2.4 Interdependence:
ln(Salience)
4
0.001
0.0001
5.6
2
8.8
1.5
1
0.5
0
-0.5
-1
-1.5
-2
-2.5
-3
-3.5
7.2
-4
-4.5
-5
0.00001
Development: Energy Consumption per capita
The figure is based on the estimates from Model 5b in Table 6–3. Relative risk is relative to a dyad with
mean value for lowest ln(Energy Consumption per Capita) (–1.21) and ln(Salience) = 0
Chapter 6: Testing the Hypotheses
105
The estimated change in the risk of fatal dispute for the 25th, 50th, and 75th
percentiles are +6%, –19%, and –35%, respectively.
The development variables were defined as the value for the least developed state in the dyad. A dyad consisting of a rich country, such as the USA,
and a poor one, such as Somalia, are represented by Somalia’s development
score. In section 6.6, I will estimate the importance of asymmetries in development.
A characteristic feature of Cox regression is the non-parametric baseline
hazard. Combined with my choice of calendar time as the time variable in the
survival analysis, this implies that all comparisons are done cross-sectionally,
not over time. The advantage of this is that the results are immune to spurious
effects from factors that systematically vary over time (cf. Raknerud & Hegre,
1997: 390–391). If current-dollar GDP per capita had been used as measure of
development, this would have given exactly the same parameter estimates. The
difference between the current-dollar and constant-dollar measures would be
reflected only in the baseline hazard. The advantage of this for the present
analysis is that we know that the effects of all variables are purely crosssectional. Any trend in variables over time are disregarded. It is wealth and interdependence relative to current average levels that makes the difference in the
models estimated in Table 6–3.
However, if we want to know whether the possible increase in average
wealth and average interdependence has changed the world, the parameter estimates of the Cox regression model provide no answer. The estimated baseline
hazard is plotted in Figure 6–3. From 1960 on, it displays little variation and no
clear trend. In the first ten years, it is significantly higher and drops suddenly
around 1960. This is probably due to the decolonialization that vastly increased
the number of dyads in the interstate system.49 The even baseline suggests that
49
Problems related to the expanding interstate system are discussed in Gleditsch & Hegre (1997:
298–300) and Raknerud & Hegre (1997: 390–391). In all the models reported in Tables 6–1, 6–2,
and 6–3, I tried including the variable that controls for variations in system size proposed in the
latter article. In contrast to that study, the variable never reached statistical significance in this
analysis. This is reflected in the even baseline hazard reported in Figure 6–3. There are two reasons for the difference between the two studies: Firstly, the system has increased less in the past
40 years than in the entire period from 1840–1992 studied in Raknerud & Hegre (1997). Sec-
106
The Limits of the Liberal Peace
there is no difference between cross-sectional effects and effects over time. To
validate this, I estimated the data using exponential regression. This is equivalent to setting α(t) = 1 in (1). The parameter estimates emerging from that analysis were virtually unchanged from the results in Table 6–3. This implies that the
effect of development is not only cross-sectional, but also temporal. The results
give reasons to expect the interstate system to become more peaceful as its
member states become more developed.
Figure 6-3 Estimated Baseline Hazard of Fatal Disputes, 1950–92
.019594
bas
eli
ne
.000502
1950
1971
1992
I also ran the models using Oneal & Russett’s ‘Least Dependent’ measure,
in original and log-transformed, and the non-transformed version of Barbieri’s
‘Salience’ measure. When juxtaposed with the development variables and the
‘Time in Peace’ and ‘Past Dispute’ variables they invariably got negative but
insignificant parameter estimates. These results indicate, together with my arguments in favor of them in section 5.3, that the two measures of interdependence used here capture more precisely the concept of interdependence.
ondly, the decision to omit all dyads that are not contiguous, not allied, not two major powers,
and more than 3,000 kilometers from each other further stabilizes the number of dyads over
time in the dataset.
Chapter 6: Testing the Hypotheses
6.4
107
Hypotheses 6 and 7: Power Asymmetry
Hypothesis 6 states that the probability of war should decrease as the pair of
countries becomes more asymmetric in terms of power. Hypothesis 7 predicts
that the relationship between interdependence and peace should be weaker the
more asymmetric the dyad is.
6.4.1 Previous studies
Bueno de Mesquita & Lalman (1992: 205) run a dyad-level logit analysis with
COW wars as the dependent variable and their estimates for the two states in a
dyad’s subjective probability of winning as independent variables. They find
strong support for their hypothesis that the likelihood of war is the strongest
when both sides believe that their probabilities of winning is greater than 0.5.
This supports Bueno de Mesquita & Lalman’s formal model as well as my Hypothesis 6.
6.4.2 Results from the Cox regression analysis
In the analyses above, some control variables never achieved statistical significance when controlling for temporal dependence: The regime variables and the
alliance variable. In the models using GMM and GDP per capita, the variables
for one or two major powers were not significant, either. In the following analyses, I remove these from the models. This simplifies the presentation and reduces the amount of missing data. Statistical theory also predicts this will improve the precision of the estimation (Agresti, 1990: 182–184). For the sake of
comparison, the two left-most columns (labeled Reduced Model A and B) in
Table 6–4 report the results from these reduced models.
Hypothesis 6 was tested by adding the variables for power asymmetry to
the model. The results are reported in the columns labeled 6A and 6B in Table
6–4. The hypothesis does not receive any support in either of these analyses:
The parameter estimate is positive. That is the opposite direction of what expected from the hypothesis. It is also contrary to what most comparable studies
have found (e.g., Barbieri, 1996a; Bremer, 1992; Bueno de Mesquita & Lalman,
1992; Oneal & Russett, 1997; 1999). On the other hand, this result supports bal-
108
The Limits of the Liberal Peace
ance-of-power theory (although this is largely a systemic theory, see section
4.2.1).
Table 6-4 Test of Hypothesis 6: Estimated Effect of Power Asymmetry on the Risk of
Fatal Dispute, 1950–92
Variable
Category
Interdependence Measure
Development Measure
Power Asymmetry Measure
Interdependence
Development
Interdependence
* Development
Interaction
Power
Asymmetry
Relevance
Contiguity
Reduced
Model A.
GMM
GDP
Reduced
Model B.
Ln(Salience)
En. Cons.
0.872
0.279
0.002
-0.610
0.153
<0.0005
-0.145
0.039
<0.0005
-0.474
0.113
<0.0005
-0.653
0.101
<0.0005
-0.199
0.039
<0.0005
2.963
0.374
<0.0005
2.414
0.258
<0.0005
0.635
0.246
0.010
1.514
0.413
<0.0005
2.543
0.278
<0.0005
2.002
0.207
<0.0005
–792.8
158
356,679
One Major
Power
Two Major
Powers
Peace History
Time in Peace
(exp(–Days in
Peace/3,162))
Past Dispute
Log likelihood
No. of disputes
No. of obs.
The figures in each cell are:
2.710
0.336
<0.0005
1.854
0.278
<0.0005
–450.0
103
266,095
Parameter estimate
Robust standard error
p-value (two-sided test)
Model 6A.
GMM
GDP
Size
0.862
0.276
0.002
-0.631
0.151
<0.0005
-0.143
0.039
<0.0005
0.150
0.082
0.068
3.016
0.362
<0.0005
2.659
0.330
<0.0005
1.885
0.274
<0.0005
–448.8
103
266,094
Model 6B.
Ln(Salience)
En. Cons.
Capabilities
-0.482
0.115
<0.0005
-0.634
0.103
<0.0005
-0.201
0.039
<0.0005
0.082
0.043
0.056
2.392
0.257
<0.0005
0.368
0.269
0.172
1.514
0.414
<0.0005
2.555
0.282
<0.0005
2.016
0.214
<0.0005
–744.1
149
343,148
The discrepancy seems related to the modeling of temporal dependence. If I
take the two peace history variables out of the model, the power asymmetry
variables are rendered insignificant. When comparing dyads with similar histories of peace, an increase in power asymmetry increases the risk of fatal disputes. When comparing dyads disregarding the history, there is no difference.
Chapter 6: Testing the Hypotheses
109
In terms of substantial significance, the interpretation of the estimate for
power asymmetry in Model 6A is this: The risk of fatal dispute in a dyad where
one country is 2.7 times larger than the other is exp(0.150) = 1.16 relative to a
symmetric dyad. In other words, increasing the size ratio by the factor 2.7 increases the risk of dispute with 16%. The risk for the 90th percentile relative to
the 10th is exp(0.150*(3.41–0.21)) = 1.62, which implies that the variable does not
make very much of a difference.
Hypothesis 7 was tested by including the interaction term between Size Ratio and GMM, and between Capability Ratio and Ln(Salience). If Hypothesis 7
holds, these interaction terms should be positive. None of them were close to
statistical significance. Power asymmetry have no moderating effect on the relationship between trade and peace.
6.5
Hypotheses 8 and 9: Asymmetry in the Gains from
Trade
Hypothesis 8 stated that the more asymmetric a pair of states is in terms of
gains from trade, the lower is the probability of war, while Hypothesis 9 predicted that the relationship between trade and war should be weaker the more
asymmetric the relationship is.
6.5.1 Previous studies
As noted above, Gasiorowski (1986: 32) finds high export partner concentration
to increase a country’s predicted level of conflict. It is difficult to say what this
nation-level finding has to say for the dyad-level hypotheses. A country with
high export partner concentration has a high dyadic trade to total trade ratio
with a few partners, but these ratios are very low with the remaining countries
in the world. It is, then, not possible to infer anything from the nation-level
study to the dyadic level.
In section 5.6.1, I argued that Barbieri’s (1995; 1996a) measure of symmetry
has serious weaknesses. She concludes that both symmetrical and asymmetrical
trade relationships increase the likelihood of interstate disputes, but that asymmetrical relationships are the most dispute-prone. However, the weaknesses in
110
The Limits of the Liberal Peace
her operationalization makes it difficult to draw any firm conclusions on the
issue of asymmetry from her analysis.
Polachek et al. (1999: 417) uses the interaction between exports and targetactor GNP difference to test the proposition that ‘trade with a large target reduces conflict more than trade with a small target’. The dataset (covering 30
countries in the period 1955–67) and the dependent variable is the same as in
Polachek (1980). They find support for the proposition – the interaction variable
is negative and statistically significant. This is consistent with the reasoning in
section 4.2.4: If Aggressia becomes more dependent on trade with Deterristan, it
is less likely to challenge the status quo. As in the deterrence model, however,
some types of conflict (labeled uncontested use of force there) becomes more
likely – large actors are correspondingly less constrained by their trade with
small partners. Their results indicate that the net effect of trade on the probability of dispute in asymmetric dyads is indeterminate.
6.5.2 Results from the Cox regression analysis
I constructed two variables to test Hypothesis 8: ‘Trade Asymmetry’ and ‘Concentration Asymmetry’ (see section 5.6.2). ‘Trade asymmetry’ is the logarithm
of the ratio of the two countries’ total exports. ‘Concentration Asymmetry’ is
the logarithm of the ratio of the two countries’ export partner concentration.
These variables were added to Model 6 to test Hypothesis 8. The ‘Power
Asymmetry’ variable was retained in the model as a control variable – we are
interested in the effect of trade asymmetry over and beyond the effect of power
asymmetry. In the models containing the export partner information, I also included the main term for export partner concentration. The results from these
analyses are reported in Table 6–5.
The columns labeled Model 8A and 8B test the hypothesis using ‘Trade
Asymmetry’ as asymmetry variable. The results show that the risk of fatal dispute is significantly reduced with increasing asymmetry, as the hypothesis predicted. In both models, the estimate for the power asymmetry variable has increased.
Chapter 6: Testing the Hypotheses
111
Table 6-5 Test of Hypothesis 8: Estimated Effect of Trade Asymmetry on the Risk of Fatal Dispute, 1950–92
Variable
Category
Interdependence Measure
Development Measure
Trade Asymmetry Measure
Power Asymmetry Measure
Interdependence
Development
Interdependence
* Development
Interaction
Power
Asymmetry
Lowest Export
Concentration
Index
Trade/
Concentration
Asymmetry
Relevance
Contiguity
Model 8A.
GMM
GDP
Trade Ratio
Size
0.816
0.287
0.004
-0.650
0.147
<0.0005
-0.135
0.041
0.001
0.285
0.101
0.005
Model 8B.
Ln(Salience)
En. Cons.
Trade Ratio
Capabilities
-0.494
0.120
<0.0005
-0.690
0.113
<0.0005
-0.209
0.041
<0.0005
0.100
0.050
0.047
-0.226
0.119
0.058
2.989
0.363
<0.0005
-0.159
0.073
0.029
2.307
0.261
<0.0005
0.439
0.264
0.097
1.566
0.421
<0.0005
2.512
0.290
<0.0005
2.022
0.220
<0.0005
–742.0
149
303,082
One Major
Power
Two Major
Powers
Peace History
Time in Peace
(exp(–Days in
Peace/3,162))
Past Dispute
Log likelihood
No. of disputes
No. of obs.
The figures in each cell are:
2.631
0.341
<0.0005
1.837
0.277
<0.0005
–447.0
103
265,210
Parameter estimate
Robust standard error
p-value (two-sided test)
Model 8C
GMM
GDP
Export Conc.
Size
0.991
0.289
0.001
-0.763
0.157
<0.0005
-0.159
0.041
<0.0005
0.120
0.084
0.154
-5.274
1.584
0.001
0.002
0.414
0.996
3.030
0.352
<0.0005
2.571
0.327
<0.0005
1.774
0.262
<0.0005
–442.1
103
265,200
Model 8D
Ln(Salience)
En. Cons.
Export Conc.
Capabilities
-0.516
0.121
<0.0005
-0.689
0.110
<0.0005
-0.183
0.041
<0.0005
0.064
0.044
0.147
-6.239
1.377
<0.0005
-0.779
0.388
0.045
2.430
0.256
<0.0005
0.203
0.271
0.454
1.338
0.409
0.001
2.423
0.298
<0.0005
1.816
0.211
<0.0005
–732.3
149
342,273
The results for asymmetry in export partner concentration are mixed.
Model 8C indicate that the risk of fatal dispute is not affected by asymmetry in
export partner concentration as Hypothesis 8 implies – the parameter estimate
is very close to zero. In Model 8D, however, the estimate for the ‘Concentration
112
The Limits of the Liberal Peace
Asymmetry’ variable is negative and significant, with a p-value of 0.045. This is
in support of Hypothesis 8.
Note that the estimate for ‘Export Partner Concentration’ (the main term) is
negative and strongly significant. Dyads where both states have highly concentrated trade are estimated to have a low risk of fatal dispute. This is slightly
surprising, and contradicts Gasiorowski’s (1986) nation level result for the same
variable. To interpret this, it is important to keep the levels of analysis from
each other. At the nation level, having a high export partner concentration
means that the country has a large share of its trade with one or a few trading
partners. In many cases, this reflects a small country’s asymmetrical dependence on a large country. The ‘Lowest Export Concentration’ index used here is
equal to the lowest value for export partner concentration in the dyad. If the
dyad has a high value on this variable, the export partner concentration has to
be high for both states. Their relationship, then, is not very asymmetrical. Accordingly, the strong negative estimate for this variable is supportive of Hypothesis 1 rather than Hypothesis 8: If both countries have a high export partner concentration, they should care more for the trade with all their trading
partners. Assuming that countries want to minimize their dependence on a single trading partner, the trading relationships with other countries become more
important as countries try to direct more of their trade to those. Disproportional
dependence on one partner, then, may affect the trade-conflict calculations for
all partners.
The result for ‘Lowest Export Concentration’ has an alternative interpretation: Countries with high export concentration are typically dependent on the
regional major power. To the extent that the major power is interested in peace
and stability in the region, it may use its economic power to force the minor
states to keep peace between them. The variable, then, is rather a proxy for regional hegemony than for particularly strong trade dependence.
I also investigated the models without controlling for power asymmetry.
This did not change the other parameter estimates.
Hypothesis 9 were tested by adding interaction terms between the trade
asymmetry and interdependence variables. None of these were close to be significant – the hypothesis is clearly not supported.
Chapter 6: Testing the Hypotheses
6.6
113
Hypothesis 10: Development Asymmetry
Hypothesis 10 predicts a weakening of the relationship between development
and peace with increasing development asymmetry. I am not aware of any
comparable studies that have tested this hypothesis.
6.6.1 Results from the Cox regression analysis
Hypothesis 10 was tested by adding the development asymmetry variable (see
section 5.6.3) to the model. The results are reported in Table 6–6. The hypothesis
receives no support: The coefficients’ signs are right, but both p-values are
larger than 0.25. The estimates for lowest development score and this variable’s
interaction with interdependence is changed little by the inclusion of the
asymmetry variable. It seems that the ‘least developed’ variable captures adequately the relationship between development and the risk of dispute.
6.7
Summary of Results
The Cox regression analysis reported in this chapter yielded statistically significant evidence for the ‘peace through interdependence’ hypothesis (Hypothesis
1). Likewise, dyads with two developed states have a lower probability of fatal
disputes, confirming Hypothesis 4. However, both relationships became much
clearer when I added the interaction between them, as predicted by Hypothesis
5. Dyads that are both highly developed and interdependent were estimated to
have considerably lower hazard of dispute than dyads that are not interdependent or not developed. This result held equally well for two different measures of interdependence and for two measures of development. Both in terms of
statistical and substantial significance this finding was very strong.
I found less conclusive results for the remaining hypotheses. Power asymmetry is positively associated with the probability of dispute rather than negatively as predicted by Hypothesis 6. Increasing asymmetry in the gains from
trade decreases the likelihood of armed conflicts, supporting Hypothesis 8. According to Hypothesis 7 and 9, the effect of trade should be weaker the more
asymmetric the dyad is in terms of power or the gains from trade. Neither of
these hypotheses received any support.
114
The Limits of the Liberal Peace
Table 6-6 Test of Hypothesis 10: Estimated Effect of Development Asymmetry on the
Risk of Fatal Dispute, 1950–92
Variable
Category
Interdependence Measure
Development Measures
Power Asymmetry Measure
Interdependence
Development
Interdependence
* Development
Interaction
Power
Asymmetry
Export
Concentration
Index
Development
Asymmetry
Relevance
Contiguity
One Major
Power
Two Major
Powers
Peace History
Time in Peace
(exp(–Days in
Peace/3,162))
Past Dispute
Log likelihood
No. of disputes
No. of obs.
The figures in each cell are:
Model 10A.
GMM
GDP
Size
1.010
0.286
<0.0005
-0.806
0.160
<0.0005
-0.162
0.041
<0.0005
0.128
0.083
0.123
-5.283
1.557
0.001
-1.258
1.440
0.382
2.978
0.349
<0.0005
Model 10B.
Ln(Salience)
En. Cons.
Capabilities
-0.367
0.070
<0.0005
-0.364
0.068
<0.0005
-0.141
0.027
<0.0005
0.083
0.043
0.0056
-5.642
1.263
<0.0005
-0.125
0.111
0.262
2.387
0.261
<0.0005
0.246
0.279
0.379
1.529
0.420
<0.0005
2.371
0.295
<0.0005
1.825
0.211
<0.005
–731.1
149
342,273
2.525
0.332
<0.0005
1.795
0.262
<0.0005
–441.7
103
265,200
Parameter estimate
Robust standard error
p-value (two-sided test)
Finally, the estimation of a model with an indicator of development asymmetry showed no signs that the risk of fatal dispute depends on symmetry in
terms of development, contrary to what predicted by Hypothesis 10.
Chapter 7
Conclusion
T
his thesis has explored ‘the limits of the liberal peace’. The liberal peace
rests on two arguments: That democracies are very unlikely to fight
wars with each other, and that extensive trade between two countries
decreases the risk of armed conflict between them since the costs of breaking
the trade bonds then adds to the war costs. I have concentrated on the ‘peace
through interdependence’ argument. A literature survey suggested three major
criticisms: Firstly, can we be sure that any correlation between trade and conflict reflects that trade leads to peace rather than the opposite – that peace is a
prerequisite for maintaining trade bonds? Secondly, does the liberal peace require a certain level of socio-economic development? And finally, is the liberal
proposition confined to symmetric trade relationships?
To evaluate these questions theoretically, I constructed a simple gametheoretical model (section 3.2.1). The game captured the logic behind the ‘peace
through interdependence’ argument: In situations where trade is extensive, the
threat of economic sanctions may be sufficiently serious to deter a military action. Trade may thus reduce the likelihood of militarized conflict between
states. In situations with limited trade, trade has no effect on the military
choices of states, since the threat of economic sanctions is not sufficiently serious. With this model as a point of departure, I discussed the three objections to
the ‘peace through interdependence’ hypotheses. The arguments and counterarguments were formulated as empirically testable hypotheses.
Most of the hypotheses were tested for time-series data for a wide range of
countries in Chapter 6. A crucial question when evaluating the proposition that
states that trade much have few wars, is how to interpret ‘much trade’. I introduce a new measure of economic interdependence based on the extent to which
the dyadic trade deviates from expected trade, given the size of the two states’
economies and the distance between them. In contrast to the measures of inter-
116
The Limits of the Liberal Peace
dependence used so far in the literature, this ‘Gravity Model Measure’ is independent of the size of the states in the dyad, and has a roughly symmetric distribution. I also argued that using a particular formulation of Cox regression
avoids several methodological problems that plague former studies of these
questions. This method allows efficient use of available information and allows
the precise modeling of temporal dependence, such that the estimates for standard errors and significance levels are reliable.
I found evidence for a liberal peace, but also for the idea that there are limits to it: Rosecrance (1986) argues that socio-economic development increases
the potential gains from trade as well as the economic and political costs of war,
and thereby decreases the utility of occupying territories relative to the pursuit
of wealth. Based on this assumption, the game-theoretical model corroborated
Rosecrance’s conclusion that we should expect the peace-conducive effect of
trade to be more marked for dyads where both states have a high level of socioeconomic development than for dyads where at least one of the countries are
less developed. The empirical testing of this hypothesis strongly supported this
hypothesis: For highly developed countries, trade strongly reduces the likelihood of conflict. For the least developed countries, there is no such effect. In one
model, I even found evidence for the opposite, that much trade is related to
much conflict.
The insignificance of the development asymmetry variable demonstrated
that it is the level of development of the least developed country in the dyad
that determines the dyad’s probability of dispute. In other words, a dyad consisting of one rich and one poor country are as dispute-prone as one made up of
two poor countries. Increasing wealth in the richest of the two countries does
not change the likelihood of militarized conflict between them. To some extent,
this suggests that the liberal peace is the rich world’s peace.
I found no support for the symmetry objection to the liberal peace. The review of the theoretical literature proved highly inconclusive: On the issue of
power asymmetry and the likelihood of war, there is a long-standing debate between balance-of-power and power-preponderance theorists. The first claim
that symmetrical relationships are the most peaceful, while the latter maintain
the opposite. On the issue of trade asymmetry, Albert Hirschman (1945/1980)
Chapter 7: Conclusion
117
argues that asymmetric dependence may be exploited by the stronger power.
However, it is far from evident that this exploitation will take the form of militarized conflict nor of political concessions. It may simply be reflected in that
the terms of trade will favor the stronger party. Similar arguments apply to the
question of development asymmetry. Still, both the game-theoretical model and
the empirical testing suggested that dyads with asymmetric trade relationships
are less likely to engage in militarized disputes than are symmetric.
Based on the game, I argued in section 3.3.3 that causation flows from trade
to peace rather than from peace to trade – at least to a greater extent than the
opposite. States that expect militarized conflict with another state will have incentives to reduce the level of trade with that partner, just as claimed by neorealists. On the other hand, the game demonstrated that there exists a threshold
of interdependence over which military gains will not outweigh the gains from
trade. Over this threshold, no state will have any security-related incentives to
reduce the bilateral trade. However, this argument was based on judging
whether the two states in the model would have reason, in retrospect, to regret
the trade level between them before the game started. To provide a firmer basis
for my conclusion, it would be useful to extend the model so that the states
might choose trade levels endogenously with the aim of maximizing utility at
the end of the game. However, that has to be left to future work.
The final result that should be noted concerns the democratic peace. In a
majority of the models reported in Chapter 6, the regime type variables had
non-significant parameter estimates. This is puzzling, given the firm evidence
for the democratic peace in previous studies. The explanation is probably that
the democratic peace and the ‘development/interdependence peace’ are highly
interrelated: Socio-economic development, market economy, free trade and
democracy strongly tend to go together, such that a double democratic dyad is
very likely to be highly developed and interdependent. Theoretically, they are
based on the same liberal framework, and both rest on the interest of individuals rather than the interests of the state. It is interesting, though, that I obtain
significantly more robust results for the interdependence variables than for my
regime variables. The ‘interdependence peace’ might be a more general phenomenon than the democratic peace, as it applies to all states, independent of
118
The Limits of the Liberal Peace
regime type. Moreover, the results of the analysis suggested that socioeconomic development is the most general phenomenon of these, since the
peace-promoting effect of trade seemed contingent on a certain level of development.
There is a large literature on the relationship between development and
democracy that supports this idea. This argument builds on Lipset’s (1960: 49–
50) assertion that ‘the more well-to-do a nation, the greater the chances that it
will sustain democracy’. As could be expected from that argument, the support
for the democratic peace in my statistical model was further weakened when
adding the development variable to the statistical model. Just as for interdependence, my analysis suggests that ‘peace trough development’ may be a
more general phenomenon than the democratic peace.
There are caveats to note to all of these findings. The strongest apply to the
direction-of-causation argument. My choice of a single-equation method is inappropriate if we have no firm theoretical basis for assuming one direction of
causation or the other. The results of my analysis also supports hypotheses
where the direction of causation is reversed. I found justifications for assuming
that causation flows from trade to peace and not vice versa through surveying
the handful of studies that have tested the direction of causation statistically,
using simultaneous-equation models (section 6.2). Many of these studies lend
support to the trade-to-peace assumption, although they are far from unanimous. All in all, I think that it is justifiable to test the peace through interdependence proposition in a single-equation model, assuming that trade causes
peace and not vice versa. I admit, however, that my analysis is vulnerable to
this critique, but have to leave simultaneous-equation modeling to future work.
I have argued that the level of development, to some extent, at least, is
causally prior to both trade and democracy. However, this may not hold either.
A military-political state may increase its power and wealth through military
conquest without increasing the output per capita. A trading state in Rosecrance’s terms will have to increase its economic output per capita in order to
increase its power and total wealth. But this implies that choosing to be a trad-
Chapter 7: Conclusion
119
ing state is causally prior to increasing the level of development. Trade, then,
may cause development, rather than the opposite.50
The empirical analysis is not immune to this criticism, either, as the analysis presented here covers the years 1950–92. The major part of this period was
characterized by the Cold War. Farber & Gowa (1995) warn against concluding
that there is a democratic peace since it may only be found in the post-1945 period – which coincides with the Cold War. This objection of course applies as
much to the results for development and interdependence as to the studies of
the democratic peace. Moreover, the analysis excludes World War II. Many of
the participants in that war had high levels of development according to the indicators used here.
My regime variable was rather crudely constructed. I would probably have
obtained more significant estimates with a refined variable. However, this is
highly speculative. Firstly, the results obtained in this analysis may hide important interactions between democracy, interdependence, and development.
Moreover, the debate on the relationship between democracy and development
is not settled yet, and the substantial importance of the ‘development causes
democracy’ finding may have been overstated (Gleditsch, 1999; Przeworski &
Limongi, 1997).
In contrast to the strong support for Hypothesis 1, 4, and 5, most of the hypotheses concerning asymmetry received little support. This may reflect weaknesses in how the game-theoretical model captures the interdependence and
conflict relationship. However, it is possible that the research design employed
is unsuitable. Instead of looking at the outcomes in the dyads as units, it might
have been more appropriate to study what each state does towards the other
within the dyad. This ‘directional dyad’ design would allow more precise testing of under what conditions a militarily strong party alters the status quo by
force, when a unilaterally dependent actor accepts the change without contestation, etc. This, too, is left for future work.
All in all, this thesis suggests that there is a liberal peace, but that it is
largely confined to the developed world. However, since many underdeveloped countries experience some economic growth, this may provide a hope for
50
I am grateful to Soo Yeon Kim for pointing this out to me.
120
The Limits of the Liberal Peace
the long-term future. Still, the model developed here predicts that high levels of
trade, development, and democracy on only one side of a conflict do little to
prevent wars like the one presently fought over Kosovo. In order to reach a
point where major war really is obsolete, every country in the world have to
reach a sufficient level of development, interdependence and democracy.
Appendices
Appendix 1: Results of Gravity Model Regressions
Year
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
Intercept
5.760
5.398
5.359
5.075
4.965
5.559
5.792
6.431
6.944
7.178
7.360
2.146
2.108
2.326
2.427
2.502
1.879
1.459
1.603
1.619
1.622
-3.562
-1.972
-1.160
0.149
0.423
-0.425
-0.709
-2.540
-1.956
-0.921
-2.633
-2.484
-2.387
-2.731
-4.317
-6.898
-3.818
-0.177
1.250
3.313
6.926
7.354
8.520
ln(GDP
country 1)
0.264
0.251
0.272
0.281
0.287
0.250
0.251
0.240
0.225
0.222
0.232
0.460
0.458
0.452
0.455
0.456
0.467
0.481
0.478
0.494
0.495
0.809
0.736
0.754
0.672
0.637
0.666
0.669
0.783
0.742
0.687
0.767
0.722
0.722
0.718
0.762
0.967
0.749
0.647
0.557
0.462
0.307
0.204
0.198
ln(GDP
country 2) ln(Distance) Contiguous
0.125
-0.972
0.689
0.128
-0.912
0.682
0.140
-0.918
0.614
0.168
-0.907
0.319
0.177
-0.920
0.133
0.160
-0.936
0.160
0.149
-0.929
0.489
0.124
-0.972
0.497
0.130
-1.019
0.442
0.113
-1.028
0.286
0.120
-1.061
0.388
0.388
-1.094
0.384
0.390
-1.099
0.484
0.396
-1.133
0.299
0.396
-1.138
0.275
0.377
-1.125
0.319
0.375
-1.050
0.479
0.392
-1.036
0.340
0.399
-1.064
0.417
0.399
-1.099
0.513
0.408
-1.102
0.418
0.644
-1.096
0.513
0.515
-1.069
0.523
0.508
-1.195
0.567
0.514
-1.245
0.347
0.524
-1.234
0.375
0.600
-1.273
0.355
0.572
-1.220
0.344
0.644
-1.215
0.311
0.615
-1.211
0.299
0.622
-1.274
0.143
0.732
-1.303
0.313
0.682
-1.227
0.513
0.669
-1.245
0.507
0.706
-1.262
0.423
0.842
-1.304
0.407
0.895
-1.319
0.354
0.841
-1.352
0.266
0.572
-1.319
0.461
0.499
-1.273
0.611
0.395
-1.261
0.829
0.219
-1.242
0.815
0.184
-1.123
0.912
0.161
-1.186
0.948
122
The Limits of the Liberal Peace
Appendix 2: Descriptive Statistics
Gravity Model Measure
Smallest
-13.49976
Largest
8.322582
Obs
272279
Sum of Wgt.
272279
Mean
-.0539972
Std. Dev.
1.875232
Variance
3.516494
Skewness
-.4835237
Kurtosis
4.438289
Percentiles
1%
5%
10%
25%
50%
75%
90%
95%
99%
Ln(Salience)
Smallest
Largest
Obs
Sum of Wgt.
Mean
Std. Dev.
Variance
Skewness
Kurtosis
-3.912023
13.0083
360302
360302
5.451949
5.414913
29.32128
-.9745797
2.310397
Percentiles
1%
5%
10%
25%
50%
75%
90%
95%
99%
Salience
Smallest
Largest
Obs
Sum of Wgt.
Mean
Std. Dev.
Variance
Skewness
Kurtosis
0.00
44.61
360302
360302
1.162876
2.804268
7.863919
5.985692
55.8359
Percentiles
1%
5%
10%
25%
50%
75%
90%
95%
99%
0.00
16.86
267617
267617
0.1634704
0.5720738
0.3272684
11.71647
211.803
Percentiles
1%
5%
10%
25%
50%
75%
90%
95%
99%
Least Dependent
Smallest
Largest
Obs
Sum of Wgt.
Mean
Std. Dev.
Variance
Skewness
Kurtosis
Lowest GDP per Capita
Smallest
5.3982
Largest
10.3725
Obs
307724
Sum of Wgt.
307724
Mean
7.332731
Std. Dev.
.9328675
Variance
.8702418
Skewness
.3472121
Kurtosis
2.236911
Percentiles
1%
5%
10%
25%
50%
75%
90%
95%
99%
-5.132803
-3.254503
-2.431556
-1.168284
.0854435
1.163495
2.140983
2.789507
4.110505
-3.912023
-3.912023
-3.912023
4.60537
7.696222
9.239902
10.32876
10.89859
11.8671
0.00
0.00
0.00
0.01
0.22
1.03
3.06
5.41
14.25
0
0
0
0
2
11
38
74
215
5.7038
6.0355
6.1944
6.5681
7.2277
8.0024
8.674
9.0034
9.3808
Lowest Energy Consumption per Capita
Smallest
-6.723
Percentiles
Largest
3.108
1%
-5.062
Obs
420956
5%
-4.254
Sum of Wgt.
420956
10%
-3.733
Mean
-1.382212
25%
-2.794
Std. Dev.
1.775448
50%
-1.331
Variance
3.152214
75%
-.056
Skewness
-.1087326
90%
1.125
Kurtosis
2.227923
95%
1.448
99%
1.763
Interaction GMM*GDP per Capita
Smallest
-104.6917
Largest
60.04597
Obs
266095
Sum of Wgt.
266095
Mean
.0768475
Std. Dev.
13.48074
Variance
181.7303
Skewness
-.4234311
Kurtosis
4.721182
1%
5%
10%
25%
50%
75%
90%
95%
99%
Percentiles
-35.26076
-21.90557
-16.72092
-8.187718
.7304448
8.796741
16.33345
20.67033
31.19423
Interaction ln(Salience) * Energy Cons. per Capita
Smallest
-35.64909
Percentiles
Largest
125.8497
1% -30.25246
Obs
269676
5% -27.54612
Sum of Wgt.
269676
10% -26.16987
Mean
43.32729
25% 31.85857
Std. Dev.
41.16765
50% 56.43036
Variance
1694.775
75% 72.10283
Skewness
-.7790376
90% 85.03701
Kurtosis
2.24846
95% 92.66002
99% 104.3834
Size Asymmetry
Smallest
Largest
Obs
Sum of Wgt.
Mean
Std. Dev.
Variance
Skewness
Kurtosis
.000017
9.6317
274024
274024
1.577872
1.282645
1.645177
1.183514
4.419881
Power Asymmetry
Smallest
-12.09076
Largest
11.29876
Obs
409905
Sum of Wgt.
409905
Mean
.1457514
Std. Dev.
2.333733
Variance
5.446311
Skewness
.2406773
Kurtosis
3.562488
1%
5%
10%
25%
50%
75%
90%
95%
99%
Percentiles
.0218
.0983
.2094
.59
1.272
2.2553
3.4108
4.0752
5.6214
1%
5%
10%
25%
50%
75%
90%
95%
99%
Percentiles
-5.221356
-3.50323
-2.69711
-1.384296
.0886517
1.498618
3.086473
4.1963
6.298003
Appendices
Energy Consumption per capita Asymemry
Smallest
-6.395596
Percentiles
Largest
7.967627
1% -3.652776
Obs
301009
5% -2.214972
Sum of Wgt.
301009
10%
-1.64408
Mean
-.2933757
25% -.8513989
Std. Dev.
1.223893
50% -.2756721
Variance
1.497913
75% .2026629
Skewness
.4113423
90% .9445625
Kurtosis
6.870903
95% 1.728447
99% 3.650894
Export Partner Concentration Asymmetry
Smallest
0
Percentiles
Largest
1.493434
1% .0045351
Obs
406928
5% .0226043
Sum of Wgt.
406928
10% .0451696
Mean
.3089314
25% .1160824
Std. Dev.
.2463475
50% .2524672
Variance
.0606871
75%
.441647
Skewness
1.115976
90%
.65814
Kurtosis
4.044418
95% .8097369
99% 1.058739
Lowest Export Partner Concentration
Smallest
.1881
Percentiles
Largest
1
1%
.2001
Obs
406928
5%
.2376
Sum of Wgt.
406928
10%
.2505
Mean
.3407272
25%
.2746
Std. Dev.
.0936066
50%
.3161
Variance
.0087622
75%
.3814
Skewness
1.438917
90%
.4683
Kurtosis
5.655206
95%
.5346
99%
.6557
GDP per capita Asymmetry
Smallest
0
Largest
.5914569
Obs
307724
Sum of Wgt.
307724
Mean
.0987633
Std. Dev.
.0795491
Variance
.0063281
Skewness
1.129109
Kurtosis
4.319898
Time in Peace
Smallest
Largest
Obs
Sum of Wgt.
Mean
Std. Dev.
Variance
Skewness
Kurtosis
1.00
0.63
0.26
0.22
0.27
0.27
0.99
0.62
0.06
0.13
0.01
-0.04
-0.08
0.18
-0.06
0.01
1.00
0.42
0.30
0.54
0.58
0.62
0.98
0.10
0.23
0.00
-0.02
-0.13
0.31
-0.32
-0.21
1.00
0.34
0.321
0.23
0.35
-0.13
0.04
-0.15
-0.05
-0.16
0.12
-0.16
-0.10
1.00
0.91
0.29
0.67
0.21
0.27
0.02
-0.00
-0.43
0.45
-0.37
-0.37
1.00
0.29
0.68
0.20
0.25
-0.03
-0.00
-0.24
0.49
-0.43
-0.37
1.00
0.61
0.07
0.15
0.03
-0.04
-0.09
0.19
-0.07
-0.00
1.00
0.13
0.26
0.00
-0.02
-0.19
0.37
-0.36
-0.25
1.00
0.15
0.68
0.06
-0.06
0.12
-0.10
0.02
1.00
0.05
0.13
0.01
-0.05
0.04
1.00
0.01
-0.02
-0.23
0.03
Percentiles
3.73e-08
.0000202
.0012286
.0247409
.1314944
.3788672
.6847107
.8243021
.9558966
1.00
-0.19
-0.02
0.05
1.00
-0.21
-0.08
Tip
Encoasym
Gdpasym
Expasym
Trdasym
1.00
0.13
-0.06
-0.06
0.20
-0.14
-0.06
1%
5%
10%
25%
50%
75%
90%
95%
99%
Expconasym
1.11e-09
.9996802
439201
439201
.2379442
.2680182
.0718337
1.171506
3.257793
Lncap
Saliwlt
gmmwlt
Or_least
1.00
0.65
0.37
0.36
0.27
0.47
0.04
0.15
-0.06
0.04
-0.15
0.18
-0.23
-0.10
Percentiles
.0013511
.0067865
.0135383
.0354405
.080406
.1442658
.21241
.2502853
.3389342
Gdpcapmi
1%
5%
10%
25%
50%
75%
90%
95%
99%
Kb_salie
Lnsali
Gmm
gmm
lnsali
kb_salie
or_least
Gdpcapmi
Eccapmin
gmmwlt|
Saliwlt
ln_size_
Lncap
Trdasym
Expasym
Gdpasym
Encoasym
Expconmi
tip
1%
5%
10%
25%
50%
75%
90%
95%
99%
Ln_size
Percentiles
.0267191
.1308157
.260552
.6675973
1.448918
2.490702
3.605879
4.402686
5.809694
Eccapmin
Trade Asymmetry
Smallest
3.90e-06
Largest
15.62459
Obs
408014
Sum of Wgt.
408014
Mean
1.73836
Std. Dev.
1.351902
Variance
1.827638
Skewness
1.115512
Kurtosis
4.49197
123
1.00
0.26
1.00
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