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European Economic Review

European Economic Review 56 (2012) 54–71

0014-29

doi:10.1

E-m1 D2 Sc

journal homepage: www.elsevier.com/locate/eer

Trade, conflict, and political integration: Explaining theheterogeneity of regional trade agreements

Vincent Vicard

Banque de France, France

a r t i c l e i n f o

Article history:

Received 7 December 2009

Accepted 29 June 2011Available online 21 July 2011

JEL classification:

D74

F15

F51

F52

Keywords:

International relations

Regionalism

Trade

War

21/$ - see front matter & 2011 Elsevier B.V. A

016/j.euroecorev.2011.06.003

ail address: vincent.vicard@banque-france.fr

eclaration of 9 May 1950, http://europa.eu/ab

hiff and Winter (2003) identify a third chann

a b s t r a c t

Many historians argue that the main goal of European trade integration was the

preservation of peace. This paper investigates whether this reasoning is relevant for the

EU and other regional trade agreements (RTAs). I provide empirical evidence that customs

unions and common markets (deep RTAs) do reduce the probability of war between

members. Partial scope and free trade agreements (shallow RTAs) however have no effect

on war probabilities. Accordingly, international insecurity has a differential impact on

incentives to create RTAs. Deep RTAs are signed between countries that are involved in

many interstate disputes and that have low trade costs with the rest of the world, whereas

the opposite is true for shallow RTAs.

& 2011 Elsevier B.V. All rights reserved.

1. Introduction

The European Union (EU) is unquestionably the most integrated regional trade agreement (RTA) in the world, and ayardstick for other regions of the world. Many historians argue that the main goal of the European integration process wasthe preservation of peace after three increasingly destructive wars in Europe in less than a century. This view is illustratedby Robert Schuman’s proposal for the creation of the European Coal and Steel Community, the forerunner to EU: ‘‘by

pooling basic production and by instituting a new High Authority, whose decisions will bind France, Germany and other member

countries, this proposal will lead to the realization of the first concrete foundation of a European federation indispensable to the

preservation of peace’’.1 This paper investigates whether the reasoning linking security and regional trade integration isrelevant for Europe and other regions of the world by asking two questions: do RTAs prevent the outbreak of war and isinternational security a motive for RTA creation?

The literature in international relations identifies two channels through which regional trade integration is likely to affectinternational insecurity (Bearce, 2003).2 First, since war disrupts bilateral trade (Martin et al., 2008; Glick and Taylor, 2010), anRTA increases the opportunity cost of war by increasing intra-regional trade (Martin et al., 2008; Polachek, 1980; Oneal andRussett, 1999). Second, supranational institutions created in relation to regional integration promote the exchange ofinformation on military capabilities and resolve and patience in conflicts, through formal security/military substructures, jointmilitary exercises and forums of defence ministers. Moreover, regular meetings of head of states and high level officials or the

ll rights reserved.

c/symbols/9-may/decl_en.htm.

el related to access to raw materials.

V. Vicard / European Economic Review 56 (2012) 54–71 55

existence of an executive secretariat create habits of negotiation and build trust between political leaders.3 Internationalinstitutions are thus likely to reduce asymmetries of information in conflicts and to mitigate problems of crediblecommitment in interstate negotiations, which reduces the probability that a dispute escalates into war (Fearon, 1995;Grossman, 2004).4

Supranational institutional frameworks however differ greatly depending on the form of regional trade integration.Creating a customs union requires agreement on a common external tariff and revenue distribution between memberstates. A common market requires more comprehensive political institutions to agree on a broader set of issues(harmonization of regulation and standards, free movement of goods and factorsy),5 whereas a free trade agreementor partial scope arrangement involves little or no political or institutional integration.6 According to the politicalintegration criterion, two categories of RTAs can be distinguished: deep (customs unions and common markets) andshallow (partial scope and free trade agreements) RTAs. Only deep RTAs require a significant common institutionalframework likely to promote the negotiated settlement of conflicts and support peace between members.

If countries can design regional trade agreements to pacify interstate relations, international security should affect decisionson trade policy. In a purely economic framework in which RTAs have no effect on war probabilities, two partners that have moreissues of dispute would have fewer incentives to create an RTA since disputes may escalate into war and disrupt bilateral trade.7

Conversely, if an RTA reduces the probability of war between members, then having more disputes may increase the likelihoodof an RTA being set up. To the extent that only deep RTAs pacify relations between members, international insecurity shouldhave a differential effect on incentives to create RTAs (and should affect both the choice of form of trade integration and thechoice of partner). In a nutshell, a history of conflicts should enhance the creation of deep RTAs, but not shallow ones.

In this paper, I set out an empirical analysis of the relevance of international security in the creation of shallow anddeep RTAs. The motives for choosing different strategies of integration are based on the premise that a deep RTA reducesthe probability of war between members while a shallow RTA does not. I first test this proposition using data onmilitarized interstate disputes from the Correlates of War (COW) project covering the 1950–1991 period. I address theselection issue due to the heterogeneity of dispute occurrence across country pairs using a bivariate probit modelaccounting for selection and event data from Kinsella and Russett (2002) to measure interstate dispute occurrence. I find asizeable impact of membership in a deep RTA: it reduces the probability of a dispute escalating into war by two-thirds.Membership of a partial scope or free trade agreement has no significant effect on war probabilities.

Second, I test the determinants of the likelihood of deep and shallow RTAs on a cross-section of 2814 unique countrypairs in 2005. The endogeneity bias related to past membership of RTAs and omitted variables is addressed by controllingfor several co-determinants of regionalism and conflict and by implementing an instrumental variable strategy. I find thatdeep RTAs are signed between countries that have many interstate disputes and that have low trade costs with the rest ofthe world, whereas the opposite is true with respect to shallow RTAs. These empirical results provide strong support forthe differential effect of international insecurity on incentives to create deep and shallow RTAs. Besides the reduction oftariffs, this paper explicitly emphasizes the role of RTAs as a regulating mechanism for interstate relations. By offeringempirical evidence on the choice of RTA partners as well as the form of regional integration, this paper complements Baierand Bergstrand’s (2004) analysis of the economic determinants of RTAs.

This paper is related to the theoretical literature on the endogenous formation of RTAs that emphasizes non-traditionalgains from regional integration.8 This strand of the literature explicitly recognizes various motives for regional integrationand identifies distinct problems that a trade agreement may solve (Maggi and Rodriguez-Clare, 1998; Mitra, 2002; Limao,2007). Regional trade integration may indeed provide non-traditional gains and help solving problems of timeinconsistency, signaling, insurance, cooperation and security (Fernandez and Portes, 1998; Whalley, 1998; Schiff andWinters, 1998). In such a framework, RTAs are not only regarded as engines of preferential liberalization but also asinternational institutions providing public goods to their members (Limao, 2007; Alesina et al., 2005). These papershowever only consider the case of free trade agreements or customs unions, or do not distinguish between RTAs accordingto the form they take.9 The usual classification of RTAs, derived from Balassa (1961), considers regional trade integration asa step-by-step process leading to economic union, through free trade area, customs union and common market. Theunderlying assumption is that more integrated arrangements provide deeper trade integration.10 Vicard (2009) however

3 For instance, Manzetti (1993/94) reports that discussions of sensitive policy issues such as nuclear proliferation concerns have taken place within

the MERCOSUR institutions.4 Jackson and Massimo (2007) also show, in a setting where countries are at war because of the political biases of their leaders that when state

leaders lack the ability to credibly commit to a negotiated deal, the scope for negotiated settlement of disputes is reduced.5 See, for instance, Alesina and Wacziarg (1999) for a detailed mapping of policy areas carried out at the EU level, and Bouzas and Soltz (2001)

concerning the institutional framework of MERCOSUR.6 The ASEAN free trade agreement is an illustrative example, with weak regional institutions in order to limit any supranationalism (Best, 2005).

Pomfret (1997) also emphasizes how the will to limit political integration has been fundamental to the creation of NAFTA.7 This reasoning assumes either that negotiating or implementing an RTA involves costs or that increasing trade integration increases the number of

disputes and thus the probability of trade disruption in the future.8 The optimal tariff strand of the literature focuses on traditional trade gains (Riezman, 1985; Yi, 1996; Ornelas, 2005).9 From an empirical point of view, Mansfield and Pevehouse (2000) and Martin et al. (2010) also investigate the impact of RTAs on security without

differentiating between RTAs.10 In his seminal paper, Balassa (1961) also mentions social integration, but he dismisses this second criterion.

V. Vicard / European Economic Review 56 (2012) 54–7156

shows that different kinds of RTAs have, on average, a similar effect on intra-regional trade. Empirical evidence of gradualregional integration processes is also lacking: out of the 18 customs unions created worldwide since 1948, 14 have beencreated directly as such. This paper offers an alternative explanation for the choice of different strategies of regionalintegration. The form of RTAs reflects different institutional arrangements that provide different non-traditional gains totheir members.

The paper proceeds as follows. The next section presents data on interstate dispute and war. Section 3 presents theanalysis of the impact of RTAs on war probabilities. Section 4 investigates the determinants of the creation of deep andshallow RTAs, and Section 5 concludes.

2. Data on interstate dispute and war

The probability of war between two countries i and j at date t is the probability of occurrence of a dispute between i andj multiplied by the conditional probability that the dispute escalates into war:

PrðwarijtÞ ¼ PrðdisputeijtÞ � Prðescalationijt9disputeijtÞ: ð1Þ

The probability of dispute varies by country pair and over time. Disagreements over territorial issues or religious andethnic minorities are more likely to occur between neighboring countries. Policies fostering international trade integrationare also likely to increase dispute occurrence. In the same manner, many factors affect the probability of a disputeescalating into war. For instance, one of the few accepted regularities in international relations is that democracies are lessprone to war with each other because their state leaders are accountable to citizens (Oneal and Russett, 1997; Conconiet al., 2008). Accordingly, the history of wars does not accurately reflect the extent of dispute issues at stake between twocountries. The question addressed in this paper is to understand what motivates the choice to settle disputes throughnegotiation rather than through war and how international institutions affect this choice. Distinguishing the presence ofdispute issues between two countries from their most severe outcome, i.e. war, is therefore particularly relevant to thisstudy. In this paper, I use two different sources of data to measure the occurrence of interstate disputes and wars.

The Correlates of War (COW) project provides detailed data on Militarized Interstate Disputes (MIDs) over the period1816–2001 (Faten et al., 2004). War is restrictively defined as a MID involving at least 1000 deaths of military personnel,which reduces the number of events considered as war to less than 100 cases since 1815. Adopting such a restrictivedefinition prevents robust empirical analysis. I follow the literature and use a broader definition of war that includesarmed conflicts involving the display or the use of military force, i.e. a MID of hostility level 3 (display of force), 4 (use offorce) or 5 (war) in the COW database.11 Robustness analysis is conducted on a stricter definition of war, i.e. MID ofhostility levels 4 and 5.

Such qualitative data on military conflicts require that the actors, duration, geographical location and intensity of eachconflict have been coded by researchers. Such a process prevents similar exercises on conflicts of lower intensity. In orderto measure dispute occurrence, I use an alternative type of data: event data. Event data are reported, by trained students orautomatically by computers, on a day-by-day basis from newspapers or wire services and coded by actor, target, form ofaction and date. Data on daily events have the great advantage of providing information on interstate interactionswhatever the intensity of the underlying event. Event data do not allow us to assess the evolution of a given conflict overtime. They nevertheless make it possible to measure the occurrence of disputes that clear a minimum threshold betweentwo countries in a given year and that are resolved through negotiation or using military force. I use the event datacompiled by Kinsella and Russett (2002) to measure disputes exceeding a threshold defined as strong verbal hostility.12

Kinsella and Russett (2002) overlap data from three event databases, the Conflict and Peace Data Bank (COPDAB), theWorld Event/Interaction Survey (WEIS) and the Protocol for the Assessment of Nonviolent Direct Action (PANDA), toconstruct a dummy variable coded 1 if a dispute occurs for any dyad-year over the 1950–1991 period.13 Table 1 providesevent categories coded as disputes and their level of severity according to the Goldstein (1992) scale. Only events classifiedat least as conflictual as categories ‘‘Cancel or postpone planned events’’ and ‘‘Charge; criticize; blame; disapprove’’ arecoded as a dispute.

Table 2 shows that the proportion of MIDs and RTA members remains similar when the sample is restricted due to theavailability of event and trade data. MIDs are nevertheless slightly biased towards less severe MIDs. Out of the 128 368dyad-years of our restricted sample, 7937 experience a dispute, of which 586 spillover into MIDs.

Appendix A provides details on the source of other data. The dataset includes 103 RTAs, comprising 17 partial scopeagreements, 70 free trade agreements, 14 customs unions and two common markets.

11 MID level 2 (threat to use force) is not deemed to be a military conflict. See the COW website (http://www.correlatesofwar.org/) for more

information and records of MIDs.12 See Kinsella and Russett (2002, pp.1054–1055) for more details on databases used and the operationalizing of the minimum conflict intensity

threshold. Schrodt and Gerner (2000) present limitations related to the use of event data. Using events exceeding a certain intensity reduces the biases

they identify.13 One hundred and eighty nine cases exhibit a MID but no dispute in the restricted sample, of which 170 exhibit a dispute in t�1. I follow Kinsella

and Russett (2002) and treat them as measurement errors, due to the fact that event databases rely on major news media and do not cover all regions of

the world equally. The dummy variable is thus recoded as if a dispute occurred.

Table 1Events and Goldstein scale.

Event category Goldstein

Request action; call for �0.1

Explicit decline to comment �0.1

Urge or suggest action or policy �0.1

Comment on situation �0.2

Deny an accusation �0.9

Deny an attributed policy, action, role or position �1.1

Grant asylum �1.1

Make complaint (not formal) �1.9

Cancel or postpone planned events �2.2

Charge; criticize; blame; disapprove �2.2

Issue formal complaint or protest �2.4

Give warning �3

Denounce; denigrate; abuse �3.4

Halt negotiation �3.8

Turn down proposal; reject protest, demand, threat �4

Refuse; oppose; refuse to allow �4

Reduce routine international activity; recall officials �4.1

Detain or arrest person(s) �4.4

Threat without specific negative sanction stated �4.4

Issue order or command, insist, demand compliance �4.9

Expel organization or group �4.9

Order person or personnel out of country �5

Nonmilitary demonstration, walk out on �5.2

Reduce or cut off aid or assistance; act to punish/deprive �5.6

Threat with specific negative nonmilitary sanction �5.8

Ultimatum; threat with negative sanction and time limit �6.9

Threat with force specified �7

Break diplomatic relations �7

Armed force mobilization, exercise, display; military buildup �7.6

Noninjury destructive action �8.3

Nonmilitary destruction/injury �8.7

Seize position or possessions �9.2

Military attack; clash; assault �10

Source: Goldstein (1992).

Table 2Descriptive statistics 1950–1991.

Sample Full Restricteda

Observations 366 546 128 368

MIDs of which: 1969 586

Display of force (3) 14% 20%

Use of force (4) 66% 75%

War (5) 20% 5%

Dispute – 7937

Mean

Deep RTAs 0.007 0.008

Shallow RTAs 0.028 0.042

a Sample conditioning on the explanatory variables in column 4 of Table 3.

V. Vicard / European Economic Review 56 (2012) 54–71 57

3. The impact of regionalism on the likelihood of war

3.1. Empirical strategy

The aim of this section is to test the proposition that RTAs requiring significant political integration do reducesignificantly the probability that disputes between members escalate into war, whereas other RTAs do not. As emphasizedabove, using a simple probit or logit model to estimate the conditional probability of war would severely bias resultsbecause heterogeneity in dispute occurrence creates a selection bias. The literature on the determinants of war have dealtwith this issue either by limiting the sample to ‘politically relevant dyads’ (i.e. pairs of countries sharing a common border

Table 3Impact of RTAs on war: bivariate censored probit model.

Dependent variable (1) (2) (3) (4)

MID MID MID Dispute MID Dispute

Deep RTA membership dum. �0.21 �0.48b�0.67a 0.26a

�0.59b 0.11

(0.20) (0.24) (0.23) (0.09) (0.29) (0.10)

Shallow RTA membership dum. �0.07 �0.09 �0.20c 0.00 �0.06 �0.03

(0.11) (0.15) (0.11) (0.05) (0.12) (0.06)

No. of peaceful years �0.02a�0.03a

�0.01a�0.00a

�0.01a�0.00a

(0.00) (0.01) (0.00) (0.00) (0.00) (0.00)

Log distance �0.23a�0.10 �0.04 �0.28a

�0.08 �0.32a

(0.04) (0.09) (0.06) (0.02) (0.11) (0.02)

Contiguity dum. 0.78a 0.66a 0.47a 0.58a 0.60a 0.29a

(0.10) (0.16) (0.15) (0.07) (0.17) (0.07)

No. of landlocked countries �0.36a�0.22a

(0.03) (0.03)

Bil. trade dependence (t�4) 0.51 1.66a

(0.55) (0.23)

Multil. trade dependence (t�4) 0.26b�0.30a

(0.13) (0.05)

Zero trade dum. (t�4) 0.05 �0.21a

(0.19) (0.03)

Common language dum. �0.28a 0.16a

(0.10) (0.04)

Colonial relationship dum. �0.17 0.55a

(0.24) (0.09)

Common colonizer dum. 0.09 0.11b

(0.13) (0.06)

Sum log area 0.00 0.13a

(0.05) (0.01)

Sum of democracy indexes �0.38a 0.23a

(0.09) (0.03)

Common defense alliance dum. �0.27 0.48a

(0.21) (0.06)

UN voting correlation (t�4) 0.25 �0.99a

(0.37) (0.05)

Observations 201 627 6503 201 627 128 368

Uncensored observations – – 12 047 7937

Log likelihood �4518.0 �924.8 �43 452.2 �2358.3

Rho (Wald test of independent eqn.) – – �0.32 �0.18

Estimation method Probit Probit Bivariate probit with censoring

Sample Full disto1000 km Full Full Full Full

Time dummies Yes Yes Yes Yes Yes Yes

Note: Robust standard errors in parentheses. Intercept and time dummies not reported. Standard errors clustered by country pair.a Significance at the 1% level.b Significance at the 5% level.c Significance at the 10% level.

V. Vicard / European Economic Review 56 (2012) 54–7158

or involving a major power) or by focusing on one cross-sectional determinant of disputes, i.e. bilateral distance. I go onestep further and use event data to directly measure disputes (Kinsella and Russett, 2002).

Determinants of dispute occurrence are indeed numerous. Focusing on some as a proxy for dispute probability ignoresmuch heterogeneity in disputes between country pairs and over time. Indeed, the restricted sample for which data ondisputes and other explanatory variables are available (column 4 of Table 3) contains 584 MIDs at the country pair level,of which 404 (69%) occur between ‘‘politically relevant dyads’’ and 199 (34%) between dyads separated by less than1000 km.14

Since the escalation into war process can only be observed when a dispute has occurred, using a bivariate probitwith censoring is a natural empirical strategy to estimate the conditional probability of war for each dyad-year.The log-likelihood function is based on the unconditional probabilities associated with the three possible outcomes(Greene, 2003, p. 713): no dispute (dispute¼0), a dispute emerges but does not escalate into war (dispute¼1 and war¼0),and the dispute escalates into war (dispute¼1 and war¼1). Two equations are jointly estimated, one explaining the

14 The corresponding figures for the full sample are 1969 MIDs, of which 1358 (69%) are between ‘‘politically relevant dyads’’, and 595 (30%) are

between countries separated by less than 1000 km.

V. Vicard / European Economic Review 56 (2012) 54–71 59

initiation of the dispute and the second the dispute’s escalation into war. Consider y1 and y2, two latent (unobserved)variables, representing the difference in utility levels from the initiation of the dispute and the dispute’s escalation intowar respectively. The model estimated is derived from a standard bivariate probit model:

y1 ¼ b1X1þe1 and dispute¼1 if y140

0 if y1r0,

(

y2 ¼ b2X2þe2 and war¼1 if y240

0 if y2r0,

(ð2Þ

where X1,2 are vectors of explanatory variables, b1,2 vectors of parameters, and error terms e1 and e2 are assumed to beindependent from X1,2 and to follow Eðe1Þ ¼ Eðe2Þ ¼ 0, Varðe1Þ ¼ Varðe2Þ ¼ 1, and Cov½e1,e2� ¼ R.

Wooldridge (2002, p. 564) emphasizes that, technically, the coefficients can be identified due only to the nonlinearity ofthe two equations in the bivariate probit. Hence, it is not necessary for X2 to be a strict subset of X1 for the outcomeequation to be identified. However, the identification of the model’s parameters is better achieved when X1 contains atleast one variable that is not in X2, so that we have an exclusion restriction, i.e. a variable that influences the selectionequation but not the outcome equation. The number of landlocked countries in a dyad is a good candidate as anidentification variable. Having no access to the ocean indeed reduces a country’s geographical scope of interest andreduces the opportunity for contacts with countries other than neighboring countries. Landlocked countries shouldtherefore be less likely to interact with distant countries, through cooperative as well as conflictual actions, and shouldhave less interstate disputes on average. There is however no reason that being landlocked affects the way conflicts aresettled.15

All specifications control for autocorrelation by clustering standard errors by country pair.

3.2. Results

The results are presented in Table 3. All specifications include the basic determinants of war put forward by theliterature in political science: contiguity, distance and the number of peaceful years between the two countries (Beck et al.,1998). I first present the results from a simple probit estimator. Column 1 shows that RTA membership has no significanteffect on war probabilities on the full sample of dyad-years. When only countries separated by less than 1000 km areconsidered, belonging to a deep RTA, but not a shallow one, does significantly reduce war probabilities (specification (2)).These crude results emphasize the need to account for heterogeneity in dispute occurrence. Specification (3) reportsestimates using the bivariate probit accounting for selection. The first and second columns present the results of theescalation into war and dispute initiation equations respectively. As expected, landlocked countries face a lowerprobability of dispute. The coefficient on the exclusion variable is significant at the 1% level in all specifications. Theresults confirm that membership of a deep RTA does significantly reduce the probability that a dispute escalates into war.In this specification, membership of a shallow RTA is found to have a lower, albeit significant, effect on escalation into warprobabilities. It is however not significant when additional controls are included.

Specification (4) in Table 3 includes several potential co-determinants of regionalism and war (see Appendix A for datasource). First, I include year dummies to control for any global shock affecting war probabilities and regionalism over time.Other controls can be divided into two sets: trade and political variables. Regarding trade, we control for both bilateral (thelog of the mean of bilateral imports as a percentage of GDP) and multilateral (the log of the mean of multilateral (excludingbilateral) imports as a percentage of GDP) trade openness.16 Martin et al. (2008) indeed argue that trade has an ambiguouseffect on peace. Bilateral trade does reduce war probabilities but multilateral trade openness, by reducing the dependenceon a particular partner, increases war probabilities. The results confirm that multilateral trade openness increases theprobability that a dispute escalates into war, but show no significant effect of bilateral trade.17 A dummy variable for zerotrade flows is included as well as dummies indicating countries sharing a common language, countries that have had acolonial relationship or a common colonizer. Countries sharing a colonial history are indeed more likely to have unresolveddisputes. They also share historical, cultural and institutional traits that make them more likely to create a RTA.

The set of political variables control for political regime, the size of countries, alliances and diplomatic relations. Thelevel of democracy is included as a control since democracies have been found to be less likely to wage wars (see Levy andRazin (2004) and Jackson and Massimo (2007) for a theoretical treatment, and Oneal and Russett (1997) among others forempirical evidence). Democratic status has also been argued to affect the choice to create an RTA (Mansfield et al., 2002).The (sum of the log of the) area of the two countries is included since a bigger territory is exposed to more opponents.Larger countries also depend less on foreign trade, which could affect their incentives to create RTAs. Finally, I control fordiplomatic affinity between countries using a dummy variable for common membership of a defense alliance and thecorrelation of voting in the UN General Assembly (lagged four years).

15 When introduced into a probit model of the second stage equation, the number of landlocked countries is not statistically significant.16 Following Martin et al. (2008), trade variables are lagged 4 years to remove any contemporaneous reverse effect of war on trade.17 More precisely, the peaceful effect of bilateral trade vanishes when other controls are added. Martin et al. (2008) find a similar pattern.

Table 4Impact of RTAs on war: robustness.

Dependent variable (1) (2) (3) (4) (5) (6) (7)

MID 4 & 5 MID MID MID MID MID MID

Deep RTA membership dum. �0.52c�1.19b

�0.48c�0.51 �0.51c

�0.57b�1.04a

(0.29) (0.59) (0.28) (0.32) (0.27) (0.29) (0.28)

Shallow RTA membership dum. �0.07 �0.23 �0.02 �0.03 �0.05 �0.06 �0.18

(0.11) (0.26) (0.12) (0.12) (0.11) (0.12) (0.39)

No. of major powers �0.36

(0.24)

One communist country dum. �0.46b

(0.22)

Two communist countries dum. �1.45a

(0.40)

GATT membership dum. �0.21a

(0.08)

Sum log military �0.07c

expenditure (t�4) (0.04)

Abs. diff. log military expenditure (t�4) �0.03

(0.02)

First stage IV Shallow Deep

Sum deep RTAs with third countries (t�5) �0.06a 0.24a

(0.02) (0.03)

Sum shallow RTAs with third countries (t�5) 0.18a�0.21a

(0.01) (0.05)

Observations 128 368 55 409 128 368 128 368 123 405 7937 7678 7678

Uncensored observations 7937 5013 7937 7937 7776 – – –

Log likelihood �23 245.2 �12 998.7 �22 659 �23 447.7 �21 642.1 �1543.4 �1462.6

Rho (Wald test of independent eqn.) �0.40 �0.18 �0.22 �0.02 �0.42 – – –

Estimation method Bivariate probit with censoring Probit IV Probit

Sample Full OECD Full Full Full dispute¼1 dispute¼1

Time dummies Yes Yes Yes Yes Yes Yes Yes

Note: Robust standard errors in parentheses. Intercept and time dummies not reported. All estimates include the same control variables as in our

preferred specification (specification (4) in Table 3). In specifications (6) and (7), only the second step of the bivariate censored probit is reported.

Standard errors clustered by country pair.a Significance at the 1% level.b Significance at the 5% level.c Significance at the 10% level.

V. Vicard / European Economic Review 56 (2012) 54–7160

Controlling for all these potential co-determinants of war and regionalism, specification (4) confirms that deep RTAspromote the peaceful settlement of disputes between members. Membership of shallow RTAs has no effect on warprobabilities. Moreover, the insignificant impact of bilateral trade on the likelihood of a dispute escalating into warconfirms that the institutional channel dominates in regional integration. It is worth noting that when all these controlsare added, the Wald test of independent equations is no longer significant, meaning that the two equations estimatedsimultaneously are independent.

3.3. Robustness

Tables 4 and 5 present a number of robustness tests.18 The first column tests the sensitivity of the results to a morerestrictive definition of war including only MIDs of hostility levels 4 and 5, i.e. implying the actual use of military force andwars resulting in the death of at least 1000 military personnel. This more restrictive definition of war reduces slightly thesignificance of the coefficient on deep RTAs but the results remain qualitatively similar. I also restrict the sample tocountry pairs including at least one OECD country in 1991. Event data are indeed coded from international newspaperswhich do not cover all the world’s countries evenly. Disputes involving richer countries may be more likely to be reportedby international newspaper than disputes involving poor countries. On this restricted sample, deep RTAs—but not shallowones—are still negatively and strongly significantly associated with the likelihood of disputes escalating into war. Thecoefficient on deep RTAs is however twice as large as in the benchmark estimation, suggesting measurement errors.Finally, columns 3–5 control for additional potential co-determinants of war and regionalism. Controlling for the numberof major powers, communist regimes, membership of GATT and the level and difference of (log of) military expenditure

18 To save space, only the coefficients of the variables of interest and of the second stage equation are reported. All specifications include the control

variables included in specification (4) of Table 3.

Table 5Impact of RTAs on war: robustness, continued.

Dependent variable (8) (9) (10) (11) (12) (13) (14)

MID MID MID MID MID MID MID

Deep RTA membership dum. �0.54c�0.53c

�0.14a�0.12a

�0.14a�0.10a

�0.58b

(0.31) (0.29) (�0.03) (0.03) (0.04) (0.03) (0.29)

Shallow RTA membership dum. �0.04 �0.02 0.05 0.03 0.00 0.06 �0.06

(0.13) (0.12) (�0.04) (0.04) (0.04) (0.04) (0.12)

One oil exporter dum. 0.17c 0.18b

(0.09) (0.09)

Two oil exporters dum. �0.05 0.03

(0.22) (0.21)

Abs. diff in log GDP per capita (t�4) �0.03

(0.05)

log sum GDP per capita (t�4) �0.11c

(0.06)

Interaction deep RTA 0.87a 0.35 0.76 0.43

(0.2) (0.53) (0.61) (0.92)

Interaction shallow RTA �0.57c�0.34 �0.05 �0.55

(0.3) (0.29) (0.29) (0.42)

Abs. diff in share agriculture in value added �0.06

(0.06)

Avg share of agriculture in value added 0.19

(0.12)

Abs. diff in share industry in value added �0.04

(0.06)

Avg share of industry in value added �0.19b

(0.09)

Abs. diff in share manufacturing in value added �0.17b

(0.07)

Avg share of manufacturing in value added �0.08

(0.12)

Abs. Diff in of share services in value added 0.14

(0.15)

Avg share of services in value added �0.13

(0.26)

Lagged deep RTA membership dum. 0.56

(0.50)

Observations 128 368 128 368 4204 4190 4190 1867 128 368

Uncensored observations 7937 7937 – – – – 7937

Log likelihood �23 456.3 �23 318.9 – – – – �23457.7

Rho (Wald test of independent eqn.) �0.01 �0.15 – – – – �0.19

Estimation method Heckprob LPM Heckprob

Sample Full Full dispute¼1 Full

Time dummies Yes Yes Yes Yes Yes Yes Yes

Note: Robust standard errors in parentheses. Intercept and time dummies not reported. All estimates include the same control variables as in our

preferred specification (specification (4) in Table 3). Standard errors clustered by country pair.a Significance at the 1% level.b Significance at the 5% level.c Significance at the 10% level.

V. Vicard / European Economic Review 56 (2012) 54–71 61

does not affect the results. Nonetheless, omitted (unobservable) variables could bias the results. The next sectionimplements an instrumental variable (IV) strategy to deal with this issue.

3.3.1. Instrumental variables

The domino theory of regionalism suggests that the creation or enlargement of an RTA increases incentives of non-members to apply for membership (Baldwin, 1997). Using spatial econometrics, Egger and Larch (2008) show that theprobability that two countries create an RTA increases with the creation of RTAs by third countries. The number of RTAssigned by each country with third countries could therefore qualify as a strong instrument correlated with the existence ofan RTA between two countries in a given year. Since we control for bilateral and multilateral trade dependence in ourregression, there is no reason to believe that the number of RTAs signed with third countries is correlated with warprobabilities. The number of deep and shallow RTAs signed with third countries in t�5 by the two countries are usedseparately as instrumental variables for RTA membership. The enlargement of an existing RTA to include a new countryindeed extends the same form of RTA; a country that is already a member of a deep RTA would be more likely to create adeep RTA with a new country and less likely to create a shallow RTA.

V. Vicard / European Economic Review 56 (2012) 54–7162

Since our endogenous variables are dummy variables, using the traditional two stage methodology would yieldinconsistent estimates unless the first-stage model is exactly right. The fitted value from a probit model may neverthelessbe used as an instrument, together with other exogenous covariates, to generate first-stage estimates using an ordinaryleast square (OLS) model (Angrist and Krueger, 2001). We thus apply a three stage methodology. In the first stage, fittedvalues for deep and shallow RTA membership are generated using a probit model with our two instruments. The fittedvalues are used, together with other exogenous covariates, to predict the two endogenous RTA membership dummiesusing OLS. These predictions are then used in the estimation of war probabilities. In the third stage, we estimate directlythe probability of war between countries involved in a dispute, i.e. the second stage of the bivariate probit with censoring.The Wald test of independent equations reported in Table 3 indeed shows that the second equation, i.e. dispute escalatinginto war, can be estimated independently when we control for enough covariates. For the sake of comparison, specification(6) in Table 4 presents the estimate of the dispute escalating into war equation using a probit model without IV. Results ondeep and shallow RTA membership are similar to specification (4) in Table 3.

The coefficient on the IVs in the first stage equation are reported at the bottom of column (7) in Table 4. Both aresignificant at the 1% level, confirming that they are strong instruments. As expected from the domino theory ofregionalism, countries that have already signed RTAs with third countries are more likely to conclude similar agreementswith new partners. The results of the final stage of the IV empirical strategy confirm that members of deep - but notshallow - RTAs are less likely to escalate a dispute into war. The coefficient is strongly significant and is almost twice aslarge as in the benchmark regression. It suggests that unobservable variables that make country pairs more likely to belongto the same deep RTA simultaneously increase the probability that a dispute escalates into war.

3.3.2. Asymmetric members

Schiff and Winter (2003) argue that a deep RTA may have negative security effects when countries are very different,because tariff preferences under a common external tariff may lead to large income transfers and a concentration ofindustry in a given country/region. Asymmetric gains from regional integration may therefore increase the risk of conflictsbetween unbalanced members. Table 5 deals with this issue. First, columns 8 and 9 include additional control variables fordifferences in export specialization: dummy variables indicating whether one or two countries in the pair are oil exporters,as defined by the IMF in the DoTS, and the difference and average level of GDP per capita. The results show that poorcountries and country pairs involving one oil exporter are more likely to escalate disputes into war, but the deep RTAvariable remains significant. Differences in GDP per capita are found to have no impact on war probabilities.

A direct test of Schiff and Winter’s argument requires to account for the interaction between asymmetries betweencountries and RTA membership. The non-linearity of our estimator however makes the interpretation of coefficients oninteraction terms potentially misleading (Ai and Norton, 2003). I therefore estimate a linear probability model (LPM) onthe dispute escalating into war stage. This alternative methodology yields the marginal effects on the interaction terms(Angrist and Pischke, 2009). Schiff and Winter’s argument involves a positive coefficient on the interaction betweencountries asymmetries and deep RTA membership. Asymmetries between countries’ structure of production are measuredby the difference in the share of agriculture, industry, manufacturing and services in value added. Columns 10–13 ofTable 5 present the results using, in turn, each measure and its interaction with deep and shallow RTA membershipdummies. The average share of the sector considered (agriculture, industry, manufacturing and services) in value added isalso controlled for. We find weak support for the argument of Schiff and Winter (2003). As expected, the coefficient on theinteraction term with the deep RTA variable is positive, but significant only when using the difference in the share ofagriculture. Note that the impact of deep RTA membership is negative for the median level of differences in productionstructure.

Finally, column 14 shows that deep RTAs that fall apart do not increase conflicts in the following 5 years.

3.4. Quantification

This section aims to quantify the impact of RTA membership on war probabilities. Since the estimator used is nonlinear,coefficients cannot be interpreted immediately. Fig. 1 presents marginal effects (or discrete change for dummy variables) onthe conditional (on dispute occurrence) predicted probability @Prðwar¼ 19dispute¼ 1Þ=@X

� �, computed from specification (4)

in Table 3. The marginal effects are computed at two different levels: at the mean value of all variables and for contiguouscountries separated by 1000 km and exhibiting positive trade flows (all other variables being held at their mean).

For contiguous countries separated by 1000 km, being members of a customs union or common market reduces theprobability that a dispute escalates into war by 9.1 percentage points. This effect is sizeable since the mean predictedconditional probability is 13.8%. The impact of belonging to a deep RTA is comparatively similar when all variables are heldat their mean: it reduces the probability of a dispute escalating into war by 1.9 percentage points, while the predictedconditional probability is 2.5%.

In comparison with other determinants of war, this effect is also sizeable. Belonging to a deep RTA is equivalent toincreasing the number of peaceful years between two countries by 28 years from its mean value. Moreover, the peacefuleffect of sharing a common language or a common defence alliance is two times smaller. Finally, when compared tothe democratic peace channel, the impact of deep RTA membership is shown to be of the same order of magnitude asan increase from the mean to the top level of democracy indexes for the two countries.

0.08

0.12

0.16

0

0.04

Contiguous and trading countries, separated by 1000km

Mean country pair

Predicted probability

Deep RTA membership dum.

10 additional peaceful year

Common language

Sum democracy indexes (1 std.dev.)

Common defence alliance dum.

Fig. 1. Impact of RTAs on war: quantification.

V. Vicard / European Economic Review 56 (2012) 54–71 63

4. Determinants of deep and shallow regional trade agreements

Having established that deep and shallow RTAs have differential effects on the probability that a dispute escalates intowar, this section tests whether security issues are a motive for creating RTAs.

4.1. Empirical specification

In line with Baier and Bergstrand (2004), I estimate the following specification on a cross-section of country pairsin 2005:

PrðRTAhij ¼ 1Þ ¼ b0þb1DPijþb2OPENijþb2Controlsijþeij, h¼ fdeep,shallowg ð3Þ

where Controlsij includes economic and political determinants of regionalism, DPij is the propensity to dispute and OPENij is aproxy for multilateral trade openness. Baier and Bergstrand (2004) show that, in a model of RTA formation in a secure world(i.e. without interstate conflict), two countries facing low trade costs with the rest of the world should have lower welfaregains from joining an RTA compared to country pairs facing high trade costs. Martin et al. (2008) however show that countriesmore open to multilateral trade are more likely to escalate disputes into war. In an insecure world, a country facing low tradecosts should therefore need more mechanisms to prevent dispute from escalating into war and secure gains from trade withtheir partners. They are more likely to create deep rather than shallow RTAs. Trade costs with the rest of the world shouldunambiguously decrease the likelihood of shallow RTAs but are likely to have an ambiguous impact on the likelihood of deepRTAs. Baier and Bergstrand (2004) measure the remoteness of countries by their mean distance to their trading partners.Anderson and van Wincoop (2003) nevertheless show that remoteness indexes are a bad proxy for trade openness andpropose a strategy for estimating structurally what they call multilateral resistance indexes from a gravity model of trade. Themethodology used to compute the multilateral resistance indexes is presented in Appendix B.

Other economic determinants of RTAs are those put forward by Baier and Bergstrand (2004). Welfare gains fromcreating an RTA should increase with the size and similarity of GDPs of the two countries. Pairs of countries with dissimilarrelative factor endowment and whose relative factor endowments are similar to the rest of the world should also receivehigher welfare gains from creating an RTA. Relative factor endowment is measured by GDP per capita.

The set of political controls includes a number of potential co-determinants of disputes and regionalism. First, the factof sharing a common border, a common language or a common colonial history is likely to affect the probability of bilateraldisputes as well as the incentives to create a RTA. Landlocked countries experience fewer disputes on average and face, atthe same time, higher trade costs. The level of democracy of the two countries is also included as a control. Finally,diplomatic affinity between states is likely to influence decisions to create RTAs as well as the set of disputes betweencountries. I use two variables to control for diplomatic affinity: a dummy variable indicating countries sharing a commondefense alliance and the correlation of voting in the UN General Assembly (see Appendix A for details on data).

Finally, dispute probability is measured using the event data presented above, as the propensity to bilateral disputesbetween 1950 and 1969. I use lagged dispute data because past membership of RTAs is likely to affect variables in 2005.

V. Vicard / European Economic Review 56 (2012) 54–7164

An important issue when estimating Eq. (3) is the endogeneity related to past membership of RTAs (Baier and Bergstrand,2004). Lagged data may suffer from an endogeneity bias as well since some regional integration processes began shortlyafter World War II (the Benelux, the EU,y) and several current RTAs have been preceded by earlier attempts at integrationin the 1950s and 1960s.19 Moreover, endogeneity may also arise because of omitted variables affecting the likelihood ofRTAs and disputes.

To deal with endogeneity, I implement an IV strategy.20 Since the dispute propensity variable is not a continuousvariable, there is no straightforward nonlinear IV model available. As suggested by Angrist and Krueger (2001) andWooldridge (2002), I use a three-stage least square (3SLS) model to estimate Eq. (3) for deep and shallow RTAssimultaneously taking dispute propensity as endogenous. The two exogenous instruments for dispute propensity arederived from international relations theory; they are the number of major powers in the country pair and the difference innational military expenditure. Major powers are countries that have military, diplomatic, economic and cultural powerthat allow them to exert a global influence (Waltz, 1979). Unlike other countries whose geographical scope of interest isregional or local, major powers have a global geographical scope of interest. They are thus likely to experience moreinterstate disputes with any country around the globe. Major power status is however not likely to be correlated withincentives to create RTAs since it is not defined solely by economic power—Japan and Germany are not considered to bemajor powers, even if they are major economic powers. Moreover, controls for economic size are included in the mainspecification, which should remove the economic component of major power status. The second instrument is thedifference in (log) military expenditure. Countries that have unbalanced military capabilities are indeed more likely to beinvolved in disputes (Kinsella and Russett, 2002). While the level of military expenditure is likely to be affected bydecisions on RTAs, the difference in military expenditure is not, since both countries should decrease their militaryspending proportionally in the face of decreasing military threats.

Since no exogenous instruments for multilateral resistance terms and GDP are available, these variables are lagged in1960. This strategy reduces the sample of countries, because several countries were not independent in 1960. We are leftwith a sample of 2814 unique country pairs.

4.2. Results

Table 6 presents estimates of Eq. (3). I start with a simple univariate regression.21 Dispute propensity is positively andsignificantly associated with the likelihood of deep RTAs, but has no significant effect on shallow RTAs. These crude resultsmay suffer from an endogeneity bias. Specification (2) of Table 6 controls for endogeneity using an IV model. Regarding thefirst stage equation, the number of major powers and the difference in military expenditure strongly and significantly increasedispute propensity. The partial R2 of IVs is 0.29 and the F-statistic of weak identification on IVs greatly exceeds the thresholdof ten recommended by Staiger and Stock (1997), confirming the relevance of the two instruments. In this specification, theHansen–Sargan overidentification test however rejects the exogeneity of the instruments. This simple univariate specificationdoes not control for the economic size of countries, which should affect welfare gains from joining a RTA. Since economicpower is also one of the attributes of major powers, the number of major powers is not exogenous when economic size is notcontrolled for. In specification (3), when we control for economic and political determinants of regionalism, the Hansen–Sargan overidentification test does not reject the exogeneity of IVs, thus confirming their validity. As expected, the partial R2

and F-statistic on IVs are greatly reduced, but still confirm that the instruments can be regarded as strong.Controlling for endogeneity confirms that dispute propensity has a differential impact on incentives to create deep and

shallow RTAs. The coefficients on dispute propensity are significant at the 1% level. Country pairs that have many interstatedisputes are more likely to create a deep RTA and less likely to create a shallow one.

The relevance of security motives for decisions on trade policy is further illustrated by the differential impact of tradeopenness on the likelihood of deep and shallow RTAs. Pairs of countries naturally more open to trade (having largermultilateral resistance indexes) tend to create deep RTAs. Countries naturally more open to trade depend less on onepartner in particular, which increases the probability that disputes spillover into war (Martin et al., 2008) and increasesaccordingly the need for international institutions supporting the peaceful resolution of disputes. By contrast, shallowRTAs are driven by the economic motives put forward by Baier and Bergstrand (2004) and are created between countrypairs facing large trade costs with the rest of the world.

Geographically close countries and countries sharing a common border are more likely to join all kinds of RTAs. Othereconomic determinants of regionalism are in line with Baier amd Bergstrand’s (2004) results concerning shallow RTAs. Countrypairs with similar endowments and with large and similar markets tend to create shallow RTAs. As in Egger and Larch (2008),countries that have endowments similar to the rest of the world are more likely to create shallow RTAs. Economic determinantsare however less relevant to the creation of deep RTAs. Differences in endowments have no significant impact on the creation of

19 For instance, the East African Community was disbanded in 1977 and relaunched in 2000 as a partial scope agreement and the Central American

Common Market collapsed in 1975 and relaunched as a customs union in 1993.20 Another advantage of using an IV model is that it also deals with measurement error in the endogenous explanatory variable, which is, as

explained above, also valuable in our case. For instance, institutions in deep RTAs are likely to publicize disputes, creating a downward bias on the

coefficient of dispute propensity in the case of deep RTAs.21 Using a bivariate probit estimator yields similar results.

Table 6Probability of deep and shallow RTAs between two countries.

(1) (2) (3)

Deep RTA Shallow RTA Deep RTA Shallow RTA Deep RTA Shallow RTA

Estimator 3SLS 3SLS 3SLS

sample Full Full Full

Propensity to dispute 0.08a 0.02 0.11a�0.38a 0.27a

�1.06a

(0.02) (0.05) (0.04) (0.08) (0.07) (0.14)

Sum log multilateral resistance indexes 0.09a�0.16a

(0.01) (0.03)

Log distance �0.09a�0.07a

(0.01) (0.01)

Continent dum. �0.01 0.08a

(0.01) (0.03)

Abs. Diff in log GDP per capita (1960) �0.01 �0.09a

(0.01) (0.02)

Squared abs. diff in log GDP per capita (1960) 0.01c 0.01

(0.00) (0.01)

Abs. Diff of (log) GDP per capita with RoW (1960) �0.01c 0.05a

(0.01) (0.01)

Log sum GDP (1960) �0.08a 0.27a

(0.01) (0.03)

Log diff. GDP (1960) 0.02a�0.14a

(0.01) (0.01)

Contiguity dum. 0.11a 0.15a

(0.03) (0.05)

Common language dum. �0.04a 0.02

(0.01) (0.02)

Common colonizer dum. 0.10a�0.14a

(0.02) (0.04)

No. of landlocked countries 0.02a�0.10a

(0.01) (0.02)

Sum of democracy indexes 0.10a�0.16a

(0.01) (0.03)

Common defence alliance dum. 0.06a�0.04

(0.01) (0.03)

UN voting correlation 0.18a�0.04

(0.02) (0.04)

No. of major powers 0.29a 0.23a

(0.01) (0.01)

Abs. diff. log military expenditure 0.00c 0.00c

(0.00) (0.00)

Observations 2814 2814 2814 2814 2814 2814

Hansen–Sargan overidentification statistic 60.94a 0.94

Partial R2d 0.29 0.16

F-test on IV 871.7 273.4

Note: Standard errors in parentheses.a Significance at the 1% level.b Significance at the 5 % level.c Significance at the 10% level.d Computed using 2SLS.

V. Vicard / European Economic Review 56 (2012) 54–71 65

deep RTAs, and deep RTAs are more likely to cover smaller and more dissimilar country pairs in terms of GDP.22 Moreover, theeconomic significance of GDP size is much smaller for deep than for shallow RTAs.

Conversely, political determinants are more relevant to the creation of deep RTAs than to shallow ones. Having a commoncolonizer increases the likelihood of deep RTAs, but decreases the likelihood of shallow RTAs. Former colonies from the sameregion are indeed more likely to have unresolved territorial disputes related to the decolonization process. They also shareinstitutional features from their past colonizer that reduce the cost of creating common supranational institutions. Sharing acommon language is surprisingly negatively and significantly associated with deep RTAs.23 In addition, diplomatic affinity only

22 Note that the negative impact of GDP similarity is difficult to reconcile with the theory of economic determinants of RTAs put forward by Baier and

Bergstrand (2004). The coefficient on GDP similarity however becomes insignificant when EU country pairs are excluded (see Table 7).23 This result however disappears when EU countries are excluded (see Table 7). The fact that most direct communication languages originate from

Europe, because of its history of colonialism, and that these languages are those coded as common languages in other regions of the world may explain

this result.

Table 7Probability of deep and shallow RTAs between two countries: robustness.

1 2

Deep RTA Shallow RTA Deep RTA Shallow RTA

Estimator 3SLS 3SLS

sample EU pairs excl. Full

Propensity to dispute 0.10b�0.98a 0.38a

�0.40a

(0.04) (0.14) (0.07) (0.08)

Sum log multilateral resistance indexes 0.01 �0.11a 0.09a�0.11a

(0.01) (0.03) (0.01) (0.02)

Log distance �0.04a�0.11a

�0.07a 0.06a

(0.01) (0.02) (0.01) (0.01)

Continent dum. �0.09a 0.13a�0.02 0.02

(0.01) (0.03) (0.01) (0.02)

Abs. diff in log GDP per capita (1960) 0.01 �0.11a 0.00 �0.00

(0.01) (0.02) (0.01) (0.01)

Squared abs. diff in log GDP per capita (1960) �0.00 0.01b 0.00 �0.00

(0.00) (0.01) (0.00) (0.00)

Abs. diff of (log) GDP per capita with RoW (1960) �0.01 0.05a�0.02a 0.01

(0.00) (0.01) (0.01) (0.01)

Log sum GDP (1960) �0.02a 0.23a�0.10a 0.11a

(0.01) (0.03) (0.01) (0.02)

Log diff. GDP (1960) 0.00 �0.13a 0.04a�0.04a

(0.00) (0.01) (0.01) (0.01)

Contiguity dum. 0.25a 0.08 0.08a�0.03

(0.02) (0.05) (0.03) (0.03)

Common language dum. 0.01 �0.01 �0.04a 0.05a

(0.01) (0.02) (0.01) (0.01)

Common colonizer dum. 0.14a�0.18a 0.11a

�0.08a

(0.01) (0.04) (0.02) (0.02)

No. of landlocked countries 0.01c�0.09a 0.03a

�0.04a

(0.01) (0.02) (0.01) (0.01)

Sum of democracy indexes 0.05a�0.12a 0.11a

�0.09a

(0.01) (0.03) (0.01) (0.02)

Common defence alliance dum. 0.12a�0.08a 0.06a

�0.03c

(0.01) (0.03) (0.01) (0.02)

UN voting correlation 0.06a 0.04 0.16a�0.17a

(0.01) (0.04) (0.02) (0.02)

Total GDP of RTA partners 0.01a 0.05a

(0.00) (0.00)

No. of major powers 0.24a 0.23a

(0.01) (0.01)

Abs. diff. log military expenditure 0.00b 0.00b

(0.00) (0.00)

Observations 2736 2736 2814 2814

Hansen–Sargan overidentification statistic 3.79 2.37

Partial R2d 0.17 0.16

F-test on IV 289.2 260.5

Note: Standard errors in parentheses.a Significance at the 1% level.b Significance at the 5% level.c Significance at the 10% level.d Computed using 2SLS.

V. Vicard / European Economic Review 56 (2012) 54–7166

impacts the decision to create a deep RTA: having a common defense alliance or similar voting patterns in the UN GeneralAssembly increases the likelihood of deep RTAs between two countries. Finally, states’ democratic status also have a differentialimpact on deep and shallow RTAs. Democratic countries tend to create deep RTAs, whereas they are less likely to create shallowRTAs. Joining a deep RTA indeed involves sharing common supranational institutions and providing some public goods incommon. Giving up some national sovereignty is possible only between countries that are similar in terms of political system,type of government and origin of legitimacy. This constraint is less binding regarding shallow RTAs, in which more autocraticregimes can retain more independent power while benefiting from gains from trade.

In Table 7, I perform two robustness tests. First, the argument put forward in this paper draws on the EU experience.The EU is undoubtedly the most integrated RTA worldwide and accounts for a large share of country pairs in deep RTAs inour sample. In the first two columns of Table 7, I re-estimate the baseline specification excluding EU country pairs.

V. Vicard / European Economic Review 56 (2012) 54–71 67

The results on dispute propensity remain qualitatively similar.24 The coefficient on natural trade openness becomesinsignificant for deep RTAs, but remains negative and significant for shallow RTAs. These results are in line with theexpected ambiguous impact of trade openness on incentives to create deep RTAs. The main results of the paper aretherefore robust to the exclusion of EU countries.

Finally, so far we have considered that the decision to create an RTA takes place at the country pair level. Many RTAshave more than two members, and a country could well join an agreement because it expects gains with some membersbut not all of them. Moreover, individual members of deep RTAs cannot sign separate agreements with third countriesbecause the common external tariffs are negotiated by all members. Not controlling for the characteristics of trade blocscould bias the results. I thus re-estimate the baseline specification including a proxy for the economic size of the countrypair’s RTA partners if one or both countries are member of an RTA: (the log of) the sum of the GDPs of each country’s RTApartners. The results show that RTAs’ characteristics matter. Members of large trading blocs are more likely to join deepand shallow RTAs, but the impact is larger for shallow RTAs. Controlling for the economic size of RTAs does not alterquantitatively the main results of the paper.

5. Conclusion

This paper asks whether international security is a motive for creating RTAs. I provide robust empirical evidence thatinternational security does matter, but that its impact depends on the form of trade integration. In this paper, RTAs areclassified according to their level of political integration. A deep RTA (customs union or common market) involves thecreation of common supranational institutions whereas a shallow agreement (partial scope or free trade agreement)requires only weak institutional integration. The empirical analysis shows that deep RTAs promote the negotiatedsettlement of disputes between members and prevent war. Shallow RTAs have no impact on war probabilities. I then showthat security issues are an important motive for the creation of deep RTAs. A pair of countries involved in many interstatedisputes and naturally more open to multilateral trade is more likely to create a deep RTA. Supranational institutionscreated on the basis of a deep RTA help to manage interstate conflicts and secure gains from bilateral trade. Conversely,interstate disputes reduce incentives to create shallow RTAs. Shallow RTAs are mainly driven by economic determinants.

This paper provides evidence of non-traditional gains from RTAs that help to explain the different strategies of regionalintegration worldwide. The analysis focuses on wars because of the availability of data on such extreme form ofconflicts—essentially a regional issue. More broadly, by analyzing RTAs as regulating institutions in a world where nosupranational institution enforces property rights properly, this paper raises the question of the relationship betweentrade integration and other areas of interstate cooperation. By providing an institutional framework or making availablesources of gains, RTAs may facilitate the internalization of international externalities and negotiations on other, morecomplex, issues (Schiff and Winter, 2003). Such interactions could explain the differential impact of regionalism onmultilateralism depending on the form of RTAs found in the literature (Karacaovali and Lim~ao, 2008; Estevadeordal et al.,2008). More work is however needed to understand the link between (regional) trade integration and deeper integrationon non-trade issues.

Acknowledgements

I would like to thank Thierry Mayer for providing data and guidance on this chapter of my Ph.D. dissertion. I also thankJames Anderson, Jeffrey Bergstrand, Antoine Berthou, Marius Bruhlart, Paola Conconi, Arnaud Costinot, MathieuCouttenier, Peter Egger, Philippe Martin, Vincent Rebeyrol, Mathias Thoenig, Julien Vauday and Thierry Verdier. I gratefullyacknowledge the financial support from ANR. This paper represents the views of the author and should not be regarded asreflecting those of the Banque de France.

Appendix A. Data

Data on RTAs have been assembled from notifications to the WTO under article XXIV of GATT or the Enabling Clause fordeveloping countries, Frankel (1997), Foroutan (1993, 1998), Langhammer and Hiemenz (1990), Machlup (1977) and otherpublic sources. I look at all regional trade agreements which take the form of partial scope trade agreements, free tradeareas, customs unions, or common markets.25 Membership of an RTA is defined by dummy variables coded 1 when twocountries belong to the same RTA in year t (Table 8).

Trade data come from the database assembled by Katherine Barbieri, who mainly uses information from the IMF andthe League of Nations international trade statistics, and are supplemented by Martin et al. (2008) using the IMF DOTS

24 The results are also robust to the exclusion of country pairs including at least one EU country.25 A partial scope trade agreement is defined as an agreement in which reciprocal preferences are exchanged to cover a limited range of the parties’

trade in goods (partial in scope); a free trade area is defined as an agreement in which reciprocal preferences are exchanged to cover substantially all

trade in goods; a customs union is defined as an RTA with the exchange of trade preferences and a common external tariff; and a common market is

defined as an RTA allowing free movements of factors (goods, capital and workers).

Table 8

Name Date

Common marketsBenelux 1961

European Union (EU)a 1992

Customs UnionsBenelux 1947–1960

European Communities (EC) 1958–1991

Equatorial Customs Union 1959–1965

Customs Union of West African States 1960–1966

East African Community 1967–1977

Mano River Union 1973–1988

Customs Union EU–Cyprus 1973

Caribbean Community and Common Market (CARICOM) 1973

Southern Common Market (MERCOSUR)a 1991

Central American Common Marketa 1993

Economic and Monetary Community of Central Africa 1994

Andean Customs Uniona 1995

Customs Union EU–Turkeya 1996

West African Economic and Monetary Uniona 1998

Free Trade AgreementsEuropean Free Trade Agreement (EFTA)a 1960

Central American Common Market 1961–1975

United Kingdom–Ireland 1966–1972

Caribbean Free Trade Area 1968–1972

EU–Norway 1973

EU–Switzerland 1973

EU–Egypta 1977

Papua New Guinea and Australia Trade and Commercial Relation Agreement 1977

Closer Trade Relations Trade Agreementa 1983

United States of America–Israela 1985

EU–Hungarya 1992

EU–Polanda 1992

EFTA–Turkeya 1992

EFTA–Bulgariaa 1993

EFTA–Hungarya 1993

EFTA–Israela 1993

EFTA–Polanda 1993

Central European Free Trade Agreementa 1993

European Economic Areaa 1994

North American Free Trade Agreement (NAFTA)a 1994

EU–Bulgariaa 1994

Group of Threea 1995

Mexico–Boliviaa 1995

Mexico–Costa Ricaa 1995

MERCOSUR–Chilea 1996

MERCOSUR–Boliviaa 1996

Canada–Chilea 1997

Canada–Israela 1997

Israel–Turkeya 1997

Poland–Israela 1998

EU–Tunisiaa 1998

Hungary–Israela 1998

Hungary–Turkeya 1998

India–Sri Lankaa 1998

Bulgaria–Turkeya 1999

Chile–Mexicoa 1999

EFTA–Moroccoa 1999

EU–Israela 2000

EU–Moroccoa 2000

EU–Mexicoa 2000

EU–South Africaa 2000

Mexico–Israela 2000

Poland–Turkeya 2000

EU–Israela 2000

EU–Mexicoa 2000

EU–Moroccoa 2000

EU–South Africaa 2000

Dominican Republic–El Salvadora 2001

Dominican Republic–Guatemalaa 2001

Dominican Republic–Hondurasa 2001

V. Vicard / European Economic Review 56 (2012) 54–7168

Table 8 (continued )

Name Date

EFTA–Mexicoa 2001

Mexico–El Salvadora 2001

Mexico–Guatemalaa 2001

Mexico–Hondurasa 2001

United States–Jordana 2001

Canada–Costa Ricaa 2002

Chile–Costa Ricaa 2002

Chile–El Salvadora 2002

Dominican Republic–Costa Ricaa 2002

EU–Jordana 2002

EFTA–Jordana 2002

El Salvador–Panamaa 2002

EU–Chilea 2003

CARICOM–Costa Ricaa 2004

EFTA–Chilea 2004

United States–Chilea 2004

United States–Moroccoa 2005

Thailand–Australiaa 2005

Thailand–New Zealanda 2005

Mexico–Japana 2005

Partial scope agreementsCouncil for Mutual Economic Assistance (CMEA) 1949–1990

Latin American Free Trade Association (LAFTA) 1961–1980

Tripartite Agreementa 1968

Protocol relating to Trade Negotiations among Developing Countriesa 1973

West African Economic Community 1973–1997

Bangkok Agreementa 1976

South Pacific Regional Trade and Economic Cooperation Agreement 1981

Andean Community 1988–1997

General System of Trade Preferences among Developing Countries (GSTP)a 1989

Economic Cooperation Organization 1992

ASEAN Free Trade Agreement 1992

Melanesian Spearhead Group 1993

Latin American Integration Association (LAIA)a 1993

Chile–Venezuelaa 1993

Chile–Colombiaa 1994

Common Market for Eastern and Southern Africa (COMSESA)a 1994

South Asian Preferential Trade Agreementa 1995

Source: WTO (http://www.wto.org/english/tratop_e/region_e/region_e.htm), Foroutan (1993, 1998),

Langhammer and Hiemenz (1990), Frankel (1997), Machlup (1977) and other public sources.a RTAs included in the second part of the empirical analysis.

V. Vicard / European Economic Review 56 (2012) 54–71 69

database. Income data also come from Martin et al. (2008), and are assembled from the Penn World Table (version 6.2),Katherine Barbieri’s database and the World Bank WDI database. Geographical and colonial data are from the CEPII. Dataon formal defence alliances and military spending are taken from the COW project. The composite democracy indicator istaken from Polity IV. It measures the openness/closedness of political institutions on a �10 / þ10 scale (10 indicates ahigh level of democracy). Finally, UN voting correlation is taken from ‘‘The Affinity of Nations: Similarity of State VotingPositions in the UN General Assembly’’ computed by Erik Gartzke. Data on shares of agriculture, industry services andmanufacturing in value added are from the World Bank WDI database.

Appendix B. Multilateral resistance terms

Let tij be the variable trade costs of exporting from i to j. Assuming symmetrical trade costs (tij ¼ tji), a gravity-likemodel of trade yields (Anderson and van Wincoop, 2003):

xij ¼yiyj

yw

tij

PiPj

� �1�sð4Þ

and

P1�si ¼

Xj

yj

yw

tij

Pj

0@

1A

1�s

, ð5Þ

where xij is the value of exports, s is the elasticity of substitution between all goods, and yj is country j’s nominal income.

Table 9Gravity equation with country fixed effects (1960).

Dependent variable Imports

Log distance �0.54a

(0.04)

Contiguity dum. 0.54a

(0.09)

Common language dum. 0.12

(0.09)

Ever in colonial relationship dum. 0.53a

(0.16)

Colonial relationship since 1945 dum. 1.30a

(0.20)

Common colonizer dum. �0.27

(0.37)

RTA dum. 0.20b

(0.09)

Common currency dum. 1.20a

(0.18)

GATT membership dum. 0.15

(0.10)

Communist country dum. �1.61a

(0.13)

Observations 8467

R2 0.89

Note: Robust standard errors in parentheses. Constant and country

dummies not reported.a Significance at the 1% level.b Significance at the 5% level.c Significance at the 10% level.

V. Vicard / European Economic Review 56 (2012) 54–7170

We assume the following trade cost function:

ln tij ¼ ln distijþX

h

ahzh: ð6Þ

The vector of observable bilateral linkages affecting trade costs includes variables measuring geographical, cultural andhistorical proximity as well as trade policy variables:

Zij ¼ ½Contigij,Langij,Colonyij,ComColij,Comcurij,RTAij,GATTij,Cocoij�, ð7Þ

where Contigij, Langij and Comcurij are dummies for countries sharing a common border, a common official language and acommon currency respectively. RTAij measures the existence of a regional trade agreement between countries i and j, andGATTij equals 1 if both countries are members of the General Agreement on Tariffs and Trade (GATT). Colonyij and ComColijare dummies equal to 1 for countries that have ever been in a colonial relationship and that share a common colonizer,respectively. Finally, Cocoij equals 1 if i and j are communist countries.

Combining (5) and (6), we have:

P1�si ¼

Xj

Ps�1j

yj

ywexpb1 ln distijþ

Phbhzh : ð8Þ

The b’s coefficients in (8) can be consistently estimated from (4) with country fixed effects (Feenstra, 2004; Anderson andvan Wincoop, 2003). We can then solve the vector of P1�s

i using the system of N goods market equilibrium condition (8),estimated coefficients from (4) and GDP shares.

An important issue here is to measure domestic trade costs, since (8) includes all trading partners including the countryitself. Internal distance of country i is calculated as dii ¼ 0:67n

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiarea=P

p. Contigij, Langij and Colonyij are set at 1 for intra-

national trade. Eq. (5) is estimated on a cross-section of country pairs in 1960 using a Poisson quasi maximum estimator(Santos Silva and Tenreyro, 2006). Table 9 reports the results.

References

Ai, C., Norton, E.C., 2003. Interaction terms in logit and probit models. Economics Letters 80 (1), 123–129.Alesina, A., Angeloni, I., Etro, F., 2005. International unions. American Economic Review 95 (3), 602–615.Alesina, A., Wacziarg, R., 1999. Is europe going too far? Carnegie-Rochester Conference Series on Public Policy 51, 1–42 (supplement of Journal of

Monetary Economics).Anderson, J.E., van Wincoop, E., 2003. Gravity with gravitas: a solution to the border puzzle. American Economic Review 93 (1), 170–192.

V. Vicard / European Economic Review 56 (2012) 54–71 71

Angrist, J.D., Krueger, A.B., 2001. Instrumental variables and the search for identification: from supply and demand to natural experiments. Journal ofEconomic Perspectives 15 (4), 69–85.

Angrist, J.D., Pischke, J.-S., 2009. Mostly Harmless Econometrics: An Empiricists Companion. Princeton University Press, Princeton.Baier, S.L., Bergstrand, J.H., 2004. Economic determinants of free trade agreements. Journal of International Economics 64 (1), 29–64.Balassa, B., 1961. Towards a theory of economic integration. Kyklos 16, 1–17.Baldwin, R.E., 1997. The causes of regionalism. The World Economy 20 (7), 865–888.Bearce, D.H., 2003. Grasping the commercial institutional peace. International Studies Quarterly 47 (3), 347–370.Beck, N., Katz, J., Tucker, R., 1998. Taking time seriously: time-series-cross-section analysis with binary dependent variable. American Journal of Political

Science 42 (4), 1260–1288.Best, E., 2005. Surpranational Institutions and Regional Integration, mimeo.Bouzas, R., Soltz, H., 2001. Institutions and regional integration: the case of mercosur. In: Bulmer-Thomas, V. (Ed.), Regional Integration in Latin America

and the Caribbean. ILAS, Londres.Conconi, P., Sahuguet, N., Zanardi, M., 2008. Democratic Peace and Electoral Accountability. CEPR Discussion Papers 6908.Egger, P., Larch, M., 2008. Interdependent preferential trade agreement memberships: an empirical analysis. Journal of International Economics 76 (2),

384–399.Estevadeordal, A., Freund, C., Ornelas, E., 2008. Does regionalism affect trade liberalization towards non-members. Quarterly Journal of Economics

123 (4), 1531–1575.Faten, G., Palmer, G., Bremer, S., 2004. The MID3 data set, 1993–2001: procedures, coding rules, and description. Conflict Management and Peace Science

21, 133–154.Fearon, J.D., 1995. Rationalist explanations for war. International Organization 49 (3), 379–414.Feenstra, R.C., 2004. Advanced International Trade: Theory and Evidence. Princeton University Press, Princeton.Fernandez, R., Portes, J., 1998. Returns to regionalism: an evaluation of nontraditional gains from regional trade agreements. The World Bank Economic

Review 12 (2), 197–220.Foroutan, F., 1993. Regional integration in sub-saharan africa: past experience and future prospects. In: de Melo, J., Panagariya, A. (Eds.), New Dimensions

in Regional Integration. Cambridge University Press, Cambridge.Foroutan, F., 1998. Does membership in an FTA make a country more or less protectionist? The World Economy 21 (3), 305–335.Frankel, J.A., 1997. Regional Trading Blocs. Institute for International Economics, Washington.Glick, R., Taylor, A.M., 2010. Collateral damage: trade disruption and the economic impact of war. The Review of Economics and Statistics 92 (1), 102–127.Goldstein, J.S., 1992. A conflict-cooperation scale for WEIS international events data. Journal of Conflict Resolution 36 (2), 369–385.Greene, W., 2003. Econometric Analysis. Prentice Hall, New York.Grossman, H., 2004. Choosing Between Peace and War. The Timbergen Lecture Series no. 19, University of Saskatchewan.Jackson, M.O., Massimo, M., 2007. Political bias and war. American Economic Review 97 (4), 1353–1373.Karacaovali, B., Lim~ao, N., 2008. The clash of liberalizations: preferential vs. multilateral trade liberalization in the European Union. Journal of

International Economics 74 (2), 299–327.Kinsella, D., Russett, B., 2002. Conflict emergence and escalation int interactive international dyads. The Journal of Politics 64 (4), 1045–1068.Langhammer, R.J., Hiemenz, U., 1990. Regional integration among developing countries. Westview Press, JCB Mohr.Levy, G., Razin, R., 2004. It takes two: an explanation for the democratic peace. Journal of the European Economic Association 2 (1), 1–29.Limao, N., 2007. Are preferential trade agreements with non-trade objectives a stumbling block for multilateral liberalization? Review of Economic

Studies 74 (3), 821–855.Machlup, F., 1977. A History of Thought on Economic Integration. Macmillan, London (Chapter 5).Maggi, G., Rodriguez-Clare, A., 1998. The value of trade agreements in the presence of political pressures. Journal of Political Economy 106, 574–601.Mansfield, E.D., Milner, H.V., Rosendorff, B.P., 2002. Why democracies cooperate more: electoral control and international trade agreements. International

Organization 56 (3), 477–513.Mansfield, E.D., Pevehouse, J.C., 2000. Trade blocs, trade flows, and international conflict. International Organization 54 (4), 775–808.Manzetti, L., 1993/94. The political economy of Mercosur. Journal of Interamerican Studies and World Affairs 35, 101–141.Martin, P., Mayer, T., Thoenig, M., 2008. Make trade not war? Review of Economic Studies 75 (3), 865–900.Martin, P., Mayer, T., Thoenig, M., 2010. The geography of conflicts and free trade agreements. CEPR Discussion Papers 7740.Mitra, D., 2002. Endogenous political organization and the value of trade agreements. Journal of International Economics 57 (2), 473–485.Oneal, J.R., Russett, B.M., 1997. The classical liberals were right: democracy, interdependence and conflict, 1950–1985. International Studies Quarterly

41 (2), 267–294.Oneal, J.R., Russett, B.M., 1999. Assessing the liberal peace with alternative specifications: trade still reduce conflicts. Journal of Peace Research 36 (4),

423–442.Ornelas, E., 2005. Endogenous free trade agreements and the multilateral trading system. Journal of International Economics 67 (2), 471–497.Polachek, S.W., 1980. Conflict and trade. Journal of Conflict Resolution 24 (1), 57–78.Pomfret, R., 1997. The Economics of Regional Trading Arrangements. Oxford University Press.Riezman, R., 1985. Customs unions and the core. Journal of International Economics 19 (3–4), 355–365.Santos Silva, J., Tenreyro, S., 2006. The log of gravity. Review of Economics and Statistics 88 (4), 641–658.Schiff, M., Winter, L., 2003. Regional Integration and Development. World Bank; Oxford University Press, Washington, DC.Schiff, M., Winters, L.A., 1998. Regional integration as diplomacy. World Bank Economic Review 12 (2), 271–295.Schrodt, P.A., Gerner, D.J., 2000. Analyzing international events data: a handbook of computer-based techniques, University of Kansas, On-line Manuscript

/http://www.ku.edu/�keds/papers.dir/automated.htmlS.Staiger, D., Stock, J.H., 1997. Instrumental variables regression with weak instruments. Econometrica 65 (3), 557–586.Vicard, V., 2009. On trade creation and regional trade agreements: does depth matter? Review of World Economics 145 (2), 167–187.Waltz, K.N., 1979. Theory of International Politics. Addison-Wesley, Reading, MA.Whalley, J., 1998. Why do countries seek regional trade agreements? In: J. Frankel (Ed.), The Regionalization of the World Economy, pp. 63–83.Wooldridge, J.M., 2002. Econometric Analysis of Cross Section and Panel Data. MIT Press, Cambridge, MA.Yi, S.-S., 1996. Endogenous formation of customs unions under imperfect competition: open regionalism is good. Journal of International Economics

41 (1–2), 153–177.