ESOTERICENTANGLEMENTS,TENACIOUSTIES:
DOESECONOMICINTERDEPENDENCE
LEADTOBILATERALCOOPERATION?
TAYYONGYAOMELVIN
ANHONOURSTHESISINPARTIALFULFILLMENT
OFTHEBACHELOROFSOCIALSCIENCES
(HONOURS)DEGREE
PRESENTEDTO
DEPARTMENTOFPOLITICALSCIENCE
NATIONALUNIVERSITYOFSINGAPORE
[ACADEMICYEAR2014‐2015]
ACKNOWLEDGEMENTS
Birthingathesiscanbeconstruedasasomewhatmasochisticendeavour.The
pain from incessantly wracking the sinews of your brain interspersed with varied
stressors of anxiety, deadlines, fatigue, self‐doubt, and existential crises, marry in
bittersweet symphony to the intellectual equivalent of an orgasm – seeing the
longest essay you’ve ever written coming to pass. Looking back upon my months
spent alternating between the ends of this pain‐pleasure dichotomy, there are a
numberofpeopleIoweadebtofgratitudeandloveto.
Firstandforemost,Iwouldliketothankmythesissupervisor,ProfKimSoo
Yeonforherinvaluableinput,feedback,andassistanceprofferedtomethroughout
thesemester.Thisessaywouldnothavecometopasswithoutthecountlessregular
consults and her efforts to constantly sharpen, critique, and perfect my work with
the fervour of a mother – amidst her chock‐full schedule and commitments. I am
deeplyappreciativefortheopportunitytodevelopunderherwingsofguidance.
The behind‐the‐scenes crew further encompasses a group of friends who
sacrificedaportionoftheirdailylivesandsleepovertwoweekstoassistmevis‐à‐
vis the most mundaneof tasks – proof‐reading and data‐checking. Iam grateful to
IsaacWong,JonathanLwee,ValerieYeo,andYeamChengTenginthisregard.
Additionally,Iwouldliketoacknowledgethelabourofthevariousprofessors
intheNUSPoliticalScienceandPhilosophydepartments.Thoseintheformerhave
taught andequippedmewellduringmyfirstthreeyearsinNUS toundertakethis
endeavour–inparticular,ProfessorsNaomiAoki(nowinLKYSPP),GaoJie,Shamsul
Haque,andTerenceLee.IfurtherthankProfAokiforgrantingmetheopportunityin
myfreshmanyeartocutmyteethinresearchandco‐authorapaperwithher.Prof
TenChinLiew,andChinChuanFeifromPhilosophyhaveaddedtheproverbialicing
onthecakebycaptivatingmeandstokingmyavocationinthemoredeontological
andexistentialaspectsoflife.
Academicsupportaside,Iamdeeplygratefultoanothergroupofpeoplewho
haveaccordedmuchemotionalandmentalcareduringthecourseofmywriting.At
theoutset,Iambeholdentomyparentsfortheirencouragementandunderstanding
throughout,beingaconstantsourceofmotivation,andforthelovethatIreturntoat
the end of each day, fruitful or otherwise. I would like to thank my friends David
Hoe, Joel Foo, and Isaac Wong – for their listening ears, unceasing support,
conversations,andmealstogether.Ashout‐outtotheHopeNUScommunity‐at‐large
isalsowarrantedfortheirpresenceandsupportduringthisperiodtoo.
Thisthesisisdedicatedtomybestfriendofsevenyears,mate,andconfidante
Valerie Chan; whose love, presence, and understanding I could not have done
without.Sheisaconstantreminderofwhatistrulyimportantinlife.Ahappierand
moreblessedpersonwrotethepagesthatfollowbecauseofher.
i
TABLEOFCONTENTS
ACKNOWLEDGEMENTS‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐i
TABLEOFCONTENTS‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ii
LISTOFFIGURESANDTABLES‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐iii
LISTOFABBREVIATIONS‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐iv
ABSTRACT‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐v
CHAPTERI–INTRODUCTION‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐1
CHAPTERII–LITERATUREREVIEW‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐4
2.1 LimitationsofExistingScholarship‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐4
2.2 TheConflict‐PeaceDichotomyversusCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐6
2.3 EconomicInterdependenceandConflict ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐8
CHAPTERIII–THEORYANDHYPOTHESES‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐12
3.1 EconomicInterdependenceandBilateralCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐12
3.2 ConceptualPropertiesofEconomicInterdependence‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐15
3.3 DelineatingaDefinitiveModelofBilateralCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐16
3.4 Hypotheses:OfCooperation,Hierarchy,andDecorum‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐22
CHAPTERIV–RESEARCHDESIGNANDMETHODOLOGY‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐23
4.1 DependentVariable:BilateralCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐24
4.1.1 Socio‐CulturalCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐25
4.1.2 EconomicCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐27
4.1.3 PoliticalCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐28
4.1.4 Military/SecurityCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐30
4.1.5 ModellingtheBilateralCooperationIndex‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐31
4.2 IndependentVariable:EconomicInterdependence‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐33
4.3 ControllingGeography,Gods,Gold,Governments,andGuns‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐35
4.4 Simultaneity:AcknowledgingInherentEndogeneity‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐38
4.5 Methodology:Time‐Lagging,OLS,andLogisticRegressions‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐40
CHAPTERV–STATISTICALFINDINGSANDDISCUSSION‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐41
5.1 AssessingtheResults:SizinguptheHypotheses‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐41
5.2 DiggingDeeper:TheDirtontheDeficiencies‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐46
5.3 OpportunitiesforFurtherResearch‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐50
CHAPTERVI–CONCLUSION‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐52
APPENDICES‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐53
BIBLIOGRAPHY‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐57
ii
LISTOFFIGURESANDTABLES
Figure1:HypothesisedTheoryofBilateralCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐18
Figure2:HypothesisedFrameworkofBilateralCooperation‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐21
Table1:DescriptiveStatisticsofComponentDependentVariables‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐24
Table2:FormulaeandDescriptiveStatisticsoftheDependentVariableModels‐‐32
Table3:DescriptiveStatisticsofIndependentVariableandControls‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐38
Table4:OLSRegressionsofEconomicInterdependenceonBilateralCooperation42
Table5:OrderedandConventionalLogisticRegressionsofEconomic
InterdependenceonComponentBCIDependentVariables‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐47
iii
LISTOFABBREVIATIONS
ASEAN
BCI
BIT
CARICOM
CINC
COPDAB
COW
DBCC
DPRK
ERASMUS+
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
EU
FDI
FTA
GDP
HST
IATA
IAU
ICB
IIA
IGO
IPE
JCR
JPR
MID
NATO
OLS
PD
PRC
PTA
RTA
SCO
TfT
TVR
U.K.
U.S.
UIA
UN
UNCTAD
US$
WEIS
WWII
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
‐
AssociationofSouth‐EastAsianNations
BilateralCooperationIndex
BilateralInvestmentTreaty
CaribbeanCommunity
CompositeIndexofNationalCapability
ConflictandPeaceDataBank
CorrelatesofWar
DistancebetweenCapitalCities
DemocraticPeople’sRepublicofKorea/NorthKorea
EuropeanCommunityActionSchemefortheMobilityof
UniversityStudents
EuropeanUnion
ForeignDirectInvestment
FreeTradeAgreement
GrossDomesticProduct
HegemonicStabilityTheory
InternationalAirTransportAssociation
InternationalAssociationofUniversities
InternationalCrisisBehaviourProject
InternationalInvestmentAgreement
Inter‐GovernmentalOrganisation
InternationalPoliticalEconomy
JournalofConflictResolution
JournalofPeaceResearch
MilitarisedInterstateDispute
NorthAtlanticTreatyOrganisation
OrdinaryLeastSquares
Prisoner’sDilemma
People’sRepublicofChina
PreferentialTradeAgreement
RegionalTradeAgreement
ShanghaiCooperationOrganisation
Tit‐for‐Tat
Tourist‐VisaRegimes
UnitedKingdom
UnitedStates
UnionofInternationalAssociations
UnitedNations
UnitedNationsConferenceonTradeandDevelopment
UnitedStatesDollar
WorldEvent/InteractionSurvey
WorldWarTwo
iv
ABSTRACT
Economic interdependence has been linked to either conflict or peace by
much of the extant scholarship. This study offers a novel conception of
interdependenceandbilateralrelationsbypositingtheformer’slinktocooperation
– which is distinct from mere peace. Juxtaposed against the bulk of contemporary
literature addressing notions of the liberal or Kantian peace with largely realist
underpinnings,Iofferafreshtakeonthestudyofinternationalpoliticaleconomyby
constructingatheoreticalbaseforacomprehensive,hierarchicalmodelofbilateral
cooperation,andperusingitvis‐à‐visdyadicinterdependence.
Myresearchleveragesuponbothoriginaldataspanningcooperationacross
various spheres and existing comprehensive datasets, and employs a quantitative
large‐nassessmentofcountrypairsworldwide.Insodoing,Iestablishcorrelations
differing in magnitude between economic interdependence and increased bilateral
informalandformalcooperation–spanningsocio‐cultural,economic,political,and
securityspheres.
Keywords: Economic interdependence, bilateral relations, cooperation, conflict,
positivepeace,internationalpoliticaleconomy
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ChapterI|Introduction
CHAPTERI–INTRODUCTION
In recent times, the concept of economic interdependence in international
relations has drawn avid interest from bureaucrats, international organisations,
scholars,andglobalcitizenryalike;afterall,thisphenomenoninfluencesalmostall
aspects of contemporary society in some way. Mounting cross‐border interactions
through intensifying commodity, capital, and investment flows across national
boundaries have rendered countries increasingly reliant on and integrated with
each other. Economic interdependence is concomitant with other frequently
thrown‐about buzzwords like ‘globalisation’ and ‘integration’ too; while vague and
oft‐poorlyunderstooduponcursoryappraisals,anydoubtsastotheirveracityand
modern‐dayrelevancewouldbefarcical.
The network of economic ties binding countries hence seems unlikely to
recedeanytimesoon,withthearchetypalfocusofthesetiescentringuponwelfare
gainsresultingfromfreermarketaccessandincreasedtrade.However,theirimpact
onensuinginteractionsamongstcountriesislessobvious–justhowdoeseconomic
interdependence influence the way countries interact? The bulk of the scholarship
spanning the past centuries are by no means definitive or prescient – positing a
disparate contrast of relations ranging from the pacific nature of economic
interdependence (Montesquieu [1750]1989; Kant [1795]1991; Polachek 1980;
O’Neal 2003; Hegre, O’Neal, and Russett 2010), to interdependence merely being
additional cause for conflict (Rousseau [1762]1994; Barbieri 1996; 2002; Goenner
2004;Hafner‐BurtonandMontgomery2012).
Against this backdrop, my research embarks upon a factor‐centric study by
examining this question: does economic interdependence lead to bilateral
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ChapterI|Introduction
cooperation?Inthiscontext,Icogniseeconomicinterdependenceasmutualreliance;
if economic ties between countries are broken, both will incur costs. This
differentiateseconomicinterdependencefromeconomicinteraction;whilethelatter
simply represents cross‐border transactions of entities such as goods and capital,
the former connotes constraint and costly entanglement (Crescenzi 2005).
Cooperation,ontheotherhand,canbeconceivedsimplyasthemutuallybeneficial
process of working together towards the same end, rather than competing. While
much limelight has been cast upon conflictual interaction (or the lack thereof),
cooperative relations have not been accorded their due by the extant literature.
Given how the status quo in international relations pivots for the most part on
bilateral(ormultilateral)cooperationratherthanconflictandwar,itisnecessaryto
bettercomprehendcooperationanditsbases.
The research that ensues presents a novel approach vis‐à‐vis perusing the
above phenomena. By attempting to marry traditional conceptions of economic
interdependencewithabroaderpictureofbilateralinteractionswithininternational
relations, I work against the grain of well‐worn analytical pathways that have
dichotomised the outcome of interdependence as either conflictual or peaceful to
various degrees. I begin our journey in the next chapter by first perusing the
prevailingscholarshipforitslimitations,variousdelineationsofconflict,peace,and
cooperation, and what it has to offer regarding the conceptual link between
economic interdependenceanddecreased conflict. I then use these as a theoretical
substratumformyconceptualleapinChapterIII,whereIillustratethelinkbetween
economic interdependence and bilateral cooperation; summarise the relevant
conceptual properties of economic interdependence; and attempt to delineate an
originaltheoreticalmodelandframeworkofbilateralcooperation.
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ChapterI|Introduction
Consequently,Ioutlinethreehypothesesrelatingeconomicinterdependence
to increased bilateral cooperation, and proceed to lay out the various facets of my
research design in Chapter IV. To test my hypotheses, I employ a comprehensive
quantitativecross‐sectionalstudyoncountry‐pairs(ordyads)acrosstheworld,and
detail the operationalisation of economic interdependence, aspects of bilateral
cooperation, and explanatory control variables detailed in the contemporary
literature. In this section, my original research on and data collation of university
exchange agreements, tourist‐visa regimes, mutual IGO memberships, bilateral
visits, and joint military exercises, are amalgamated with existing comprehensive
socio‐economic datasets to construct a quantitative index measuring bilateral
cooperation.Thediscussionleadsontotheconceivableendogeneityissueswithmy
research,andonwardstoChapterV,whereIexplicatemyresearchmethodology–a
combination of time‐lagged OLS regression, and ordered and conventional logistic
regression. I then analyse and discuss the implications of my results, identify
inherentinadequaciesofmystudy,andidentifyopportunitiesforfurtherresearch.
ChapterVIconcludesmystudybyrevisitingthepreviouschapters’achievements.
Now,letusbeginproperbysurveyingtheextantliteratureasaprimertothis
exploratoryjourney.
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ChapterII|LiteratureReview
CHAPTERII–LITERATUREREVIEW
2.1 LimitationsofExistingScholarship
The concept of bilateral relations between states has been extensively
exploredbymuchoftheinternationalrelationsscholarship.Traditionally,thebulk
of relevant literature framed bilateral relations in the context of war or political
conflict (Klein, Goertz, and Diehl 2008). This disproportionate focus on conflict
rather than cooperation can actually be attributed to the historical backdrop upon
whichthisbodyofliteraturewasfirstinstituted–theCold‐Warera.Amidstthreats
of a third world war and nuclear apocalypse, academics sought to marry their
endeavourswiththebroaderaimofshiftingtheworldawayfromtheseprospects.
Hence,thenotionofnegativepeace–thereduction,prevention,orlackofconflictor
violence, was the key objective of most bilateral relations literature; rather than
positive peace or cooperation (Galtung 1964; 1985; 1996). These included leading
research bodies dedicated to the study of polity relations such as JCR and JPR
(Gleditsch,Nordkvelle,andStrand2014).
Hence,thisexplainswhythepreponderanceofresearchexaminingbilateral
relations and its relationship with interdependence have adopted a conflictual or
‘negative peace’ rather than ‘cooperative’ slant; focusing principally on war and
conflict prevention. Furthermore, this orientation towards negative peace rather
thancooperation(positivepeace)meansthatthelatterisatbestmisconceptualised,
oratworst,ignoredintheliterature(Wagner1988;Christieetal.2008).Itishence
evident there is a wide gap to be filled within the current scholarship on
interdependence and bilateral relations due to scant input on cooperative
mechanisms.Whilesomestudiespurporttoscrutinisetheserelationshipsvis‐à‐vis
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ChapterII|LiteratureReview
‘cooperation’ (Pollins 1989b; Suzuki 1994; Reuveny and Kang 1998; Robst,
Polachek,andChang2007),thetheoriesandmeasuresemployedinmoststillfocus
onconflictreduction,andextensivelyperuselarge‐nmeasuresbasedontheconflict‐
negativepeacedichotomysuchastheCOPDAB,COW,ICB,andWEISdatasets.
Such a confined view of bilateral relations does not do justice to the
prevailing climate of increasing cooperation amidst growing interdependence
amongstpolities.Inthisregard,weneedtofirstrealisethattheabsenceofconflict
bynomeansequatestobilateralcooperation(Christieetal.2008).Conflictimplies
‘goal‐seeking behaviour that strives to reduce the gains available to others’ or to
impedetheirdesiresandsatisfaction(Milner1992;1997).Whiletheconflict‐peace
dichotomy is oft‐taken as a given, there are other possibilities as well; while
countries may not be in conflict, either may still choose to exhibit unilateral
behaviour and disregard the consequences of their actions on others, or simply
display inactivity. Both of which, while not conflictual per se, can still be deemed
fundamentally uncooperative as they do not diminish negative consequences for
othersviapolicy–whichispartofcooperation(Milner1992).
Therefore, my research seeks to build upon two extant but as‐yet discrete
bodies of literature; one that has developed general conceptions of international
cooperation,andanother(substantiallylargerbody)thathasextensivelyexamined
the nexus between economic interdependence and conflict. The following sections
explicatetheseinturn.
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ChapterII|LiteratureReview
2.2 TheConflict‐PeaceDichotomyversusCooperation
While the conflict‐peace dichotomy has been instrumental in generating
insightsvis‐à‐viswhatimpactsbilateralrelations,anexplicitfocusonthetheoretical
underpinningsofcooperationisrequiredtogleanacontemporaryunderstandingof
international political economy. The current literature has yielded little in this
regard,withmosttheoreticalstudiesoriginatingfromthe1970s‐1990s.
At the outset, hegemonic stability theory was touted as a plausible realist
explanation of what motivates nations to cooperate (Kindleberger 1973; Krasner
1976;1983;Gilpin1987).Itsbasiccontentionisthe‘distributionofpoweramongst
states[as]theprimarydeterminantof…theinternationaleconomicsystem’(Webb
andKrasner1989).Byextension,cooperationasapublicgoodasperHSTcanonly
be achieved if a strong state with a power preponderance is able and willing to
coerce others and coordinate their actions. In essence, the hegemon provides a
‘public good’ by engendering free trade, and the establishment of an open, liberal
internationaltradesystem.ThesalienceofHSTwasbuttressedbyseveralhistorical
periods which corroborated the possible correlation between the presence of a
politicalhegemonandaliberalisinginternationaleconomy;suchaslate‐19thcentury
Britain,andtheU.S.inthefirsttwodecadesafterWWII.
However, this theory has been subsequently opposed on theoretical and
empirical grounds (Snidal 1985; Frieden 1986; Gowa 1989; 1995), with the
development of a subsequent neo‐liberalist strand focusing instead on structural
conditions resolving collective action problems (Keohane and Nye 1977; Axelrod
andKeohane1985;Oye1985;Stein1990amongstothers).Thisstrandunderscores
theroleofformalandinformalinternationalinstitutionsandregimesinfacilitating
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ChapterII|LiteratureReview
cooperation, through the ‘interests built up by regimes and the information they
provideaboutotherstates’preferencesandactions’(Martin1993).Inthisrespect,
cooperation is comprehended as a collective action and information asymmetry
problem,withinternationalinstitutionsbeingthepanacea.Inaddition,therulesand
norms established by institutions and regimes are theorised to actually ‘positively
constrain’ state behaviour within particular issue‐areas, by making cooperation a
moreviable,worthwhileoption.
Despitetheprevailingdifferencesbetweenthesetwocompetingconceptions
ofcooperationininternationalpoliticaleconomy,itisworthytonotethatbothstill
employsimilarsystemicrationalistapproachesthatutiliserationalchoiceandgame
theoryaskeyanalyticaltools.Thisiswhythescholarshiphaswidelyagreedupona
commondefinitionofcooperation,hinginguponactors‘adjustingtheirbehaviourto
the actual or anticipated preferences of others, through a process of policy
coordination’(Milner1992).However,itwouldseemthattheprevalentneo‐liberal
conceptionofcooperationhastheupper‐handoveritsrealistcounterpartpresently;
its ability to explicate statist relations through institutional enforceability in
response to models such as PD or TfT, makes for a compelling viewpoint that has
since given rise to a multitude of robust trade regimes and agreements – bilateral
andmultilateral. Thebroaderscholarshiphas sincepositedthisviewina rangeof
issue‐areas,suchasnationalsecurityandtheenvironment.
However, as for the literature on economic interdependence and bilateral
ties, these works do not seem to have fully integrated the aforementioned
perspectivesoncooperation.Instead,moststillleverageuponarealistnotionofthe
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ChapterII|LiteratureReview
roleoftradeinreducingoraugmentingthepropensityforconflictthroughshifting
powerbalancesandbenefitdistribution–asthenextsectionexplicates.
2.3 EconomicInterdependenceandConflict
Appraising the extant literature‐at‐hand will yield insights regarding the
theoreticalmechanismslinkingeconomicinterdependencetodecreasedconflict;and
by extension, provide a possible theoretical substratum linking economic
interdependencetocooperation.Itisimportanttonoteattheoutsetthough,thatthe
former is by no means a recent proposition; it originated from the likes of Kant
([1795]1991) some three centuries ago, who conjectured the existence of three
factors leading to (negative) peace – democracy, economic interdependence, and
internationalorganisations.
Aburgeoningbodyofliteraturehassubsequentlyensuedaroundeachlegof
the ‘Kantian Tripod’, with trade used liberally as an unequivocal representation of
economic interdependence in association with political conflict (or the absence
thereof).Thepastfewdecadesinparticularhasseenanupsurgeininterestapropos
of the liberal argument of ‘more trade, less conflict’, with much of the research
‘generally concluding that trade has a pacifying influence on interstate relations’
(Xiang, Xu, and Keteku 2007). Various hypotheses linking trade flows, trade‐GDP
ratios, or even the type of goods traded with political conflict levels or MIDs, have
since been advanced. These hypotheses are often supported by large‐scale
quantitative data analysis. In the ensuing sections, I explore how the surfeit of
accounts is aligned roughly to three causal mechanisms detailing how more trade
resultsinareducedlikelihoodofconflict.
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ChapterII|LiteratureReview
The first causal mechanism expounding the negative correlation between
trade and conflict draws from macroeconomic theory; and centres on constraint,
expectedutilityarisingfromtrade,andopportunitycostsoftradedisruptionarising
from conflict. This argument’s basic formulation is that conflict amongst polities
disrupts commerce – which iscostly. The rise of expected opportunity costs in the
eventofconflictthroughincreasingtradehencediminishesthepotentialofconflict
orviolenceamongstcountrieswithextensivetradingrelationships.Thisisperhaps
the mostly ‘widely accepted theoretical link’ explaining the pacifying influence of
tradeonbilateralrelations(Kastner2009),thathasbeenadvancedbytheliterature
for more than half a century (Viner 1951; Polachek 1980; Copeland 1996; Doyle
1997; O’Neal and Russett 1997; 1999a; 1999b; Polachek, Robst, and Chang 1999;
Polachek and Seiglie 2006; Peterson 2014). Some studies reinforce this theory by
extendingthismacroeconomicexplananstodomesticpolitics;increasedtradecould
alsoextendtheinfluenceofeconomicfactionsbenefitingmostfromtrade,whichin
turn have ‘incentives to pressure the government’ to maintain a conflict‐free
environment conducive to trade (Buzan 1984; Rogowski 1989; Papayoanou 1999;
RussettandO’Neal2001;Levy2003;McDonald2004).
However,despitetherelativelylongheritageofthefirstapproach,itsnarrow
economic foundation has led to many in the field such as Mansfield and Pollins
(2001; 2003) seeking alternative explanations for trade inhibiting conflict. This,
alongside divergent studies and reviews of existing literature calling into question
the salience of the above causal mechanism (McMillan 1997), led to the birth of a
second,morerecentlineofscholarship.Thisapproachdrawslargelyfromsignalling
literature, and focuses on incomplete information predicaments. Essentially,
countriesinadyadhavedifficultiesknowinghowcommittedorresolutetheotheris
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ChapterII|LiteratureReview
regarding issues‐at‐hand; hence both have incentives to exaggerate their
commitmentinthehopethattheotherwillyieldmorethanitotherwisemight(i.e.
engage in a game of bluff). Consistent with bargaining models of war, if one party
mistakenlybelievestheothertobebluffingwhenthelatterisinfacthighlyresolute
initsenunciatedscheme‐of‐action,militaryconflictcanensue(Fearon1995;Reiter
2003). In this regard, high levels of economic integration mitigate this incomplete
information dilemma in dyadic relations, by providing an additional platform for
countriestocrediblysignalactualresolve(e.g.imposingeconomicsanctions)short
of conflict (Gartzke, Li, and Boehmer 2001; Gartzke 2003; Gartzke and Li 2003;
Morrow2003;Stein2003;Krustev2006).Anumberofscholarsextendthisline‐of‐
reasoning to incorporate other factors such as game theory and equilibria (Kim
2009);third‐partystates seekingtodefend alliesagainstaggressors(Aydin2010);
andevenmicro‐economictheory(Bearce2003).
Thus, increased trade seems to lessen the likelihood of military conflict
amongst states arising from ‘miscalculating’ resolve. However, much like the first
explanation, this conception still lacks a theory of state‐society relations that goes
beyond mere economic concerns (McMillan 1997; Stein 2003). The third causal
argumentaddressesthisneedandisslightlymoresociologicalinitsunderpinnings;
focusing upon the greater contact and interaction between dyadic actors due to
economic integration or trade. This argument postulates trade’s ‘transformative
impact’ – with frequent interaction between two polities, both can gradually
gravitate towards a view of shared interests, and consequently deprioritise their
formerly disparate goals (Adler and Barnett 1996; Blanton 2006). This would also
spawnnewfactionsinpoliticsandsocietywhichviewconflictascounterproductive,
and consequently advocate a more collaborative stance towards the attainment of
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goals. Such factions would eventually crowd out older, possibility more inimical
actors.Overtime,thislowersthepropensityforconflictduetoincreasinglyshared
nationalinterests.Thisline‐of‐reasoningisas‐yetstillemergingwithalimitedbody
of literature focusing on the ‘connections’ beneath the systemic level (Hirschman
[1945]1980; Rogowski 1989; Abdelal and Kirshner 1999; Arikan and Shenkar
2013),andevenmicro‐levelimplicationssuchasindividualperceptionsandforeign‐
policyattitudes(DorussenandWard2010;KleinburgandFordham2010).
However,theconceptualisationofpeacefromthe‘negative’tothe‘positive’is
still underdeveloped in this regard. The as‐yet most pertinent research, while
contending that interdependence extends beyond mere economics as per the
conceptofacommunityofstates(Deutsch,Burrell,andKann1968;Blanton2006),
still draw heavily on the conflict‐negative peace dichotomy; and/or are narrow‐
scopesingle‐norsingle‐issuestudies(EstevadeordalandSuominen2008;Demiryol
2013). This is where my research comes in to fill this gap and develop the theory
behind trade’s ‘transformative impact’. In the next chapter, I explicate the link
betweeninterdependenceandcooperation;referencingthetransformationofpolity
behaviourthroughtrustwithinalong‐termbilateralrelationship.
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ChapterIII|TheoryandHypotheses
CHAPTERIII–THEORYANDHYPOTHESES
Does economic interdependence in a dyad hence influence the degree of
bilateralcooperationbetweenitsconstituentstates?Ifirstmakeaconceptualleap
fromtheextantliterature,byarguingthateconomicinterdependenceincreasesthe
propensity for bilateral cooperation via strengthening trust and perceptions of
shared futures. This also explicates why some dyads seem to co‐exist in extended
harmony, while tenuous or fractured peace haunts others; it is also theoretically
distinctfromthenotionofinterdependencedecreasingthepropensityforconflict.I
subsequently corroborate my theory by expounding the conceptual properties of
economic interdependence, and delineating a working model of bilateral
cooperation by means of outlining its various constituents. I conclude this chapter
withatrioofhypothesesdesignedtotesttheoreticalveracity.
3.1 EconomicInterdependenceandBilateralCooperation
In the following sections, I explicate how economic interdependence
engendersa)bilateralcooperationintheeconomicsphere;b)bilateralcooperation
in other issue‐spheres, i.e. contributing to a spill‐over effect due to its inherent
nature;andc)moreformalisedcooperation.
Atypicalconceptionofeconomically‐interdependentcountriespivotsonthe
notion of one relying upon another for commodities that cannot be efficiently
produced domestically. Far from being a contemporary conception accompanying
the phenomena of globalisation and expanding economic ties between states,
economicinterdependencewasidentifiedintheearly‐19thcenturyasacorollaryof
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an international division of labour (Cournot and Fisher [1838]2005). However, of
relevancearetheimplicitattributesofinterdependence;ifacountryisreliantupon
others, it is vulnerable to the actions of others. For instance, if country A relies
extensively on country B for sand imports to satisfy its infrastructural needs, A is
vulnerable in that if B chooses to renege upon existing agreements to support A’s
infrastructure‐buildingeffortsbyhaltingsandexports,Awillbeseverelyimpacted
orworse‐off.
Hence,economicinterdependenceisasalientplatformformutualtrusttobe
exercised in cooperative engagements, as countries choose to ‘expose’
vulnerabilities for want of longer‐term overall benefits that will result due to the
(expected)fulfilmentoftrust.Inthisregard,economicinterdependenceengenders
bilateralcooperationintheeconomicsphere–intermsofliberalisingandopening
up markets, as well as trade. Drawing from the aforementioned hypothetical
scenario,asAchoosestoimportB’sgoodsandishencevulnerabletoB’sbehaviour,
BcanchoosetodemonstratethatA’strustiswell‐placedbymeetingA’sneedsand
not reneging on agreements. This will render A more confident that B is
trustworthy;AwillsubsequentlybemoredisposedtodependonBinthefuture.
As trust is built across a chronological continuum, we see how economic
interdependence can strengthen cooperation across time too – in addition to
sustaining it. States (potentially) experience economic interdependence across a
wide range of factor endowments; this is constantly evolving and iterative, rather
thanepisodic innature.Hence,statesina dyadwill constantly be confrontedwith
the need to cooperate for want of better outcomes vis‐à‐vis the status quo, and
consequentlybecontinuallybequeathedopportunitiestobuild(orerode)trust.IfA
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recognises that B has been trustworthy for the bulk of their past interactions, and
thatBcanbereliedupontoactbenevolentlyfortheinterestsofA,thisdyadwillbe
increasingly inclined to cooperate more. Conversely, if B has been constantly
breaking A’s trust by reneging on agreements (to reduce or remove tariffs for
instance),itisunlikelythatAwouldbewillingtotrustBandcooperateattheriskof
being‘played’infuture‘iterations’.
This somewhat manifest account aside, I posit that dyadic economic
interdependence has the ability to engender cooperation in other, more immersive
issue‐sphereswithhigherstakestoo–overandbeyondstimulatingsimplyeconomic
cooperation.Thisincreasedcooperationacrossissue‐spherescanbeelucidatedfrom
thenatureoftrust.Accretedtrust fromsuccessfulcooperationin oneissue‐sphere
doesnotonlyapplytofutureconsiderationstocooperatewithinthatissue‐sphere,
but also to future considerations for cooperation in other issue‐spheres. If A’s
economic tie‐ups with B have been recurrently successful due to B ‘upholding its
sideofthebargain’,A’strustinBisvalidatedandaugmented,withitsperceptionof
B’strustworthinessamidstA’svulnerability,enhanced.Ifopportunitiesformilitary
collaboration ensue in this instance, trust accreted in the economic sphere would
undoubtedlypositivelyimpactA’sdecisiontocooperatewithBmilitarily–sinceB
hasprovenitselfreliableenoughinitspreviousdealingstobeentrustedwithmore.
Asidefromthe‘scope’orissue‐spheresofcooperation,Iadditionallyadvance
thelinkbetweeneconomicinterdependenceandformalisedcooperation(or‘mode’
ofcooperation).Formalmodesofcooperationaremoremulti‐facetedandextensive
relative to informal cooperation (further illustrated in section 3.3). The causal
mechanism linking economic interdependence and formalised cooperation
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ChapterIII|TheoryandHypotheses
(regardless of issue‐sphere), builds on the relationship between interdependence
andeconomiccooperation.Witheachsuccessfulinteraction,countriesinadyadfind
eachotherincreasinglytrustworthyandreliable,andwillhencebemoreinclinedto
cooperateatadeeperlevel.Asaresult,moreformalcooperationmechanismsthat
provide for greater collaboration through legal instruments and treaties will be
pursued–versusinformal‘touch‐and‐go’cooperation.Ofcourse,thereverseapplies
too;ifdistrustisengenderedinthecourseofinteraction,thencountriesareunlikely
topursuemoreformalisedcooperation.
3.2 ConceptualPropertiesofEconomicInterdependence
As Crescenzi puts it succinctly, ‘typically when we think of economic ties
amongnations,thefocusisonthe[mutual]welfaregainsthatresultfromopening
marketaccessandincreasingtrade’(2005).However,acounter‐intuitiveapproach
has
prevailed
across
contemporary
conceptualisations
of
economic
interdependence.Asopposedtomutualbenefit,mostofthescholarshipidentifytwo
privative constituent properties of economic interdependence. The first is the
opportunity cost of not having existing economic ties with a country; this has been
conceivedinvariousways,suchthelackofalternativescountrieshaveinrelationto
anexistingeconomicrelationship(Hirschman[1945]1980);reciprocalopportunity
costs of severing economic ties in a dyad (Baldwin 1980); and the sensitivity and
vulnerabilityofastateinrelationtoaseveredeconomicrelationship(Keohaneand
Nye 1977). To illustrate this, let us assume that trade flows within a country‐pair
(exports from A to B and imports of A from B) constitute five percent of A’s total
global exports, and B’s total global exports. If the duo were to stop trading, each
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wouldincurafivepercentdecreaseinboththeirexportsandimports.Thisreflects
therelativeeconomicinterdependenceofAandB.
The second constituent property of economic interdependence is the
symmetry(orlackthereof)instatedependence.Givenhowwithinadyad,onestate
canbemoredependentontheotherthanviceversa,symmetrycapturesthe‘relative
balance of economic interdependence’ (Crescenzi 2005). At one extreme, absolute
symmetry transpires when states A and B in a dyad are equally dependent upon
eachothereconomically.Ontheotherhand,absoluteasymmetrytranspiresifstate
Aiscompletely(economically)dependentuponstateBinadyad,butstateBisnot
economically dependent at all on state A. Conceptions of symmetry have been
advancedintermsofrelativepower(KeohaneandNye1977),importanceoftrade
(Barbieri 1996), or even trade as a proportion of GDP (O’Neal and Russett 1997).
However,itisimportanttonotethatsymmetrycomesintoplayonlywhenweare
interestedintherelativelevelsofdependenceonecountryhasontheotherwithina
dyad.While instructivein somecontexts,symmetry isancillarywithinmyscopeof
research,whichseeksanamalgamatedunderstandingofdyadicinterdependence.
3.3 DelineatingaDefinitiveModelofBilateralCooperation
Withasubstantiveconceptionofeconomicinterdependenceinplaceandits
linktobilateralcooperation,afurthercodiciltothenovelconceptionofcooperation
betweenstatesemployedbymytheorywillservetofurthersharpenthenarrative.
Contrary to most traditional conceptions employed by the IPE literature, the
delineation of cooperation in my research extends beyond economic bases. States
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cooperate because they trust each other. Trust is built or eroded, as a country A
appraisestheactionsanddeducestheintentionsofanothercountryB,andevaluates
B’s actions and intents against its own preliminary benevolent expectations or
predictionsofB’sbehaviour.
However,trustisalsolargelytiedtotheconceptofvulnerability;thebuilding
orerodingoftrustcannotoccurunlessthereisriskinvolved.Ahypotheticalscenario
involvingacountryArequestingmilitaryassistancefromcountryBtoquellacivil
war,illustratestheriskunderlyingAtrustingB.IfA’sexpectationsofB’simpending
supportareunfulfilled,Awillbecategoricallyworseofforsufferalossofutilitydue
tothecostofpossiblyundergoingmassiveinternalupheaval.Othercostsinthiscase
could include continued domestic pressures on A’s government, and the further
weakeningofA’sstatecapabilities.Conversely,ifA’sexpectationsofBarefulfilled,A
willbecategoricallybetteroffandexperienceanetgaininutility.Fromthisexample,
wecandefinetrustbetweencountriesasfollows:AtrustsBifA,byexpectingBto
actinacertainwaybeneficialtothewell‐beingofA,exposesitselftorisk.Thistrust
isvalidatedifBfulfilsA’sexpectations,buterodedorbrokenifBdoesotherwise.
Asuccessfulepisodeofcooperationcanhencebeconceivedasthatwherebya
countryAhasitstrustwell‐placedincountryB,throughBmeetingA’sexpectations
forbenevolentactionwhenAchoosestobevulnerableandexposeitselftoriskby
trustingB.Incontrast,anunsuccessfulepisodeofcooperationcanbeconceivedas
thatwherebyBhasbreached thetrustplacedinit byA,duetoB’sdecision tonot
meet A’sexpectationsfor benevolentaction,andsubsequentlyresultinginAbeing
worseoff.Itisimportanttonotethoughthatcooperationisnot‘one‐sided’,inthat
states engaging bilaterally often choose to engage in mutual trust, and incur
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ChapterIII|TheoryandHypotheses
reciprocal risk too – across a range of issues. Figure 1 illustrates how bilateral
cooperationoccurswithintheaforementionedframework.
Since bilateral relations occur across a continuum, trust in a dyad can be
augmentedordiminishedacrosstime.Consequently,itisconsistenttoconceivethat
with greater trust andgreater vulnerability, comes varying degrees of cooperation
across a continuum too. As such, it is useful to regard cooperation across various
spheres, as trust manifested at different intensities. At the outset, there is socio‐
culturalcooperationwhichrequireslittlemorethanatokenleveloftrustbetween
twopolities,giventhatexchangesinthissphereoftendonotentailmuchriskvis‐à‐
vis the state (but also do not result in much gain for states too). Consider, for
instance, the 2008 New York Philharmonic’s visit to the DPRK in the name of
culturalexchange–amidstthefrostinessofU.S.‐DPRKbilateralrelations.Evenifthe
DPRKhadseizedtheopportunitytodetainthemusiciansforpoliticalleverage,the
U.S. as a state wouldnot have suffered much inherently (apartfrom the loss of an
acclaimed orchestra amidst much public outcry). Though this visit defused the
inherent tensions between the U.S. and DPRK for a period of time, this was short‐
lived–demonstratingthe‘littlerisk,littlegain’adage.
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ChapterIII|TheoryandHypotheses
As countries build upon positive experiences and mutual trust over time,
economic and political cooperation comes into play. These two spheres seem
entwined due to the synergetic nature of international politics and the economy;
consequently,cooperationacrossthesespheresentailaplethoraoflinkagesranging
fromtrade,FDI,politicalalignment,andmutualmembershipsinIGOsamongstmany
others.Acountryengaginginsubstantialpolitico‐economicexchangewithanother
issusceptibletosizeable‘losses’ifagreed‐uponobligations,suchasremovingtariffs
orquotasinthecontextofanFTA,arenotupheld;butalsostandstogainmuchby
wayofeconomiesand/oralliesintheinternationalarenaifitstrustiswell‐placed.
The case of post‐2005 Sino‐Singapore relations illustrates this, as a slew of
comprehensive agreements in free trade, foreign investment, and technology were
forgedonmutualtrust,leadingtosubstantialmutualgains.Singapore’sassistancein
developing Chinese industrial and eco‐parks has both increased economic
development in the PRC, and contributed greatly to Singapore’s international
standingaproposofitstechnologicalexpertise.
Finally,dyadswiththehighestlevelsoftrustcultivatedtendtocooperatein
the military and security spheres too. These are oft‐founded upon the bedrock of
similar political leanings or ideals, which would have engendered much initial
politicalcooperation.Thedemocraticpeacetheory,alongwiththeestablishmentof
security blocs like NATO, the former Warsaw Pact, and more recently the SCO,
validatesthenotionofhowmilitarycooperationtendstooccuramongststateswith
similarideals.Cooperationinthesecuritysphereisalsothemostprofoundvis‐à‐vis
other issue‐spheres, as countries run the greatest risks and are at their most
vulnerablewhilecooperating.Indeed,the‘greattrustcomesgreatrisk’adageisbest
illustrated by the unique example of Switzerland, which relies on the military
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ChapterIII|TheoryandHypotheses
capabilitiesofitsFrenchandItalianneighbourstopoliceitsownairspaceoutsideof
the Schweizer Luftwaffe’s ‘office hours’. Essentially, Switzerland is placing its
sovereignty–theverynatureofitsexistence–inthehandsofitsneighbours.Even
for typical military collaborations, countries still incur great risk by coordinating
military tactics and hardware with their partners – implying implicit deep‐seated
trustinpartnerstonottakeadvantageofsuchknowledgeand‘screwthemover’.
The hierarchy of cooperation across issue‐spheres aside, it is worth noting
thatthemodeofcooperationcanvarytoo–formally,orinformally.Whileitmaynot
seemparticularlyconstructivetoconsiderthesedichotomousmodesuponacursory
examination, further scrutiny comparing formal and informal cooperation yields
insightsvis‐à‐visthesignificanceoftheissuesinthebalance,alongwithcountries’
commitment levels. Formal modes of cooperation are generally institutionalised,
and often originate from legislative treaties or ratified agreements mandating
periodic contact or linkage. Examples of these include planned yearly summits
between ministers, cooperative mechanisms between law enforcement agencies,
andbilateraltradeagreements.Hence,ifstatescooperateformally,thissignalstheir
sizeable resolve to commit and seek the trust of another since significant
consequenceswillarisefromthenon‐fulfilmentofobligations.
Informal cooperation in contrast often occurs outside the purview of
institutions, and is not the product of a legal instrument. This comprises ad‐hoc,
issue‐based engagements such as diplomatic communications between countries’
foreign ministries. While still significant in terms of the potential mutual goodwill
andamitythatcanbefostered,thelackoftangibleconsequencesshouldonecountry
renege upon its agreements in any sphere (apart from the ‘inconveniences’ as a
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ChapterIII|TheoryandHypotheses
resultofonecountry‘standinganotherup’)meansthatinformalcooperationcanbe
considered as an indication of a state’s lesser resolve to commit or want for
another’strust–relativetoitsformalcounterpart.
The illustration that follows encapsulates the various spheres in which
bilateralcooperationcanbeengendered,alongwiththelatter’sdifferentmodes.
These causal mechanisms are drawn from parallel fields of psychology and
sociology (Deutsch 1958; Balliet and van Lange 2013), and depict how general
patternsofindividualbehaviourcanhavecogentapplicabilityatthecollectivelevel
of nations. After all, the motivations behind a course of action of a country, along
with the reactions of other countries, can be construed simply as an aggregate of
individual opinions or attitudes affected by cognitive perceptions. Since ‘actions’
undertaken by states in the international arena are merely the products of their
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ChapterIII|TheoryandHypotheses
constituent policy‐makers and politicians’ decisions (rather than that of an
amorphous mass), it is clear how inherent motivations and perceptions at the
individual level can bear on bilateral relations. Such a postulation is by no means
far‐fetched; in fact, many contemporary IPE theories are steeped in cognitive
reasoning at the individual level. These include theories such as those expounding
thedifficultyofenforcingbilateraltradeagreements.Thelatterhasbeenextensively
modelled via the PD, which portrays countries as rational individual ‘players’
seeking maximum utility; and the TfT, which builds on themes of behaviourial
reciprocity (Axelrod 2006). Together, these theories further reduce notions of the
‘unitary’statetoitsindividualanthropologicalconstituents.
3.4 Hypotheses:OfCooperation,Hierarchy,andDecorum
Inordertotesttheveracityofthetheoreticalbasesoutlinedthusfar,Ihence
constructatrioofhypothesestoguidemyinvestigationsinthefollowingchapter.
H1: The more economically interdependent countries in a dyad are, the
morebilateralcooperationengendered.
H2: The more economically interdependent countries in a dyad are, the
more bilateral cooperation engendered – in different spheres, to differing
incremental degrees; ranging from relatively low for the socio‐cultural
sphere,torelativelyhighforthemilitary/securitysphere.
H3: The more economically interdependent countries in a dyad are, more
formal modes of cooperation ensue relative to informal modes of
cooperation.
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ChapterIV|ResearchDesign&Methods
CHAPTERIV–RESEARCHDESIGNANDMETHODOLOGY
For this chapter, I delineate my course‐of‐action to test theaforementioned
hypothesesandoperationalisethesalientvariables.Againstthebackdropofcross‐
sectional quantitative data analysis, my unit of analysis is the undirected dyad (as
opposed to the bidirectional dyad used in a sizeable portion of the literature thus
far). The undirected dyad is a pair of countries A and B, whereby the pair A‐B is
taken as equivalent to the pair B‐A. I choose the undirected dyad, as my scope of
researchomitsthesymmetryofstates’economicinterdependenceoneachotherand
varyinglevelsofintra‐dyadimpetustoengagecooperatively.
The 7,891 undirected dyads under consideration are derived from a list of
149countries(seeAppendixI).Toensuredataintegrityandfaircomparisonacross
dyads,excludedfromanalysisarecountriesa)withpopulationsoflessthan500,000
asper2012UNestimates(UNDESA2013);b)withoutastandingmilitaryforceasof
2012;c)undergoingregimetransitionasof2012(CenterforSystemicPeace2014);
d) lacking reliable 2012 trade data (UN COMTRADE 2014); or e) belonging to a
combinationoftheabove.Allpossibleundirecteddyadsderivedfromtheindividual
countrylistweresubsequentlyconstructed.Duetodifferingcategorisationsacross
countries and problems with interpolating or extrapolating data (Barbieri, Keshk,
and Pollins 2009; Gleditsch 2010), dyads are excluded if they have zero‐value or
unavailabletradeflowfiguresrespectively.
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ChapterIV|ResearchDesign&Methods
4.1 DependentVariable:BilateralCooperation
In keeping with my conception of bilateral cooperation across various
spheresastrustmanifestedatdifferentintensities,atheory‐drivenaggregateindex
ofbilateralcooperation(BCI)operationalisesthisvariable.TheBCIcomprisesfour
compositesub‐indicesrepresentingthespheresinwhich bilateralcooperation can
occur along an ordinal scale: 1) socio‐cultural, the least ‘intensive’ of the four
spheres; 2) economic; 3) political; and 4) military or security, oft‐regarded as the
most ‘intensive’ sphere of cooperation. These spheres are subsequently accounted
forandintegratedwithinseveralmodelsofcooperation.Astatisticaldescriptionof
thesixcomponentdependentvariablesfollows,alongwiththeirexplications.
TABLE1.DESCRIPTIVESTATISTICSOFCOMPONENTDEPENDENTVARIABLES
Concept
Explanatory
Variable
DependentVariable BCIComponents
University
InformalSocio‐
Exchange
cultural
Agreements
Cooperation
FormalSocio‐
TouristVisa
cultural
Regimes
Cooperation
Economic
BITsandIIAs
Cooperation
InformalPolitical
Officialand
Cooperation
StateVisits
FormalPolitical
MutualIGO
Cooperation
Memberships
Military/Security
JointMilitary
Cooperation
Exercises
Min.
Max.
Mean
Median
SD
0
1
.244
0
.429
0.125
1
.457
0.375
.223
0
1
.114
0
.166
0
1
.178
0
.225
0
1
.097
0
.155
0
1
.059
0
.131
n=7,891
Notes:Allvariableshavebeennormalisedtosimilarscalesinordertofacilitatecross‐comparability
andweightingfortheirsubsequentinclusionintheBilateralCooperationIndex.
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4.1.1 Socio‐CulturalCooperation
The conceptual characteristics of dyadic socio‐cultural cooperation are the
low levels of risk entailed through trust‐building activities, relative to the other
spheresofcooperation.Thisisoftenexemplifiedbycollaborativemechanismsinthe
fieldofacademiaorculture,wherebythe‘fallout’isrelativelylowtothestateshould
cooperation fail. I use academic exchange agreements or programmes between
countries’ tertiary educational institutions, and tourist‐visa regimes as measures of
informalandformalbilateralsocio‐culturalcooperationrespectively.
Academic exchange agreements (e.g. semester or year‐abroad programmes)
betweenuniversitiescanbeseenasareflectionofcountries’willingnesstoengage
in cultural and intellectual interchange – effectively synergising their collective
academic competencies and leveraging on talent diversity. While often seemingly
‘formalised’indocumentedinstitutionalstatutes,academicexchangesaretakenasa
gaugeofinformalcooperation,aspunitiveorreprisalmechanismsarenotapplicable
intheeventofnon‐conformity.Thus,inkingacademicexchangescan be conceived
ascooperatinginformallysinceithasnostatutorysignificanceatthestatelevel.
Icompiledanoriginaldatasetthatcodesforacademicexchangeagreements
within dyads, using a binary measure of whether an agreement exists between
universitiesofcountriesinadyadorotherwise.Agreementseitherexistbilaterally,
orwithinalargermultilateralframework(suchastheERASMUS+programme).The
universitiesconsideredinmydatacompilationwerederivedfromthedirectoriesof
three comprehensivehigher‐education ranking establishments asof end‐2013:the
QS‐WorldUniversityRankings(2014),theTimesHigherEducationWorldUniversity
Rankings (2014), and the IAU World Higher Education Database (2014). These
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collectively comprise 18,000‐odd university‐level institutions across all the
countries‐of‐interest.Tofacilitatedatacompilation,Iemployedanautomatedopen‐
sourcedata‐crawlersearchalgorithm(DataparkSearch2014)toqueryandlogdata
fromindividualuniversitywebsiteswithcountrynames‐of‐interest.
Conversely,tourist‐visaregimes(TVRs)canbeperceivedasanindicationofa
state’s disposition towards ‘anthropological flows’; country A’s open‐door visa
policyregardingcountryBoftenconnotesthatB’scitizensarewarmlywelcomedin
A. The degree of amenability or openness countries exhibit to their counterparts’
tourists is an indication of formal socio‐cultural cooperation; given that TVRs are
officially enforced by the foreign affairs and immigration apparatuses, and that
foreignstatesareentitledtoformaldiplomaticremonstrationsshouldtheircitizens
besubjecttoinconsistentTVRenforcement.
IcodeforTVRsusingacompoundvaluethataggregatestheopennessofA’s
tourist‐visaregimevis‐à‐visB,withtheopennessofB’stourist‐visaregimevis‐à‐vis
A. TVR openness for each ‘direction’ is measured on an ordinal scale of 0 to 4; ‘0’
denotesadmission refusaltoincomingtouristsof thenationality‐in‐question;‘1’, a
visa‐in‐advance policy; ‘2’, a visa‐on‐arrival policy; ‘3’, visa‐exempt or visa‐free
policies; and ‘4’, additional reductions of entrance requirements on top of visa‐
exempt or visa‐free policies (e.g. unlimited stay or passport‐free ID‐card travel
policies). Adding the TVR openness values of A‐B and B‐A together gives us the
dyadic TVR measure. I compiled information based on cached raw data for end‐
2013, obtained from the IATA’s TimaticWeb2 database (2014) which details
worldwidecross‐borderpassengerdocumentationrequirements.
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4.1.2 EconomicCooperation
Aswearestudyingtherelationshipbetweeneconomicinterdependenceand
bilateralcooperation,measuringdyadiceconomiccooperationusingthe‘customary’
trade flows, stocks or trade‐related bilateral data as per much of the extant
literature will not be adequate. These measures also encompass economic
interdependence – the independent variable‐of‐interest (a further discussion of
inherent endogeneity follows in a subsequent section). A more precise and robust
operationalisation ishence requiredvis‐à‐vis dyadic economiccooperation.Also,a
bimodal concept of cooperation in the economic sphere does not seem relevant;
most economic sphere collaborative mechanisms between countries tend to be
formalised,suchaslegislatedPTAsortradeandcustomsunions.Giventhenatureof
integrationintheeconomicsphere,countriessacrificeasubstantialdegreeoftheir
sovereigntyorautonomy,astheycooperatewitheachotherintermsofstreamlining
standardsandenactinglegislatureamongstotherstoreapeconomicbenefits.
Tothiseffect,IhenceuseBITsandotherinternationalinvestmentagreements
(IIAs) as a measure. With currently more than 2,500 BITs in force worldwide,
countriescooperateviaBITsinordertoattractmoreFDI.Thisisdonebyprotecting
foreigninvestorsthroughthemandatingoffairandequitabletreatment,proscribing
expropriation,andevenallowingforalternativedisputeresolutionmechanismsvia
international arbitration panels. States potentially direct much of their resources
andeffortstoenactlegislativeorsystemicchangeastheyenterintoBITsorother
IIAs;meaningthatthecorollariesstemmingfromanon‐fulfilmentofobligationsare
relativelyhighcomparedtosocio‐culturalcooperation.
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IcodeforBITsandIIAsbetweencountriesinadyadusinganamalgamated
measure;thisisacompoundvaluethatsumsallexistinginvestmenttreatieswithin
a dyad – both BITs, intra‐economic bloc IIAs (e.g. ASEAN, CARICOM, EU), and
investment chapters within broader bilateral trade agreements. The more
investmentagreementswithinadyad,thebroaderanddeeperthescopeandextent
of cooperation. Data (as of end‐2013) were derived from the UNCTAD’s IIAs
database(2014),andtheWTO’sPTA(2014)andRTA(2014)databases–whichare
the most comprehensive and reliable BIT/IIA datasets available to date. For each
BIT/IIA surveyed, a ‘1’ indicates that an agreement was signed but not ratified or
enteredintoforce;a‘2’indicatesasignedandratifiedagreement.Addingallthese
togetherfortherelevantdyadsgivesustheamalgamatedmeasure.
4.1.3 PoliticalCooperation
I use the incidence of high‐level official and state visits between dyad
membersasagaugeofinformalpoliticalcooperation.Despitethe‘formal’sounding
appellation, these visits are neither legally obligatory, nor binding, nor
institutionalised – and hence considered informal in nature. While occurring
frequentlytheyarenotinherentlyregular;infact,thesouringofpoliticalrelations
withindyadsoftencausessuchvisitstodeclineorevendesisttemporarily.However,
thesevisitsarealsosalientindicatorsofastate’swillingnesstoengageindialogue
withtheircounterparts,andmaintainorcultivateexistingbilateralrelations.These
visits can be further categorised into state visits, which often comprise public
ceremonial events and deemed as the topmost articulation of good bilateral
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relationsamongststates;andofficialvisits,whichhaveamorefunctionalslant,and
focusmoreonthedevelopmentofexistingbilateralties.
Icompiledanoriginaldatasetforofficialandstatevisitsfrom2013to2014,
and take the aggregate of Country A to Country B’s visits and B to A’s visits
convertedintoa0‐6scaleasthemeasure‐of‐interest.Thisaggregaterepresentsthe
intensityoftotaldyadicvisitsderivedfromdirectionaldatacodedona0‐3scale;‘0’
denotesnovisits;‘1’denotes1‐3visits;‘2’denotes4‐7visits;and‘3’denotesmore
than8incidencesofvisits.IcollectedthedataviaaGoogleAnalyticskeywordsearch
onpubliclyavailablenews releases derivedfrom official foreignorexternalaffairs
ministrywebsitesofsampledcountries,alongsideanonlinenewsaggregatorsearch.
Contrariwise, formal political cooperation can be gauged in terms of the
numberofjointIGOmembershipswithinadyad.Thiscanbeconceivedasasignalof
states’alignmentormutualassociationinagivenissue‐area;forinstance,inthecase
of ASEAN, member countries accede to the ASEAN Charter which promotes
principles of non‐interference and consensus through dialogue. In so doing, they
recognise the legal status of ASEAN along with the codification of its rules and
values. While the individual political stances of countries may differ within each
issue‐bloc or organisation, the very undertaking of mutual affiliation is one that
illustrates their desire to work together in the political sphere, government‐to‐
government. Given the legal code adopted by most IGOs, membership signals a
country’s relatively strong intent to abide by mutual standards, and willingness to
collaboratewiththelike‐minded.
I collected original data on joint IGO memberships by first cross‐checking
memberships of countries in a dyad for 60 leading contemporary IGOs with
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substantial clout and prominence in the international arena. I rely on the UIA
YearbookofInternationalOrganizations(2014)toidentifyalldocumentedpolitical
IGOs,beforesubsequentlycompilingtheabridgedlistof60usingGoogleTrendsand
Analytics to identify the most active, influential, and prominent in terms of
substantive work (e.g. conferences, joint press releases, and research). Mutual IGO
membershipsarecodedforasabinaryvariable,andsubsequentlyusedtoderivethe
aggregatenumberofmutualmembershipsforeachdyad.
4.1.4 Military/SecurityCooperation
Whilecooperationinthemilitaryspherevariesintermsofpotencyanddepth
(compare for instance the long‐lasting U.S.‐U.K. military partnership with the
somewhat delicate Singapore‐Malaysia security agreements), the formal‐informal
dichotomydoesnotseemapplicableinthisrespect.Securityormilitarylinkagesare
mostly not legislated or ratified with ‘punitive’ mechanisms for non‐compliance.
Evenifthelatterishypotheticallythecase,countriesmaystillchoosetoviolatetheir
agreementsatverylittleactualcost(e.g.renegingondefensepactandwatchingits
partner get conquered) – making the formal‐informal dichotomy somewhat
incoherentinthiscontext.
Hence, a single measure will suffice to provide insight vis‐à‐vis military
cooperation–thenumberofjointmilitaryorsecurityexercisesdyadsareengagedin.
Thesearedifferentiatedfromother‘on‐paper’agreementssuchas‘formal’alliances,
mutual defense pacts, non‐aggression treaties, and ententes. I collated year 2013
originaldatafortheseexercisesviaaGoogleAnalyticskeywordsearchonpublicly
availablenewsreleases,derivedfromofficialdefenceministryandmilitarywebsites
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ofindividualcountriesalongsideanonlinenewsaggregatorsearch.Anordinalscale
isthenutilisedtorepresentthisdata:‘0’denotesnojointexercises;‘1’denotes1‐2
exercises;‘2’denotes3‐5exercises;and‘3’denotesmorethan5jointexercises.
4.1.5 ModellingtheBilateralCooperationIndex
With the component measures of bilateral cooperation across the various
spheressetforth,Inextconstructseveralmodelsthatmarrythesecomponents,and
weighthemaccordingtotheirhierarchicalsignificanceinmytheory.Twoissuesof
relevance are 1) the defined sphere in which the component measure exemplifies
bilateral cooperation; and 2) the mode of cooperation the component measure
represents. I use either a simple linear or geometric/exponential sequence to
representthe‘hierarchyofcooperationspheres’inthefirstfourconceptionsofthe
BCI, and weigh either in favour of informal or formal cooperation in each of the
models. The subsequent two models disregard the hierarchical conception of
cooperation, and focus only on the mode in which bilateral cooperation is
engendered.Theseventhmodelservesasaninternalcheckonthenotionofbilateral
cooperation as the amalgamation of cooperation across spheres. Table 2 (p32)
summarisesthemodels.
The BCI scores derived from these seven models are then used in the
correspondingsevenregressionsassetforthinChapterV;providingafirmbasisfor
comparing the relevance of the conceptual properties, hierarchy and mode of
bilateralcooperation.
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TABLE 2. FORMULAE AND DESCRIPTIVE STATISTICS OF THE DEPENDENT
VARIABLEMODELS
Model Formulation
1
BCIScore=
a+2b+4c
+3d+6e+8f
2
BCIScore=
2a+b+2c
+6d+3e+4f
3
BCIScore=
a+2b+4c
+4d+8e+16f
4
BCIScore=
2a+b+2c
+8d+4e+8f
5
BCIScore=
a+2b+2c
+d+2e+2f
6
BCIScore=
2a+b+c
+2d+e+f
7
BCIScore=
a+b+c+d+e+f
Min.
.25
.125
.25
.125
.25
.125
.125
Max.
21.48
16.74
32.12
23.56
8.922
7.461
5.461
Mean
3.199
2.765
4.041
3.452
1.875
1.570
1.148
Median
2.045
1.786
2.370
2.233
1.333
.917
.75
SD
Description
3.146
Linearhierarchy
(1,2,3,4)ofBC
acrossspheres
withformalBC
weightedmore
2.790
Linearhierarchy
(1,2,3,4)ofBC
acrossspheres
withinformalBC
weightedmore
4.428
Geometric
hierarchy(1,2,4,8)
ofBCacross
sphereswith
formalBC
weightedmore
3.656
Geometric
hierarchy(1,2,4,8)
ofBCacross
sphereswith
informalBC
weightedmore
1.467
Equalweightage
ofBCacross
spheres;formal
BCweightedmore
1.485
Equalweightage
ofBCacross
spheres;informal
BCweightedmore
.969
Equalweightage
ofBCacross
spheresand
modes
n=7,891
Notes:a,b,c,d,e,andfdenoteUniversityExchangeAgreements,TouristVisaRegimes,BITsandIIAs,
OfficialandStateVisits,MutualIGOMemberships,andJointMilitaryExercisesvariablesrespectively.
BC=BilateralCooperation.
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4.2 IndependentVariable:EconomicInterdependence
Dyadic economic interdependence has been operationalised in a plethora of
approaches in the scholarship (consider Barbieri 2003; Barbieri and Peters 2003;
Gartzke and Li 2003; 2005; O’Neal 2003, for a general flavour). However, for the
purposesofmyresearch,Iusethefollowingmeasure
←
→
wherebytheeconomicinterdependenceofcountries(AandB)inadyad‐of‐interest
is derived from the summation of commodity imports of A from B and commodity
exportsfromAtoB,dividedbythecombinedtotalcommodityexportsworldwideof
AandB.Twokeystrengthsofthisoperationalisationstandout.First,theabilityof
trade flow figures as a proportion of total world exports of both countries, to
illustrate the magnitude of potential costs to countries in terms of potentially
severingeconomictiesiskey.Thiscapturesthebroadconceptualpropertiesofour
independent variable poignantly by expressing it as a ‘hazard’ ratio. If the EIDYAD
ratio is relatively high for a dyad‐in‐question relative to other dyads, countries in
thatdyadarecomparativelymoreeconomicallyinterdependentoneachother,since
thevalueoftheirbilateraltradecomprisesalargershareoftheirtotalexports.
Secondly, this method and its myriad variations have been already been
extensively used and debated in the literature; signalling its credibility and
facilitating cross‐comparisons with preceding research. Originating from Barbieri
(1995; 1996) and Barbieri and Levy (1999), economic interdependence can be
derived as the proportion of bilateral trade to a state’s total trade, as this (trade
share) corresponds to mutual vulnerability (Hirschman 1977; Gasiorowski and
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Polachek 1982; Gasiorowski 1986). While opposition has emerged with a
countervailingoperationalisationofeconomicinterdependencebasedontheratioof
bilateraltradetoastate’sGDP(O’NealandRussett,1997;Russett,O’Neal,andDavis
1998; Russett and O’Neal, 2001; O’Neal, 2003), this conception does not seem
applicable in my scope of research given that my unit of analysis is the undirected
dyad rather than the directional dyad (noted earlier in Chapter III) – which takes
into account relational symmetry. While O’Neal and colleagues’ conception reflects
directional dependence, my construct of dyadic economic interdependence draws
from the more straightforward notion that it is an undirected feature of relations
amongstcountries(deVries1990);ofwhichtheextent(Maoz2009)isthefocus.
My compilation of this measure is first derived from the UN Statistics
Division’s COMTRADE data and amalgamated International Trade Centre
calculationsfordirectedpairs.IthentakethehigherofeithercountryA’sreported
import(orexport)figures,orcountryB’sreportedexport(orimport)figures.Thisis
to counteract the discrepancies in reportingdueto a number of reasons identified
by UN COMTRADE (misallocation, confidentiality, methodological differences, and
including peripheral costs in trade value amongst others); largely resulting in
underreportingissuesonthepartofonecountryinadyad.Inthecasewherebyone
ofthesevaluesismissing,Isimplyusethesolefigureavailablefromeithercountry
(reporter or mirror data). I then convert the raw figures to constant US$ millions
(base year 2005), before computing the EIDYAD ratio for each undirected dyad,
multiplied by a hundred for ease of regression. A summary description of the
independentvariablealongwiththecontrolsisprovided(Table3,p38).
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4.3 ControllingGeography,Gods,Gold,Governments,andGuns
My research design is further supplemented with a number of contingent
considerationsastotheinterdependence‐cooperationrelationship.Someofthekey
factorshighlightedbytheprevailingliteraturethusfarincludedemocracy,another
leg in the posited Kantian Tripod of peace (O’Neal, Russett, and Berbaum 2003;
Bayer 2010); the ‘political relevance’ of countries in a dyad (O’Neal and Russett
1999a);geographicalproximity(Polachek,Robst,andChang1999;Robst,Polachek,
andChang2007;Hegre,O’Neal,andRussett2010);differingregionalcontextssuch
as Asia‐Pacific (Goldsmith 2007; 2013) or the U.S.‐Warsaw Pact comparisons
(Gasiorowski and Polachek 1982); national wealth and economic state (Mousseau,
Hegre, and O’Neal 2003; Gartzke and Li 2005); and a country’s ‘hard power’
(Blanton 2006). These attest to how the cooperative (or pacific) benefits of
interdependence are by no means absolute, but rather dependent upon a host of
considerations.
Inthisregard,Iemployanumberofcontrolsthatsimultaneouslycorrespond
tothevariousspheresinwhichbilateralcooperationcanbeengendered.Atotalof
six salient controls have been selected to best complement the prevailing
hypothesised model of relations: geographical proximity (distance), dominant
religious differences (socio‐cultural), national economy (LOG Dyadic GDP), political
regimedifferences,thestatepowerdimension(centringuponnationalandmilitary
capabilities),andtheinteractioneffectbetweennationaleconomyandstatepower.
Ifirstaccountforgeographicaldifferencesbetweendyads.Operationalisation
isviathenumericvalueofthegreatcirclegeographicdistancebetweenthecapital
citiesoftwocountriesofadyad,inkilometres.Thisdistancerepresentstheeffective
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travelling distance between countries; a lower value denotes that countries are
physically and proximally closer to each other, while a higher value denotes
otherwise. My computation leverages on taking the log of the distance between
capitalcities(DBCC)(GleditschandWard1999).TheDBCCdatasetcoversalldyadic
pairsinmyresearch,andisupdatedthroughend‐2012.
Secondly,Icontrolfordominantreligiousdifferencesbetweencountriesina
dyad – which may affect their propensity to cooperate (Lewer 2005; Helble 2006;
Lewer and van den Berg 2007; Henne 2012). This control is a binary measure of
whether two countries in a dyad share a similar dominant religion. A value of ‘1’
indicates ashared dominant religion; a ‘0’ indicates otherwise. Individual country‐
level data are delineated using broad categories (Islam, Christianity/Catholicism,
Buddhism/Taoism, Hinduism, Indigenous Beliefs, None) as per both the UN
Statistics Division’s Demographic Statistics as well as Maoz and Henderson’s
NationalReligionDataset(2013),fortheyear2012.
Next,theinter‐dyaddifferencesintheirconstituenteconomiesarecontrolled
forbyconsideringtheaggregateoftheGDPfiguresofthecountriesinadyad,and
applyingalogarithmicfunctionforsalience.Country‐specific2012GDPdatainbase
year 2005 constant US$ are gleaned from the World Bank’s World Development
Indicators databank (2014); which is in turn compiled from officially recognised
internationalandnationalsources.This enablesus toaccount for the capacityand
resulting proclivity of each country to cooperate with others with the size of their
economies.
The fourth control employed accounts for the political regime differences
between countries in a dyad; or ‘political relevance’ (O’Neal and Russett 1999a).
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Thisisanamalgamatedvaluerepresentingthedifferencebetweenregimetypesof
two countries in a dyad. Essentially conceived as ‘political distance’, a lower value
indicatesthattheregimesofthetwocountriesinadyadaremoresimilar,whilea
highervaluedenotesmoreinherentdifferences.Thisabsolutevalue,onascaleof0‐
20, is derived from taking the difference between individual measures of each
country’s political regimes; which range from institutionalised autocracy (‐10) to
democracy (+10). In my analysis, I employ the weighted values from the Polity IV
Project’sPoliticalRegimeCharacteristicsandTransitionsforyear2012(Centerfor
SystemicPeace2014).
Fifth, I employ a derivative of the statistical measure of national power in
termsofdemographic,infrastructuralandmilitarystrength–theCompositeIndex
of National Capability (CINC). CINC is derived from David Singer’s COW dataset
(Singer,Bremer,andStuckey[1972]2014),andassessesacountry’s‘hardpower’in
the world arena. Its components include total population, urban population, iron
and steel production, primary energy consumption, military expenditure, and
militarypersonnel.Thesecomponentsaretakenasapercentageoftheworldtotal
togiveanamalgamatedCINCratio.IconsiderthedifferencebetweentheCINCratios
of two countries in a dyad, multiplied by a hundred for regressive salience. The
smaller the value, the more similar the countries are in terms of their national
powerendowment;whilethelargerthevalue,thegreaterthepowerdisparity.
Finally,onemaynoticethattwoofthecontrolsemployedexhibitaninherent
interaction effect. Given that the size of a country’s economy (as measured by its
GDP)affectsitsabilitytoengender‘hardpower’viadevelopingmilitarycapability,
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the CINC measure is thereby associated with a country’s GDP. I account for this
directlyinmyregressionmodels.
TABLE3.DESCRIPTIVESTATISTICSOFINDEPENDENTVARIABLEAND
CONTROLS
Explanatory
Variables
Concepts
Independent
Variable
Max.
Mean
.001
31.49
.371
SD
.033
1.264
Spatial:
Geographic
Distance
Geographical
DistanceLOG
Socio‐Cultural:
Religious
Differences
Differencein
DominantReligion
0
Economic:
CombinedGDP
CombinedDyadic
GDPLOG
3.341
Political:Regime
Differences
Differencein
RegimeType
0
Military/
Security:
StatePower
Differences
Differencein
CINCScores
.001
Median
Economic
DyadicTradeFlow/
Interdependence OverallTradeRatio
Controls
Min.
1.462
4.297 3.725
1
.419
7.318 5.550
20
6.332
19.86 1.379
3.796
.364
0
.493
5.543
.669
4
5.708
.345
3.281
n=7,891
4.4 Simultaneity:AcknowledgingInherentEndogeneity
It is at this point where attention should be given to the conceivable
reciprocal relationship between economic interdependence and bilateral
cooperation. While high levels of dyadic economic interdependence may lead to
increased bilateral cooperation, it is also plausible that the level of cooperation
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between states will consequently affect their interdependence too. For instance, if
states choose to increase their cooperation in the economic sphere by signing an
FTAorparticipatinginatradebloc,thiswouldpotentiallyleadtoincreasedmutual
trade over time – which can be conceived as an increase in their economic
interdependence.Inthisinstance,increasedeconomicinterdependencedidnotlead
to increased bilateral economic cooperation; rather, increased economic
cooperation led to increased economic interdependence. Parallel studies have also
documentedrelationshipsshowingthenegativecorrelationsofconflictontradeand
interdependence(Pollins1989a;GowaandMansfield1993;Kastner2007).
Fortunately,therehavebeenseveralattemptstoaddresssimultaneityinthe
literature on economic interdependence and conflict, along with accompanying
studies detailing solutions to this methodological hurdle (Reuveny 2003; Ripsman
and Blanchard 2003; Goenner 2011). While conceptually unlike my developed
theorybetweeneconomicinterdependenceandcooperation,thechoicesofresearch
design employed thus far by the conflict scholarship is highly instructive vis‐à‐vis
the topic‐at‐hand, given the identical independent variable at play and the
perceptively‘comparable’keydependentvariablesofconflictandcooperation.Two
broad mitigating mechanisms have been engaged to combat the simultaneity
problem:a)thesimultaneousequationestimationmethodwith twoorthree‐stage
least‐squares regression, seen in the likes of Keshk, Pollins and Reuveny (2004),
Mansfield (2003), Kim and Rousseau (2005), and Polachek (1997); and ii)
distributed(time)‐lagsanalysesorrelatedestimationmethods,seeninthelikesof
O’Neal,RussettandBerbaum(2003)andReuvenyandKang(1998).
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4.5 Methodology:Time‐lagging,OLS,andLogisticRegressions
Takingintoaccounttheinherentendogeneityandthebroad‐spectrumnature
of my research, I employ a ‘poor‐man’s’ approach by lagging all explanatory
variables covered in 4.2‐4.3 by one year to year 2012, in comparison to the
dependent variables collated for year 2013. This takes into account the time lapse
required between changes in the former, and resulting changes in the latter;
countries do not instantaneously cooperate more or less as they become
interdependentorexperienceeconomicorpoliticalclimatechanges.
Ithenuseatwin‐prongedapproachtoprovideforin‐depthanalysisvis‐à‐vis
therelationship‐of‐interest.IstartwithconventionalOLSregressionsfortheseven
BCI models as outlined in Table 2 (p32) to facilitate cross‐model parallel
comparisons of the summative, hierarchical, and formal aspects of bilateral
cooperation. Subsequently, I shift to a more micro‐level analysis of the individual
components representing cooperation in the four different spheres, to cross‐check
theveracityoftheOLSregressionresults.Asthesecomponentvariablesareordinal
or binary in nature, I perform either an ordered logistic or conventional logistic
regressiononthemrespectively.ChapterVintegratestheseintothediscussion.
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ChapterV|Stat.FindingsandDiscussion
CHAPTERV–STATISTICALFINDINGSANDDISCUSSION
5.1 AssessingtheResults:SizinguptheHypotheses
Table 4 (p42) summarises the statistical findings from the OLS regressions
performed on the seven BCI models. I begin at the outset by perusing the results
yielded by the first four models (1‐4); the effects of economic interdependence on
increasing intra‐dyad cooperationacross spheres are statistically significant for all
ofthem.Foreveryunitincreaseininterdependenceinadyad,anincreaseof0.857
to 1.424 units of cooperation can be expected, depending on the BCI model used.
Thiscriticallyvalidatesthefirsthypothesis(H1):increasinginterdependenceresults
inmorebilateralcooperation.
I then extend my analysis and attend to the second hypothesis (H2), which
addresses the hierarchical nature of the positive correlation expected across the
four spheres of cooperation. By weighing Models 1 and 2 which assemble a linear
hierarchy of ordered incremental intensity of bilateral cooperation across the four
spheres, against Models 3 and 4 which posit an ordered geometric or exponential
hierarchy of cooperative growth across the spheres instead, this provides insight
intotheaforementionedpositivecorrelationfindingbysheddinglightonthenature
ofthecooperationhierarchythatbestservesthepositedtheory.Fromtheresults,an
exponentiallyincrementalmodelofcooperationacrossspheresseemsmorein‐line
with the hypothesised relationship, given that Models 3 and 4’s regression line
gradientsaresteeperrelativetoModels1and2’s.Theimplicationsarethatdyadic
bilateral relations have the potential to progress exponentially, as states become
moreinterdependentandcooperatemoreintensivelyinmore‘demanding’spheres.
41
TABLE4.OLSREGRESSIONSOFECONOMICINTERDEPENDENCEONBILATERALCOOPERATION
BilateralCooperationIndexModels
ExplanatoryVariables
IndependentVariable
1
2
.941***
(.018)
EconomicInterdependence
3
.857***
(.017)
4
1.424***
(.025)
Controls
5
1.208***
(.022)
6
7
.360***
(.009)
.349***
(.010)
.236***
(.006)
‐4.397***
(.063)
‐3.388***
(.061)
‐5.899***
(.089)
‐4.384***
(.078)
‐1.983***
(.032)
‐1.689***
(.036)
‐1.224***
(.022)
DifferenceinDominantReligion
.585***
(.045)
.306***
(.044)
.727***
(.063)
.378***
(.056)
.315***
(.023)
.169***
(.026)
.162***
(.016)
CombinedDyadicGDPLOG
1.235***
(.039)
1.369***
(.038)
1.697***
(.056)
1.726***
(.049)
.661***
(.020)
.830***
(.023)
.497***
(.014)
DifferenceinRegimeType
‐.100***
(.004)
‐.076***
(.004)
‐.133***
(.005)
‐.096***
(.005)
‐.057***
(.002)
‐.049***
(.002)
‐.035***
(.001)
DifferenceinCINCScore
‐2.223***
(.157)
‐1.746***
(.153)
‐3.383***
(.222)
‐2.353***
(.195)
‐1.151***
(.079)
‐1.156***
(.090)
‐.769***
(.055)
.316***
(.023)
.247***
(.022)
.482***
(.032)
.334***
(.028)
.162***
(.011)
.163***
(.013)
.108***
(.008)
13.02
.666
8.026
.597
16.97
.663
10.46
.618
5.830
.610
3.508
.506
3.112
.569
GeographicalDistanceLOG
InteractionEffectofCombined
DyadicGDPLOGandDifferencein
CINCScore
n=7,891
Intercept
R2
Notes:Thistablepresentscross‐sectionalOrdinaryLeastSquaresregressioncoefficientswithrobuststandarderrorsinparentheses.Eachcolumn(numbered
1‐7)correspondstoadiscreteregressionmodelmatchedtoeachofthesevenBCImodelsdelineatedpriorinTable2.+,*,**,and***denotesignificanceatthe
0.1,0.05,0.01,and0.001levelsrespectively.RegressionswereperformedontheRStudio(v0.98.1074)integrateddevelopmentenvironmentplatformforR
(v3.1.1),usingthelinearmodelfunction(lm).
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ChapterV|Stat.FindingsandDiscussion
My line‐of‐reasoning is further buttressed by juxtaposing these results
againstthoseofModels5to7–allofwhicheschewthepositedhierarchicalnature
ofbilateralcooperationbysimplyweightingcooperativeactivityineachofthefour
spheres equally. Compared to Models 1‐4, 5‐7 show considerably weaker positive
correlationbetweenourvariables‐of‐interest,alongsidemarginallylowerR2values
too–theirregressionsdonotapproximatethedatapointsnearlyaswellasthatof
1‐4.Whilenotanexactscience,allthesefindingstie‐inwiththenotionthatthevalue
of being perceived as trustworthy, has the power to appreciate and consequently
motivate others to render themselves asymmetrically more vulnerable through
cooperation. An exponential hierarchy of bilateral cooperation is also in keeping
withseveralotherreal‐worldprecepts,suchaseconomicandpopulationgrowth–
possiblyfurtherattestingtoitsapplicability.
Next, I turn my attention to some noteworthy findings vis‐à‐vis the other
explanatory variables. Perhaps of interest are the statistically significant findings
acrossallsevenBCImodels,thatsimilaritiesindominantreligionbetweencountries
in a dyad seem to have a higher than anticipated impact on ensuing bilateral
cooperation. Socio‐cultural influences are often relegated to the sidelines in the
pursuitofthekeyfactorsengenderingconflictorcooperation,duetotheirperceived
nebulousness or imprecision relative to more ‘concrete’ political or economic
influences.However,inthecaseofcooperation,theyseemofnotablevalue;perhaps
shared religious adherences between countries perpetuate an increased sense of
shared ‘destiny’, ideals, or even kinship – imagined or otherwise. Such a frame of
mind adopted by their governments could render them more amenable to
cooperate, compared to those with differences in religious beliefs. This is also in
keepingwithextantliteraturedetailingthe(parallel)associationbetweenreligious
43
EsotericEngagements,TenaciousTies
ChapterV|Stat.FindingsandDiscussion
differences and conflict (Seul 1999; Hasenclever and Rittberger 2000; Fox and
Sandler2004).
Anotherexplanatoryvariable‐of‐interestinthecontextofthefindingsisthe
combined dyadic GDP; its log values show statistically significant positive
associationswithallBCImodelstoo.Inthecontextofthedyadsusedinmyanalysis,
thisoffersanadditionallogicalbasisformorebilateralcooperation.Ifcountriesin
onedyadarecollectivelyinabettereconomicstatethanthoseinanotherdyad,they
wouldaccordinglyhavemoremeansandresourcestosupportanaugmentedlevel
of inter‐state cooperation. This could take the form of greater capacities to forge
deeper,morecomprehensiveagreements;sustainmorerobustdiplomaticnetworks
capable of continual interaction with their counterparts; and maintain a
sophisticatedmilitarycapableofcollaborationwithitscounterparts.Muchlikethe
aphoristic‘richgettingricherandthepoorgettingpoorer’,theeconomicwealthand
ability of countries seem tied to their resultant ‘cooperative capacities’. Results of
the CINC score variable paint a similar picture, as they are measures of countries’
capacitiestoo–albeitofasomewhatdifferentaspect.
The three other controls employed in the analysis – geographical distance,
differences in regime type, and CINC score difference, have all yielded results
consistent and significant across all seven models, and in keeping with prevailing
research.Distancebetweencountrieshasbeenrecurrentlyshowntobeafactorin
thelead‐uptoconflict(Pollins1989b;Polachek,Robst,andChang1999);similarly,
results for regime differences proxy an alternate leg (democracy) of the Kantian
Tripod by illustrating how dyads comprising countries with the most regime
differences also tend to have the lowest levels of cooperation. On the whole, the
44
EsotericEngagements,TenaciousTies
ChapterV|Stat.FindingsandDiscussion
regression results of the explanatory variables less economic interdependence
againsttheBCImodelsstrengthenthecaseforbilateralcooperationoccurringonan
exponentialincrementacrossthefoursphereswithmoreinterdependence.TheBCI
conceptualised in Models 3 and 4 have the greater positive (or negative)
correlations with all these variables in comparison with their linear‐increment
counterparts1and2–withoutexception.Theseservetofurthervalidatethelogical
veracityofthetheoryunderlyingbilateralcooperationoutlinedinthispaper.
Movingthediscussionalongtothethirdhypothesis(H3),theresultsderived
fromtheregressionsseemtosupportthenotionthatformalcooperationisvalued
over informal cooperation, as states become increasingly interdependent.
Comparing in tandem Models 1, 3, and 5 which weigh formal cooperation
components more heavily, against Models 2, 4, and 6 which weigh informal
components more heavily, an increase of one unit of economic interdependence
seems to lead to a slightly greater increase in the former models favouring formal
cooperation,ceterisparibus.AllotherexplanansexceptthelogcombineddyadicGDP
measure also producecorrespondinglygreaterincreasesfor formalBCI models,as
compared to the informal ones. This reinforces the line‐of‐reasoning advanced by
my theory; that with increasing interdependence comes greater trust, and
consequently greater impetus to signal firm resolve and commitment towards the
bettermentofbilateralrelations.Sinceformalmodesofcooperationbetterindicate
resolve due to the greater stakes involved relative to informal cooperation,
countrieshenceseemtocooperatemoreformallywithrisinginterdependence.
Nonetheless, it is worth pondering over the notion that dyads with higher
levels of combined GDP are more associated with informal cooperation instead –
45
EsotericEngagements,TenaciousTies
ChapterV|Stat.FindingsandDiscussion
which runs against the grain of the aforementioned logic. One conceivable
possibility that explains this is that the variety of informal modes of cooperation
availablefaroutweighsthatofformalisedones–whichare‘restrained’inasenseby
limitationstocross‐borderofficialorlegislativeratification.Insomecircumstances,
informal diplomacy such as meetings on the sidelines of formal summits or talks
maywellprovemorefruitfultoo.Inthissense,ifweoperateontheassumptionthat
economically‐powerful interdependent countries would probably have already
pursuedlimitedformalchannelsofcooperationtothegreatestextentpossiblegiven
theircapacityandcapabilityendowments,thenitdoesmakesensethatthepossible
avenues left for even greater cooperation across the spheres with an additional
increaseininterdependence,wouldrestintheinformalrealm.
5.2 DiggingDeeper:TheDirtontheDeficiencies
Againstthisbackdrop,acriticalconsiderationoftheothersideofthecoinis
also required – given that the seeming successes of the results thus far are not
without their limitations. I approach this by analysing a more micro‐level state of
relations – between our explanatory variables, and the individual components that
make up the seven BCI models. Table 5 (p47) summarises the statistical findings
from the ordered logistic regressions (and a conventional logit one) performed on
thesecomponents.
A cursory perusal of the results yields statistically significant findings for
most explanatory variables on the six individual components used to compute the
BCImodels.Sincethecomponentvariableswerenormalisedtoasimilarscaleprior
to the regression, we can infer from the coefficients’ differences that for every
46
TABLE 5. ORDERED AND CONVENTIONAL LOGISTIC REGRESSIONS OF ECONOMIC INTERDEPENDENCE ON COMPONENT BCI
DEPENDENTVARIABLES
ExplanatoryVariable
University
Exchanges^
BilateralCooperationIndexComponentVariables
TouristVisa
Official&State MutualIGO
BITs&IIAs
Regimes
Visits
Memberships
JointMilitary
Exercises
IndependentVariable
EconomicInterdependence
Controls
GeographicalDistanceLOG
DifferenceinDominantReligion
CombinedDyadicGDPLOG
DifferenceinRegimeType
DifferenceinCINCScore
InteractionEffectofCombinedDyadicGDPLOG
andDifferenceinCINCScore
n=7,891
LOGLikelihood
LikelihoodRatioχ²
.337***
(.038)
.188***
(.022)
1.250***
(.041)
.245***
(.024)
.523***
(.029)
‐1.410***
(.068)
.729***
(.045)
.663***
(.041)
‐.119***
(.004)
‐2.291***
(.171)
.314***
(.024)
.479***
(.029)
‐3.639***
(.081)
.510***
(.050)
.508***
(.045)
‐.015***
(.004)
‐.041
(.170)
.010
(.024)
‐1.809***
(.095)
.024
(.066)
1.734***
(.068)
‐.080***
(.006)
‐1.991***
(.231)
.278***
(.033)
‐1.357***
(.070)
.012
(.049)
.852***
(.045)
‐.014***
(.004)
‐.094
(.161)
.011
(.023)
‐3.936***
(.084)
.568***
(.049)
.311***
(.045)
‐.086***
(.005)
‐1.274***
(.186)
.180***
(.027)
‐2.597***
(.091)
.179**
(.066)
1.130***
(.060)
‐.061***
(.006)
‐2.551***
(.223)
.367***
(.032)
‐3394.2***
1977.7
‐11294***
2659.2
‐9484.9***
4083.7
‐9212.4***
3477.9
‐8910.93***
4353.8
‐4600.67***
2805.5
Notes:Thistablepresentscross‐sectionalregressioncoefficientspertainingtoeithertheorderedlogitorconventionallogitmodel,withstandarderrorsin
parentheses.EachcolumncorrespondstoadiscreteregressionmodelmatchedtoeachofthesixrawcomponentvariablesmakinguptheBCI.Inthecontextof
orderedandconventionallogitregressions,+,*,**,and***denotesignificanceatthe≥0.05,0.05,0.01,and0.001levelsrespectively,asderivedfromp‐values
associatedwithz‐scores.RegressionswereperformedontheRStudio(v0.98.1074)integrateddevelopmentenvironmentplatformforR(v3.1.1),usingeitherthe
cumulativeorderedlogitfunction(clm)orthegenerallogitfunction(glm).^ConventionallogisticregressionisusedfortheUniversityExchangescomponent
variableduetoitsdichotomousnature;orderedlogitregressionsareusedforthefiveotherordinalcomponentvariables.Interceptsforeachregressionare
reportedseparately(seeAppendixII)forconciseness,giventhatorderedlogisticregressionsentailmultipleintercepts.
47
EsotericEngagements,TenaciousTies
ChapterV|Stat.FindingsandDiscussion
unit increase in dyadic interdependence, the cooperation in terms of official and
state visits tend to surge faster than tourist‐visa policy let‐ups or university
exchanges, for instance. While this corresponds to the hierarchy of spheres
advancedprior,othercomparisonsproblematisethisconception;theincidencesof
joint military exercises, for instance, do not rise nearly as much as that of the
diplomatic visits with every unit increase in interdependence. The statistically
insignificantfindingsintermsofdifferencesinCINCscoresanddominantreligions
alsoaddtothemix;forinstance,thelatterdoesnotseemtohaveanysalientimpact
on the incidence of diplomatic visits, providing an antithetical take on the earlier
conclusion that socio‐cultural similarities provide firm bases for cooperation to
transpire.
Thisleadstoabroaderinherentweakness–thatofgeneralisability.Whilethe
data on the whole seem to support the advanced hypotheses, the more precise
characteristics surrounding each form or ‘instrument’ of cooperation are not
deliberated upon in my large‐n study. While inferences can be drawn as to
directional correlation between the explanatory variables and resulting bilateral
cooperation in general, specific types of cooperation might have distinctive
motivations. For instance, if the amount of flights between countries were to be
takenasanindicatorofsocio‐culturalexchangeorcooperation,increasingdistances
mightnotnecessarilyleadtoaresultingreductionofflights.IfcountriesAandBare
separated by mere hundreds of kilometres as opposed to A and C, separated by
thousandsofkilometres,AandCwouldinsteadexperiencemoreflightconnections,
ceteris paribus – since A and B are close enough to instead pursue expansions in
land‐basedconnectionsinstead.
48
EsotericEngagements,TenaciousTies
ChapterV|Stat.FindingsandDiscussion
Asecondaspectofthedifficultiesingeneralisingtheresultsstemfromhow
welltheBCImodelsactuallyrepresentbilateralcooperationinreality.GiventheBCI
is compiled with only a limited mix of six components, it is hard to argue that
bilateral cooperation in each sphere can be represented thoroughly and effectively
just by one or two measures alone. Exemplifying this is the context of economic
cooperation; the BITs and IIAs measure used in the BCI models is in essence only
representativeofinvestment‐linkedcooperation.Otheraspectsofeconomiclink‐ups
intheformofcustomsunions,FTAs,PTAs,mutualrecognitionofstandardsandthe
like, are not covered. Each of these is comprehensive in its own right, and comes
withdiffering‘idiosyncrasies’.
In terms of operationalising economic interdependence, three weaknesses
have been discussed in the literature. First, the operationalisation captures only
tradeinterdependence(Gartzke,Li,andBoehmer2001).Unfortunately,thisistrue
of virtually all measures of interdependence, because many possible supplemental
measures, such as investment flows, are either wholly unavailable (Barbieri and
Keshk 2011), or not available for all countries‐of‐interest. Additionally, if the
research incorporates such additional measures, subsequent difficulties regarding
endogeneity will arise too. Second, if we also wish to capture the extent to which
statesaredominanttradingpowersinthesystem,thisoperationalisationmightbe
inappropriate(Barbieri2003)–sinceitdoesnotcapturethesymmetryofrelations
betweencountriesinadyad.Thisalsoiscauseforthethirdweaknessasidentified
byMansfieldandPollins(2003);myoperationalisation’svalidityasanindicatorof
vulnerability interdependence (the costs associated with the disruptions of the
tradingrelations)isquestionabletoo.
49
EsotericEngagements,TenaciousTies
ChapterV|Stat.FindingsandDiscussion
Finally,myresearch,likeallotherlarge‐nquantitativestudies,isalsoplagued
by some fundamental shortcomings. It does not yield much in terms of contextual
factorstohelpexplainvariationsinbilateralcooperation,fordyadswithsimilarities
in interdependence levels and other explanatory variables. The correlations
generatedmaywellignoreorconcealotherpossibleunderlyingcausesorrealities
too. Against this backdrop of considerations together with a string of other
deficiencies of the quantitative method set forth by the scholarship (Onwuegbuzie
and Leech, 2005; Stanfield 2006 amongst many others), let us now consider the
opportunitiesthatcanbepursuedbyfurtherresearch.
5.3 OpportunitiesforFurtherResearch
Giventhatthisconceptionofbilateralrelationsdiffersfromtheusualstudies
on interdependence and the conflict‐negative peace dichotomy, and is still in its
theoretical infancy, more can be done to further develop the causal mechanisms
beyond mere appeals to the notion of trust and vulnerability in international
relations; alongside detailing decision‐making processes at the state level.
Improving the current BCI construct is essential too if we are to increase the
external validity of this measure; an expansion of its scope to include more
component measures over the above current six, will enable it to better reflect
bilateralcooperation.
Separately, more in‐depth and focused studies are needed to elucidate the
nature of bilateral cooperation – taking into account more contextual differences
suchasgeographicalregions,historicalbackdrops,thirdparties,andthelike.Thisis
illustratedbytheinstancesofoutlierdyadsinmystudy,aswellasparallelsingle‐n
50
EsotericEngagements,TenaciousTies
ChapterV|Stat.FindingsandDiscussion
orsmall‐n casestudiesshowinghow conflictcanstillbetheorderofthedayeven
amidst intensive economic interdependence (Kastner 2007), or the need for pre‐
requisites in the form of asymmetric relations (Ripsman 2005) to encourage and
nurture potential and future cooperation. Further research can also extend the
theory to include directed dyads – paving the way for a far more intimate
understanding.
51
EsotericEngagements,TenaciousTies
ChapterVI|Conclusion
CHAPTERVI–CONCLUSION
Inthispaper,Ihavedemonstratedapositivecorrelationbetweeneconomic
interdependence and bilateral cooperation. I began this pursuit by developing a
novelconceptionofbilateralrelations;directingthespotlightoncooperationrather
than conflict. Using existing literature as a substratum for my theoretical
construction of bilateral cooperation, I harnessed insights both from the parallel
scholarshipontradeandconflictinChapter2,aswellasinspirationfromindividual‐
levelsocio‐psychologicalrelations;torelatecooperationtothenotionsoftrustand
vulnerability in Chapter 3. With the identified attributes of cooperation – depth,
issue‐spheres, and modes, I proceeded to engineer a broad‐scale cross‐sectional
study in Chapter 4 to test the applicability of my theory across some 7,891 dyads
spanning149countriesworldwide.Followingwhich,Idelineatedanddiscussedmy
researchfindingsinChapter5–drawingfocustothesalientimplications,aswellas
shortcomingsofmystudy.
So, whither cooperation? As Jonathan Haidt puts it succinctly, the ‘most
powerful force ever known on this planet is human cooperation – a force for
construction,anddestruction[initsabsence]’(2006).Whileputforthinthecontext
of general psychology, we would do well to harness the benefits of exploring this
construct the realm of international relations – given how states are but the
amalgamationofitsconstituent,humanindividuals.Byturningoureyesawayfrom
thesomewhat nihilist notionofavertingconflicttowardsengenderingcooperation
instead,weareputtingtogetherthebuildingblocksinthequestforabetterfuture.
52
EsotericEngagements,TenaciousTies
Appendices
APPENDIXI
CONSTITUENTCOUNTRIESOFDYADSINCLUDEDINANALYSIS
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Albania
Algeria
Angola
Argentina
Armenia
Australia
Austria
Azerbaijan
Bahrain
Bangladesh
Belarus
Belgium
Benin
Bhutan
Bolivia
Botswana
Brazil
Bulgaria
BurkinaFaso
Burundi
CaboVerde
Cambodia
Cameroon
Canada
CentralAfricanRepublic
Chad
Chile
China
Colombia
Comoros
Congo
Côted'Ivoire
Croatia
Cyprus
CzechRepublic
DemocraticRepublicoftheCongo
Denmark
Djibouti
DominicanRepublic
Ecuador
ElSalvador
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
EquatorialGuinea
Eritrea
Estonia
Ethiopia
Fiji
Finland
France
Gabon
Gambia
Georgia
Germany
Ghana
Greece
Guatemala
Guinea
Guinea‐Bissau
Guyana
Honduras
Hungary
India
Indonesia
Iran(IslamicRepublicof)
Iraq
Ireland
Israel
Italy
Jamaica
Japan
Jordan
Kazakhstan
Kenya
Korea,Republicof
Kuwait
Kyrgyzstan
LaoPeople'sDemocraticRepublic
Latvia
Lebanon
Lesotho
Liberia
Libya
Lithuania
53
EsotericEngagements,TenaciousTies
Appendices
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
Luxembourg
Macedonia
Madagascar
Malawi
Malaysia
Mali
Mauritania
Mexico
Mongolia
Montenegro
Morocco
Mozambique
Namibia
Nepal
Netherlands
NewZealand
Nicaragua
Niger
Nigeria
Norway
Oman
Pakistan
PapuaNewGuinea
Paraguay
Peru
Philippines
Poland
Portugal
Qatar
RepublicofMoldova
Romania
RussianFederation
Rwanda
SaudiArabia
Senegal
Serbia
SierraLeone
Singapore
Slovakia
Slovenia
SouthAfrica
Spain
SriLanka
Suriname
Swaziland
Sweden
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
Switzerland
Tajikistan
Tanzania,UnitedRepublicof
Thailand
Timor‐Leste
Togo
TrinidadandTobago
Turkey
Turkmenistan
Uganda
Ukraine
UnitedArabEmirates
UnitedKingdom
UnitedStatesofAmerica
Uruguay
Uzbekistan
Venezuela
VietNam
Yemen
Zambia
Zimbabwe
54
EsotericEngagements,TenaciousTies
Appendices
APPENDIXII|ORDEREDANDCONVENTIONALLOGISTIC
REGRESSIONSOFECONOMICINTERDEPENDENCEON
COMPONENTBCIVARIABLES–FULLTABLE
BilateralCooperationIndexComponentVariables
ExplanatoryVariable
University
Exchanges^
IndependentVariable
EconomicInterdependence
.337***
(.038)
Controls
Tourist
MutualIGO
Joint
Official&
Visa
BITs&IIAs
Member‐
Military
StateVisits
Regimes
ships
Exercises
.188***
.479***
1.250***
.245***
.523***
(.022)
(.029)
(.041)
(.024)
(.029)
‐1.809***
(.095)
‐1.410***
(.068)
‐3.639***
(.081)
‐1.357***
(.070)
‐3.936***
(.084)
‐2.597***
(.091)
.024
(.066)
.729***
(.045)
.510***
(.050)
.012
(.049)
.568***
(.049)
.179**
(.066)
CombinedDyadicGDPLOG
1.734***
(.068)
.663***
(.041)
.508***
(.045)
.852***
(.045)
.311***
(.045)
1.130***
(.060)
DifferenceinRegimeType
‐.080***
(.006)
‐.119***
(.004)
‐.015***
(.004)
‐.014***
(.004)
‐.086***
(.005)
‐.061***
(.006)
DifferenceinCINCScore
‐1.991***
(.231)
‐2.291***
(.171)
‐.041
(.170)
‐.094
(.161)
‐1.274***
(.186)
‐2.551***
(.223)
.278***
(.033)
.314***
(.024)
.010
(.024)
.011
(.023)
.180***
(.027)
.367***
(.032)
GeographicalDistanceLOG
DifferenceinDominantReligion
InteractionEffectofCombined
DyadicGDPLOGandDifferencein
CINCScore
n=7,891
LOGLikelihood ‐3394.2***
LikelihoodRatioχ² 1977.7
ThresholdCoefficients ‐3.680
(byintervalsfrom
minimumto
maximumvaluesfor
orderedlogistic
regressions)/
Intercepts
‐11294*** ‐9484.9***
2659.2
4083.7
‐10.28
‐10.46
‐3.221
‐10.27
‐1.956
‐8.557
‐0.994
‐8.401
‐0.849
‐7.276
0.876
‐6.939
1.146
‐6.167
‐5.255
‐9212.4*** ‐8910.93*** ‐4600.67***
3477.9
4353.8
2805.5
‐0.165
‐13.29
‐2.274
0.727
‐11.86
‐0.533
1.945
‐10.75
1.506
3.920
‐9.921
3.045
5.733
‐9.180
3.941
9.136
‐8.511
5.553
‐7.554
‐5.956
‐4.303
‐3.275
‐1.447
Notes:Thistablepresentscross‐sectionalregressioncoefficientspertainingtoeithertheorderedlogitorconventional
logitmodel,withstandarderrorsinparentheses.Eachcolumncorrespondstoadiscreteregressionmodelmatchedto
each of the six raw component variables making up the BCI. In the context of ordered and conventional logit
regressions,+,*,**,and***denotesignificanceatthe≥0.05,0.05,0.01,and0.001levelsrespectively,asderivedfromp‐
values associated with z‐scores. Regressions were performed on the RStudio (v0.98.1074) integrated development
environment platform for R (v3.1.1), using either the cumulative ordered logit function (clm) or the general logit
function (glm). ^Conventional logistic regression is used for theUniversityExchanges component variable due to its
dichotomousnature;orderedlogitregressionsareusedforthefiveotherordinalcomponentvariables.Interceptsfor
eachregressionarereportedbelowthe LOGLikelihoodandLikelihoodRatioχ²measures;fortheconventionallogistic
regression performed on the University Exchanges component variable, the lone intercept is reported; for the other
ordered logistic regressions, the list of intercepts are reported by intervals from minimum to maximum values (e.g.
0.125|0.25intercept,0.25|0.375intercept,0.375|0.5intercept,0.5|0.625intercept,andsoforth).Thenumberof
intercepts provided for each component variable regressions equates to the number of intervals between discrete
ordered values. Component variables with more than six intervals are also additionally OLS‐regressed against the
explanatoryvariablestocounter‐checkthesalienceoftheorderedlogitresults.Inallrelevantinstances,relationships
anddirectionalitiespositedbytheadditionalOLSregressionscorrespondtotheirorderedlogitcounterparts.
55
EsotericEngagements,TenaciousTies
Appendices
APPENDIXIII
REGRESSIONMODELANDDESCRIPTION
GeneralequationforthesevenBCImodels(OLSRegression)andcomponent
dependentvariables(OrderedLogitandConventionalLogisticRegression)
∗
Ydv refers to either one of seven BCI models (numbered 1 to 7)
conceptualisedforcross‐comparison,oroneofsixcomponentdependentvariables
(UniversityExchanges,VisaRegimes,BITsandIIAs,OfficialandStateVisits,Mutual
IGO Memberships, and Joint Military Exercises). EIiv refers to the economic
interdependence measure, the independent variable‐of‐interest time‐lagged by a
periodofoneyear(p33,35);DISTLOGreferstothefirstcontrolvariable,andisthe
(natural) log of the geographical distance between countries (p37). GODC is the
secondcontrolvariable(p38),andisabinaryrepresentingdifferencesindominant
religionbetweencountriesinadyadasof2012(1ifsimilar,0ifdifferent).Thethird
controlvariable,GDPLOG,isthe(natural)logofthecombinedGDPofcountriesina
dyadforyear2012(p38).POLCisthefourthcontrolvariable(p38),andisthescored
difference between regime types between countries in a dyad. CINCC is the fifth
control variable (p39), and represents the difference in ‘hard power’ or national
capabilitiesbetweencountriesinadyad.Asixthcontrolvariable,GDPLOG *CINCC,is
aninteractiontermmeanttocapturetheeffectofGDPonnationalcapabilities(p39).
56
EsotericEngagements,TenaciousTies
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