Multimethod Research, Causal Mechanisms and Case Studies: An Integrated Approach

302 Pages·2017·1.134 MB·English

by  Gary Goertz

MULTIMETHOD RESEARCH,
CAUSAL MECHANISMS,
AND CASE STUDIES
An Integrated Approach
GARY GOERTZ
PrincetonUniversityPress
PrincetonandOxford
Copyright(cid:1)c 2017byPrincetonUniversityPress
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ISBN978-0-691-17411-2
ISBN(pbk.)978-0-691-17412-9
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CONTENTS
ListofTables vii
ListofFigures ix
Acknowledgments xi
CHAPTER1
Introduction 1
CHAPTER2
CausalMechanisms 29
CHAPTER3
TheBasicLogic 58
CHAPTER4
ConstraintMechanismsandNecessaryConditions:
ExplainingNonoccurrence 90
CHAPTER5
InteractiveCausalMechanisms 123
CHAPTER6
MultimethodGameTheory 165
CHAPTER7
Large-NQualitativeTesting:ANewMethodology? 190
CHAPTER8
CaseStudies,Scope,andGeneralization 217
AppendixA
AStatisticalApproachtoMultimethodResearchand
CaseStudies 245
References 271
Index 289
TABLES
3.1. X–Y configurations 59
3.2. Casestudyselection:rationalesandrolesof
X–Y configurations 72
3.3. Casestudyselection:counterfactualanalysis 76
4.1. Necessaryconditions:nondemocracyisnecessary
forinterstatewar 94
4.2. Casestudyselection: X–Y configurations 99
4.3. Casestudylogic:necessaryconditions 104
4.4. Casestudylogic:sufficientconditions 105
5.1. Incomeandlandinequality:
probabilityofdemocratization 128
5.2. Incomeandlandinequality:examplecases 129
5.3. Interactiontheories:Downing’stheoryof
absolutismandconstitutionalism 132
5.4. Caseselectionpossibilities: X AND X →Y
1 2
model 137
5.5. Relativeimportanceof X versus X ,
1 2
X AND X →Y model,hypotheticaldata 141
1 2
5.6. The X AND X →Y model:Statesand
1 2
socialrevolutions 147
6.1. Multimethodgametheory:researchpractice 177
7.1. Caseselection:democratization,weakinstitutions,
andinternationalwar 197
7.2. Relativeimportancecriterion:balanceof
powertheory 205
7.3. Nostatisticalsignificanceandlarge-Nqualitative
testing 209
A.1. X–Y configurations 252
A.2. Zvariables:matchingon Z=1or Z=0 257
FIGURES
1.1. Theresearchtriad:causalmechanism,cross-case
inference,andwithin-casecausalinference 2
1.2. Causalmechanismsandstatisticalmultimethod
research:democraticIGOsanddemocratic
stability 7
2.1. Conceptualizingcausalmechanisms 31
2.2. Causalmechanismsascausalchains:Wood’s
analysisofthedemocratictransitionin
ElSalvador 32
2.3. Thecausalmechanismleadingtononexploitation
ofthestate 38
2.4. Constraintcausalmechanisms 44
2.5. InstitutionalconstraintsANDideology:decisions
toparticipateinthe2003IraqWar 47
2.6. Inequalityanddemocratictransition:the
distributionalconflictcausalmechanism 50
2.7. Equifinalityandcausalmechanisms 53
2.8. Causalmechanismsandequifinality:pathsto
fragmentedcounterrevolutionarystates 55
3.1. Casestudyselection:continuous XandY 65
4.1. Constraintcausalmechanisms,necessary
conditions,andvetoplayers:expecteddata
scatterplot 97
4.2. Constraintcausalmechanisms:constraintson
stateexploitation 109
4.3. Fuzzylogicnecessaryconditionsandcaseselection 113
5.1. Choosingcases: X AND X →Y model 142
1 2
5.2. Membershipinthesetoffalsifyingcases:
necessaryconditions 145
5.3. Casestudyselection:contributingfactormodel 156
6.1. Gametheorymodelingandempiricalevaluation:
anoverview 170
8.1. Theresearchtriad:causalmechanism,cross-case
inference,andcasestudies 232
8.2. Generalizationandextrapolation:thedemocratic
peace 237
A.1. Casestudyselection:continuous XandY 251
CHAPTER 1
Introduction
Singularcausalclaimsareprimary.Thisistrueintwosenses.
First, they are a necessary ingredient in the methods we use
toestablishgenericcausalclaims.Eventhemethodsthattest
causal laws by looking for regularities will not work unless
somesingularcausalinformationisfilledinfirst.Second,the
regularities themselves play a secondary role in establishing
a causal law. They are just evidence—and only one kind of
evidence at that— that certain kinds of singular causal fact
havehappened.
—NancyCartwright
T
HIS book addresses some of the core issues in doing (1)
multimethod research, (2) causal mechanism analysis, and
(3) case studies. Multimethod research has become very
popular and almost a requirement for book-length studies.
Multimethodcanmeanmanythings,buthereitmeanscombin-
ing case studies with statistics, qualitative comparative analysis
(QCA), experiments, or game theory models. The purpose of
case studies is to explore causal mechanisms at the heart of
theories. One does case studies because cross-case methods give
little purchase on the causal mechanisms (M) by which X
i
produces Y. For multimethod researchers, showing a significant
causaleffectinacross-caseanalysisisnotsufficient;oneneedsto
provide a causal mechanism and evidence for it. Demonstrating
a causal effect is only half the job; the second half involves
specifying the causal mechanism and empirically examining it,
usuallythroughcasestudies.
Causal mechanisms, cross-case analyses, and case studies
form the research triad; see figure 1.1. This volume rests
on the proposition that commitment to multimethod research
is commitment to the research triad. Multimethod research
2 (cid:127) Chapter1
Game theory Interactive Constraints
Causal mechanism
Within-case inference Cross-case inference
Case studies Generalization
Process tracing Counterfactuals Experiments Statistics QCA Multiple
case studies
Figure1.1: The research triad: causal mechanism, cross-case inference, and
within-casecausalinference.
typically is conceptualized as qualitative—within-case inference
—along with quantitative cross-case inference. The research
triad adds a third dimension to that, i.e., causal mechanisms.
The research triad is an integrated approach because a com-
mitment to multimethod research is also a commitment to a
causal mechanism approach to explanation and social science
research.
One way to see the integration is by looking at research that
focuses,e.g.,90percentoftheresearcheffort,onjustonecorner
of the triad. For many experimentalists most of the effort is
devotedtodeterminingthetreatmenteffect.Theyusuallydonot
talk about causal mechanisms per se. While they usually have
theoriesandhypotheses,theseallboildowntotheonetreatment
effect. Game theorists provide an nice example of those who
focus a lot of attention on the model, i.e., causal mechanism. It
is quite possible to publish articles where essentially the whole
article is the model (this is very true in economics). Often
historians focus on single events and the whole focus of the
article is explaining some individual historical event. They are
Introduction (cid:127) 3
not interested in generalization and maybe only very implicitly
interestedincausalmechanisms.
Theintegratedapproachrestsonacentralclaim:
As you move away from one-corner-only research you
embracetheresearchtriad.
For example, as a game theorist moves away from exclusive
interest in the model, she begins to be involved in multimethod
research, cross-case analyses, and within-case analyses. As soon
as a case study researcher moves from one case to more cases,
he is asking about generalization. Finally, as the Cartwright
epigraph forcefully states, all statistical, experimental analyses
andgeneralizationimplyindividualcasecausalinference.
Good multimethod and causal mechanism research means a
relative balance between the three corners of the research triad.
If 90 percent of the effort is in demonstrating significant causal
effects via cross-case analysis then the research is not serious
multimethod or serious about the investigation of the causal
mechanism.Ifthecasestudiesareonly“illustrations,”thenthere
is little commitment to multimethod research. Conversely, re-
searchusingcasestudies—e.g.,thepopularpairedcomparison—
is weak on generalization. Doing five or six case studies—as is
commoninsecuritystudiesbooks—dealspoorlywithcross-case
analysis and generalization. The ideal is a fairly balanced effort
onallthreepointsofthetriangle.
Case studies are often considered of questionable inferential
value.ClarkeandPrimoillustratethisviewofcasestudies.When
they refer to case studies they almost always describe them as
“exploratory”:“onecanalsodesignexploratorymodelswithan
eye toward explaining the events surrounding a specific case”
(2012, 92). By “exploratory” they strongly imply the endeavor
is not about causal inference. For example, their discussion of
the analytic narratives project (Bates et al. 1998) falls into this
category. When they talk about “empirical models” they mean
statistical models. So a model of the US Senate—statistical or
formal—is not exploratory, but a case study of the American
Civil War in analytic narratives is exploratory. In contrast, the
research triad emphasizes that case studies are about causal
inference.
4 (cid:127) Chapter1
In everyday life—along with virtually all natural sciences—
people successfully make individual-case causal inferences, e.g.,
originsoftheuniverse,originsofthehumanspecies,whyagiven
persondied,whytheChallengershuttleexploded.Noneofthese
inferentialsuccessesreliesonrandomizedtreatmentsassignedto
subjects,nordotheydependonconditionalprobabilities.
A core philosophy motivating this study is that we want to
explain individual outcomes. Statistical analyses do not provide
explanations: “There is little argument in political science that
statistical models cannot serve as explanations in and of them-
selves. This belief manifests itself in the relegation of statistical
models to devices for testing explanations” (Clarke and Primo
2012,154).
The research triad assumes that one accepts the importance
andvalueofcausalmechanismanalysis.Onecanfindstatistical
methodologistswhodonotbelievethisispossibleorimportant:
“The importance of searching for causal mechanisms is often
overestimatedbypoliticalscientists,andthissometimesleadsto
an underestimate of the importance of comparing conditional
probabilities. We do not need to have much or any knowledge
about mechanisms in order to know that a causal relationship
exists....Ingeneral,asourunderstandingofanissueimproves,
studying individual cases becomes less important” (Sekhon
2004,288–89;lastsentenceofthearticle).Gerringillustratesthe
skepticismaboutwhethercausalmechanismanalysisisessential:
“To clarify, this is not a polemic against mechanisms. It is a
polemic against a dogmatic interpretation of the mechanismic
mission. I argue that the analysis of causal mechanisms is best
regarded as an important, but secondary, element of causal
assessment—notanecessarycondition”(Gerring2010,1500).
I do not survey or discuss how one goes about doing within-
casecausalinferenceinthisbook.Thereisaboomingliterature
on the topic, e.g., Bennett and Checkel (2014), and Beach and
Pedersen (2012; 2016) on process tracing, Mahoney (2012) on
hoop and smoking gun tests, Goertz and Levy (2007), Levy
(2008), and Harvey (2011) on counterfactuals. One can do
statisticalwithin-casecausalinference.Itakenopositiononhow
one does within-case inference. Similarly I do not cover how to
do observational statistics, experiments, or QCA. As illustrated