Case Studies and Causal Inference: An Integrative Framework

271 Pages·2012·2.78 MB·English

by  Ingo Rohlfing (auth.)

Case Studies and Causal Inference
Research Methods Series
General Editors: B ernhard Kittel, Professor of Social Science Methodology, Department of Social
Sciences, Carl von Ossietzky , Universität Oldenburg, Germany and Benoît Rihoux, Professor of
Political Science, Université catholique de Louvain (UCL), Belgium.
In association with the European Consortium for Political Research (ECPR), Palgrave Macmillan
is delighted to announce the launch of a new book series dedicated to producing cutting-edge
titles in Research Methods. While political science currently tends to import methods developed
in neighbouring disciplines, the series contributes to developing a methodological apparatus
focusing on those methods which are appropriate in dealing with the specific research problems
of the discipline.
The series provides students and scholars with state-of-the-art scholarship on methodology,
methods and techniques. It comprises innovative and intellectually rigorous monographs and
edited collections which bridge schools of thought and cross the boundaries of conventional
approaches. The series covers both empirical-analytical and interpretive approaches, micro and
macro studies, and quantitative and qualitative methods.
Titles include:
Joachim Blatter and Markus Haverland
DESIGNING CASE STUDIES
Explanatory Approaches in Small-N Research
Alexander Bogner, Beate Littig and Wolfgang Menz (editors)
INTERVIEWING EXPERTS
Bernhard Kittel, Wolfgang J. Luhan and Rebecca B. Morton (editors)
EXPERIMENTAL POLITICAL SCIENCE
Principles and Practices
Audie Klotz and Deepa Prakash (editors)
QUALITATIVE METHODS IN INTERNATIONAL RELATIONS
A Pluralist Guide
Lane Kenworthy and Alexander Hicks (editors)
METHOD AND SUBSTANCE IN MACROCOMPARATIVE ANALYSIS
Ingo Rohlfing
CASE STUDIES AND CAUSAL INFERENCE
An Integrative Framework
Research Methods Series
Series Standing Order ISBN 978–0230–20679–3–hardcover
ISBN 978–0230–20680–9–paperback
(outside North America only)
You can receive future titles in this series as they are published by placing a standing order.
Please contact your bookseller or, in case of difficulty, write to us at the address below with your
name and address, the title of the series and one of the ISBNs quoted above.
Customer Services Department, Macmillan Distribution Ltd, Houndmills, Basingstoke,
Hampshire RG21 6XS, England
Case Studies and Causal

Inference
An Integrative Framework
Ingo Rohlfing
Assistant Professor of Comparative Social Research,
University of Cologne, Germany
© Ingo Rohlfing 2012
Softcover reprint of the hardcover 1st edition 2012 978-0-230-24070-4
All rights reserved. No reproduction, copy or transmission of this
publication may be made without written permission.
No portion of this publication may be reproduced, copied or transmitted
save with written permission or in accordance with the provisions of the
Copyright, Designs and Patents Act 1988, or under the terms of any licence
permitting limited copying issued by the Copyright Licensing Agency,
Saffron House, 6–10 Kirby Street, London EC1N 8TS.
Any person who does any unauthorized act in relation to this publication
may be liable to criminal prosecution and civil claims for damages.
The author has asserted his right to be identified as the author of this work
in accordance with the Copyright, Designs and Patents Act 1988.
First published 2012 by
PALGRAVE MACMILLAN
Palgrave Macmillan in the UK is an imprint of Macmillan Publishers Limited,
registered in England, company number 785998, of Houndmills, Basingstoke,
Hampshire RG21 6XS.
Palgrave Macmillan in the US is a division of St Martin’s Press LLC,
175 Fifth Avenue, New York, NY 10010.
Palgrave Macmillan is the global academic imprint of the above companies
and has companies and representatives throughout the world.
Palgrave® and Macmillan® are registered trademarks in the United States,
the United Kingdom, Europe and other countries
ISBN 978-1-349-31657-1 ISBN 978-1-137-27132-7 (eBook)
DOI 10.1057/9781137271327
This book is printed on paper suitable for recycling and made from fully
managed and sustained forest sources. Logging, pulping and manufacturing
processes are expected to conform to the environmental regulations of the
country of origin.
A catalogue record for this book is available from the British Library.
A catalog record for this book is available from the Library of Congress.
10 9 8 7 6 5 4 3 2 1
21 20 19 18 17 16 15 14 13 12
For Stephanie and Adrian
This page intentionally left blank
Contents
List of Figures viii
List of Tables ix
Preface xi
1 Introduction 1
2 Case, Case Study, and Causation: Core Concepts and
Fundamentals 23
3 Types of Case Studies and Case Selection 61
4 Forms and Problems of Comparisons 97
5 Enhancing Causal Inference in Comparisons 125
6 Process Tracing: Theory, Temporality, and Method 1 50
7 From Evidence to Inference: Use of Sources and Counterfactuals 1 68
8 Frequentist and Bayesian Causal Inference in Tests of Hypotheses 1 80
9 External Validity and Generalization: Challenges and Strategies 2 00
10 Conclusion: Guided by Theory, Moving Forward Step by Step 212
Notes 215
References 237
Index 253
vii
Figures
1.1 The research process for three theory-centered research goals 1 1
2.1 Levels of analysis and types of observations 29
2.2 Single-mechanism explanation 35
2.3 Triple-mechanism explanation 36
2.4 Multiple-mechanism explanation 38
2.5 Venn diagram for sufficiency 53
2.6 Venn diagram for necessity 54
2.7 Venn diagram for necessity and sufficiency 55
2.8 Venn diagram for equifinality 56
2.9 Venn diagram for conjunctural causation 57
2.10 Venn diagram for INUS conditions 58
2.11 Venn diagram for SUIN conditions 59
3.1 Types of case studies and case selection strategies 62
3.2 Case selection on the basis of continuous outcome 69
3.3 Case selection on the basis of two continuous variables 7 2
3.4 Case selection on the basis of a continuous variable 78
3.5 Case selection on the basis of two continuous variables
for test of an interaction effect 80
3.6 C ase selection on the basis of two continuous variables
for test of an interaction effect 83
6.1 Process tracing by the example of tax competition 151
6.2 Democratic norms and anticipated processes 155
6.3 Visualization of the decision-making process 157
7.1 Illustration of process tracing and indeterminacy 172
8.1 The research process and frequentist and Bayesian
causal inference 188
9.1 Population comprising four cases 207
9.2 Three strategies of layered generalization 208
9.3 Uneven layered generalization 209
viii
Tables
1.1 Three theory-centered research goals 9
1.2 Ends and means of cross-case and within-case level 14
1.3 Six generic types of case studies 15
1.4 Frequentist and Bayesian causal inference 17
2.1 Causal perspectives and theory-centered research goals 41
2.2 Interaction effects and correlational causation 49
3.1 Measurement levels and types of causal effects 6 3
3.2 Types and selection for formation of cross-case hypothesis 7 1
3.3 Types and selection for formation of within-case hypothesis 77
3.4 Case selection on the basis of a 2 × 2 table 81
3.5 Choice of cases for test of sufficiency hypothesis on
the basis of a 2 × 2 table 82
3.6 Types and selection for test of cross-case hypothesis 89
3.7 Types and selection for test of within-case hypothesis 9 0
3.8 Types and selection for modification of cross-case
and within-case hypothesis 95
4.1 Comparisons for the formation of hypothesis 103
4.2 Cross-case comparison on institutional change 104
4.3 Method of agreement 1 06
4.4 Test for sufficiency of an international debate about
democracy and unitarism 109
4.5 Method of difference 110
4 .6 Alternative method of difference for set-relational
case study 112
4.7 No-variance-on-Y comparison 115
4.8 Variance-on-Y comparison 116
4.9 Inverse-correlation comparison 118
4.10 Correlational comparisons for modification of
cross-case hypothesis 119
4.11 Presence-of-Y comparison for necessity 1 19
4.12 Absence-of-Y comparison for sufficiency 120
4.13 Presence-of-Y comparison for sufficiency 121
4.14 Set-relational comparisons for modification of
cross-case hypothesis 122
5.1 Unit-related and time-related comparability and
generalizability of two-case comparisons 133
5.2 Imperfect method of difference and multicase comparisons 1 35
5.3 Indirect method of difference 135
ix