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Lecture 3 Case studies: Research Methods RESEARCH METHODS NATIONAL RESEARCH UNIVERSITY, HIGHER SCHOOL OF ECONOMICS PH.D. PROGRAMME DR C S LEONARD JUNE 2011

Lecture 3 Case studies: Research Methods

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Research Methods National Research University, Higher School of Economics Ph.D. Programme Dr C S Leonard June 2011. Lecture 3 Case studies: Research Methods. Outline. What is a case study? Context and N Causal reasoning Case Selection - PowerPoint PPT Presentation

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Page 1: Lecture 3 Case studies: Research Methods

Lecture 3Case studies: Research Methods

RESEARCH METHODSNAT I O N AL R ES EA RC H U N I V E RS I T Y, H I GHE R S C HO O L O F ECO NO M I C S

PH.D. PROGRAMME

DR C S LEONARD JUNE 2011

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OUTLINE

What is a case study?

Context and N

Causal reasoning

Case Selection

Building a theory: getting help from a statistically derived case study

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WHAT IS A CASE STUDY?

What is it?

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CONTEXT

The examination of a single unit within its real life context.

The aim is to elucidate the features of a broader set of similar cases (Gerring).

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IS A CASE STUDY SMALL N?

Common criticism: ‘how can you generalise from one case?’ Confusion over language and the meaning of a

‘case’ – a case study is not one observation (Shleifer)

Some case studies use a survey and therefore have multiple observations, e.g. Middletown (cited in Gerring 2007 and Yin 2003)

Some case studies contain nested sub-cases or within case units, e.g. before and after.

Even if the case under study is one individual, there will be multiple observations of different kinds.

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NOT N, CONTEXT

The examination of a single unit within its real life context.

The aim is to elucidate the features of a broader set of similar cases (Gerring).

A unit is a relatively bounded phenomenon – e.g. a nation, a firm, a department, an industry, a strategy, or person.4/20/2011GSOM RESEARCH METHODS 2011

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CONTEXT AND CAUSAL MECHANISMS

A study which investigates a contemporary phenomenon within its real life context (Yin, 2003)

- The strength of case studies is that they can identify causal mechanisms, and tracing causal mechanisms entails sensitivity to local context (Bennett and George, 2005)

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WHY CASE STUDIES?

Research can contain two conflicting requirements Data Integrity Generalizability (high currency)

Depends on research topic and type of problem

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GENERALIZABILITY

There is much versatility – it depends on the nature of your case and on your research question.

Some case studies use only qualitative data Some use both qualitative and quantitative

data The use of different kinds of evidence is

very common in case study research4/20/2011GSOM RESEARCH METHODS 2011

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THE “SO WHAT” QUESTION

Both theory and case studies focus on the particular and on detail.

Both theory and case studies must deal with the ‘So What?’ question.

For both theory and case studies in-depth understanding and context provide a way of dealing with the ‘so what’ question.

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EMBEDDEDNESS

Case study thus defined is especially suitable for studying phenomenon that are high complex and/or embedded in their cultural context (Verschuren, 2003)

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RATIONALITY

• Daniel Little illustrates this in relation to rational choice theory – ‘context bound rationality’ (the authors of Analytic Narratives refer to Daniel Little when advocating their approach to case study research)

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EXAMPLES OF CASE STUDIES

Benedict Anderson: ‘imagined communities’ (earnings repatriation and economic growth)

Chalmers Johnson: the ‘developmental state’ (Ministry of Trade and Industry in Japan)

“Smart” Growth Clusters

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RELEVANCE OF CASE STUDIES FOR ECONOMICS

• Much of the case literature on how to define a research question, identify suitable data, link data to theory and make appropriate generalisations have relevance for research design more generally.

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CASE SELECTION

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CASE STUDY OF WHAT?

What your case study is a case of will affect your population (or unit selection), your materials, the theoretical propositions that inform your research

Failure to clarify early on what your case study is a study of could leave you with a list of details and facts – an information download.

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HELPS DECISION-MAKING

It helps you to identify and define potential variables of interest.

It helps you to formulate theories.

It helps you decide to which wider conversation or ‘scholarly mosaic’ you will contribute your piece.

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CAVEATS The objective must be causal inference (with

reference to the larger population) Larger reference, not within group distinctions The research must begin with understanding of the

inferences being made (not searching for cases) All have large and small-N implications, or

possibilities Most important: statistical means to identify the

cases you wish to study further

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CASE SELECTION

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PRINCIPLES OF SELECTION

Typicality Probably somewhat illusory Most often the basis for choice Useful in finding causal

mechanism in general cross case relationship

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MOST SIMILAR

A case that is like another case in all respects except for either a key independent variable or the dependent variable of interest (2 villages similar for all major socio-economic indicators except one has a female high suicide rate)

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MOST DIVERSE Achievement of maximum variance along relevant

dimensions, the diverse case method

Minimum of 2 cases to represent the full range of values characterizing X, Y or X/Y relationship

Exploratory, hypothesis seeking when X or Y, and hypothesis confirming, when X/Y

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DIVERSE, CONT

Either categorical (one from each group), continuous (from each extreme plus the mean or median), break points, where causal factor is vector of variables that can be measured, leads to cross tabs (sometimes you need to redefine a variable for categorical responses)

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THE EXTREME Because of its extreme value on X or Y

(outlier), in large N, defined in terms of the sample mean and standard deviation

Seems to violate maxim: don’t select on dependent variable, but not. Treat it as not representative.

Its objective is purely exploratory May morph into something else later

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DEVIANT CASE Surprising value, anomalous Relative to the mean of a single

distribution By reference to cross case relationships

and are poorly explained Relative to general model (ie, it may

change the general model) Probe for new unspecified explanations

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MOST INFLUENTIAL

Need to check assumptions behind the model Checking cases that have influence to make

sure they fit the sample To explore cases that may be influential in a

larger cross case study Leverage of a case (large n)

Hat matrix, tells of potential influence Cook’s distance (the extent to which the

coefficient would change if a case were omitted)

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MOST SIMILAR AND MOST DIFFERENT

Like diverse case method Chosen pair similar on all measured independent

variables except the one of interest That is, you expect that the pattern of co-variation

depends upon the absence of a variable Statistical tool: matching techniques (major topic in

econometrics) comes from experimental logic: (difference of means test?) using a treatment group and matching cases in the control group

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SUMMARY

1. There is the need to show wider relevance – this entails offering explanations that can be applied at a higher level of abstraction, and so some of the detail of the case study must be lost

2. In most case study research, there is ongoing interaction between theoretical propositions and revisions to them (deduction), and collection and analysis of empirical data (induction).

3. Regardless of approach to the case study rigor and clarity are necessary (case study protocols ala Yin help, or the structured approach of Bennett and George part 2 do the same).

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EXAMPLE OF CASE SELECTION (ADAPTED FROM GERRING, 2007)

Most different: Cases that are different in all respects except for x and y variables, so both IBM and GAZPROM have large scale operations and a conservative culture but differ in all other respects

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THE STATISTICAL SAMPLING APPROACH

• Places emphasis on replication (interview replication/within case unit replication/case replication) in order to saturate theoretical categories.

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USE OF THEORY IN CASE STUDY DESIGN AND ANALYSIS

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THEORY BUILDING FROM CASES

Iterative process

Multiple investigators

Results in greater originality

Hypotheses can be proven false

Theories generated apart from evidence have testability problems

Bottom up approach, however, may have problems of idiosyncracy

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TO TEST RELIABILITY

Reliability: Inconsistency in data collection affects findings

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TO TEST VALIDITY

Validity: Construct validity: are you looking at what

you think you are looking at? Congruence between key concepts in the research question and the material that you gather (context is important).

Internal validity: causal mechanisms. External validity: the scope conditions, the

domain to which generalisations can be applied. 4/20/2011GSOM RESEARCH METHODS 2011

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QUANTITATIVE

• Quantitative approach (DSI/Geddes): Theory is used in formulating a hypothesis against which the findings of a representative case study contained many observations is tested

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STRUCTURED

• Structured/Theory Driven Approach (Gerring.Bennett and George): Literature informs a theory which is modified based on limited understanding of an empirical case. Then through the process of data gathering and analysis the theory is modified and revised and informs further data gathering and analysis: ongoing process of deduction and induction

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PROBLEM DRIVEN/ANALYTIC NARRATIVE

The aim is to explain the problem of why within a particular case one outcome resulted rather than another

Rational actors making rational choices are assumed

The case focuses on how institutions shape causal linkages, particular pathways and the choices actors make

Theory is developed along with the empirical data

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THE EXTENDED CASE METHOD (BURAWOY):

The theoretically informed researcher extracts what is general from the unique.

Theory helps to explain the macro-processes and structures within which the locally based case is situated.

Wider relevance is claimed not by saying that the explanation of the study applies to many other cases but by explaining: (1) the wider structures in which the particular is embedded(2) by showing how the particular is the incarnation of a more abstract macro-level process.

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INTERPRETIVE METHOD:

Tries to privilege inductively derived insider categories and understandings.

The researcher reads a wider theoretically literature but then brackets this out.

The researcher then immerses him/herself in the empirical data and codes inductively to identify indigenous ways of explaining, before returning to the wider literature to position, revise, contextualise etc.

(see Tavory and Timmermans, 2009 and their bibliography)4/20/2011GSOM RESEARCH METHODS 2011

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GENERALISING Always make delimited and contingent

claims. The goal is rarely to refute theory, but to

identify whether and how the scope conditions of competing theories should be expanded or narrowed (Gerring).

Rather than try to claim a causal effect across a number of similar cases it is better to specify the ways in which causal mechanisms converge and interact in your case.

Rather than ‘generalise’ you may want to extrapolate from your case to other cases, and do so at the theoretical level 4/20/2011GSOM RESEARCH METHODS 2011

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INTERACTION

In most case study research, there is ongoing interaction between theoretical propositions and revisions to them (deduction), and collection and analysis of empirical data (induction).

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SELECTION ON DEPENDENT VARIABLE: NO CONTROL

Barbara Geddes – Elaborates the concern of many quantitative scholars that case studies are selected on the dependent variable

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BUILDING A THEORY FROM CASE STUDY RESEARCH (EISENHARDT

1989)

Getting started Can get overwhelmed by information, volume of

data Go in with special aims: collect specific kinds of

data systematically A priori specification of constructs

Important in the case study (ie, conflict, power, competition, transition economy)

Of course no construct is guaranteed a place in the resultant theory and question may shift

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USED FOR BUILDING NOT TESTING THEORY

Theory building research, as opposed to theory testing research Should specify ex ante the

research problem and potentially important variables but be open to the theory and their relationship

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EX: STRATEGIC CHANGE AND COMPETITIVENESS

Choosing cases For theoretical reasons (from

previous research), to fill theoretical categories and provide examples of polar types

Likely to replicate or extend the emerging theory

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COMBINING SOURCES

Qualitative and quantitative Theory building seems to require rich

description But the quantitative information is the

foundation Multiple investigators usually help Make visits to case study sites in teams Want divergent views

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BUILDING THE THEORY

Analyzing cases from within Least codified part of project Pure descriptions may help being flooded

with too much information Revise construct, search for measure Note differences between cases Establish construct validity (important in

hypothesis testing and theory building)

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REPLICATION

Cases that confirm the theory or construct are supplemented by those that don’t, allowing for theory extension Example of stable coalitions (one case was not

stable, leading to reexamination of data, and it turned out that stability occurred over time, evolving in coalitions)

Qualitative work at this points helps understand why something is happening (internal validity)

You must judge the strength and consistency of a relationship across cases without an F

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GO BACK TO THE LITERATURE

Find confirming and conflicting studies Overcoming the reasoning in the latter, will

help build confidence in your case Finding differences forces you into frame-

braking mode, more creative, deeply insightful

Finding similarities in other literature, also confirms your work and enhances its internal validity (which may rest on too few cases)

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SATURATION

Stop when you have proved your case

Incremental learning is minimal Stop iterating when saturated

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At last...

THE END