Lecture 3 Case studies: Research Methods R ESEARCH M ETHODS N ATIONAL R ESEARCH U NIVERSITY, H IGHER...

Lecture 3Case studies: Research Methods

RESEARCH METHODS

NATIONAL RESEARCH UNIVE RSITY, H IGHER SCHOOL OF ECONOMICS

PH.D. PROGRAMME

DR C S LEONARD JUNE 2011

OUTLINE

What is a case study?

Context and N

Causal reasoning

Case Selection

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

4/20/2011GSOM RESEARCH METHODS 2011

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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).

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. 4/20/2011GSOM RESEARCH METHODS 2011

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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.


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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 problem4/20/2011GSOM RESEARCH METHODS 2011

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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 research


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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. 4/20/2011GSOM RESEARCH METHODS 2011

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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).

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


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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...

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Lecture 3 Case studies: Research Methods R ESEARCH M ETHODS N ATIONAL R ESEARCH U NIVERSITY, H IGHER...

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