Comparative Research

Comparative Research General Comparative Research Proper (Ragin) All research is comparative Terms of comparative social science Comparative Research Proper (Ragin) Goals/Advantages Characteristics Comparative Methods Method of Agreement (Mill) Method of Difference (Mill) Qualitative Comparative Analysis (QCA) (Ragin)

All research is comparative ! Implicit vs explicit comparison Synchronic vs diachronic comparison Case studies (n = 1) and comparison Implicit comparison (description, concepts) Within-case comparison Case = process (implicit diachronic comparison

Types of Case Studies Extreme Case Typical Case Crucial Case Deviant Case Counterfactual Case What makes your case significant? By assigning your case study to one of these types, you are relating your case to the universe of other cases, your are setting it into context. Even though you might be doing a case study (n=1), you are “comparing” (going beyond that single case).

Terms of comparative social research Observation: One characteristic of one case Description: representation of all relevant features/aspects of a case Classification: Grouping of cases along one (and only one ) feature. Each case can be attributed to one class only. Ex: Classification of voters according to their party preference: Labour voters, Con Voters, LibDem Voters Typology: Grouping of cases along two or more aspects. Real type – aspects that can be found together quite often empirically. Ideal type (Max Weber) - one-sided accentuation of some logically connected characteristics. Real cases do not necessarily fit into these types. Ex: Aristotle’s forms of government (number of people involved + normative judgement) Lijphart’s types of democracy: Consensus v. Majoritarian Democracy Note: neither of the four does offer an explanation of reality, they are meant to bring order/perspective to social life and to the (potentially) infinite number of possible observations

The comparative method (proper)

The comparative method (proper) Small/medium number of cases + Small/medium number of aspects/variables Why use such a research strategy? Answer to problem in social science: many variables, few cases (not enough for quantitative analysis) But also (according to Ragin): it is a deliberate choice in order to study patterns of diversity. Remember: qualitative approach – commonality quantitative approach – diversity with regard to one variable

Research Goals Exploring Diversity Interpreting Cultural or Historical Significance Advancing Theory Typical goal: “… unravel different causal conditions connected to different outcomes” (Ragin 1994: 108)

Characteristics Unites case orientation with variable orientation Detailed knowledge of cases important for analysis, but also part of the research goal Studies cases as configurations (no isolation of variable) Analytic frame not as flexible/fluid as in qualitative research, but much more flexible than in quantitative studies Importance of case selection (form of theoretical sampling, rather than random selection), because of quasi-experimental character

3 comparative methods Method of agreement Method of difference QCA (Qualitative Comparative Analysis)

Method of agreement (MDSO) Based on John Stuart Mill Basic idea: In order to find explanations for a certain phenomenon (dependent variable), we look at the most different cases which all share this particular feature Also known as: “most different with same outcome” (MDSO)

Method of agreement (II) Select dependent variable (what is to be explained?): Ex: 2-party system Select cases: select cases as different as possible, which all/both exhibit the dependent variable (USA, UK, 19th century, 20th century) Analysis: look for common features in all these cases: plurality electoral system (FPTP)

Method of Agreement Case Independent variables Dependent variable Context A (a,b,f,g) Outcome X Case 2 Context B (a,c,d,e) Test case Context C (b) Outcome: not X

Analysis Case 1 and 2 differ drastically, yet in both cases the outcome X occurs The only common variable is a Reasoning: a is the cause of X (sufficient condition: a leads always to X)

Problems Presumption: variable has always the same consequences (no matter of context) (peasant discontent in agrarian and industrial society, quite different consequences) Presumption: dependent variable is caused by the same cause (what if different factors produce the same outcome?) Selection bias: by only looking at positive cases (with outcome x) we cannot “know”, whether there are cases were a exists yet X does not follow. We need test case(s), where X did not occur (hope that a was not present)

Method of Difference (MSDO) Based on John Stuart Mill Basic idea: Find the most similar cases which nevertheless differ with regard to dependent variable (phenomenon to be explained). The feature(s) these different cases do NOT have in common explains whether the result is x or not Also known as: “most similar with different outcome” (MSDO)

Method of Difference (II) Classify cases according to dependent variable Select cases that differ with regard to dependent variable yet are most similar with regard to potential causes Look for existing differences with regard to independent variables (potential causes)

Method of Difference Case Independent variables Dependent variable Context A (a,b,c,d) Outcome X Case 2 Context A (a,c,d) Outcome Y

Analysis Case 1 + 2 are very similar with respect to context (broad historical situation, institutional setting etc.) and potential causes Yet in case 1 X occurs, in case 2 it does not occur Case 1 and 2 differ only in one independent variable (b) Therefore: b is the cause of X (necessary condition: without b there is no X)

Problems b is necessary, but is it sufficient (perhaps a + b are the cause)? How to control for context (when is it the same)? How to distinguish between context and independent variable?

General Problems of Mill’s Methods Direction of causality can be contested (what is cause, what is effect) Isolating variables. Patterns of variables (specific configurations) can not be detected as cause Do not account for multiple causation Uses dichotomous variables (a, non-a), what about matters of degree? No relationships of a probabilistic nature can be detected (relationships that are not perfect, but work only most of the time)

Purpose of Mill’s Methods Help to explore diversity Help to eliminate wrong hypotheses Help to getting closer to a causal explanation But should not be pursued to mechanistically Need to be grounded in theoretical arguments

Qualitative Comparative Research Ragin’s answer to (some) problems of Mill’s methods Allows for and detects configurations of variables as causes and allows for multiple causation Problem still: Dichotomous variables (not always possible) Non probabilistic, only deterministic

You should know: All research is comparative Some technical terms Classification v. Typology Dependent v. Independent variable Characteristics and goals of comparative research Basic idea of Method of Agreement/Difference Problems of these methods