The purpose of this course is provide training on all aspects that enable a researcher to conceive and conduct the most appropriate comparative research design – the latter broadly defined as any research enterprise that comprises at least two ‘cases’ or observations.
On the one hand, the course will cover fundamental questions ‘upstream’ of practical and hands-on choices: what is comparison? Why compare; what is the added value of comparison? What are the logical underpinnings and mental operations behind comparison? What should be the ‘mind set’ of a good comparative researcher? What should be his/her goals? What is the link between a research puzzle and the choice for a comparative research design? What would be the alternative(s)? Does one conceive and does one perform comparison in the same way when the ‘cases’ are situated at the micro (i.e. individuals), meso (e.g. organizations) or macro (e.g. political or policy systems) levels? Etc.
On the other hand, the practicalities of different types of comparative research designs will be examined in detail, by following all the hands-on steps: (1) prior arbitrations and ‘casing’, i.e. the definition of the cases; (2) case selection, through more basic or more advanced strategies; (3) collecting and managing comparative data; (4) comparative data analysis. As explained below in detail, steps (1) and (2) will be examined in greater detail.
In concrete terms, the course will be organized in 5 sessions, each one of them allowing time for open discussions and interaction.
On Day 1, after an introduction on all the practical and organizational aspects of the course, the main topic will be to frame comparative research in the broader context of a comparative approach. This necessitates to consider some epistemological issues underpinning comparison as such. Starting from the discussion of comparison as a basic mental operation, we will progress to comparison in the social sciences then to political science more specifically. One core focus will be laid on the different goals of comparison, with practical examples. The session will be concluded by the discussion of a first series of participants’ projects, with a focus on the goals pursued (why go for a comparative research design?).
On Day 2, we will locate comparative research designs vis-à-vis other research designs, i.e. within the whole range of possible designs. We will also present all the practical steps of a ‘good’ comparative research design, with a focus on the major arbitrations to be made. We will also have a first look at “step 1” operations that lie upstream of the case selection step. Indeed quite a few core arbitrations must be made upstream, such as the formulation of the research question(s) and hypotheses, the correct use of concepts for the purpose of comparison, the number of cases one will be able to manage, and the choice between cross-country or within-country case selection. The session will be concluded by the discussion of a second series of participants’ projects, with a focus on upstream arbitrations.
On Day 3, we will pursue the examination of the “step 1” operations, and deepen the question of “what is a case” within a comparative research design – with an emphasis on some core arbitrations such as depth v/s breadth and cross-country v/s within-country v/s within-system casing and case selection. Then we’ll go through a systematically survey all the main options for the core “step 2” operation: case selection. We will first envisage rather basic or simple strategies of case selection, from very small N to very large N, and following different criteria; the pros and cons of each strategy will also be discussed. The session will be concluded by the discussion of a second series of participants’ projects, with a focus on “casing” and case selection
On Day 4, following the survey of the “step 2” operation, we will turn to more advanced or refined strategies, in particular taking into consideration issues of time/sequence and of multilevel phenomena. The pros and cons of each strategy will also be discussed. Then we’ll move on to hands-on ‘tricks of the trade’ on how to collect and manage data in a comparative research (“step 3”) – including ways to trouble-shoot and to make adjustments in terms of case selection as the research develops. This will be pursued by a fourth interactive section (around the participants’ projects), with a focus on case selection and data collection/management. Further, we’ll examine different ways to engage in comparative data analysis, from more case-oriented (or ‘qualitative’) to statistical or formal tools, through some other tools (such as QCA) geared towards intermediate-N research designs. The pros and cons of each one of these tools will be discussed in short, as well as the potential and difficulties of triangulating, sequencing or ‘mixing’ different data analysis techniques.
Finally, on Day 5, we will focus on one particular strategy to conduct multiple cross-case comparison, QCA (Qualitative Comparative Analysis), which will first be briefly presented as an approach with specific goals and assumptions. We’ll also survey the different potential uses and types of data that can be processed through QCA. Then we’ll turn to more applied aspects of QCA, i.e. how to use QCA as a set of techniques, following a basic QCA protocol, with real-life data, from A to almost Z, using the most straightforward technique, csQCA (crisp-set QCA). Then, in the second part of the morning session, we’ll wrap up the course by “revisiting” some of the core points – with a focus on the strengths of comparative research designs, but even more on main perils or caveats of comparison. The goal is that each participant will become more aware about the ways to “mis-compare” – and hopefully avoid this in his/her own research. This will be followed by an open interactive session, discussing points still to be clarified, points of debate or disagreements, remaining questions and answers about participants’ projects, etc.
In the afternoon of day 5 (NB: optional, additional session, for those specifically interested in QCA), animated mainly by the teaching assistants (qualified in QCA), we’ll go further into concrete empirical QCA applications, including software use (both for csQCA and fsQCA [fuzzy-set QCA] analyses) on prepared datasets. The analyses will be replicated by the participants on their laptops, including trouble-shooting. Based on this, we’ll also briefly present and discuss various refinements in the analysis, as well as strengths and limitations/bottlenecks of QCA.
Insofar as possible, each participant is encouraged to bring his/her own research questions & hypotheses, his/her first thoughts and difficulties (if any) in terms of case definition and case selection, and (if applicable) any data he/she has already compiled. The course is designed to help each individual participant make his/her most appropriate choices in terms of comparative research design. Each participant will be able to reflect and to work on his/her own project as we follow the sequence of more fundamental and then more applied steps. Insofar as possible, we’ll use some input from the participants’ own projects in each one of the 5 sessions (in the interactive parts).
Connections with other courses (see also section 13 below):
- This course can be taken as a stand-alone course, but it has been designed as an introductory course, particularly in the view of best preparing participants to different courses at the ECPR Summer School – in particular (non-limitative list) Methodologies of Case Studies, QCA and Fuzzy Sets and Mixed Methods Designs (labels may be subject to change).
- Note that this course is not a specialized course on QCA. Some of the main features of QCA (both as an approach and a set of operations incl. software) will be presented and applied at an introductory level, and various resources will be pointed to, but full training on QCA is to be followed in the 2018 two-week Summer School course
- The course may also be of interest for participants engaged in ‘thick’ observational work (e.g. ethnography, participant observation, interviews, …) or in in-depth single case studies (using e.g. process tracing), as well as participants interested in following more formalized or statistical approaches (large-N statistical techniques, experiments, …), especially if their populations and/or samples are not so obvious to circumscribe
Tasks for ECTS Credits
- Participants attending the course: 2 credits (pass/fail grade) The workload for the calculation of ECTS credits is based on the assumption that students attend classes and carry out the necessary reading and/or other work prior to, and after, classes.
- Participants attending the course and completing one task (see below): 3 credits (to be graded)
- Participants attending the course, and completing two tasks (see below): 4 credits (to be graded)
- In order to obtain 2 credits: reply to the short pre-course survey, read in advance the daily readings (see reading list), actively take part in the 5 morning course sessions, and deliver the 4 daily assignments that will be given from Monday to Thursday (to be delivered at the latest the next morning, from Tuesday to Friday).
- In order to obtain 2 additional credits (hence a total of 4 credits): write up a thorough take-home research paper that will be evaluated by the teaching team. The format, focus, evaluation criteria, submission deadline etc. of the paper will be explained on days 1 and 5 of the course. There is some flexibility in terms of focus (more details will be discussed on day 5 of the course), with – among other possibilities – a paper laying out out all the main elements of one’s CRD, or a paper focusing more in-depth on one specific step of one‘s CRD.