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Member rate £492.50
Non-Member rate £985.00
Save £45 Loyalty discount applied automatically*
Save 5% on each additional course booked
*If you attended our Methods School in Summer/Winter 2024.
Monday 6 August - Friday 10 August
14:00-15:30 / 16:00-17:30
This course is a practical, hands-on course in using Process Tracing (PT) methods in one’s own research, complementing the more theoretical PT I ECPR Summer School course held in the first week, which focuses on the research design aspects of the method.
This course focuses on how we can use within-case evidence to make causal inferences about mechanisms. The course starts with an introduction to how we can make causal inferences using Bayesian logic, i.e. using mechanistic evidence where we have no variation upon which to make inferences. We then turn to the practicalities of empirical testing and making causal inferences in days 2 and 3, focusing on how we can strengthen the inferences we can make by improving the empirical tests that we employ in our research. We will work on this topic using a combination of analysis of existing work and tests developed based on your own research. Day 4 discusses inductive theory-building using PT. The final day discusses how we can utilize PT in practical case study research.
The course requires active participation. It is expected that participants are able to use parts of their own research in the exercises and group work during the course.
Tasks for ECTS Credits
To receive 2 ECTS, you will have done the readings and taken part actively in the course.
To receive 3 credits, you will do the above and complete all of the daily assignments.
The full 4 credits will be awarded with the above and the completion of a 5-10 final assignment (take-home project that will be turned in within 3 weeks of the completion of the course).
Derek Beach is a professor of Political Science at Aarhus University.
He has authored articles, chapters, and books on case study research methodology, international negotiations, referendums, and European integration, and co-authored Process-tracing Methods: Foundations and Guidelines (University of Michigan Press).
Derek has taught qualitative case study methods at ECPR, IPSA and ICPSR summer and winter schools, and numerous workshops and seminars on qualitative methods throughout the world. He is an academic co-convenor of the ECPR Methods School.
The promise of process-tracing as a methodological tool is that it enables the researcher to study more-or-less directly the causal mechanism(s) linking a cause (or set of causes) and an outcome, allowing us to open up the ‘black box’ of causality itself. By unpacking causal mechanisms into their constituent parts, composed of entities engaging in activities, and then tracing the empirical manifestations these activities leave in actual cases, we are able to collect what has been termed mechanistic evidence upon which we can make causal inferences about how causal mechanisms actually work (Machamer, Darden and Craver, 2000; Machamer, 2004; Bogen, 2004; Waskan, 2008, 2011). Strong causal inferences about the effect a cause has on an outcome are naturally only possible when we use evidence of difference-making that is produced through experimental manipulation across cases (Woodward, 2003). However, when we use mechanistic evidence to make causal inferences, we are using observational, within-case evidence to make causal inferences about the actual operation of mechanisms in real world cases (Russo and Williamson, 2007; Illari, 2011; Waskan, 2008, 2011). In other words, instead of studying causal effects we are studying how things work. As an example, in medical research the causal mechanism linking smoking and cancer has been broken down into a series of parts that describe the entities and their activities that transmit causal forces to the outcome (Russo and Williamson, 2007: 162). The cause that triggers the process is smoke inhalation. The mechanism then is composed of several steps that are linked together in a causally productive relationship where the causal links are made explicit in the form of activities: smoke inhalation -> hair-like cilia in lungs are destroyed by the smoke -> lungs cannot clean themselves effectively, resulting in cancer-producing agents in the smoke becoming trapped in mucus -> these agents alter cells (especially cell division) in the lungs -> cancer. Mechanistic evidence is the observational data that captures empirically the observables left by the activities of entities (for example smoke destroying cilia) that transmit causal forces to the next part of the causal process, enabling researchers to make evidence-based claims about how smoking produces cancer.
The first day introduces the Bayesian logic of inference, followed by hands-on exercises for how we can develop and improve empirical tests in ways that enable strong causal inferences to be made, using an example from a Sherlock Holmes story.
Day 2 introduces recent developments in empirical testing in PT, focusing on the Bayesian underpinnings of two dimensions of test strength (certainty and uniqueness). We utilize Tannenwald’s well-known article to illustrate Bayesian logic and empirical tests.
Day 3 introduces source criticism and the practical challenges in working with empirical evidence in PT. We focus upon archival material, elite interviews and secondary historical sources. This includes questions such as how we should evaluate bias, what a ‘good’ source is, and how we deal with bias in secondary historical material. We will utilize a set of materials from the Cuban Missile Crisis to discuss the challenges relating to evidence in PT.
Day 4 turns to a discussion of how we can use empirical material to build theorized causal mechanisms, using Janis’ study of Groupthink as an example.
The course concludes with a discussion of practical challenges in using PT, drawing on the exercises participants will be drafting during the week.
Note from the Academic Convenors to prospective participants: by registering to this course, you certify that you possess the prerequisite knowledge that is requested to be able to follow this course. The instructor will not teach again these prerequisite items. If you doubt whether you possess that knowledge to a sufficient extent, we suggest you contact the instructor before you proceed to your registration.
Considering this is a second week/advanced course the course requires that one has already had an introduction to Process Tracing, either by taking the week 1 course 'Process Tracing Methodology I', the course 'Introduction to Process Tracing' at the ECPR Winter School, or another introductory course on PT.
Day | Topic | Details |
---|---|---|
1 | Making causal inferences using within-case evidence – Bayesian logic | |
2 | Operationalization of tests | |
3 | Working with evidence | |
4 | Building theorized mechanisms | |
5 | Using PT in practice |
Day | Readings |
---|---|
1 |
Making causal inferences using within-case evidence
|
2 |
Operationalization of tests
|
3 |
Working with evidence
|
4 |
Building theorized mechanisms using empirical material
|
5 |
Using PT in practice Discussion based on exercises during the week. |
None.
None.
Beach and Pedersen (forthcoming) Process Tracing: Foundations and Guidelines. 2nd edition. Ann Arbor: University of Michigan Press.
Beach and Pedersen (2016) Causal Case Studies. Ann Arbor: University of Michigan Press.
Winter School
Introduction to Process Tracing
Introduction to the Philosophy of Science
Comparative Research Designs
Summer School
Process Tracing Methodology I – Foundations and Guidelines
Case Study Research: Method and Practice
Winter School
Master Course: Multi-Method Research
Summer School
Qualitative Comparative Analysis and Fuzzy Sets