ECPR

Install the app

Install this application on your home screen for quick and easy access when you’re on the go.

Just tap Share then “Add to Home Screen”



ECPR General Conference 2020, University of Innsbruck

WD203 - Process Tracing Methods

Instructor Details

Instructor Photo

Derek Beach

Institution:
Aarhus Universitet

Instructor Bio

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.

  @beach_methodman


Course Dates and Times

Monday 5 to Friday 9 March 2018
25 hours over 5 days
09:00-12:30 and 14:00-16:30

Prerequisite Knowledge

A critical requirement for participation in this course is that your are using in-depth case study methods in your current research project (ph.d., post doc or other), and that you are advanced enough in your research that you have clear theoretical conjectures and ideas about potential empirical observations that can be worked with in the course.

This course also requires that you are familiar with the recent literature on case study methods (post 2010), and assumes familiarity with basic concepts related to Process-tracing. In particular, you should have basic knowledge about debates about causal mechanisms and empirical tests and how they are used in case studies.

The course requires submission BEFORE the course of a theorized causal mechanism and empirical proposition. The instructor will provide information about this well in advance of the course.

 

Short Outline

This hands-on Master Course aims to provide participants with the methodological tools to refine their use of process-tracing methods in their own substantive research, while also enabling them to embed process-tracing case studies in mixed-methods research design. The course requires VERY active participation.

It is assumed that participants have taken previous courses on process-tracing and/or in-depth case study methods.

Participants will be asked to submit to the instructor in advance a theorized causal mechanism and at least one proposition about an observable that a part of the mechanism might leave in a case.

Morning sessions will be devoted to lectures and discussions about key methodological issues, whereas the afternoon sessions are used to discuss particular aspects of participant projects.

 

Tasks for ECTS Credits

To receive 4 credits, you will be asked to be an active participant, doing the readings, submitting the presentation material (theory of a causal mechanism + an observable of a part of the mechanism) at least two weeks in advance of the course, and doing the in-class presentations.

An additional 2 credits will be awarded with daily assignments that are assigned after class every day.

An additional 2 credits will be awarded upon the submission of a take-home paper of between 7-10 pages, in which you revise your theorized mechanism and observable manifestation, and discuss case selection.

 

 

Long Course Outline

This hands-on Master Course aims to provide participants with the methodological tools to refine their use of process-tracing methods in their own substantive research, while also enabling them to embed process-tracing case studies in mixed-methods research design. The course requires VERY active participation.

Morning sessions will be devoted to lectures and discussions about key methodological issues, whereas the afternoon sessions are used to discuss particular aspects of participant projects, including theories of causal mechanisms and how we can develop testable predictions about evidence that the activities associated with parts of mechanisms might leave in a given case.

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. 

In the first morning session, we start by discussing how to differentiate process-tracing from other methods; including both large-n quantitative methods, but also other small-n methods such as analytical narratives, comparative case studies etc. Here we define process-tracing by the interest in studying causal mechanisms in single case studies in ways that enable within-case causal inferences to be made. We discuss the four variants of Process Tracing: theory-testing, theory-building, theoretical revision, and explaining outcome process-tracing. This is followed by an in-depth the ontological underpinnings of process-tracing in the second session of day 1, and the full session of day 2, focusing on how to understand causal mechanisms and how they differ from other types of causal theorization.

In day three morning session, we will discuss how inferences can be made using mechanistic evidence, focusing on how to operationalize theories of mechanisms by utilizing informal Bayesian logic. On day four we will discuss challenges relating to the evaluation of evidence in a joint session with the Historical Methods course. The final session on day 5 will turn to questions of case selection and mixed/multi-methods.

The afternoon sessions on days 1 and 2 will be devoted to presentation and discussion of theories of causal mechanisms prepared by each participant. In the afternoon sessions on days 3 and 4, we turn to presentation and discussion of observable manifestations of the activities of parts of mechanisms of each participant, followed on day 5 by a discussion of why participants chose particular cases.

Day-to-Day Schedule

Day-to-Day Reading List

Literature

See daily schedule.

Supplemental:

Brady, Henry E. and David Collier (eds) (2010) Rethinking Social Inquiry: Diverse Tools Shared Standards. 2nd Edition. Lanham MD: Rowman Littlefield.

Bunge, Mario. 2004. How Does It Work?: The Search for Explanatory Mechanisms. Philosophy of the Social Sciences 34(2): 182-210.

Cartwright, Nancy. 2007. Hunting Causes and Using Them: Approaches in Philosophy and Economics. Cambridge: Cambridge University Press.

Central Intelligence Agency. 1968. Intelligence Report – Bayes’ Theorem in the Korean War. July 1968, No. 0605/68. (approved for release date April 2005)

Doyle, A. Conan. 1975. The Memoirs of Sherlock Holmes. London: George Newnes.

Fairfield, Tasha and Andrew E. Charman. 2017a. ‘Explicit Bayesian Analysis for Process Tracing: Guidelines, Opportunities, and Caveats, Political Analysis, 25: 363-380.

Gerring, John. 2006. Single-Outcome Studies: A Methodological Primer International Sociology Vol. 21(5): 707-734.

Gerring (2007) Case Study Research. Cambridge: Cambridge University Press.

Glennan, Stuart S. 2002. Rethinking mechanistic explanation. Philosophy of Science 69: 342-353.

Groff, Ruth. 2011. 'Getting past Hume in the philosophy of social science.' In Causality in the Sciences, edited by Phyllis McKay Illari, Federica Russo and Jon Williamson. Oxford: Oxford University Press, 296-316.

Gross, Neil. 2009. 'A Pragmatist Theory of Social Mechanisms.' American Sociological Review 74 (3): 358–79.

Grzymala-Busse, Anna. 2011. 'Time Will Tell? Temporality and the Analysis of Causal Mechanisms and Processes.' Comparative Political Studies 44 (9): 1267–97.

Hedström, Peter and Richard, Swedberg (ed). 1998. Social Mechanisms an Analytical Approach to Social Theory. Cambridge: Cambridge University Press.

Illari, Phyllis and Federica Russo. 2014. Causality: Philosophical Theory meets Scientific Practice. Oxford: Oxford University Press.

King, Keohane and Verba (1994) Designing Social Inquiry: Scientific Inference in Qualitative Research. Princeton: Princeton University Press.

Mayntz, Renate. 2004. Mechanisms in the Analysis of Social Macro-Phenomena.  Philosophy of the Social Sciences 34(2): 237-259.

Pieson, Paul. 2003. Big, Slow-Moving, and…Invisible: Macrosocial Processes in the Study of Comparative Politics, In Comparative historical analysis in the social sciences. Ed. Mahoney, James and D. Rueschemayer, 177-207. Cambridge: Cambridge University Press.

Roberts, Clayton. 1996. The Logic of Historical Explanation. University Park: Pennsylvania State University Press.

Rueschmeyer, Dietrich. 2003.Can One or a Few Cases Yield Theoretical Gains? In Comparative historical analysis in the social sciences. Ed. Mahoney, James and D. Rueschemayer, 305-337. Cambridge: Cambridge University Press.

The following other ECPR Methods School courses could be useful in combination with this one in a ‘training track .
Recommended Courses Before

Summer School

Process-tracing Methodology I - an introduction (week 1)

Case Study Research : Method and Practice
 

Winter School

Introduction to the Philosophy of Science

Comparative Research Designs

Introduction to Process-tracing

Recommended Courses After

Summer School

Qualitative  Comparative Analysis and Fuzzy Sets

 

Master course in multi-method research

Additional Information

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc). Registered participants will be informed in due time.

Note from the Academic Convenors

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, contact the instructor before registering.


Share this page
 


Back to top