The Logic & Best Practices of Process Tracing (QMMR A)

Session Submission Type: Short Course Half Day

Session Description

This short course covers the underlying logic and best practices of process tracing, which is a within-case method of developing and testing causal explanations of individual cases. We begin by exploring the philosophies of science behind process tracing: scientific realist and interpretive. Next, we highlight, define and provide examples of the central concept process tracing measures - causal mechanisms - noting their difference from causal effects and interpretive understandings of causation.

The core of the short course is then an introduction to the logic and best practices of process tracing, both its ‘front end’ data collection and ‘back end’ data analysis. For data collection, we consider the typical ways in which process tracing gathers evidence on the observable implications of causal mechanisms, including archival work, document analysis of secondary sources, various field methods (interviews, political ethnography, ethnography), and surveys. In reviewing these methods, we consider the inferential and ethical challenges each raises when accessing process-tracing data. On data analysis and process tracing, we begin by considering the informal manner in which many scholars proceed; more important, we survey the growing number of techniques (e.g., Bayesian logic, directed acyclic graphs) that allow us to conduct the process tracing analysis more formally and transparently. We finish this part of the course by articulating a set of best practices for conducting process tracing.

After this overview of the philosophical, causal and data logics of process tracing, the course introduces participants to two different types. We begin with Bayesian process tracing—comparing rival hypotheses; evaluating the inferential weight of evidence by “mentally inhabiting” the world of each hypothesis and asking which one makes the evidence more expected; updating prior views about which hypothesis is more plausible; and fostering transparency through systemization. We then turn to interpretive process tracing—inductive approach; practice logic; establishing local causation; transparency through ethical self-reflection.

Throughout the course we will emphasize best practices and applications to exemplars of process tracing research. While the examples are primarily drawn from international relations and comparative politics, the methods we discuss are applicable to all the subfields of political science, to sociology, economics, history, business studies, public policy, and many other fields.

The course’s final section is devoted to small-group breakout sessions, where participants workshop how they plan to use process tracing in their research. Are there data access, data collection, data analysis or ethical issues with which they are grappling? Instructors and fellow students will offer constructive advice on how best to address such issues.

This morning short course is designed as an introduction that can usefully be taken in conjunction with Bayesian Reasoning (QMMR B) or Interpretive Process Tracing (QMMR C) in the afternoon. These three courses are complementary and can also be taken separately.

Instructor bios:

Andrew Bennett is Professor of Government at Georgetown University. He is the co-author, with Alexander George, of Case Studies and Theory Development in the Social Science (MIT Press, 2005), and co-author, with Jeffrey T. Checkel, of Process Tracing: From Metaphor to Analytic Tool (Cambridge University Press, 2015). Professor Bennett’s substantive research focuses on security issues in international relations, including military interventions, alliances, and decision-making. He has many years of methods teaching experience at Georgetown and at summer methods institutes around the world.

Jeffrey T. Checkel is a professor at the European University Institute, where he holds the Chair in International Relations. His research interests include international relations theory, international institutions, civil war, identity/identity-formation and qualitative methods. At EUI, he offers seminars on international relations theory, international institutions, qualitative methods, and philosophies of social science. Most years since 2014, Checkel has co-taught the foundational APSA short course on ‘The Logic and Best Practices of Process Tracing.’

Tasha Fairfield is Associate Professor in Development at the London School of Economics. Her methodological research examines the Bayesian logic of inference in qualitative social science. Her most recent book – with Andrew Charman - is Social Inquiry and Bayesian Inference: Rethinking Qualitative Research (Cambridge University Press, 2022). She has been teaching workshops and courses on this material since 2016 at IQMR, APSA, LSE, GSERM and other forums. Her substantive research examines the comparative politics of business power and inequality.

Sub Unit

• Pre-Conference Short Courses

Chair

• Andrew Bennett Georgetown University

Presenters

• Andrew Bennett Georgetown University

• Jeffrey T. Checkel European University Institute

• Tasha A. Fairfield London School of Economics