Process Tracing And Causal Inference
Abstract
How should we judge competing explanatory claims in social science research? How can we make inferences about which alternative explanations are more convincing, in what ways, and to what degree? Case study methods—especially methods of within-case analysis such as process tracing— are an indispensable part of the answer to these questions (George and Bennett 2005: chap. 10). This chapter offers an overview of process tracing as a tool for causal inference, focusing on the study of international relations, an area rich with examples of this approach. In contrast to the subsequent two chapters in this volume (chaps. 11 and 12), where Freedman and Brady analyze micro-level examples, the present chapter explores process tracing in macro studies.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Basic ideas about applying process tracing to causal inference may be summarized in terms of four empirical tests: straw-in-the-wind, hoop, smoking-gun, and doubly decisive.
“Basic ideas about applying process tracing to causal inference may be summarized in terms of four empirical tests. Slightly adapting the formulation of Bennett (2010), who builds on the work of Van Evera (1997), the tests are classified according to whether passing the test is necessary and/or sufficient for accepting the inference. Based on these criteria, table 1 presents the four tests: straw-”
From Understanding Process Tracing (2011) · cites this paper as Bennett 2010
Passing a straw-in-the-wind test only slightly weakens rival hypotheses.
“If a given hypothesis passes a straw-in-thewind test, it only slightly weakens rival hypotheses; with hoop tests it somewhat weakens them; with smoking-gun tests it substantially weakens them; and with doubly decisive tests passing eliminates them”
From Understanding Process Tracing (2011) · cites this paper as Bennett 2010
Passing a doubly decisive test eliminates rival hypotheses.
“If a given hypothesis passes a straw-in-thewind test, it only slightly weakens rival hypotheses; with hoop tests it somewhat weakens them; with smoking-gun tests it substantially weakens them; and with doubly decisive tests passing eliminates them”
From Understanding Process Tracing (2011) · cites this paper as Bennett 2010
Passing a hoop test somewhat weakens rival hypotheses.
“If a given hypothesis passes a straw-in-thewind test, it only slightly weakens rival hypotheses; with hoop tests it somewhat weakens them; with smoking-gun tests it substantially weakens them; and with doubly decisive tests passing eliminates them”
From Understanding Process Tracing (2011) · cites this paper as Bennett 2010
Passing a smoking-gun test substantially weakens rival hypotheses.
“If a given hypothesis passes a straw-in-thewind test, it only slightly weakens rival hypotheses; with hoop tests it somewhat weakens them; with smoking-gun tests it substantially weakens them; and with doubly decisive tests passing eliminates them”
From Understanding Process Tracing (2011) · cites this paper as Bennett 2010
Single tests that accomplish doubly decisive leverage are rare in social science, but this leverage may be achieved by combining multiple tests that together support one explanation and eliminate all others.
“As Bennett (2010, 211) notes, single tests that accomplish this are rare in social science, but this leverage may be achieved by combining multiple tests, which together support one explanation and eliminate all others.”
From Understanding Process Tracing (2011) · cites this paper as Bennett (2010, 211)
Cited by
Sorted by citations
Collier, D. (2011) · PS: Political Science & Politics · doi:10.1017/s1049096511001429 · Cited by 2,238 · see citing works
Broadening the range of designs and methods for impact evaluations
Stern, E., Stame, N., Mayne, J., Forss, K., Davies, R., & Befani, B. (2012) · doi:10.22163/fteval.2012.100 · Cited by 369 · see citing works
Mixing Methods: A Bayesian Approach
HUMPHREYS, M., & JACOBS, A. M. (2015) · American Political Science Review · doi:10.1017/s0003055415000453 · Cited by 198 · see citing works
Befani, B., & Mayne, J. (2014) · IDS Bulletin · doi:10.1111/1759-5436.12110 · Cited by 142 · see citing works
Going Where the Money Is: Strategies for Taxing Economic Elites in Unequal Democracies
Fairfield, T. (2013) · World Development · doi:10.1016/j.worlddev.2013.02.011 · Cited by 134 · see citing works
Smith, A., & Johns, J. (2020) · Journal of Business Ethics · doi:10.1007/s10551-019-04318-1 · Cited by 43 · see citing works
Updating Bayesian(s): A Critical Evaluation of Bayesian Process Tracing
Zaks, S. (2021) · Political Analysis · doi:10.1017/pan.2020.10 · Cited by 24 · see citing works
- Authors
- Bennett, A.
- Corresponding author
- Bennett, Andrew
- ORCID
- Bennett, Andrew
- Venue
- Rethinking Social Inquiry
- Published
- 2010
- Pages
- 207-220
- OpenAlex
- W1938565716
- Cited by
- 415
- References
- 0
- Citations by year
- 2026: 46 · 2025: 11 · 2024: 27 · 2023: 47 · 2022: 38 · 2021: 40 · 2020: 24 · 2019: 41 · 2018: 12 · 2017: 25 · 2016: 26 · 2015: 20 · 2014: 30 · 2013: 12 · 2012: 8
- Type
- other
- Language
- en
- Open access
- closed
- Locations
- PhilSci-Archive (University of Pittsburgh) (acceptedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Qualitative Comparative Analysis Research
- Social Sciences › Political Science and International Relations › Political Science Research and Education
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- process tracing, causal inference, alternative explanations, within-case analysis, case study method, international relations, macro-level analysis, explanation in social science
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
