Explicit Bayesian analysis for process tracing: guidelines, opportunities, and caveats

Tasha Fairfield and Andrew Charman

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Bayesian probability holds the potential to serve as an important bridge between qualitative and quantitative methodology. Yet whereas Bayesian statistical techniques have been successfully elaborated for quantitative research, applying Bayesian probability to qualitative research remains an open frontier. This paper advances the burgeoning literature on Bayesian process tracing by drawing on expositions of Bayesian “probability as extended logic” from the physical sciences, where probabilities represent rational degrees of belief in propositions given the inevitably limited information we possess. We provide step-by-step guidelines for explicit Bayesian process tracing, calling attention to technical points that have been overlooked or inadequately addressed, and we illustrate how to apply this approach with the first systematic application to a case study that draws on multiple pieces of detailed evidence. While we caution that efforts to explicitly apply Bayesian learning in qualitative social science will inevitably run up against the difficulty that probabilities cannot be unambiguously specified, we nevertheless envision important roles for explicit Bayesian analysis in pinpointing the locus of contention when scholars disagree on inferences, and in training intuition to follow Bayesian probability more systematically.

JEL-codes: C1 (search for similar items in EconPapers)
Date: 2017-07-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Published in Political Analysis, 1, July, 2017, 25(3), pp. 363 - 380. ISSN: 1047-1987

Downloads: (external link)
http://eprints.lse.ac.uk/69203/ Open access version. (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:69203

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().