Causal Explanation with Ideal Types: Opportunities for Comparative Area Studies

Ryan Saylor, University of Tulsa

Making comparisons across different world regions often contravenes the conventional wisdom on case selection. In response, a burgeoning approach contends that researchers can make such comparisons through the use of comparative area studies (e.g., the edited volume "Comparative Area Studies," Oxford University Press, 2018). The comparative area studies initiative challenges researchers to undertake cross-regional research while remaining sensitive to contextual nuance within and between different world regions. This paper argues that this goal can best be met by using Weberian ideal types. This epistemic approach, by its design, forces researchers to distill causal claims into ideal-typical statements while also identifying factors that are not part of the ideal type but that influenced the outcome in a particular case. Ideal-typical statements resemble what many of us think of as good theorizing. The determination of the factors pertinent to a case-specific outcome but extraneous to the ideal type prompts us to weigh and adjust for context. Using ideal types assists scholars wanting to elevate contextual considerations as fundamental features of cross-regional research. The paper advances this argument by: (1) describing what ideal types are; (2) showing how ideal types are useful for achieving causal explanation; (3) providing practical guidance for building and using ideal types; and (4) illustrating their vitality through two seminal works—one from sociology, the other from political science—that have had lasting influence on their fields. Using ideal types for causal explanation is a robust epistemic approach for researchers interested in making macro-structural comparative historical comparisons.

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 Presented in Session 195. New Frontiers in Social Science Historical Methods