Department of Political Science

TY - JOUR

T1 - Selecting appropriate cases when tracing causal mechanisms

AU - Beach, Derek

AU - Pedersen, Rasmus Brun

PY - 2018

Y1 - 2018

N2 - The last decade has witnessed resurgence in the interest in studying the causal mechanisms linking causes and outcomes in the social sciences. This article explores the overlooked implications for case selection when tracing mechanisms using in-depth case studies. Our argument is that existing case selection guidelines are appropriate for research aimed at making cross-case claims about causal relationships, where case selection is primarily used to control for other causes. However, existing guidelines are not in alignment with case-based research that aims to trace mechanisms, where the goal is to unpack the causal mechanism between X and Y, enabling causal inferences to be made because empirical evidence is provided for how the mechanism actually operated in a particular case. The in-depth, within-case tracing of how mechanisms operate in particular cases produces what can be termed mechanistic evidence, which can be contrasted to difference-making evidence that are produced by variance-based, experimental designs.The article proceeds in three steps. We first develop the underlying assumptions of studying mechanisms using case-based methods, focusing on mechanisms understood as systems, ontological determinism, causal asymmetry and causal homogeneity and the importance of context. We then develop a set of case selection guidelines that are in methodological alignment with these underlying assumptions. Section 4 develops guidelines for research where the mechanism is the primary focus, contending that only typical cases where both X, Y and the requisite contextual conditions are present should be selected. We compare our guidelines with the existing, finding that practices like selecting most/least-likely cases are not compatible with the underlying assumptions of tracing mechanisms. Section 5 present guidelines for deviant cases, focusing on tracing mechanisms until they breakdown as a tool to shed light on omitted contextual and/or causal conditions.

AB - The last decade has witnessed resurgence in the interest in studying the causal mechanisms linking causes and outcomes in the social sciences. This article explores the overlooked implications for case selection when tracing mechanisms using in-depth case studies. Our argument is that existing case selection guidelines are appropriate for research aimed at making cross-case claims about causal relationships, where case selection is primarily used to control for other causes. However, existing guidelines are not in alignment with case-based research that aims to trace mechanisms, where the goal is to unpack the causal mechanism between X and Y, enabling causal inferences to be made because empirical evidence is provided for how the mechanism actually operated in a particular case. The in-depth, within-case tracing of how mechanisms operate in particular cases produces what can be termed mechanistic evidence, which can be contrasted to difference-making evidence that are produced by variance-based, experimental designs.The article proceeds in three steps. We first develop the underlying assumptions of studying mechanisms using case-based methods, focusing on mechanisms understood as systems, ontological determinism, causal asymmetry and causal homogeneity and the importance of context. We then develop a set of case selection guidelines that are in methodological alignment with these underlying assumptions. Section 4 develops guidelines for research where the mechanism is the primary focus, contending that only typical cases where both X, Y and the requisite contextual conditions are present should be selected. We compare our guidelines with the existing, finding that practices like selecting most/least-likely cases are not compatible with the underlying assumptions of tracing mechanisms. Section 5 present guidelines for deviant cases, focusing on tracing mechanisms until they breakdown as a tool to shed light on omitted contextual and/or causal conditions.

U2 - 10.1177/0049124115622510

DO - 10.1177/0049124115622510

M3 - Journal article

VL - 47

SP - 837

EP - 871

JO - Sociological Methods & Research

JF - Sociological Methods & Research

SN - 0049-1241

IS - 4

ER -