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Summary

We connect the literature on causal models to qualitative inference strategies used in process tracing. The chapter outlines a procedure for drawing case-level causal inferences from a causal model and within-case evidence. We also show how a key result from the causal-models literature provides a condition for when the observation of a node in a causal model (a “clue”) may be (or certainly will not be) informative, and we extract a set of implications for process-tracing methods.

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We apply the causal-model-based approach to process tracing to two major substantive issues in comparative politics: the relationship between inequality and democratization and the relationship between institutions and growth. Drawing on case-level data, we use qualitative restrictions on causal types together with flat priors to draw inferences about a range of causal queries. The applications illustrate the different types of learning that can be gleaned from information on moderators and mediators, as well as the scope for learning from historical data when researchers have informative beliefs about confounding processes.

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7 - Process Tracing with Causal Models

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8 - Process-Tracing Applications

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2 results

7 - Process Tracing with Causal Models

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8 - Process-Tracing Applications

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