Mechanisms, Bayesianism, and process tracing

This essay examines the role of mechanisms and Bayesian inference in process tracing. With respect to mechanisms, I argue that the core of process tracing with causal inference is the identification of mechanisms understood as intervening events. Events are different from standard intervening variables when used with process tracing, because events are treated as sets in which cases can have membership. With respect to Bayesian analysis, I concur with recent writings that suggest Bayesian inference is at the heart of process tracing. The Bayesian nature of process tracing explains why it is inappropriate to view qualitative research as suffering from a small-N problem and certain standard causal identification problems. More generally, the paper shows how the power of process tracing as a qualitative methodology depends on and grows from its set-theoretic underpinnings.