Infinite Regress Stopping Rules

Abstract

How can social scientists uncover the root causes of contemporary outcomes? Many scholars have assumed that the problem of infinite regress poses a central impediment to this endeavor. However, there have been few attempts to clearly conceptualize infinite regress or offer more than solutions in passing. This article undertakes the challenge, seeking to answer three main questions. First, what is infinite regress? I conceptualize this misunderstood concept as the cycle initiated when assessing the relative weight of proximate versus antecedent causes in a causal chain. Second, how do we weigh causes? I build on Mahoney, Kimball, and Koivu’s “sequence elaboration” method to show how it is best able to do so. Third, when do we stop? I endorse four ‘stopping rules’ and provide examples of each: the ‘necessary and sufficient cause stopping rule,’ the ‘insufficient data stopping rule,’ the ‘theory-driven stopping rule,’ and the ‘mechanism stopping rule.’

Keywords: Infinite Regress, History, Causation, Qualitative Methods, Process-Tracing