Transparency and Deliberation within the FOMC: a Computational Linguistics Approach

Abstract

How does transparency, a key feature of central bank design, affect monetary policymakers’ deliberations? We answer this question with a natural experiment in the Federal Open Market Committee in 1993 and computational linguistics algorithms. Theory predicts a positive discipline effect and negative conformity effect. We first find large behavioural responses to transparency. We then propose a difference-in-differences approach inspired by the career concerns literature, and find evidence for both effects. Finally, we use an influence measure that suggests the positive effect dominates.