Transparency and deliberation within the FOMC: a computational linguistics approach

Stephen Hansen, Michael McMahon and Andrea Prat

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: How does transparency, a key feature of central bank design, affect the deliberation of monetary policymakers? We exploit a natural experiment in the Federal Open Market Committee in 1993 together with computational linguistic models (particularly Latent Dirichlet Allocation) to measure the effect of increased transparency on debate. Commentators have hypothesized both a beneficial discipline effect and a detrimental conformity effect. A difference-in-differences approach inspired by the career concerns literature uncovers evidence for both effects. However, the net effect of increased transparency appears to be a more informative deliberation process.

Keywords: Monetary policy; deliberation; FOMC; transparency; career concerns (search for similar items in EconPapers)
JEL-codes: D78 E52 E58 (search for similar items in EconPapers)
Pages: 56 pages
Date: 2014-06
New Economics Papers: this item is included in nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (49)

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http://eprints.lse.ac.uk/60287/ Open access version. (application/pdf)

Related works:
Journal Article: Transparency and Deliberation Within the FOMC: A Computational Linguistics Approach (2018)
Working Paper: Transparency and Deliberation within the FOMC: a Computational Linguistics Approach (2015)
Working Paper: Transparency and Deliberation within the FOMC: A Computational Linguistics Approach (2014)
Working Paper: Transparency and Deliberation within the FOMC: a Computational Linguistics Approach (2014)
Working Paper: Transparency and Deliberation within the FOMC: a Computational Linguistics Approach (2014)
Working Paper: Transparency and deliberation within the FOMC: a computational linguistics approach (2014)
Working Paper: Transparency and deliberation within the FOMC: A computational linguistics approach (2014)
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