Data and Code for: The Voice of Monetary Policy

Principal Investigator(s):  View help for Principal Investigator(s) Yuriy Gorodnichenko, University of California-Berkeley; Tho Pham, University of Reading; Oleksandr Talavera, University of Birmingham

Version:  View help for Version V1

Name File Type Size Last Modified
  ML 08/22/2022 05:39:AM
  Main 12/05/2022 12:59:PM
FOMC_transcripts.zip application/zip 3.1 MB 12/05/2022 07:55:AM
LICENSE.txt text/plain 689 bytes 12/06/2022 10:00:AM
README.pdf application/pdf 470.2 KB 12/05/2022 07:55:AM

Project Citation: 

Gorodnichenko, Yuriy, Pham, Tho, and Talavera, Oleksandr. Data and Code for: The Voice of Monetary Policy. Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-01-23. https://doi.org/10.3886/E178302V1

Project Description

Summary:  View help for Summary
We develop a deep learning model to detect emotions embedded in press conferences after the Federal Open Market Committee meetings and examine the influence of the detected emotions on financial markets. We find that, after controlling for the Fed’s actions and the sentiment in policy texts, a positive tone in the voices of Fed chairs leads to significant increases in share prices. Other financial variables also respond to vocal cues from the chairs. Hence, how policy messages are communicated can move the financial market. Our results provide implications for improving the effectiveness of central bank communications.

Scope of Project

Subject Terms:  View help for Subject Terms Machine learning
JEL Classification:  View help for JEL Classification
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      E50 Monetary Policy, Central Banking, and the Supply of Money and Credit: General
      G10 General Financial Markets: General (includes Measurement and Data)
Geographic Coverage:  View help for Geographic Coverage US
Time Period(s):  View help for Time Period(s) 2011 – 2019
Data Type(s):  View help for Data Type(s) aggregate data; audio: sound data; observational data; program source code; text


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Published Versions

V1 [2023-01-23]

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