Threats to central bank independence: High-frequency identification with twitter

Bianchi, F, Gomez Cram, R, Kind, T and Kung, H (2023) Threats to central bank independence: High-frequency identification with twitter. Journal of Monetary Economics, 135. pp. 37-54. ISSN 0304-3932

Abstract

A high-frequency approach is used to analyze the effects of President Trump’s tweets that criticize the Federal Reserve on financial markets. Identification exploits a short time window around the precise timestamp for each tweet. The average effect on the expected fed funds rate is negative and statistically significant, with the magnitude growing by horizon. The tweets also lead to an increase in stock prices and to a decrease in long-term U.S. Treasury yields. VAR evidence shows that the tweets had an important impact on actual monetary policy, the stock market, bond premia, and the macroeconomy.

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Item Type: Article
Subject Areas: Finance
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© 2023 Elsevier B.V.

Date Deposited: 18 Jan 2023 12:20
Date of first compliant deposit: 06 Apr 2023
Subjects: Central banks
Asset valuation
Social media
Last Modified: 29 Feb 2024 02:38
URI: https://lbsresearch.london.edu/id/eprint/2777
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