Threats to Central Bank Independence: High-Frequency Identification with Twitter

64 Pages Posted: 7 Oct 2019 Last revised: 22 Sep 2021

See all articles by Francesco Bianchi

Francesco Bianchi

Johns Hopkins University; NBER; CEPR

Thilo Kind

London Business School

Howard Kung

London Business School; Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 2 versions of this paper

Date Written: September 2019

Abstract

We use a high-frequency approach 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 the stock market, breakeven inflation, and spreads linked to the risk of financial instability. VAR evidence shows that the tweets had an important impact on actual monetary policy, the stock market, bond premia, and the macroeconomy.

Keywords: central bank independence, fed funds target, High-Frequency Identification, monetary policy, Twitter

JEL Classification: D72, E40, E50

Suggested Citation

Bianchi, Francesco and Kind, Thilo and Kung, Howard, Threats to Central Bank Independence: High-Frequency Identification with Twitter (September 2019). CEPR Discussion Paper No. DP14021, Available at SSRN: https://ssrn.com/abstract=3464551

Francesco Bianchi (Contact Author)

Johns Hopkins University ( email )

Baltimore, MD 20036-1984
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NBER ( email )

1050 Massachusetts Avenue
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CEPR ( email )

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Thilo Kind

London Business School ( email )

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London, London NW1 4SA
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Howard Kung

London Business School ( email )

Sussex Place
Regent's Park
London NW1 4SA
United Kingdom

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

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