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

70 Pages Posted: 23 Sep 2019 Last revised: 21 May 2023

See all articles by Francesco Bianchi

Francesco Bianchi

Johns Hopkins University; NBER; CEPR

Howard Kung

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

Thilo Kind

London Business School

Multiple version iconThere are 2 versions of this paper

Date Written: September 2019

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.

Suggested Citation

Bianchi, Francesco and Kung, Howard and Kind, Thilo, Threats to Central Bank Independence: High-Frequency Identification with Twitter (September 2019). NBER Working Paper No. w26308, Available at SSRN: https://ssrn.com/abstract=3458233

Francesco Bianchi (Contact Author)

Johns Hopkins University ( email )

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NBER ( email )

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CEPR ( email )

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Howard Kung

London Business School ( email )

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Centre for Economic Policy Research (CEPR) ( email )

London
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Thilo Kind

London Business School ( email )

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

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