Citation

Discussion Paper Details

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Full Details

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

Author(s): Francesco Bianchi, Thilo Kind and Howard Kung

Publication Date: September 2019

Keyword(s): central bank independence, fed funds target, High-Frequency Identification, monetary policy and Twitter

Programme Area(s): Financial Economics and Monetary Economics and Fluctuations

Abstract: This paper presents market-based evidence that President Trump influences expectations about monetary policy. The main estimates use tick-by-tick fed funds futures data and a large collection of Trump tweets criticizing the conduct of monetary policy. These collected tweets consistently advocate that the Fed lowers interest rates. Identification in our high-frequency event study exploits a small time window around the precise time stamp for each tweet. The average effect of these tweets on the expected fed funds rate is strongly statistically significant and negative, with an average cumulative effect of around -10 bps with a peak of -18.5 bps at the longest horizon. Therefore, we provide evidence that market participants do not perceive the Fed as a fully independent institution.

For full details and related downloads, please visit: https://cepr.org/active/publications/discussion_papers/dp.php?dpno=14021

Bibliographic Reference

Bianchi, F, Kind, T and Kung, H. 2019. 'Threats to Central Bank Independence: High-Frequency Identification with Twitter'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=14021