DP14021 Threats to Central Bank Independence: High-Frequency Identification with Twitter

Author(s): Francesco Bianchi, Thilo Kind, Howard Kung
Publication Date: September 2019
Date Revised: January 2020
Keyword(s): central bank independence, fed funds target, High-Frequency Identification, monetary policy, Twitter
JEL(s): D72, E40, E50
Programme Areas: Financial Economics, Monetary Economics and Fluctuations
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=14021

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.