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

Author(s): Francesco Bianchi, Thilo Kind, Howard Kung
Publication Date: September 2019
Keyword(s): central bank independence, fed funds target, High-Frequency Identification, monetary policy, Twitter
JEL(s): E52, E58, G1
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 a cumulative effect of around negative 10 bps. Therefore, we provide evidence that market participants believe that the Fed will succumb to the political pressure, which poses a significant threat to central bank independence.