Threats to Central Bank Independence: High-Frequency Identification with Twitter
51 Pages Posted: 7 Oct 2019 Last revised: 13 Jan 2020
There are 2 versions of this paper
Threats to Central Bank Independence: High-Frequency Identification with Twitter
Date Written: September 2019
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.
Keywords: central bank independence, fed funds target, High-Frequency Identification, monetary policy, Twitter
JEL Classification: D72, E40, E50
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Threats to Central Bank Independence: High-Frequency Identification with Twitter
This is a CEPR Discussion Paper. CEPR charges a fee of $8.00 for this paper.
If you wish to purchase the right to make copies of this paper for distribution to others, please select the quantity.
