Working Paper: NBER ID: w26308
Authors: Francesco Bianchi; Thilo Kind; Howard Kung
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.
Keywords: Central Bank Independence; Monetary Policy; Political Pressure; Financial Markets
JEL Codes: E52; E58; G1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Trump's tweets criticizing the Federal Reserve (E52) | expected federal funds rate (FFR) (E52) |
| cumulative effect of Trump's tweets (D79) | expected federal funds rate (FFR) (E52) |
| Trump's tweets (Y60) | stock prices (G12) |
| Trump's tweets (Y60) | long-term U.S. Treasury yields (E43) |
| Trump's tweets (Y60) | revisions in expectations regarding monetary policy (E52) |
| Trump's tweets (Y60) | perception of Federal Reserve's autonomy (E58) |
| negative tweet shocks (D91) | shadow FFR (Y50) |
| negative tweet shocks (D91) | stock prices (G12) |
| inflation and GDP (E31) | response to Trump's tweets (F59) |