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

Author

Listed:
  • 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.

Suggested Citation

  • Francesco Bianchi & Thilo Kind & Howard Kung, 2019. "Threats to Central Bank Independence: High-Frequency Identification with Twitter," NBER Working Papers 26308, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:26308
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    More about this item

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G1 - Financial Economics - - General Financial Markets

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