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

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  • Bianchi, Francesco
  • Kind, Thilo
  • Kung, Howard

Abstract

We use a high-frequency approach 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 the stock market, breakeven inflation, and spreads linked to the risk of financial instability. VAR evidence shows that the tweets had an important impact on actual monetary policy, the stock market, bond premia, and the macroeconomy.

Suggested Citation

  • Bianchi, Francesco & Kind, Thilo & Kung, Howard, 2019. "Threats to Central Bank Independence: High-Frequency Identification with Twitter," CEPR Discussion Papers 14021, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:14021
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    More about this item

    Keywords

    Central bank independence; Monetary policy; Twitter; Fed funds target; High-frequency identification;
    All these keywords.

    JEL classification:

    • E40 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - General
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior

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