Threats to central bank independence: High-frequency identification with twitter

• 成果类型: Article
• 署名作者: Bianchi, Francesco; Gomez-Cram, Roberto; Kind, Thilo; Kung, Howard
• 署名单位: Johns Hopkins University; National Bureau of Economic Research; Center for Economic & Policy Research (CEPR); University of London; London Business School
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/j.jmoneco.2023.01.001
• 发表日期: 2023
• 页码: 37-54
• 关键词: High-frequency identification; Social media; asset prices; Fed funds rate; Central bank independence

摘要

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. (c) 2023 Elsevier B.V. All rights reserved.