| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w26308 |
| 来源ID | Working Paper 26308 |
| Threats to Central Bank Independence: High-Frequency Identification with Twitter | |
| Francesco Bianchi; Thilo Kind; Howard Kung | |
| 发表日期 | 2019-09-23 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | 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. |
| 主题 | Macroeconomics ; Monetary Policy ; Financial Economics ; Financial Markets |
| URL | https://www.nber.org/papers/w26308 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/583980 |
| 推荐引用方式 GB/T 7714 | Francesco Bianchi,Thilo Kind,Howard Kung. Threats to Central Bank Independence: High-Frequency Identification with Twitter. 2019. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w26308.pdf（736KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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