In the Fed we Trust? Measuring Trust in Central Banking and its Effects on the Macroeconomy

David Aikman, Francesca Monti and Shunshun Zhang

No 19811, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: We develop a novel measure of trust in the Federal Reserve using Generative Artificial Intelligence to analyse millions of tweets about the Fed, its leadership and its policy framework and decisions. Our measure reacts in an intuitive way to various macro-financial variables and indicators of U.S. monetary policy. To study the effects of trust shocks, we use a narrative identification approach based on ethical scandals embroiling some FOMC members, and we study the effects of these shocks using a daily VAR. We find that trust shocks have highly persistent effects on macroeconomic variables despite having short-lived effects on our trust measure: they weaken business conditions, the stock market and news sentiment, while increasing the VIX index. Inflation expectations also increase following a trust shock, worsening the inflation-output trade-off.

Keywords: Trust; Narrative identification; Central banks (search for similar items in EconPapers)
JEL-codes: D83 D84 E52 E58 (search for similar items in EconPapers)
Date: 2024-12
References: Add references at CitEc
Citations:

Downloads: (external link)
https://cepr.org/publications/DP19811 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:19811

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP19811

Access Statistics for this paper

More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK.
Bibliographic data for series maintained by CEPR ().