Federal Reserve Communication and the COVID-19 Pandemic

• URL: http://arxiv.org/abs/2508.04830v1
• Date: Wed, 06 Aug 2025 19:17:24 GMT
• Title: Federal Reserve Communication and the COVID-19 Pandemic
• Authors: Jonathan Benchimol, Sophia Kazinnik, Yossi Saadon,
• Abstract summary: We identify a distinct focus in Fed communication during the pandemic on financial stability, market volatility, social welfare, and unconventional monetary policy (UMP)<n>Our findings reveal that Fed communication and policy actions were more reactive to the COVID-19 crisis than to previous crises.<n>We further document that communicating about UMP has become the "new normal" for the Fed's Federal Open Market Committee meeting minutes and Chairman's speeches since the Global Financial Crisis.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this study, we examine the Federal Reserve's communication strategies during the COVID-19 pandemic, comparing them with communication during previous periods of economic stress. Using specialized dictionaries tailored to COVID-19, unconventional monetary policy (UMP), and financial stability, combined with sentiment analysis and topic modeling techniques, we identify a distinct focus in Fed communication during the pandemic on financial stability, market volatility, social welfare, and UMP, characterized by notable contextual uncertainty. Through comparative analysis, we juxtapose the Fed's communication during the COVID-19 crisis with its responses during the dot-com and global financial crises, examining content, sentiment, and timing dimensions. Our findings reveal that Fed communication and policy actions were more reactive to the COVID-19 crisis than to previous crises. Additionally, declining sentiment related to financial stability in interest rate announcements and minutes anticipated subsequent accommodative monetary policy decisions. We further document that communicating about UMP has become the "new normal" for the Fed's Federal Open Market Committee meeting minutes and Chairman's speeches since the Global Financial Crisis, reflecting an institutional adaptation in communication strategy following periods of economic distress. These findings contribute to our understanding of how central bank communication evolves during crises and how communication strategies adapt to exceptional economic circumstances.

Related papers

• Can We Reliably Predict the Fed's Next Move? A Multi-Modal Approach to U.S. Monetary Policy Forecasting [2.6396287656676733]
  This study examines whether predictive accuracy can be enhanced by integrating structured data with unstructured textual signals from Federal Reserve communications.<n>Our results show that hybrid models consistently outperform unimodal baselines.<n>For monetary policy forecasting, simpler hybrid models can offer both accuracy and interpretability, delivering actionable insights for researchers and decision-makers.
  arXiv  Detail & Related papers  (2025-06-28T05:54:58Z)
• Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets [53.0367886783772]
  Labor markets are affected by the economic forces of adverse selection, moral hazard, and reputation.<n>Agents must use metacognitive and strategic reasoning to perform effectively.
  arXiv  Detail & Related papers  (2025-05-26T15:22:04Z)
• BICompFL: Stochastic Federated Learning with Bi-Directional Compression [70.37629026426104]
  We address the prominent communication bottleneck in federated learning (FL)<n>We show that bi-directional compression for FL has inherent challenges, which we address by BICompFL.<n>Our BICompFL is experimentally shown to reduce the communication cost by an order of magnitude compared to multiple benchmarks, while maintaining state-of-the-art accuracies.
  arXiv  Detail & Related papers  (2025-01-31T22:48:43Z)
• Temporal Relational Reasoning of Large Language Models for Detecting Stock Portfolio Crashes [46.259921167692895]
  We propose an algorithmic framework named Temporal Reasoning (TRR) TRR seeks to emulate the spectrum of human cognitive capabilities used for complex problem-solving. We show that TRR is able to outperform state-of-the-art solutions on detecting stock portfolio crashes.
  arXiv  Detail & Related papers  (2024-10-07T11:15:52Z)
• FMPAF: How Do Fed Chairs Affect the Financial Market? A Fine-grained Monetary Policy Analysis Framework on Their Language [3.760301720305374]
  We propose the Fine-Grained Monetary Policy Analysis Framework (FMPAF), a novel approach that integrates large language models (LLMs) with regression analysis. Based on our preferred specification, a one-unit increase in the sentiment score is associated with an increase of the price of S&P 500 Exchange-Traded Fund.
  arXiv  Detail & Related papers  (2024-03-10T07:21:31Z)
• Evolution of Neural Architectures for Financial Forecasting: A Note on Data Incompatibility during Crisis Periods [0.0]
  This study aims to investigate whether the training data from market dynamics prior to the crisis are compatible with the data during the crisis period. Two distinct learning environments are designed to evaluate and reconcile the effects of possibly different market dynamics. To test the hypothesis of pre-crisis data incompatibility, the day-ahead movement prediction of the NASDAQ index is considered during two recent and major market disruptions.
  arXiv  Detail & Related papers  (2023-11-24T16:49:35Z)
• Analysis of the Fed's communication by using textual entailment model of Zero-Shot classification [0.0]
  We analyze documents published by central banks using text mining techniques. We compare the tone of the statements, minutes, press conference transcripts of meetings, and the Fed officials' speeches.
  arXiv  Detail & Related papers  (2023-06-07T09:23:26Z)
• Hallucinated Adversarial Control for Conservative Offline Policy Evaluation [64.94009515033984]
  We study the problem of conservative off-policy evaluation (COPE) where given an offline dataset of environment interactions, we seek to obtain a (tight) lower bound on a policy's performance. We introduce HAMBO, which builds on an uncertainty-aware learned model of the transition dynamics. We prove that the resulting COPE estimates are valid lower bounds, and, under regularity conditions, show their convergence to the true expected return.
  arXiv  Detail & Related papers  (2023-03-02T08:57:35Z)
• Distributed Adaptive Learning Under Communication Constraints [54.22472738551687]
  This work examines adaptive distributed learning strategies designed to operate under communication constraints. We consider a network of agents that must solve an online optimization problem from continual observation of streaming data.
  arXiv  Detail & Related papers  (2021-12-03T19:23:48Z)
• Who shapes crisis communication on Twitter? An analysis of influential German-language accounts during the COVID-19 pandemic [0.0]
  This study identifies influential German-language accounts from almost 3 million German tweets collected between January and May 2020. We discuss implications for crisis communication during health crises and for analyzing long-term crisis data.
  arXiv  Detail & Related papers  (2021-09-12T11:33:34Z)
• When a crisis strikes: Emotion analysis and detection during COVID-19 [96.03869351276478]
  We present CovidEmo, 1K tweets labeled with emotions. We examine how well large pre-trained language models generalize across domains and crises.
  arXiv  Detail & Related papers  (2021-07-23T04:07:14Z)
• When Wireless Communication Faces COVID-19: Combating the Pandemic and Saving the Economy [93.08344893433639]
  The year 2020 is experiencing a global health and economic crisis due to the COVID-19 pandemic. Countries across the world are using digital technologies to fight this global crisis. We show how these technologies are helping to combat this pandemic, including monitoring of the virus spread. We discuss the challenges faced by wireless technologies, including privacy, security, and misinformation.
  arXiv  Detail & Related papers  (2020-05-12T12:27:29Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.