News-driven uncertainty fluctuations

Arbeitspapier

We embed a news shock, a noisy indicator of the future state, in a two-state Markovswitching growth model. Our framework, combined with parameter learning, features rich history-dependent uncertainty dynamics. We show that bad news that arrives during a prolonged economic boom can trigger a "Minsky moment" - a sudden collapse in asset values. The effect is greatly amplified when agents have a preference for early resolution of uncertainty. We leverage survey recession probability forecasts to solve a sequential learning problem and estimate the full posterior distribution of model primitives. We identify historical periods in which uncertainty and risk premia were elevated because of news shocks.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Working Papers ; No. 18-3

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Bayesian Analysis: General ; Asset Pricing; Trading Volume; Bond Interest Rates ; Business Fluctuations; Cycles ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
• Thema: Bayesian learning ; discrete environment ; Minsky moment ; news shocks ; recursive utility ; risk premium ; survey forecasts ; uncertainty

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Song, Dongho ; Tang, Jenny
• Ereignis: Veröffentlichung
• (wer): Federal Reserve Bank of Boston
• (wo): Boston, MA
• (wann): 2018

Weitere Informationen

• Handle: http://hdl.handle.net/10419/202919
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ