Learning about Consumption Dynamics
71 Pages Posted: 17 Mar 2010 Last revised: 29 Jan 2016
Date Written: September 15, 2014
This paper characterizes U.S. consumption dynamics from the perspective of a Bayesian agent who does not know the underlying model structure but learns over time from macroeconomic data. Realistic, high-dimensional macroeconomic learning problems, which entail parameter, model, and state learning, generate substantially different subjective beliefs about consumption dynamics compared to the standard, full-information rational expectations benchmark. Beliefs about long-run dynamics are volatile, with counter-cyclical conditional volatility, and drift over time. Embedding these beliefs in a standard asset pricing model significantly improves the model's ability to match the stylized facts, as well as the sample path of the market price-dividend ratio.
JEL Classification: G12
Suggested Citation: Suggested Citation