Learning about consumption dynamics

• Autores: Michael Johannes, Lars A. Lochstoer, Yiqun Mou
• Localización: The Journal of finance, ISSN 0022-1082, Vol. 71, Nº 2, 2016, págs. 551-600
• Idioma: inglés
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• Resumen

  • 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.