Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle

No 2005-005, Working Papers from Federal Reserve Bank of St. Louis

Abstract: In the presence of infrequent but observable structural breaks, we show that a model in which the representative agent is on a rational learning path concerning the real consumption growth process can generate high equity premia and low risk-free interest rates. In fact, when the model is calibrated to U.S. consumption growth data, average risk premia and bond yields similar to those displayed by post- depression (1938-1999) U.S. historical experience are generated for low levels of risk aversion. Even ruling out pessimistic beliefs, recursive learning inflates the equity premium without requiring a strong curvature of the utility function. Simulations reveal that other moments of equilibrium asset returns are easily matched, chiefly excess volatility and the presence of ARCH effects. These findings are robust to a number of details of the simulation experiments, such as the number and dating of the breaks.

Keywords: Assets (Accounting); Rational expectations (Economic theory) (search for similar items in EconPapers)
Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Published in Journal of Economics and Business, March-April 2006, 58(2), pp. 85-118

Downloads: (external link)
http://research.stlouisfed.org/wp/2005/2005-005.pdf (application/pdf)

Related works:
Journal Article: Pessimistic beliefs under rational learning: Quantitative implications for the equity premium puzzle (2006)
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:fip:fedlwp:2005-005

Ordering information: This working paper can be ordered from

Access Statistics for this paper

More papers in Working Papers from Federal Reserve Bank of St. Louis Contact information at EDIRC.
Bibliographic data for series maintained by Anna Oates ().