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Modeling the Evolution of Expectations and Uncertainty in General Equilibrium
We develop methods to solve general equilibrium models in which forward-looking agents are subject to waves of pessimism, optimism, and uncertainty that turn out to critically affect macroeconomic outcomes. Agents in the model are fully rational, conduct Bayesian learning, and they know that they do not know. Therefore, agents take into account that their beliefs will evolve according to what they will observe. This framework accommodates both gradual and abrupt changes in beliefs and allows for an analytical characterization of uncertainty. Shocks to beliefs affect economic dynamics and ...
Learning, Rare Disasters, and Asset Prices
In this paper, we examine how learning about disaster risk affects asset pricing in an endowment economy. We extend the literature on rare disasters by allowing for two sources of uncertainty: (1) the lack of historical data results in unknown parameters for the disaster process, and (2) the disaster takes time to unfold and is not directly observable. The model generates time variation in the risk premium through Bayesian updating of agents' beliefs regarding the likelihood and severity of disaster realization. The model accounts for the level and volatility of U.S. equity returns and ...
A Likelihood-Based Comparison of Macro Asset Pricing Models
We estimate asset pricing models with multiple risks: long-run growth, long-run volatility, habit, and a residual. The Bayesian estimation accounts for the entire likelihood of consumption, dividends, and the price-dividend ratio. We find that the residual represents at least 80% of the variance of the price-dividend ratio. Moreover, the residual tracks most recognizable features of stock market history such as the 1990's boom and bust. Long run risks and habit contribute primarily in crises. The dominance of the residual comes from the low correlation between asset prices and consumption ...