Marco Cagetti (University of Virginia) Lars Peter Hansen (University of Chicago) Thomas Sargent (Stanford University) Noah Williams (Princeton University)
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We study how decision-makers' concerns about robustness affect prices and quantities in a stochastic growth model. In the model economy, growth rates in technology are altered by infrequent large shocks and continuous small shocks. An investor observes movements in the technology level but cannot perfectly distinguish their sources. Instead the investor solves a signal extraction problem. We depart from most of the macroeconomics and finance literature by presuming that the investor treats the specification of technology evolution as an approximation. To promote a decision rule that is robust to model misspecification, an investor acts as if a malevolent player threatens to perturb the actual data-generating process relative to his approximating model. We study how a concern about robustness alters asset prices. We show that the dynamic evolution of the risk-return trade-off is dominated by movements in the growth-state probabilities and that the evolution of the dividend-price ratio is driven primarily by the capital-technology ratio. Copyright 2002, Oxford University Press.
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Article provided by Oxford University Press for Society for Financial Studies in its journal Review of Financial Studies.
Volume (Year): 15 (2002) Issue (Month): 2 (March) Pages: 363-404 Download reference. The following formats are available: HTML,
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Larry Epstein & Martin Schneider, 2002.
"Learning Under Ambiguity,"
RCER Working Papers
497, University of Rochester - Center for Economic Research (RCER), revised Mar 2005.
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