Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/253501 
Year of Publication: 
2021
Citation: 
[Journal:] Theoretical Economics [ISSN:] 1555-7561 [Volume:] 16 [Issue:] 1 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2021 [Pages:] 275-315
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
We provide a production-based asset pricing model with dispersed information and small deviations from full rational expectations. In the model, aggregate output and equity prices depend on the higher-order beliefs about aggregate demand and individual stochastic discount factors. We prove that equity price volatility becomes arbitrarily large as the volatility of idiosyncratic shocks diverges to infinity due to the interaction of signal-extraction with idiosyncratic trading decisions, while aggregate output volatility falls. We propose a two-step spectral factorization method that permits closed-form solutions in the frequency domain applicable to a wide range of models with more hidden states than signals. Our model can quantitatively match output and equity volatilities observed in US data.
Subjects: 
Dispersed information
frequency domain analysis
higher-order beliefs
asset pricing
business cycles
incomplete markets
JEL: 
E32
E44
G12
G14
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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