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Many consumption-based models succeed in matching long lists of asset price moments. We propose an alternative, full-information Bayesian evaluation that decomposes the price-dividend ratio (p/d) into contributions from long-run risks, habit, and a residual. We find that long-run risks account for less than 25% of the variance of p/d and that habit’s contribution is negligible. This result is robust to the prior, including priors that assume long-run risks in consumption and highly persistent habit. However, the residual mostly tracks decades-long movements in p/d. At business cycle frequency, long-run risks explain about 70% of the movements of p/d while habit’s contribution stays negligible.
Keywords:
Long run risks,
Rare disasters,
Habit,
Bayesian estimation,
Particle filter,
Time-varying beliefs,
Time-varying preferences,
Excess volatility,
G10,
G12,
E21,
E30,
E44,
C11,
C15
© 2021 Andrew Y. Chen, Fabian Winkler and Rebecca Wasyk
2021
Andrew Y. Chen, Fabian Winkler and Rebecca Wasyk
Licensed re-use rights only
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