Measuring the 'Dark Matter' in Asset Pricing Models
83 Pages Posted: 19 Sep 2013 Last revised: 18 Sep 2019
Date Written: September 9, 2019
We introduce an information-based fragility measure for GMM models that are potentially misspecified and unstable. A high fragility measure reflects a model's lack of internal refutability (weak power of specification tests) and external validity (poor out-of-sample fit). The fragility of a set of model-implied moment restrictions is tightly linked to how much more the econometrician can learn about the model parameters by imposing these restrictions. Our fragility measure can be computed at little cost even for complex dynamic structural models. We illustrate its applications in a rare-disaster risk model and a long-run risk model.
Keywords: Fragile beliefs, Unstable models, Misspecification, Time series, Out-of-sample fit, Disaster risk, Long-run risk, Semiparametric efficiency
JEL Classification: C52, G12, D81, E32
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