We formalize the concept of "dark matter" in asset pricing models by quantifying the additional informativeness of cross-equation restrictions about fundamental dynamics.The dark matter measure captures the degree of fragility for models that are potentially misspecified and unstable: a large dark matter measure signifies that the model lacks internal refutability (weak power of optimal specification tests) and external validity (high overfitting tendency and poor out-ofsample fit).The measure can be computed at low cost even for complex dynamic structural models.To illustrate its applications, we provide quantitative examples applying the measure to (time-varying) rare-disaster risk and long-run risk models.
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