Macro-Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models
33 Pages Posted: 26 May 2020 Last revised: 8 Nov 2021
Date Written: August 25, 2021
This paper shows that robust inference under weak identification is important to the evaluation
of many influential macro asset pricing models, including (time-varying) rare-disaster risk
models and long-run risk models. Building on recent developments in the conditional inference
literature, we provide a novel conditional specification test by simulating the critical value
conditional on a sufficient statistic. This sufficient statistic can be intuitively interpreted as
a measure capturing the macroeconomic information decoupled from the underlying content
of asset pricing theories. Macro-finance decoupling is an effective way to improve the power
of the specification test when asset pricing theories are difficult to refute because of a severe
imbalance in the information content about the key model parameters between macroeconomic
moment restrictions and asset pricing cross-equation restrictions. We apply the proposed conditional specification test to the evaluation of a time-varying rare-disaster risk model and the
construction of robust model uncertainty sets.
The supplemental appendix can be found at: https://ssrn.com/abstract=3609598.
The note on additional materials can be found at: https://ssrn.com/abstract=3787125.
Keywords: Conditional inference, Information imbalance, Long-run risk, Rare disasters, Structural asset pricing, Weak identification.
JEL Classification: C12, C32, C52, G12.
Suggested Citation: Suggested Citation