Econometrica: Mar 2022, Volume 90, Issue 2

Macro-Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models

https://doi.org/10.3982/ECTA18506
p. 685-713

Xu Cheng, Winston Wei Dou, Zhipeng Liao

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.



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Supplemental Material

Supplement to "Macro-Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models"

This zip file contains the replication files for the manuscript.  There is also an additional supplemental appendix.

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Supplement to "Macro-Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models"

This supplemental appendix provides the following supporting materials. Sections SA – SC provide the proofs of Lemmas A1 – A7 in the appendix to the main text Cheng, Dou, and Liao (2021). Section SA provides the proofs of several lemmas on the asymptotic convergence of the random components in the test statistic T and the conditional critical value cα( ˆd). Section SB verifies the bounded Lipschitz properties of the test statistic and the conditional critical value, which are used to show their weak convergence in large samples. Section SC includes some auxiliary lemmas. Section SD provides additional theoretical results on the power of the proposed conditional test. Section SE provides comparison with some power envelopes through simulations. Section SF collects details and additional results of the empirical application.

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