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Econometrica Vol. 90 No. 2 2022

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

Xu Cheng1; Winston Wei Dou2; Zhipeng Liao3

1 Department of Economics, University of Pennsylvania · 2 Finance Department, The Wharton School, University of Pennsylvania · 3 Department of Economics, University of California–Los Angeles.

Abstract

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.

DOI
10.3982/ecta18506
Volume
90
Issue
2
Pages
685-713
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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