Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: The bias in two-pass regression tests of asset-pricing models in presence of idiosyncratic errors with cross-sectional dependence
Authors: Gramespacher, Thomas
Bänziger, Armin
et. al: No
DOI: 10.1142/S0219091519500127
Published in: Review of Pacific Basin Financial Markets and Policies
Volume(Issue): 22
Issue: 2
Issue Date: 2019
Publisher / Ed. Institution: World Scientific Publishing
ISSN: 0219-0915
Language: English
Subjects: Asset pricing; Error in variable; Simulation; Idiosyncratic risk
Subject (DDC): 332: Financial economics
Abstract: In two-pass regression-tests of asset-pricing models, cross-sectional correlations in the errors of the first-pass time-series regression lead to correlated measurement errors in the betas used as explanatory variables in the second-pass cross-sectional regression. The slope estimator of the second-pass regression is an estimate for the factor risk-premium and its significance is decisive for the validity of the pricing model. While it is well known that the slope estimator is downward biased in presence of uncorrelated measurement errors, we show in this paper that the correlations seen in empirical return data substantially suppress this bias. For the case of a single-factor model, we calculate the bias of the OLS slope estimator in the presence of correlated measurement errors with a first-order Taylor-approximation in the size of the errors. We show that the bias increases with the size of the errors, but decreases the more the errors are correlated. We illustrate and validate our result using a simulation approach based on empirical data commonly used in asset-pricing tests.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Management and Law
Organisational Unit: Institute of Wealth & Asset Management (IWA)
Appears in Collections:Publikationen School of Management and Law

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