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RFS Advance Access published online on June 13, 2008
Review of Financial Studies, doi:10.1093/rfs/hhn056
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© The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Multiple-Predictor Regressions: Hypothesis Testing

Yakov Amihud
New York University

Clifford M. Hurvich
New York University

Yi Wang
New York University

Address correspondence to Ira Leon Rennert, Professor of Finance, Stern School of Business, New York University, New York, NY 10012; telephone: 212-998-0720; fax: 212-995-4220; e-mail: yamihud{at}stern.nyu.edu.

JEL Classification: C32, G12


  Abstract

We propose a new hypothesis-testing method for multipredictor regressions in small samples, where the dependent variable is regressed on lagged variables that are autoregressive. The new test is based on the augmented regression method (Amihud and Hurvich, 2004), which produces reduced-bias coefficients and is easy to implement. The method's usefulness is demonstrated by simulations and by testing a model where stock returns are predicted by two variables, income-to-consumption and dividend yield.

The authors thank James Stock, the Editor, and the Referee for helpful comments and suggestions.


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