Multiple-Predictor Regressions: Hypothesis Testing
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 Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: firstname.lastname@example.org, Oxford University Press.
Volume (Year): 22 (2009)
Issue (Month): 1 (January)
|Contact details of provider:|| Postal: Oxford University Press, Journals Department, 2001 Evans Road, Cary, NC 27513 USA.|
Web page: http://www.rfs.oupjournals.org/
More information through EDIRC
|Order Information:||Web: http://www4.oup.co.uk/revfin/subinfo/|
When requesting a correction, please mention this item's handle: RePEc:oup:rfinst:v:22:y:2009:i:1:p:413-434. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.