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: journals.permissions@oxfordjournals.org, Oxford University Press.
Year of publication: |
2009
|
---|---|
Authors: | Amihud, Yakov ; Hurvich, Clifford M. ; Wang, Yi |
Published in: |
Review of Financial Studies. - Society for Financial Studies - SFS. - Vol. 22.2009, 1, p. 413-434
|
Publisher: |
Society for Financial Studies - SFS |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Predictive regression with order-p autoregressive predictors
Amihud, Yakov, (2010)
-
Multiple-Predictor Regressions: Hypothesis Testing
Amihud, Yakov, (2013)
-
Predictive regression with order-p autoregressive predictors
Amihud, Yakov, (2010)
- More ...