Multiple-Predictor Regressions: Hypothesis Testing
提出一种适用于小样本的多预测变量回归假设检验方法，基于增广回归法降低系数偏差，并通过模拟和股票收益预测实例验证其有效性。
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.