Year: 1998
Type: article
Abstract: We develop regression-based tests of hypotheses about out of sample prediction errors.Representative tests include ones for zero mean and zero correlation between a prediction error and a vector of predictors.The relevant environments are ones in which predictions depend on estimated parameters.We show that standard regression statistics generally fail to account for error introduced by estimation of these parameters.We propose computationally convenient test statistics that properly account for such error.Simulations indicate that the procedures can work well in samples of size typically available, although there sometimes are substantial size distortions.
Source: International Economic Review
DOI: 10.2307/2527340
Authors: Kenneth D. West, Michael W. McCracken
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W1575811129