The Optimal Size of a Preliminary Test of Linear Restrictions in a Misspecified Regression Model
作者:
DavidE. A. Giles,
Offer Lieberman,
JudithA. Giles,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1992)
卷期:
Volume 87,
issue 420
页码: 1153-1157
ISSN:0162-1459
年代: 1992
DOI:10.1080/01621459.1992.10476272
出版商: Taylor & Francis Group
关键词: Conditional inference;Ftest;Mini-max rule;Omitted regressors
数据来源: Taylor
摘要:
When the choice of estimator for the coefficients in a linear regression model is determined by the outcome of a prior test of the validity of restrictions on the model, it is well known that a minimax (risk) regret criterion leads to the simple rule that the optimal critical value for the preliminary test is approximately two in value, regardless of the degrees of freedom. We show that this result no longer holds in the (likely) event that relevant regressors are excluded from the model at the outset.
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