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J. Sargan

Econometric Reviews, 2001, vol. 20, issue 2, 171-186

Abstract: This paper examines the choice of critical values for testing both non-sequential and nested sequential sets of constraints in the standard linear regression model. Modest increases in (e.g.) t-ratio critical values relative to their one-off values are often sufficient to maintain proper size. A Bayesian decision-theoretic approach, highlighted by the Schwarz (1978) criterion, provides a framework for deriving consistency and asymptotic local power properties of both forms of testing (data mining) algorithms.

Keywords: Bayes; Bonferroni; Critical values; Data mining; Multiple testing; Scheffe; Schwarz criterion; Specification searches; JEL Classifixcation: C44; C51 (search for similar items in EconPapers)
Date: 2001
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