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Empirical Model Discovery and Theory EvaluationAutomatic Selection Methods in Econometrics$
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David F. Hendry and Jurgen A. Doornik

Print publication date: 2014

Print ISBN-13: 9780262028356

Published to MIT Press Scholarship Online: January 2015

DOI: 10.7551/mitpress/9780262028356.001.0001

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Selecting a Model in One Decision

Selecting a Model in One Decision

(p.117) 8 Selecting a Model in One Decision
Empirical Model Discovery and Theory Evaluation

David F. Hendry

The MIT Press

We now consider the special case in which a congruent, constant regression model in mutually orthogonal, valid conditioning variables can be successfully selected in one decision using the criteria discussed in chapter 5. This establishes a baseline, which demonstrates that the false null retention rate can be controlled, and that repeated testing is not an intrinsic aspect of model selection, even if there are 10300 possible models, as occurs here when N = 1000. Goodness-of-fit estimates, mean squared errors, and the consistency of the selection are all discussed. However, the estimates from the selected model do not have the same properties as if the DGP equation had been estimated directly, so chapter 10 develops bias corrections, after chapter 9 considers the 2-variable case in more detail.

Keywords:   1-cut selection, Gauge, Potency, Monte Carlo simulation, selection bias corrections

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