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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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Comparisons of 1-cut Selection with Autometrics

Comparisons of 1-cut Selection with Autometrics

Chapter:
(p.141) 11 Comparisons of 1-cut Selection with Autometrics
Source:
Empirical Model Discovery and Theory Evaluation
Author(s):

David F. Hendry

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262028356.003.0011

Having established that the properties of bias-corrected 1-cut selections match our three criteria, having appropriate gauge and potency, with near unbiased estimates, and relatively small MSEs, we now evaluate the comparative properties of Autometrics. First, the tree-search algorithm of Autometrics is described and its operational procedures outlined. The framework remains the same as in chapter 8, namely a congruent, constant regression model in mutually orthogonal, valid conditioning variables, but unlike 1-cut, Autometrics does not use, nor need, to exploit orthogonality. We wish to evaluate whether despite exploring many paths, there is any deterioration in the selection quality: in several important respects, Autometrics matches 1-cut even when the latter is applicable.

Keywords:   Comparative properties, tree-search algorithm, Autometrics

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