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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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Bias Correcting Selection Effects

Bias Correcting Selection Effects

(p.133) 10 Bias Correcting Selection Effects
Empirical Model Discovery and Theory Evaluation

David F. Hendry

The MIT Press

We develop approximate bias corrections for the conditional distributions of the estimated parameters of retained variables after model selection, such that approximately unbiased estimates of their coefficients are delivered. Such corrections also drive estimated coefficients of irrelevant variables towards the origin, substantially reducing their mean squared errors (MSEs). We illustrate the theory by simulating selection from N = 1000 variables, to examine the impacts of our approach on estimated coefficient MSEs for both relevant and irrelevant variables in their conditional and unconditional distributions.

Keywords:   Selection bias corrections, conditional distributions, mean squared errors

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