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The Properties of Automatic "GETS" Modelling Author info | Abstract | Publisher info | Download info | Related research | Statistics David F. Hendry
Hans-Martin Krolzig
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After reviewing the simulation performance of general-to-specific automatic regression-model selection, as embodied in "PcGets", we show how model selection can be non-distortionary: approximately unbiased 'selection estimates' are derived, with reported standard errors close to the sampling standard deviations of the estimated DGP parameters, and a near-unbiased goodness-of-fit measure. The handling of theory-based restrictions, non-stationarity and problems posed by collinear data are considered. Finally, we consider how "PcGets" can handle three 'intractable' problems: more variables than observations in regression analysis; perfectly collinear regressors; and modelling simultaneous equations without "a priori" restrictions. Copyright 2005 Royal Economic Society.
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Article provided by Royal Economic Society in its journal The Economic Journal .
Volume (Year): 115 (2005)
Issue (Month): 502 (03)
Pages: C32-C61
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Handle: RePEc:ecj:econjl:v:115:y:2005:i:502:p:c32-c61Contact details of provider: Web page: http://www.res.org.uk/ More information through EDIRC
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.: Krolzig, Hans-Martin & Hendry, David F., 2001.
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Other versions:
Hans-Martin Krolzig & David Hendry, 1999.
"Computer Automation of General-to-Specific Model Selection Procedures ,"
Computing in Economics and Finance 1999
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Hans-Martin Krolzig & David Hendry, 2000.
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