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The Properties of Automatic "GETS" Modelling

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  • David F. Hendry
  • Hans-Martin Krolzig

Abstract

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.

Suggested Citation

  • David F. Hendry & Hans-Martin Krolzig, 2005. "The Properties of Automatic "GETS" Modelling," Economic Journal, Royal Economic Society, vol. 115(502), pages 32-61, March.
    • Handle: RePEc:ecj:econjl:v:115:y:2005:i:502:p:c32-c61
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    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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