The Properties of Automatic Gets Modelling
|Authors:||Hendry, David F.|
|Keywords:||Econometric methodology;model selection;general-to-specific;automatic|
|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.|
|Appears in Collections:||Financial Econometrics|
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