Year: 2005
Type: article
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.
Source: The Economic Journal
Authors: David F. Hendry, Hans‐Martin Krolzig
Institutions: University of Oxford, University of Kent
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3021526567