Consistent Model Selection by an Automatic<i>Gets</i>Approach*
Oxford Bulletin of Economics and StatisticsPublished 1 December 2003
Julia Campos, David F. Hendry, Hans‐Martin Krolzig
Citations75
SJR quartileQ1
SJR score0.98
SNIP1.24
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TL;DR
The consistency of the selection procedures embodied in PcGets is established, and pre‐selecting to remove many of the candidate variables is confirmed as enhancing the performance of SIC.
Abstract
Abstract We establish the consistency of the selection procedures embodied in PcGets , and compare their performance with other model selection criteria in linear regressions. The significance levels embedded in the PcGets Liberal and Conservative algorithms coincide in very large samples with those implicit in the Hannan–Quinn (HQ) and Schwarz information criteria (SIC), respectively. Thus, both PcGets rules are consistent under the same conditions as HQ and SIC. However, PcGets has a rather different finite‐sample behaviour. Pre‐selecting to remove many of the candidate variables is confirmed as enhancing the performance of SIC.
Keywords
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