Model Selection in Under-specified Equations Facing Breaks

David Hendry and Jennifer Castle

No 509, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: Although a general unrestricted model may under-specify the data generation process, especially when breaks occur, model selection can still improve over estimating a prior specification. Impulse-indicator saturation (IIS) can 'correct' non-constant intercepts induced by location shifts in omitted variables, which surprisingly leave slope parameters unaltered even when correlated with included variables. However, location shifts in included variables do induce changes in slopes where there are correlated omitted variables. IIS acts as a 'robust method' when models are mis-specified, and helps mitigate the adverse impacts of induced location shifts on non-constant intercepts and equation standard errors.

Keywords: Model selection; mis-specification; location shifts; impulse-indicator saturation; costs of search; costs of inferencee; Autometrics (search for similar items in EconPapers)
JEL-codes: C22 C51 (search for similar items in EconPapers)
Date: 2010-10-01
References: Add references at CitEc
Citations: View citations in EconPapers (2)

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Journal Article: Model selection in under-specified equations facing breaks (2014)
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