Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification
Aris Spanos ()
Journal of Econometrics, 2010, vol. 158, issue 2, 204-220
Since the 1990s, the Akaike Information Criterion (AIC) and its various modifications/extensions, including BIC, have found wide applicability in econometrics as objective procedures that can be used to select parsimonious statistical models. The aim of this paper is to argue that these model selection procedures invariably give rise to unreliable inferences, primarily because their choice within a prespecified family of models (a) assumes away the problem of model validation, and (b) ignores the relevant error probabilities. This paper argues for a return to the original statistical model specification problem, as envisaged by Fisher (1922), where the task is understood as one of selecting a statistical model in such a way as to render the particular data a truly typical realization of the stochastic process specified by the model in question. The key to addressing this problem is to replace trading goodness-of-fit against parsimony with statistical adequacy as the sole criterion for when a fitted model accounts for the regularities in the data.
Keywords: Akaike; Information; Criterion; AIC; BIC; GIC; MDL; Model; selection; Model; specification; Statistical; adequacy; Curve-fitting; Mathematical; approximation; theory; Simplicity; Least-squares; Gauss; linear; model; Linear; regression; model; AR(p); Mis-specification; testing; Respecification; Double-use; of; data; Infinite; regress; and; circularity; Pre-test; bias; Model; averaging; Reliability; of; inference (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:158:y:2010:i:2:p:204-220
Access Statistics for this article
Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson
More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Haili He ().