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Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification

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  • Spanos, Aris

Abstract

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.

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  • Spanos, Aris, 2010. "Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification," Journal of Econometrics, Elsevier, vol. 158(2), pages 204-220, October.
    • Handle: RePEc:eee:econom:v:158:y:2010:i:2:p:204-220
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    References listed on IDEAS

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    1. Helmut Lütkepohl, 2005. "New Introduction to Multiple Time Series Analysis," Springer Books, Springer, number 978-3-540-27752-1, December.
    2. Elena Andreou & Aris Spanos, 2003. "Statistical Adequacy and the Testing of Trend Versus Difference Stationarity," Econometric Reviews, Taylor & Francis Journals, vol. 22(3), pages 217-237, January.
    3. Leeb, Hannes & Pötscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(1), pages 21-59, February.
    4. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124, September.
    5. Bénédicte Vidaillet & V. d'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    6. Spanos,Aris, 1999. "Probability Theory and Statistical Inference," Cambridge Books, Cambridge University Press, number 9780521424080.
    7. Aris Spanos & Anya McGuirk, 2001. "The Model Specification Problem from a Probabilistic Reduction Perspective," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(5), pages 1168-1176.
    8. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258, September.
    9. Aris Spanos, 2006. "Revisiting the omitted variables argument: Substantive vs. statistical adequacy," Journal of Economic Methodology, Taylor & Francis Journals, vol. 13(2), pages 179-218.
    10. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    11. Spanos, Aris, 1995. "On theory testing in econometrics : Modeling with nonexperimental data," Journal of Econometrics, Elsevier, vol. 67(1), pages 189-226, May.
    12. Aris Spanos, 2001. "Revisiting data mining: 'hunting' with or without a license," Journal of Economic Methodology, Taylor & Francis Journals, vol. 7(2), pages 231-264.
    13. Aris Spanos, 2009. "Statistical Misspecification and the Reliability of Inference: The Simple T-Test in the Presence of Markov Dependence," Korean Economic Review, Korean Economic Association, vol. 25, pages 165-213.
    14. Spanos, Aris, 1990. "The simultaneous-equations model revisited : Statistical adequacy and identification," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 87-105.
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    3. Bao, Te & Diks, Cees & Li, Hao, 2018. "A generalized CAPM model with asymmetric power distributed errors with an application to portfolio construction," Economic Modelling, Elsevier, vol. 68(C), pages 611-621.
    4. P. Dorian Owen, 2017. "Evaluating Ingenious Instruments for Fundamental Determinants of Long-Run Economic Growth and Development," Econometrics, MDPI, vol. 5(3), pages 1-33, September.
    5. Spanos, Aris, 2010. "Statistical adequacy and the trustworthiness of empirical evidence: Statistical vs. substantive information," Economic Modelling, Elsevier, vol. 27(6), pages 1436-1452, November.
    6. Aris Spanos, 2022. "Frequentist Model-based Statistical Induction and the Replication Crisis," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 133-159, September.
    7. Aris Spanos, 2016. "Transforming structural econometrics: substantive vs. statistical premises of inference," Review of Political Economy, Taylor & Francis Journals, vol. 28(3), pages 426-437, July.
    8. Michaelides, Michael & Spanos, Aris, 2020. "On modeling heterogeneity in linear models using trend polynomials," Economic Modelling, Elsevier, vol. 85(C), pages 74-86.

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