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Mis†Specification Testing In Retrospect

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  • Aris Spanos

Abstract

The primary objective of this paper is threefold. First, to undertake a retrospective view of Mis†Specification (M†S) testing, going back to the early 20th century, with a view to (i) place it in the broader context of modeling and inference and (ii) bring out some of its special features. Second, to call into question several widely used arguments undermining the importance of M†S testing in favor of relying on weak probabilistic assumptions in conjunction with generic robustness claims and asymptotic inference. Third, to bring out the crucial role of M†S testing in securing trustworthy inference results. This is achieved by extending/modifying Fisher's statistical framework with a view to draw a clear line between the modeling and the inference facets of statistical induction. The proposed framework untangles the statistical from the substantive (structural) model and focuses on how to secure the adequacy of the statistical model before probing for substantive adequacy. A case is made for using joint M†S tests based on custom†built auxiliary regressions with a view to enhance the effectiveness and reliability of probing for potential statistical misspecifications.

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  • Aris Spanos, 2018. "Mis†Specification Testing In Retrospect," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 541-577, April.
  • Handle: RePEc:bla:jecsur:v:32:y:2018:i:2:p:541-577
    DOI: 10.1111/joes.12200
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    References listed on IDEAS

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    8. Spanos,Aris, 1999. "Probability Theory and Statistical Inference," Cambridge Books, Cambridge University Press, number 9780521424080.
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    12. 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.
    13. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    14. Newey, Whitney K, 1985. "Maximum Likelihood Specification Testing and Conditional Moment Tests," Econometrica, Econometric Society, vol. 53(5), pages 1047-1070, September.
    15. 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.
    16. Domowitz, Ian & White, Halbert, 1982. "Misspecified models with dependent observations," Journal of Econometrics, Elsevier, vol. 20(1), pages 35-58, October.
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    19. Phillips, Peter C. B., 1988. "The ET Interview: Professor James Durbin," Econometric Theory, Cambridge University Press, vol. 4(01), pages 125-157, April.
    20. 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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    Cited by:

    1. Owen, P. Dorian, 2018. "Replication to assess statistical adequacy," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-16.
    2. Kiviet, Jan F., 2020. "Microeconometric dynamic panel data methods: Model specification and selection issues," Econometrics and Statistics, Elsevier, vol. 13(C), pages 16-45.
    3. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    4. Aris Spanos, 2023. "Revisiting the Large n (Sample Size) Problem: How to Avert Spurious Significance Results," Stats, MDPI, vol. 6(4), pages 1-16, December.
    5. 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.

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