Aris Spanos

Professor

 

Contact:

3025 Pamplin Hall

(540) 231-7707

Email Dr. Spanos

 

 

Current Research Interests:
My current research interests include the philosophy and methodology of statistical inference and modeling; the foundations of statistics; data mining, pre-test bias and other methodological issues pertaining to empirical modeling; statistical adequacy, Mis-Specification (M-S) testing and respecification; resampling techniques and statistical adequacy; parametric vs. nonparametric modeling; Bayesian criticisms of frequentist inference; reliability and precision of statistical inference; modeling speculative prices; revisiting the statistical foundations of panel data models; Dynamic Stochastic General Equilibrium (DSGE) models and their statistical adequacy.

Selected Bibliography:

Books:
1. Statistical Foundations of Econometric Modeling, Cambridge University Press, Cambridge, 1986.
2. Probability Theory and Statistical Inference: Econometric Modeling with Observational Data, Cambridge University Press, Cambridge, 1999.
3. Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science [with D. G. Mayo], Cambridge University Press, Cambridge, 2010.
Selected publications:
1. “The Simultaneous Equations Model Revisited: Statistical Adequacy and Identification,” Journal of Econometrics, 1990, 44, 87-105.
2. “On Modeling Heteroskedasticity: the Student's t and Elliptical Linear Regression Models,” Econometric Theory, 1994, 10, 286-315.
3. “On Theory Testing in Econometrics: Modeling with Non-experimental Data,” Journal of Econometrics, 1995, 67, 189-226.
4. “On Normality and the Linear Regression Model”, Econometric Reviews, 1995, 14(2), 195-203.
5. “Towards a Unifying Methodological Framework for Econometric Modelling”, Economic Notes, 1988, pp. 107-34. Reprinted in Modelling Economic Series: Readings on the Methodology of Econometric Modeling, pp. 335-64, edited by C.W.J. Granger, Oxford University Press, Oxford, 1990.
6. “Early Empirical Findings on the Consumption Function, Stylized Facts or Fiction: a Retrospective View,” Oxford Economic Papers, 1989, 41, pp. 150-169.
7. “On Re-reading Haavelmo: a Retrospective View of Econometric Modeling,” Econometric Theory 1989, 5, pp. pp. 405-429.
8. “Revisiting Data Mining: ‘Hunting' with or without a License,” Journal of Economic Methodology, 2000, 7, pp. 231-264.
9. “On Modeling Speculative Prices: the Empirical Literature”, [with Elena Andreou and Nikitas Pittis], Journal of Economic Surveys, 15, 187-220, 2001.
10. “The Model Specification Problem from a Probabilistic Reduction Perspective,” [with Anya McGuirk], Journal of the American Agricultural Association, 2001, 83(5), pp. 1168-1176.
11 “The Problem of Near-Multicollinearity Revisited: Erratic vs. Systematic Volatility”, [with Anya McGuirk], Journal of Econometrics, 2002, 108, 365-393.
12. “Statistical Adequacy and the Testing of Trend versus Difference Stationarity,” [with Elena Andreou], Econometric Reviews, 2003, 22, 217-237.
13. “Methodology in Practice: Statistical Misspecification Testing” [with D. G. Mayo], Philosophy of Science, 2004, 71, 1007-1025.
14. "Severe Testing as a Basic Concept in a Neyman-Pearson Philosophy of Induction," [with D. G. Mayo] The British Journal of the Philosophy of Science, 2006, 57: 323-357.
15. “Where Do Statistical Models Come From? Revisiting the Problem of Specification,”
pp. 98-119, The Second Erich L. Lehmann Symposium, Lecture Notes-Monograph Series, vol. 49, Institute of Mathematical Statistics, 2006.
16. “Econometrics in Retrospect and Prospect,” pp. 3-58 in Mills, T.C. and K. Patterson, New Palgrave Handbook of Econometrics, vol. 1, MacMillan, London, 2006.
17. “The Student's t Dynamic Linear Regression: Re-examining Volatility Modeling,” [with M. Heracleous], Advances in Econometrics, 2006, 20, 289-319.
18. “Revisiting the Omitted Variables Argument: Substantive vs. Statistical Adequacy,” Journal of Economic Methodology, 2006, 13: 179-218.
19. “The Instrumental Variables Method revisited: On the Nature and Choice of Optimal Instruments,” pp. 34-59 in Refinement of Econometric Estimation and Test Procedures, ed. by G. D. A. Phillips and E. Tzavalis, Cambridge University Press, Cambridge, 2007.
20. “Philosophical Scrutiny of Evidence of Risks: From Bioethics to Bioevidence,” [with D. G. Mayo], Philosophy of Science, 2006, 73 (5), 803-816.
21. “Curve-Fitting, the Reliability of Inductive Inference and the Error-Statistical Approach,” Philosophy of Science, 2007, 74: 1046-1066.
22. “Testing for Nonstationarity Using Maximum Entropy Resampling: A Misspecification Testing Perspective,” [with A. Koutris and M. Heracleous], Econometric Reviews, 2008, 27, 363-384.
23. “Statistics and Economics," pp. 1129-1162 in the New Palgrave Dictionary of Economics, 2nd ed., 2008, Eds. S. N. Durlauf and L. E. Blume. Palgrave Macmillan, London.
24. “Linear vs. Log-linear Unit-Root Specification: An Application of Mis-specification Encompassing,” [with D. F. Hendry and J. J. Reade], Oxford Bulletin of Economics and Statistics, 2008, 70: 829-847.
25. “Revisiting Error-Autocorrelation Correction: Common Factor Restrictions and Granger Non-Causality,” [with A. McGuirk], Oxford Bulletin of Economics and Statistics, 2009, 71: 259-282.
26. “The Pre-Eminence of Theory versus the European CVAR Perspective in Macroeconometric Modeling,” Economics: The Open-Access, Open-Assessment E-Journal, Vol. 3, 2009-10. http://www.economics-ejournal.org/economics/journalarticles/2009-10. Special issue on “Using Econometrics for Assessing Economic Models”
27. “Statistical Misspecification and the Reliability of Inference: the simple t-test in the presence of Markov dependence,” The Korean Economic Review, 2009, 25, 165-213.
28. “Akaike-type Information Criteria and the Reliability of Inference: Statistical Model Specification vs. Model Selection,” Journal of Econometrics, 158: 204-220, 2010.
29. The Discovery of Argon: A Case for Learning from Data? Philosophy of Science, 77: 359-380, 2010.
30. Is Frequentist Testing Vulnerable to the Base-Rate Fallacy? Philosophy of Science, 77: 565-583, 2010.
31. “Statistical Adequacy and the Trustworthiness of Empirical Evidence: Statistical vs. Substantive Information,” Economic Modelling, 27: 1436–1452, 2010.
32. “Error Statistics,” [with D. G. Mayo], pp. 173-208 in the Handbook of Philosophy of Science, vol. 7: Philosophy of Statistics, D. Gabbay, P. Thagard, and J. Woods (editors), Elsevier, 2011.
33. “Revisiting the Welch Uniform Model: A case for Conditional Inference?” Advances and Applications in Statistical Science, 5: 33-52, 2011.
34. “Mispaced Criticisms of Neyman-Pearson (N-P) Testing in the Case of Two Simple Hypotheses,” Advances and Applications in Statistical Science, 6: 229-242, 2011.
35. “Foundational Issues in Statistical Modeling: Statistical Model Specification and Validation,” Rationality, Markets and Morals, Vol. 2, 2011, 146–178, Special Topic: Statistical Science and Philosophy of Science
36 “Revisiting the Berger location model: Fallacious Confidence Interval or a Rigged Example?” Statistical Methodology, 9: 555-561, 2012
37. “A Frequentist Interpretation of Probability for Model-Based Inductive Inference,” (31 pages) forthcoming in Synthese, 2012.
38. “Philosophy of Econometrics," pp. 329-393 the Handbook of Philosophy of Science, vol. 12: Philosophy of Economics, editor, U. Maki, general editors D. Gabbay, P. Thagard, and J. Woods, Elsevier, 2012.
39. “Who should be Afraid of the Jeffreys-Lindley paradox?” forthcoming in Philosophy of Science, 2012.
40. “The ‘Mixed Experiment’' Example Revisited: Fallacious Frequentist Inference or an Improper Statistical Model?’’ forthcoming in Advances and Applications of Statistical Science, 2012.

 

Working Papers:

1. “Revisiting Haavelmo's Structural Econometrics: Bridging the Gap between Theory and Data”

2. “How the Decision Theoretic Perspective Misrepresents Frequentist Inference”

3. “Revisiting the Statistical Foundations of Panel Data Models”

4. “An Autoregressive Model with a Trending Variance: a Nesting Model for Unit Root Testing”

5. “Identities and their Role in Econometric Modeling”

6. “Learning from Data: the Role of Error in Statistical Modeling and Inference”

7. “The Exchange (or Two Envelope) Paradox Revisited,”

8. "Review of the book by S. T. Ziliak and D. N. McCloskey, entitled: The Cult of Statistical Significance", 2008.