Aris Spanos

Aris Spanos
Professor
Wilson Schmidt Professor of Economics

Contact:
Pamplin 3025
540-231-7707
Email Dr. Spanos

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Current Research Interests:

My current research interests include econometrics; 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; the CAPM from an econometric perspective.

Selected Bibliography:

Books: (Linked Above)
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 Publicatons:
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,” Synthese, 190: 1555-1585, 2013.
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?” Philosophy of Science, 80: 73-93, 2013.
40. “The ‘Mixed Experiment’’ Example Revisited: Fallacious Frequentist Inference or an Improper Statistical Model?’’ Advances and Applications of Statistical Science, 6: 29-47, 2013.
41. “Revisiting the Likelihoodist Evidential Account,” Journal of Statistical Theory and Practice, 7: 187-195, 2013.
42. “Recurring Controversies about P values and Confidence Intervals Revisited,” Ecology, 95(3), 2014, pp. 645-651.
43. “Revisiting Haavelmo’s Structural Econometrics: Bridging the Gap between Theory and Data,” forthcoming in Journal of Economic Methodology, 2014.
44. “Reflections on the LSE Tradition in Econometrics: a Student’s Perspective,” Oeconomia, 4(3) 2014: pp. 343-380.

Working Papers:
1. “An Autoregressive Model with a Trending Variance: a Nesting Model for Unit Root Testing”
2. “Identities and their Role in Econometric Modeling”
3. “Learning from Data: the Role of Error in Statistical Modeling and Inference”
4. “The Exchange (or Two Envelope) Paradox Revisited”
5. “Review of the book by S.T. Ziliak and D.N. McCloskey, entitled: “The Cult of Statistical Significance”, 2008.
6. “Revisiting the Welch Uniform Model: A Case for Conditional Inference?”
7. “Misplaced Criticisms of Neyman-Pearson (N-P) Testing in the Case of Two Simple Hypotheses”
8. “The ‘Mixed Experiment’ Example Revisited: Fallacious Frequentist Inference or an Improper Statistical Model?”
9. “Revisiting Haavelmo’s Structural Econometrics: Bridging the Gap between Theory and Data”

10. “Why the Decision Theoretic Perspective Misrepresents Frequentist Inference”
11. “Revisiting Bayes’ Rule and Evidence: Notional Events vs. Real Data”
12. “Revisiting Heterogeneity and Dependence in Panel Data Modeling”
13. “Model Validation and DSGE Modeling”
14. “Mis-Specification Testing in Retrospect and Prospect”
15. “Revisiting Near-collinearity: Numerical vs. Statistical Perspectives”
16. “Revisiting Simpson’s Paradox: statistically warranted vs. unwarranted inference results”