The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Model Uncertainty

  • Alexei Onatski
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2293

Abstract

Model uncertainty is a condition of analysis when the specification of the model of analysed process is open to doubt. A failure to account for model uncertainty may result in poor decisions. This article reviews various approaches to representing model uncertainty. The approaches depend on the research context, differ in their degree of generality, and may be classified as deterministic versus stochastic, Bayesian versus frequentist, and treating model uncertainty as static versus viewing model uncertainty as evolving over time.

Keywords

Ambiguity aversion Approximating model Axioms of choice Bayesian statistics Bootstrap Detection error probability Dynamic stochastic general equilibrium models Ellsberg paradox ε-contaminated priors Heterogeneity uncertainty Identification scheme Identified vector autoregressions Incommensurability Incomplete information Judgement Laplace transform Learning Linear quadratic Gaussian problem Markov processes Model averaging Model expansion Model uncertainty Model uncertainty set Models Monetary policy Overconfidence Probability Rational expectations Relative entropy Risk-sensitive control Specification uncertainty Theory uncertainty Uncertainty Vector autoregressions 

JEL Classifications

C10 C50 D81 E52 O40 
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Bibliography

  1. Anderson, E., L.P. Hansen, and T.J. Sargent. 2003. A quartet of semigroups for model specification, robustness, prices of risk, and model detection. Journal of the European Economic Association 1: 68–123.CrossRefGoogle Scholar
  2. Berger, J., and L.M. Berliner. 1986. Robust Bayes and empirical Bayes analysis with ε-contaminated priors. Annals of Statistics 14: 461–486.CrossRefGoogle Scholar
  3. Box, G.E.P., and G.C. Tiao. 1962. A further look at robustness via Bayes’s theorem. Biometrika 49: 419–432.CrossRefGoogle Scholar
  4. Brock, W.A., S.N. Durlauf, and K.D. West. 2003. Policy evaluation in uncertain economic environments. Brookings Papers on Economic Activity 2003(1): 235–322.CrossRefGoogle Scholar
  5. Brunner, K., and A. Meltzer. 1969. The nature of policy problem. In Targets and indicators of monetary policy, ed. K. Brunner and A. Meltzer. San Francisco: Chandler Publishing Company.Google Scholar
  6. Diels, H. 1951. Die Fragmente der Vorsokratiker. Berlin: Weidmannsche Verlagsbuchhandlung.Google Scholar
  7. Dow, S.C. 2004. Uncertainty and monetary policy. Oxford Economic Papers 56: 539–561.CrossRefGoogle Scholar
  8. Draper, D. 1995. Assessment and propagation of model uncertainty. Journal of the Royal Statistical Society B 57: 45–97.Google Scholar
  9. Draper, D., J.S. Hodges, E.E. Leamer, C.N. Morris, and D.B. Rubin. 1987. A research agenda for assessment and propagation of model uncertainty. Report No. 2683-RC. Santa Monica: Rand Corporation.Google Scholar
  10. Efron, B., and G. Gong. 1983. A leisurely look at the bootstrap, the jackknife, and cross-validation. American Statistican 37: 36–49.Google Scholar
  11. Epstein, L.G., and M. Schneider 2006. Learning under ambiguity. Working Paper No. 527, Rochester Center for Economic Research.Google Scholar
  12. Faust, J. 1998. The robustness of identified VAR conclusions about money. Carnegie-Rochester Conference Series on Public Policy 49: 207–244.CrossRefGoogle Scholar
  13. Fisher, R.A. 1935. The design of experiments. Edinburgh: Oliver & Boyd.Google Scholar
  14. Frankel, J.A., and K.E. Rockett. 1988. International macroeconomic policy coordination when policymakers do not agree on the true model. American Economic Review 78: 318–340.Google Scholar
  15. Giannoni, M. 2002. Does model uncertainty justify caution? Robust optimal monetary policy in a forward-looking model. Macroeconomic Dynamics 6: 111–144.CrossRefGoogle Scholar
  16. Gilboa, I., and D. Schmeidler. 1989. Maximin expected utility with non-unique priors. Journal of Mathematical Economics 18: 141–153.CrossRefGoogle Scholar
  17. Hansen, L.P., and T.J. Sargent. 2003. Robust control of forward-looking models. Journal of Monetary Economics 50: 581–604.CrossRefGoogle Scholar
  18. Hansen, L.P., and T.J. Sargent. 2006. Robustness. Working paper, New York University.Google Scholar
  19. Hoeting, J.A., D. Madigan, A.E. Raftery, and C.T. Volinsky. 1999. Bayesian model averaging: A tutorial. Statistical Science 14: 382–417.CrossRefGoogle Scholar
  20. Keynes, J.M. 1921. A treatise on probability. London: Macmillan. Repr. for the Royal Economic Society as Collected Writings, vol. 8, 1973.Google Scholar
  21. Keynes, J.M. 1939. Professor Tinbergen’s method. Economic Journal 49: 558–568.CrossRefGoogle Scholar
  22. Knight, F.H. 1921. Risk, uncertainty and profit. New York: Houghton Mifflin.Google Scholar
  23. Kullback, S., and R.A. Leibler. 1951. On information and sufficiency. Annals of Mathematical Statistics 22: 79–86.CrossRefGoogle Scholar
  24. Kwakernaak, H., and R. Sivan. 1972. Linear optimal control systems. New York: Wiley.Google Scholar
  25. McCallum, B.T. 1988. Robustness properties of a rule for monetary policy. Carnegie-Rochester Conference Series on Public Policy 29: 173–203.CrossRefGoogle Scholar
  26. Morgan, M.S., and M. Morrison. 1999. Models as mediators. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  27. Petersen, I.R., M.R. James, and P. Dupuis. 2000. Minimax optimal control of stochastic uncertain systems with relative entropy constraints. IEEE Transactions on Automatic Control 45: 398–412.CrossRefGoogle Scholar
  28. Popper, K.R. 1962. Conjectures and refutations. New York/London: Basic Books.Google Scholar
  29. Savage, L.G. 1954. The foundations of statistics. New York: Dover Publications.Google Scholar
  30. Schorfheide, F., and M. Del Negro. 2005. Monetary policy analysis with potentially misspecified models. Mimeo: University of Pennsylvania.Google Scholar
  31. Tetlow, R.J. 2006. Real-time model uncertainty in the United States: ‘Robust’ policies put to the test. Division of Research and Statistics, Federal Reserve Board: Manuscript.Google Scholar
  32. von zur Muehlen, P. 2001. Activist vs. non-activist monetary policy: Optimal rules under extreme uncertainty. Finance and economics discussion series working paper no. 2, Federal Reserve Board.Google Scholar
  33. Whittle, P. 1990. Risk-sensitive optimal control. New York: Wiley.Google Scholar
  34. Zhou, K., J.C. Doyle, and K. Glover. 1996. Robust and optimal control. Upper Saddle River: Prentice Hall.Google Scholar

Copyright information

© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Alexei Onatski
    • 1
  1. 1.