IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Modeling Model Uncertainty

Listed author(s):
  • Alexei Onatski
  • Noah Williams

Recently there has been a great deal of interest in studying monetary policy under model uncertainty. We point out that different assumptions about the uncertainty may result in drastically different robust' policy recommendations. Therefore, we develop new methods to analyze uncertainty about the parameters of a model, the lag specification, the serial correlation of shocks, and the effects of real time data in one coherent structure. We consider both parametric and nonparametric specifications of this structure and use them to estimate the uncertainty in a small model of the US economy. We then use our estimates to compute robust Bayesian and minimax monetary policy rules, which are designed to perform well in the face of uncertainty. Our results suggest that the aggressiveness recently found in robust policy rules is likely to be caused by overemphasizing uncertainty about economic dynamics at low frequencies.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.nber.org/papers/w9566.pdf
Download Restriction: no

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 9566.

as
in new window

Length:
Date of creation: Mar 2003
Publication status: published as Alexei Onatski & Noah Williams, 2003. "Modeling Model Uncertainty," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1087-1122, 09.
Handle: RePEc:nbr:nberwo:9566
Note: EFG ME
Contact details of provider: Postal:
National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.

Phone: 617-868-3900
Web page: http://www.nber.org
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as
in new window


  1. William Poole, 1999. "Monetary policy rules?," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 3-12.
  2. Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206.
  3. Laurence M. Ball, 1999. "Policy Rules for Open Economies," NBER Chapters,in: Monetary Policy Rules, pages 127-156 National Bureau of Economic Research, Inc.
  4. Eric T. Swanson, 2000. "On signal extraction and non-certainty-equivalence in optimal monetary policy rules," Proceedings, Federal Reserve Bank of San Francisco.
  5. repec:cup:macdyn:v:6:y:2002:i:1:p:85-110 is not listed on IDEAS
  6. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
  7. Craine, Roger, 1979. "Optimal monetary policy with uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 1(1), pages 59-83, February.
  8. Andrew T.. Levin & Volker Wieland & John Williams, 1999. "Robustness of Simple Monetary Policy Rules under Model Uncertainty," NBER Chapters,in: Monetary Policy Rules, pages 263-318 National Bureau of Economic Research, Inc.
  9. J. Rust & J. F. Traub & H. Wozniakowski, 2002. "Is There a Curse of Dimensionality for Contraction Fixed Points in the Worst Case?," Econometrica, Econometric Society, vol. 70(1), pages 285-329, January.
  10. Christopher A. Sims, 2001. "Pitfalls of a Minimax Approach to Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 51-54, May.
  11. Soderstrom, Ulf, 2002. " Monetary Policy with Uncertain Parameters," Scandinavian Journal of Economics, Wiley Blackwell, vol. 104(1), pages 125-145.
  12. Glenn Rudebusch & Lars E.O. Svensson, 1999. "Policy Rules for Inflation Targeting," NBER Chapters,in: Monetary Policy Rules, pages 203-262 National Bureau of Economic Research, Inc.
  13. Glenn D. Rudebusch, 2001. "Is The Fed Too Timid? Monetary Policy In An Uncertain World," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 203-217, May.
  14. Peter Isard & Douglas Laxton & Ann-Charlotte Eliasson, 1999. "Simple Monetary Policy Rules Under Model Uncertainty," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 6(4), pages 537-577, November.
  15. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
  16. Giordani, Paolo & Soderlind, Paul, 2004. "Solution of macromodels with Hansen-Sargent robust policies: some extensions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(12), pages 2367-2397, December.
  17. Mccallum, Bennet T., 1988. "Robustness properties of a rule for monetary policy," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 29(1), pages 173-203, January.
  18. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
  19. Thomas J. Sargent & LarsPeter Hansen, 2001. "Robust Control and Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 60-66, May.
  20. John Rust, 1997. "Using Randomization to Break the Curse of Dimensionality," Econometrica, Econometric Society, vol. 65(3), pages 487-516, May.
  21. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1, June.
  22. Onatski, Alexei & Stock, James H., 2002. "Robust Monetary Policy Under Model Uncertainty In A Small Model Of The U.S. Economy," Macroeconomic Dynamics, Cambridge University Press, vol. 6(01), pages 85-110, February.
  23. Gary Chamberlain, 2000. "Econometric applications of maxmin expected utility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 625-644.
  24. Alan S. Blinder, 1997. "Distinguished Lecture on Economics in Government: What Central Bankers Could Learn from Academics--And Vice Versa," Journal of Economic Perspectives, American Economic Association, vol. 11(2), pages 3-19, Spring.
  25. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:9566. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.