Advanced Search
MyIDEAS: Login to save this article or follow this journal

Learning in an estimated medium-scale DSGE model

Contents:

Author Info

  • Slobodyan, Sergey
  • Wouters, Raf

Abstract

We evaluate the empirical relevance of learning by private agents in an estimated medium-scale DSGE model. We replace the standard rational expectations assumption in the Smets and Wouters (2007) model by a constant-gain learning mechanism. If agents know the correct structure of the model and only learn about the parameters, both expectation mechanisms produce very similar results, and only the transition dynamics that are generated by specific initial beliefs seem to improve the fit. If, instead, agents use only a reduced information set in forming the perceived law of motion, the implied model dynamics change and, depending on the specification of the initial beliefs, the marginal likelihood of the model can improve significantly. These best-fitting models add additional persistence to the dynamics and this reduces the gap between the IRFs of the DSGE model and the more data-driven DSGE-VAR model. However, the learning dynamics do not systematically alter the estimated structural parameters related to the nominal and real frictions in the DSGE model.

Download Info

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.sciencedirect.com/science/article/pii/S0165188911001217
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 36 (2012)
Issue (Month): 1 ()
Pages: 26-46

as in new window
Handle: RePEc:eee:dyncon:v:36:y:2012:i:1:p:26-46

Contact details of provider:
Web page: http://www.elsevier.com/locate/jedc

Related research

Keywords: Constant-gain adaptive learning; Medium-scale DSGE model; DSGE-VAR;

Other versions of this item:

Find related papers by JEL classification:

References

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. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2006. "Adaptive Learning in Practice," CEPR Discussion Papers 5627, C.E.P.R. Discussion Papers.
  2. Marco Del Negro & Frank Schorfheide, 2006. "Forming priors for DSGE models (and how it affects the assessment of nominal rigidities)," Working Paper 2006-16, Federal Reserve Bank of Atlanta.
  3. Orphanides, Athanasios & Williams, John C., 2004. "The decline of activist stabilization policy: natural rate misperceptions, learning, and expectations," Working Paper Series 0337, European Central Bank.
  4. Adam, Klaus, 2003. "Learning to Forecast and Cyclical Behavior of Output and Inflation," CFS Working Paper Series 2003/01, Center for Financial Studies (CFS).
  5. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
  6. Smets, Frank & Wouters, Rafael, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," CEPR Discussion Papers 6112, C.E.P.R. Discussion Papers.
  7. Thomas Sargent & Noah Williams & Tao Zha, 2006. "Shocks and Government Beliefs: The Rise and Fall of American Inflation," American Economic Review, American Economic Association, vol. 96(4), pages 1193-1224, September.
  8. Juillard, Michel, 1996. "Dynare : a program for the resolution and simulation of dynamic models with forward variables through the use of a relaxation algorithm," CEPREMAP Working Papers (Couverture Orange) 9602, CEPREMAP.
  9. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
  10. Bruce Preston, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
  11. Kimball, Miles S, 1995. "The Quantitative Analytics of the Basic Neomonetarist Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(4), pages 1241-77, November.
  12. Slobodyan, Sergey & Wouters, Raf, 2012. "Learning in an estimated medium-scale DSGE model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 26-46.
  13. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, 09.
  14. Lawrence J. Christiano & Martin Eichenbaum & Charles Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper 0107, Federal Reserve Bank of Cleveland.
  15. Fabio Milani, 2005. "Learning, Monetary Policy Rules, and Macroeconomic Stability," Macroeconomics 0508019, EconWPA.
  16. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Macroeconomics 0510022, EconWPA.
  17. Branch, William A. & Evans, George W., 2006. "A simple recursive forecasting model," Economics Letters, Elsevier, vol. 91(2), pages 158-166, May.
  18. Orphanides, Athanasios & Williams, John C, 2005. "Inflation Scares and Forecast-Based Monetary Policy," CEPR Discussion Papers 4844, C.E.P.R. Discussion Papers.
  19. Thomas J. Sargent & Noah Williams, 2003. "Impacts of priors on convergence and escapes from Nash inflation," Working Paper 2003-14, Federal Reserve Bank of Atlanta.
  20. Paciello, Luigi, 2009. "Monetary Policy Activism and Price Responsiveness to Aggregate Shocks under Rational Inattention," MPRA Paper 16407, University Library of Munich, Germany.
  21. Athanasios Orphanides & John C. Williams, 2007. "Robust monetary policy with imperfect knowledge," Working Paper Series 2007-08, Federal Reserve Bank of San Francisco.
  22. Fabio Milani, 2006. "A Bayesian DSGE Model with Infinite-Horizon Learning: Do "Mechanical" Sources of Persistence Become Superfluous?," International Journal of Central Banking, International Journal of Central Banking, vol. 2(3), September.
  23. Eichenbaum, Martin & Fisher, Jonas D.M., 2007. "Estimating the frequency of price re-optimization in Calvo-style models," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2032-2047, October.
  24. Dupor, Bill & Han, Jing & Tsai, Yi-Chan, 2009. "What do technology shocks tell us about the New Keynesian paradigm?," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 560-569, May.
  25. Raf Wouters & Sergey Slobodyan, 2009. "Estimating a medium–scale DSGE model with expectations based on small forecasting models," 2009 Meeting Papers 654, Society for Economic Dynamics.
  26. Luigi Paciello, 2009. "Does Inflation Adjust Faster to Aggregate Technology Shocks than to Monetary Policy Shocks?," EIEF Working Papers Series 0917, Einaudi Institute for Economics and Finance (EIEF), revised Apr 2011.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.

Lists

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

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:eee:dyncon:v:36:y:2012:i:1:p:26-46. 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: (Zhang, Lei).

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.