IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Bridging DSGE models and the raw data

A method to estimate DSGE models using the raw data is proposed. The approach links the observables to the model counterparts via a flexible specification which does not require the model-based component to be solely located at business cycle frequencies, allows the non model-based component to take various time series patterns, and permits model misspecification. Applying standard data transformations induce biases in structural estimates and distortions in the policy conclusions. The proposed approach recovers important model-based features in selected experimental designs. Two widely discussed issues are used to illustrate its practical use.

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.econ.upf.edu/docs/papers/downloads/1320.pdf
File Function: Whole Paper
Download Restriction: no

Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 1320.

as
in new window

Length:
Date of creation: Nov 2008
Date of revision: May 2012
Handle: RePEc:upf:upfgen:1320
Contact details of provider: Web page: http://www.econ.upf.edu/

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. Fabio Canova & Luca Sala, 2007. "Back to square one: identification issues in DSGE models," Banco de Espa�a Working Papers 0715, Banco de Espa�a.
  2. Fabio Canova & Filippo Ferroni, 2011. "Multiple filtering devices for the estimation of cyclical DSGE models," Quantitative Economics, Econometric Society, vol. 2(1), pages 73-98, 03.
  3. Alejandro Justiniano & Giorgio E. Primiceri & Andrea Tambalotti, 2008. "Investment shocks and business cycles," Working Paper Series WP-08-12, Federal Reserve Bank of Chicago.
  4. Hansen, Lars Peter & Sargent, Thomas J., 1993. "Seasonality and approximation errors in rational expectations models," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 21-55.
  5. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
  6. Mark Aguiar & Gita Gopinath, 2004. "Emerging Market Business Cycles: The Cycle is the Trend," NBER Working Papers 10734, National Bureau of Economic Research, Inc.
  7. Chang, Yongsung & Doh, Taeyoung & Schorfheide, Frank, 2005. "Non-stationary Hours in a DSGE Model," CEPR Discussion Papers 5232, C.E.P.R. Discussion Papers.
  8. Gomez, Victor, 1999. "Three Equivalent Methods for Filtering Finite Nonstationary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 109-16, January.
  9. Christiano, Lawrence J. & Vigfusson, Robert J., 2003. "Maximum likelihood in the frequency domain: the importance of time-to-plan," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 789-815, May.
  10. Frank Smets & Raf Wouters, 2002. "An estimated dynamic stochastic general equilibrium model of the euro area," Working Paper Research 35, National Bank of Belgium.
  11. Aguiar, Mark & Gopinath, Gita, 2007. "Emerging Market Business Cycles: The Cycle is the Trend," Scholarly Articles 11988098, Harvard University Department of Economics.
  12. Cogley, Timothy, 2001. "Estimating and testing rational expectations models when the trend specification is uncertain," Journal of Economic Dynamics and Control, Elsevier, vol. 25(10), pages 1485-1525, October.
  13. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1995. "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," NBER Technical Working Papers 0174, National Bureau of Economic Research, Inc.
  14. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
  15. Clarida, Richard & Galí, Jordi & Gertler, Mark, 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," CEPR Discussion Papers 1908, C.E.P.R. Discussion Papers.
  16. Ellen R. McGrattan & Patrick J. Kehoe & V. V. Chari, 2008. "New Keynesian models: not yet useful for policy analysis," Working Papers 664, Federal Reserve Bank of Minneapolis.
  17. Fabio Canova & Matthias Paustian, 2007. "Business cycle measurement with some theory," Economics Working Papers 1203, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2011.
  18. Peter N. Ireland, 1999. "A Method for Taking Models to the Data," Boston College Working Papers in Economics 421, Boston College Department of Economics.
  19. Yuriy Gorodnichenko & Serena Ng, 2009. "Estimation of DSGE Models When the Data are Persistent," NBER Working Papers 15187, National Bureau of Economic Research, Inc.
  20. Rabanal, Pau & Rubio-Ramirez, Juan F., 2005. "Comparing New Keynesian models of the business cycle: A Bayesian approach," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1151-1166, September.
  21. Peter N. Ireland, 2004. "Technology Shocks in the New Keynesian Model," NBER Working Papers 10309, National Bureau of Economic Research, Inc.
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:upf:upfgen:1320. 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.