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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.

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

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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/

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  1. Diebold, Francis X & Ohanian, Lee E & Berkowitz, Jeremy, 1998. "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 433-51, July.
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  7. Canova, Fabio & Sala, Luca, 2006. "Back to square one: identification issues in DSGE models," Working Paper Series 0583, European Central Bank.
  8. Peter Ireland, 1999. "A Method for Taking Models to the Data," Computing in Economics and Finance 1999 1233, Society for Computational Economics.
  9. 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.
  10. 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.
  11. Yuriy Gorodnichenko & Serena Ng, 2009. "Estimation of DSGE Models When the Data are Persistent," NBER Working Papers 15187, National Bureau of Economic Research, Inc.
  12. Yongsung Chang & Taeyoung Doh & Frank Schorfheide, 2007. "Non-stationary Hours in a DSGE Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1357-1373, 09.
  13. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "Monetary policy rules and macroeconomic stability: Evidence and some theory," Economics Working Papers 350, Department of Economics and Business, Universitat Pompeu Fabra, revised May 1999.
  14. 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.
  15. Justiniano, Alejandro & Primiceri, Giorgio E. & Tambalotti, Andrea, 2010. "Investment shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 132-145, March.
  16. 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.
  17. 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.
  18. Fabio Canova & Filippo Ferroni, 2010. "Multiple Filtering Devices for the Estimation of Cyclical DSGE Models," Working Papers 498, Barcelona Graduate School of Economics.
  19. Mark Aguiar & Gita Gopinath, 2004. "Emerging market business cycles: the cycle is the trend," Working Papers 04-4, Federal Reserve Bank of Boston.
  20. 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.
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  22. 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.
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