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Bridging DSGE models and the raw data

  • Fabio Canova

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 Barcelona Graduate School of Economics in its series Working Papers with number 635.

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Date of creation: May 2012
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Handle: RePEc:bge:wpaper:635
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  1. Canova, Fabio & Sala, Luca, 2006. "Back to square one: identification issues in DSGE models," Working Paper Series 0583, European Central Bank.
  2. Mark Aguiar & Gita Gopinath, 2007. "Emerging Market Business Cycles: The Cycle Is the Trend," Journal of Political Economy, University of Chicago Press, vol. 115, pages 69-102.
  3. 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.
  4. Peter Ireland, 1999. "A Method for Taking Models to the Data," Computing in Economics and Finance 1999 1233, Society for Computational Economics.
  5. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1998. "Dynamic equilibrium economies: a framework for comparing models and data," Staff Report 243, Federal Reserve Bank of Minneapolis.
  6. Gorodnichenko, Yuriy & Ng, Serena, 2010. "Estimation of DSGE models when the data are persistent," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 325-340, April.
  7. 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.
  8. Aguiar, Mark & Gopinath, Gita, 2007. "Emerging Market Business Cycles: The Cycle is the Trend," Scholarly Articles 11988098, Harvard University Department of Economics.
  9. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
  10. Chang, Yongsung & Doh, Taeyoung & Schorfheide, Frank, 2005. "Non-stationary Hours in a DSGE Model," CEPR Discussion Papers 5232, C.E.P.R. Discussion Papers.
  11. 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.
  12. Peter N. Ireland, 2004. "Technology Shocks in the New Keynesian Model," NBER Working Papers 10309, National Bureau of Economic Research, Inc.
  13. V.V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2008. "New Keynesian Models: Not Yet Useful for Policy Analysis," NBER Working Papers 14313, National Bureau of Economic Research, Inc.
  14. 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.
  15. 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.
  16. Frank Smets & Raf Wouters, 2007. "Shocks and Frictions in US Business Cycles : a Bayesian DSGE Approach," Working Paper Research 109, National Bank of Belgium.
  17. Fabio Canova & Filippo Ferroni, 2010. "Multiple Filtering Devices for the Estimation of Cyclical DSGE Models," Working Papers 498, Barcelona Graduate School of Economics.
  18. 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.
  19. Alejandro Justiniano & Giorgio E. Primiceri & Andrea Tambalotti, 2008. "Investment shocks and business cycles," Working Paper Series WP-08-12, Federal Reserve Bank of Chicago.
  20. Ferroni Filippo, 2011. "Trend Agnostic One-Step Estimation of DSGE Models," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-36, July.
  21. 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.
  22. 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.
  23. Andrle, Michal, 2008. "The Role of Trends and Detrending in DSGE Models," MPRA Paper 13289, University Library of Munich, Germany.
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