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Multiple Filtering Devices for the Estimation of Cyclical DSGE Models

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  • Fabio Canova
  • Filippo Ferroni

Abstract

We propose a method to estimate time in variant cyclical DSGE models using the information provided by a variety of filters. We treat data filtered with alternative procedures as contaminated proxies of the relevant model-based quantities and estimate structural and non-structural parameters jointly using a signal extraction approach. We employ simulated data to illustrate the properties of the procedure and compare our conclusions with those obtained when just one filter is used. We revisit the role of money in the transmission of monetary business cycles.

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Bibliographic Info

Paper provided by Barcelona Graduate School of Economics in its series Working Papers with number 498.

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Date of creation: Sep 2010
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Handle: RePEc:bge:wpaper:498

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Keywords: DSGE models; Filters; Structural estimation; Business cycles;

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References

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  1. Peter N. Ireland, 2000. "Money's Role in the Monetary Business Cycle," Boston College Working Papers in Economics 458, Boston College Department of Economics.
  2. Canova, Fabio, 1993. "Detrending and Business Cycle Facts," CEPR Discussion Papers 782, C.E.P.R. Discussion Papers.
  3. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2006. "VARs, common factors and the empirical validation of equilibrium business cycle models," ULB Institutional Repository 2013/10127, ULB -- Universite Libre de Bruxelles.
  4. 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.
  5. 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.
  6. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2008. "How Structural Are Structural Parameters?," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 83-137 National Bureau of Economic Research, Inc.
  7. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
  8. Yuriy Gorodnichenko & Serena Ng, 2009. "Estimation of DSGE Models When the Data are Persistent," NBER Working Papers 15187, National Bureau of Economic Research, Inc.
  9. Justiniano, Alejandro & Primiceri, Giorgio E. & Tambalotti, Andrea, 2009. "Investment Shocks and the Relative Price of Investment," CEPR Discussion Papers 7598, C.E.P.R. Discussion Papers.
  10. Yongsung Chang & Taeyoung Doh & Frank Schorfheide, 2006. "Non-stationary hours in a DSGE model," Working Papers 06-3, Federal Reserve Bank of Philadelphia.
  11. Martin Fukac & Adrian Pagan, 2010. "Limited information estimation and evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 55-70.
  12. Fabio Canova & David López-Salido & Claudio Michelacci, 2007. "The labor market effects of technology shocks," Banco de Espa�a Working Papers 0719, Banco de Espa�a.
  13. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
  14. 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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Citations

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Cited by:
  1. Filippo Ferroni, 2010. "Commentary on MEDEA: A DSGE model for the Spanish economy," SERIEs, Spanish Economic Association, vol. 1(1), pages 245-249, March.
  2. Miguel Casares & Antonio Moreno & Jesús Vázquez, 2009. "Wage Stickiness and Unemployment Fluctuations: An Alternative Approach," Faculty Working Papers 04/09, School of Economics and Business Administration, University of Navarra.
  3. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data," Koç University-TUSIAD Economic Research Forum Working Papers 1321, Koc University-TUSIAD Economic Research Forum.
  4. Zanetti, Francesco, 2012. "Banking and the role of money in the business cycle," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 87-94.
  5. Michal Andrle & Roberto Garcia-Saltos & Giang Ho, 2013. "The Role of Domestic and External Shocks in Poland: Results from an Agnostic Estimation Procedure," IMF Working Papers 13/220, International Monetary Fund.
  6. Saijo, Hikaru, 2013. "Estimating DSGE models using seasonally adjusted and unadjusted data," Journal of Econometrics, Elsevier, vol. 173(1), pages 22-35.
  7. Jesús Fernández-Villaverde, 2009. "The Econometrics of DSGE Models," NBER Working Papers 14677, National Bureau of Economic Research, Inc.
  8. Bjørnar Karlsen Kivedal, 2013. "A New Keynesian Framework and Wage and Price Dynamics in the US," Working Paper Series 15113, Department of Economics, Norwegian University of Science and Technology.
  9. Klaus Abberger & Wolfgang Nierhaus, 2011. "Construction of Composite Business Cycle Indicators in a Sparse Data Environment," CESifo Working Paper Series 3557, CESifo Group Munich.
  10. Yuriy Gorodnichenko & Serena Ng, 2009. "Estimation of DSGE Models When the Data are Persistent," NBER Working Papers 15187, National Bureau of Economic Research, Inc.
  11. Luca Sala, 2013. "DSGE models in the frequency domain," Working Papers 504, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  12. Gelain, Paolo, 2010. "The external finance premium in the euro area A useful indicator for monetary policy?," Working Paper Series 1171, European Central Bank.
  13. Galo Nuño, 2011. "Optimal research and development and the cost of business cycles," Journal of Economic Growth, Springer, vol. 16(3), pages 257-283, September.
  14. Jan Brùha, 2011. "An Empirical Small Labor Market Model for the Czech Economy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(5), pages 434-449, November.

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