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Multiple filtering devices for the estimation of cyclical DSGE models

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  • Fabio Canova

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  • Filippo Ferroni

Abstract

We propose a method to estimate time invariant 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 Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 1135.

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Date of creation: Jan 2009
Date of revision: Sep 2010
Handle: RePEc:upf:upfgen:1135

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Web page: http://www.econ.upf.edu/

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

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  1. 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.
  2. Yuriy Gorodnichenko & Serena Ng, 2009. "Estimation of DSGE Models When the Data are Persistent," NBER Working Papers 15187, National Bureau of Economic Research, Inc.
  3. 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.
  4. Patrick J. Kehoe, 2006. "How to advance theory with structural VARs: use the Sims-Cogley-Nason approach," Staff Report 379, Federal Reserve Bank of Minneapolis.
  5. Canova, Fabio, 1993. "Detrending and Business Cycle Facts," CEPR Discussion Papers 782, C.E.P.R. Discussion Papers.
  6. Peter N. Ireland, 2001. "Money's Role in the Monetary Business Cycle," NBER Working Papers 8115, National Bureau of Economic Research, Inc.
  7. Alejandro Justiniano & Giorgio E. Primiceri & Andrea Tambalotti, 2009. "Investment shocks and the relative price of investment," Staff Reports 411, Federal Reserve Bank of New York.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
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