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Trend agnostic one step estimation of DSGE models

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  • Ferroni, Filippo

Abstract

DSGE models are currently estimated with a two step approach: data is first filtered and then DSGE structural parameters are estimated. Two step procedures have problems, ranging from trend misspecification to wrong assumption about the correlation between trend and cycles. In this paper, I present a one step method, where DSGE structural parameters are jointly estimated with filtering parameters. I show that different data transformations imply different structural estimates; the two step approach lacks a statistical-based criterion to select among them. The one step approach allows to test hypothesis about the most likely trend specification for individual series and/or use the resulting information to construct robust estimates by Bayesian averaging. The role of investment shock as source of GDP volatility is reconsidered.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 14550.

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Date of creation: 04 Apr 2009
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Handle: RePEc:pra:mprapa:14550

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

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Cited by:
  1. Gabriel, Vasco & Levine, Paul & Pearlman, Joseph & Yang, Bo, 2011. "An Estimated DSGE Model of the Indian Economy," Working Papers, National Institute of Public Finance and Policy 11/95, National Institute of Public Finance and Policy.
  2. Filippo Ferroni, 2010. "Commentary on MEDEA: A DSGE model for the Spanish economy," SERIEs, Spanish Economic Association, vol. 1(1), pages 245-249, March.
  3. Saijo, Hikaru, 2013. "Estimating DSGE models using seasonally adjusted and unadjusted data," Journal of Econometrics, Elsevier, Elsevier, vol. 173(1), pages 22-35.
  4. Girardi, Riccardo & Paruolo, Paolo, 2013. "Wages and prices in Europe before and after the onset of the Monetary Union," Economic Modelling, Elsevier, Elsevier, vol. 35(C), pages 643-653.
  5. Pierre Lafourcade & Joris de Wind, 2012. "Taking Trends Seriously in DSGE Models: An Application to the Dutch Economy," DNB Working Papers, Netherlands Central Bank, Research Department 345, Netherlands Central Bank, Research Department.
  6. Fabio Canova & Filippo Ferroni, 2009. "Multiple filtering devices for the estimation of cyclical DSGE models," Economics Working Papers 1135, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2010.
  7. 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, Koc University-TUSIAD Economic Research Forum 1321, Koc University-TUSIAD Economic Research Forum.
  8. Kai Liu, 2014. "Public Finances, Business Cycles and Structural Fiscal Balances," Cambridge Working Papers in Economics 1411, Faculty of Economics, University of Cambridge.
  9. Enrique Martínez-García & Diego Vilán & Mark Wynne, 2012. "Bayesian estimation of NOEM models: identification and inference in small samples," Globalization and Monetary Policy Institute Working Paper 105, Federal Reserve Bank of Dallas.

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