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Understanding DSGE Filters in Forecasting and Policy Analysis

  • Michal Andrle

This paper introduces methods that allow analysts to (i) decompose the estimates of unobserved quantities into observed data, (ii) to better understand revision properties of the model, and (iii) to impose subjective prior constraints on path estimates of unobserved shocks in structural economic models. For instance, a decomposition of the flexible-price output gap, or a technology shock, into contributions of output, inflation, interest rates, and other observed variables' contribution is feasible. The intuitive nature and analytical clarity of the suggested procedures are appealing for policy-related and forecasting models.

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Paper provided by International Monetary Fund in its series IMF Working Papers with number 13/98.

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Length: 23
Date of creation: 08 May 2013
Date of revision:
Handle: RePEc:imf:imfwpa:13/98
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  1. Pierce, David A., 1980. "Data revisions with moving average seasonal adjustment procedures," Journal of Econometrics, Elsevier, vol. 14(1), pages 95-114, September.
  2. International Monetary Fund, 2010. "Estimating Potential Output with a Multivariate Filter," IMF Working Papers 10/285, International Monetary Fund.
  3. Doran, Howard E, 1992. "Constraining Kalman Filter and Smoothing Estimates to Satisfy Time-Varying Restrictions," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 568-72, August.
  4. 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.
  5. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
  6. Roberto Garcia-Saltos & Douglas Laxton & Michal Andrle & Haris Munandar & Charles Freedman & Danny Hermawan, 2009. "Adding Indonesia to the Global Projection Model," IMF Working Papers 09/253, International Monetary Fund.
  7. Christoph Schleicher, 2003. "Kolmogorov-Wiener Filters for Finite Time Series," Computing in Economics and Finance 2003 109, Society for Computational Economics.
  8. Michal Andrle & Tibor Hledik & Ondra Kamenik & Jan Vlcek, 2009. "Implementing the New Structural Model of the Czech National Bank," Working Papers 2009/2, Czech National Bank, Research Department.
  9. Jaromír Beneš & Andrew Binning & Kirdan Lees, 2008. "Incorporating judgement with DSGE models," Reserve Bank of New Zealand Discussion Paper Series DP2008/10, Reserve Bank of New Zealand.
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