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Monetary Policy Forecasting In A Dsge Model With Data That Is Uncertain, Unbalanced And About The Future

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Author Info
Andrés González Gómez ()
Lavan Mahadeva ()
Diego Rodríguez ()
Luis Eduardo Rojas ()

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Abstract

If theory-consistent models can ever hope to forecast well and to be useful for policy, they have to relate to data which though rich in information is uncertain, unbalanced and sometimes forecasts from external sources about the future path of other variables. One example from many is financial market data, which can help but only after smoothing out irrelevant short-term volatility. In this paper we propose combining different types of useful but awkward data set with a linearised forward-looking DSGE model through a Kalman Filter fixed-interval smoother to improve the utility of these models as policy tools. We apply this scheme to a model for Colombia.

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Paper provided by BANCO DE LA REPÚBLICA in its series BORRADORES DE ECONOMIA with number 005480.

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Length: 35
Date of creation: 21 Apr 2009
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Handle: RePEc:col:000094:005480

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  2. Swanson, Eric T., 2004. "Signal Extraction And Non-Certainty-Equivalence In Optimal Monetary Policy Rules," Macroeconomic Dynamics, Cambridge University Press, vol. 8(01), pages 27-50, February. [Downloadable!]
  3. Koopman, Siem Jan & Harvey, Andrew, 2003. "Computing observation weights for signal extraction and filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 27(7), pages 1317-1333, May. [Downloadable!] (restricted)
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  4. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September. [Downloadable!] (restricted)
  5. Fabio Canova & Luca Sala, 2005. "Back to square one: identification issues in DSGE models," Economics Working Papers 927, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2006. [Downloadable!]
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  6. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer, vol. 20(1-2), pages 1-20, October. [Downloadable!]
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  7. Pearlman, Joseph, 1986. "Diverse information and rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 10(1-2), pages 333-338, June. [Downloadable!] (restricted)
  8. Jean Boivin & Marc Giannoni, 2006. "DSGE Models in a Data-Rich Environment," NBER Working Papers 12772, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  9. Svensson, Lars E. O. & Woodford, Michael, 2003. "Indicator variables for optimal policy," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 691-720, April. [Downloadable!] (restricted)
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  10. Svensson, Lars E. O. & Woodford, Michael, 2004. "Indicator variables for optimal policy under asymmetric information," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 661-690, January. [Downloadable!] (restricted)
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  11. Martin Lettau & Sydney C. Ludvigson, 2004. "Understanding Trend and Cycle in Asset Values: Reevaluating the Wealth Effect on Consumption," American Economic Review, American Economic Association, vol. 94(1), pages 276-299, March. [Downloadable!]
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  12. Adolfson, Malin & Andersson, Michael K. & Lindé, Jesper & Villani, Mattias & Vredin, Anders, 2005. "Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks," Working Paper Series 188, Sveriges Riksbank (Central Bank of Sweden), revised 01 Jun 2006. [Downloadable!]
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