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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 Republica de Colombia in its series Borradores de Economia with number 559.

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Handle: RePEc:bdr:borrec:559

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Related research
Keywords: Monetary Policy; DSGE; Forecast; Kalman Filter Classification JEL: F47; E01; C61.;

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  1. Tinsley, P. A. & Spindt, P. A. & Friar, M. E., 1980. "Indicator and filter attributes of monetary aggregates : A nit-picking case for disaggregation," Journal of Econometrics, Elsevier, vol. 14(1), pages 61-91, September. [Downloadable!] (restricted)
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  2. Fabio Canova & Luca Sala, 2006. "Back to square one: identification issues in DSGE models," Working Paper Series 583, European Central Bank. [Downloadable!]
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  3. 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!]
  4. 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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  5. 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)
  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. 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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  8. 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)
  9. Jean Boivin & Marc Giannoni, 2006. "DSGE Models in a Data-Rich Environment," NBER Technical Working Papers 0332, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  10. Martin Fukac & Adrian Pagan, 2006. "Issues in Adopting DSGE Models for Use in the Policy Process," Working Papers 2006/6, Czech National Bank, Research Department. [Downloadable!]
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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. 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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  13. 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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