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Evaluating a Structural Model Forecast: Decomposition Approach

Author

Listed:
  • Frantisek Brazdik
  • Zuzana Humplova
  • Frantisek Kopriva

Abstract

When presenting the results of macroeconomic forecasting, forecasters often have to explain the contribution of data revisions, conditioning information, and expert judgment updates to the forecast update. We present a framework for decomposing the differences between two forecasts generated by a linear structural model into the contributions of the elements of the information set when anticipated and unanticipated conditioning is applied. The presented framework is based on a set of supporting forecasts that simplify the decomposition of the forecast update. The features of the framework are demonstrated by examining two forecast scenarios with the same initial prediction period but different forecast assumptions. The full capabilities of the decomposition framework are documented by an example forecast evaluation where the forecast from the Czech National Bank's Inflation Report III/2012 is assessed with respect to the updated forecast from Inflation Report III/2013.

Suggested Citation

  • Frantisek Brazdik & Zuzana Humplova & Frantisek Kopriva, 2015. "Evaluating a Structural Model Forecast: Decomposition Approach," Working Papers 2015/12, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2015/12
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    References listed on IDEAS

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    1. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    2. Jan Bruha & Tibor Hledik & Tomas Holub & Jiri Polansky & Jaromir Tonner, 2013. "Incorporating Judgments and Dealing with Data Uncertainty in Forecasting at the Czech National Bank," Research and Policy Notes 2013/02, Czech National Bank.
    3. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    4. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    5. Lars E O Svensson, 2005. "Monetary Policy with Judgment: Forecast Targeting," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    6. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    7. 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 568-572, August.
    8. Michal Andrle, 2013. "What Is in Your Output Gap? Unified Framework & Decomposition into Observables," IMF Working Papers 2013/105, International Monetary Fund.
    9. 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.
    10. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    11. 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.
    12. Heilemann, Ullrich, 2002. "Increasing the transparency of macroeconometric forecasts: a report from the trenches," International Journal of Forecasting, Elsevier, vol. 18(1), pages 85-105.
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    More about this item

    Keywords

    Data revisions; DSGE models; forecasting; forecast revisions;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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