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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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    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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