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Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System

Author

Listed:
  • Costantini, Mauro

    (Department of Economics and Finance, Brunel University London, United Kingdom)

  • Gunter, Ulrich

    (Austrian National Bank, Vienna, Austria)

  • Kunst, Robert M.

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria and Department of Economics, University of Vienna, Austria)

Abstract

We study the benefits of forecast combinations based on forecast-encompassing tests relative to uniformly weighted forecast averages across rival models. For a realistic simulation design, we generate multivariate time-series samples of size 40 to 200 from a macroeconomic DSGE-VAR model. Constituent forecasts of the combinations are formed from four linear autoregressive specifications, one of them a more sophisticated factor-augmented vector autoregression (FAVAR). The forecaster is assumed not to know the true data-generating model. Results depend on the prediction horizon. While one-step prediction fails to support test-based combinations at all sample sizes, the test-based procedure clearly dominates at prediction horizons greater than two.

Suggested Citation

  • Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihsesp:292
    as

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    File URL: https://irihs.ihs.ac.at/id/eprint/2169
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    More about this item

    Keywords

    Combining forecasts; encompassing tests; model selection; time series; DGSE-VAR model;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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