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Forecast Combinations

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  • Marco Aiolfi
  • Carlos Capistrán
  • Allan Timmermann

Abstract

We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based forecasts. We also provide an analysis of the importance of model instability for explaining gains from forecast combination. Analytical and simulation results uncover break scenarios where forecast combinations outperform the best individual forecasting model.

Suggested Citation

  • Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
  • Handle: RePEc:bdm:wpaper:2010-04
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    More about this item

    Keywords

    Factor Based Forecasts; Non-linear Forecasts; Structural Breaks; Survey Forecasts; Univariate Forecasts.;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E - Macroeconomics and Monetary Economics

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