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A Hierarchical Procedure for the Combination of Forecasts ; This is a revised version of Working Paper 228, Economics Series, October 2008, which includes some changes. The most important change regards the reference of Kisinbay (2007), which was not reported in the previous version. The hierarchical procedure proposed in the paper is based on the approach of Kisinbay (2007), but some modifications of that approach are provided

Author

Listed:
  • Costantini, Mauro

    (Department of Economics, University of Vienna BWZ, Vienna, Austria)

  • Pappalardo, Carmine

    (Institute for Studies and Economic Analysis (ISAE), Rome, Italy)

Abstract

This paper proposes a strategy to increase the efficiency of forecast combination. Given the availability of a wide range of forecasts for the same variable of interest, our goal is to apply combining methods to a restricted set of models. To this aim, a hierarchical procedure based on an encompassing test is developed. Firstly, forecasting models are ranked according to a measure of predictive accuracy (RMSFE). The models are then selected for combination such that each forecast is not encompassed by any of the competing forecasts. Thus, the procedure aims to unit model selection and model averaging methods. The robustness of the procedure is investigated in terms of the relative RMSFE using ISAE (Institute for Studies and Economic Analyses) short-term forecasting models for monthly industrial production in Italy.

Suggested Citation

  • Costantini, Mauro & Pappalardo, Carmine, 2009. "A Hierarchical Procedure for the Combination of Forecasts ; This is a revised version of Working Paper 228, Economics Series, October 2008, which includes some changes. The most important change regar," Economics Series 240, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihsesp:240
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    File URL: https://irihs.ihs.ac.at/id/eprint/1923
    File Function: First version, 2009
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    More about this item

    Keywords

    Combining forecasts; Econometric models; Evaluating forecasts; Models selection; Time series;
    All these keywords.

    JEL classification:

    • 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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