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On the Evaluation of Hierarchical Forecasts

Author

Listed:
  • George Athanasopoulos
  • Nikolaos Kourentzes

Abstract

The aim of this paper is to provide a thinking road-map and a practical guide to researchers and practitioners working on hierarchical forecasting problems. Evaluating the performance of hierarchical forecasts comes with new challenges stemming from both the structure of the hierarchy and the application context. We discuss several relevant dimensions for researchers and analysts: the scale and units of the time series, the issue of sparsity, the forecast horizon, the importance of multiple evaluation windows and the multiple objective decision context. We conclude with a series of practical recommendations.

Suggested Citation

  • George Athanasopoulos & Nikolaos Kourentzes, 2021. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 10/21, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2021-10
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    File URL: https://www.monash.edu/business/ebs/research/publications/ebs/wp10-2021.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    aggregation; coherence; hierarchical time series; reconciliation;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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