On the Evaluation of Hierarchical Forecasts

George Athanasopoulos (george.athanasopoulos@monash.edu) and Nikolaos Kourentzes (n.kourentzes@lancaster.ac.uk)

No 2/20, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: The aim of this note 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 statistical structure of the hierarchy and the application context. We discuss four relevant dimensions for researchers and analysts: the scale and units of time series, the issue of sparsity, the decision context and the importance of multiple evaluation windows. We conclude with a series of practical recommendations.

Keywords: aggregation; coherence; hierarchical time series; reconciliation (search for similar items in EconPapers)
JEL-codes: C18 C53 C55 (search for similar items in EconPapers)
Pages: 22
Date: 2020
New Economics Papers: this item is included in nep-for and nep-ore
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Citations: View citations in EconPapers (11)

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