Hierarchical Forecasting

George Athanasopoulos (), Puwasala Gamakumara (), Anastasios Panagiotelis, Rob Hyndman and Mohamed Affan ()

No 2/19, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: Accurate forecasts of macroeconomic variables are crucial inputs into the decisions of economic agents and policy makers. Exploiting inherent aggregation structures of such variables, we apply forecast reconciliation methods to generate forecasts that are coherent with the aggregation constraints. We generate both point and probabilistic forecasts for the first time in the macroeconomic setting. Using Australian GDP we show that forecast reconciliation not only returns coherent forecasts but also improves the overall forecast accuracy in both point and probabilistic frameworks.

Pages: 35
Date: 2019
New Economics Papers: this item is included in nep-for
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Citations: View citations in EconPapers (6)

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