Arbeitspapier
Forecasting Swiss exports using Bayesian forecast reconciliation
This paper conducts an extensive forecasting study on 13,118 time series measuring Swiss goods exports, grouped hierarchically by export destination and product category. We apply existing state of the art methods in forecast reconciliation and introduce a novel Bayesian reconciliation framework. This approach allows for explicit estimation of reconciliation biases, leading to several innovations: Prior judgment can be used to assign weights to specific forecasts and the occurrence of negative reconciled forecasts can be ruled out. Overall we find strong evidence that in addition to producing coherent forecasts, reconciliation also leads to improvements in forecast accuracy.
- Sprache
-
Englisch
- Erschienen in
-
Series: KOF Working Papers ; No. 457
- Klassifikation
-
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Forecasting Models; Simulation Methods
General Aggregative Models: Forecasting and Simulation: Models and Applications
- Thema
-
Hierarchical Forecasting
Bayesian Forecast Reconciliation
Swiss Exports
Optimal Forecast Combination
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Eckert, Florian
Hyndman, Rob J.
Panagiotelis, Anastasios
- Ereignis
-
Veröffentlichung
- (wer)
-
ETH Zurich, KOF Swiss Economic Institute
- (wo)
-
Zurich
- (wann)
-
2019
- DOI
-
doi:10.3929/ethz-b-000354388
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Eckert, Florian
- Hyndman, Rob J.
- Panagiotelis, Anastasios
- ETH Zurich, KOF Swiss Economic Institute
Entstanden
- 2019
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