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dc.contributor.author
Eckert, Florian
dc.contributor.author
Hyndman, Rob J.
dc.contributor.author
Panagiotelis, Anastasios
dc.date.accessioned
2019-07-30T07:13:45Z
dc.date.available
2019-07-22T12:18:57Z
dc.date.available
2019-07-22T12:37:34Z
dc.date.available
2019-07-29T14:14:53Z
dc.date.available
2019-07-30T07:13:45Z
dc.date.issued
2019-07
dc.identifier.uri
http://hdl.handle.net/20.500.11850/354388
dc.identifier.doi
10.3929/ethz-b-000354388
dc.description.abstract
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.
en_US
dc.format
application/pdf
en_US
dc.format
application/gzip
en_US
dc.format
application/x-tar
en_US
dc.language.iso
en
en_US
dc.publisher
KOF Swiss Economic Institute, ETH Zurich
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Hierarchical Forecasting
en_US
dc.subject
Bayesian Forecast Reconciliation
en_US
dc.subject
Swiss Exports
en_US
dc.subject
Optimal Forecast Combination
en_US
dc.title
Forecasting Swiss Exports using Bayesian Forecast Reconciliation
en_US
dc.type
Working Paper
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2019-07-22
ethz.journal.title
KOF Working Papers
ethz.journal.volume
457
en_US
ethz.size
34 p.; 6935.36 kB
en_US
ethz.code.jel
JEL - JEL::C - Mathematical and Quantitative Methods::C3 - Multiple or Simultaneous Equation Models; Multiple Variables::C32 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
en_US
ethz.code.jel
JEL - JEL::C - Mathematical and Quantitative Methods::C5 - Econometric Modeling::C53 - Forecasting and Prediction Methods; Simulation Methods
en_US
ethz.code.jel
JEL - JEL::E - Macroeconomics and Monetary Economics::E1 - General Aggregative Models::E17 - Forecasting and Simulation: Models and Applications
en_US
ethz.publication.place
Zurich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::02525 - KOF Konjunkturforschungsstelle / KOF Swiss Economic Institute
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::02525 - KOF Konjunkturforschungsstelle / KOF Swiss Economic Institute::06330 - KOF FB Konjunktur / KOF Macroeconomic forecasting
en_US
ethz.date.deposited
2019-07-22T12:19:03Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-07-22T12:37:42Z
ethz.rosetta.lastUpdated
2019-07-30T07:14:00Z
ethz.rosetta.exportRequired
false
ethz.rosetta.versionExported
true
ethz.COinS
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