Improving models and forecasts after equilibrium-mean shifts

Equilibrium-mean shifts can result from changes in intercepts with constant dynamics, or be induced by shifts in dynamics with non-zero data means, or both. Induced shifts distort parameter estimates and create a discrepancy between the forecast origin and the equilibrium mean, leading to forecast f...

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Main Authors: Castle, J, Doornik, J, Hendry, DF
פורמט: Journal article
שפה:English
יצא לאור: Elsevier 2023
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author Castle, J
Doornik, J
Hendry, DF
author_facet Castle, J
Doornik, J
Hendry, DF
author_sort Castle, J
collection OXFORD
description Equilibrium-mean shifts can result from changes in intercepts with constant dynamics, or be induced by shifts in dynamics with non-zero data means, or both. Induced shifts distort parameter estimates and create a discrepancy between the forecast origin and the equilibrium mean, leading to forecast failure and requiring modifications to previous forecast-error taxonomies. Step-indicator saturation can detect induced shifts, but that does not correct forecast failure. To discriminate direct from induced equilibrium-mean shifts, we augment the model by multiplicative indicators where all selected step indicators interact with the lagged regressand. Forecasts can be markedly improved after induced shifts by including these interactive indicators.
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spelling oxford-uuid:7e304e98-31c3-46cf-b7aa-3f9d449d122b2024-08-06T09:20:31ZImproving models and forecasts after equilibrium-mean shiftsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:7e304e98-31c3-46cf-b7aa-3f9d449d122bEnglishSymplectic ElementsElsevier2023Castle, JDoornik, JHendry, DFEquilibrium-mean shifts can result from changes in intercepts with constant dynamics, or be induced by shifts in dynamics with non-zero data means, or both. Induced shifts distort parameter estimates and create a discrepancy between the forecast origin and the equilibrium mean, leading to forecast failure and requiring modifications to previous forecast-error taxonomies. Step-indicator saturation can detect induced shifts, but that does not correct forecast failure. To discriminate direct from induced equilibrium-mean shifts, we augment the model by multiplicative indicators where all selected step indicators interact with the lagged regressand. Forecasts can be markedly improved after induced shifts by including these interactive indicators.
spellingShingle Castle, J
Doornik, J
Hendry, DF
Improving models and forecasts after equilibrium-mean shifts
title Improving models and forecasts after equilibrium-mean shifts
title_full Improving models and forecasts after equilibrium-mean shifts
title_fullStr Improving models and forecasts after equilibrium-mean shifts
title_full_unstemmed Improving models and forecasts after equilibrium-mean shifts
title_short Improving models and forecasts after equilibrium-mean shifts
title_sort improving models and forecasts after equilibrium mean shifts
work_keys_str_mv AT castlej improvingmodelsandforecastsafterequilibriummeanshifts
AT doornikj improvingmodelsandforecastsafterequilibriummeanshifts
AT hendrydf improvingmodelsandforecastsafterequilibriummeanshifts