An Open-model Forecast-error Taxonomy
AbstractWe develop forecast-error taxonomies when there are unmodeled variables, forecast 'off-line'.� We establish three surprising results.� Even when an open system is correctly specified in-sample with zero intercepts, despite known future values of strongly exogenous variables, changes in dynamics can induce forecast failure when they have non-zero means.� The additional impact on forecast failure of incorrectly omitting such variables depends only on shifts in their means.� With no such shifts, there is no reduction in forecast failure from forecasting unmodeled variables relative to omitting them in 1-step or multi-step forecasts.� Simulation illustrations confirm these results.
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Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 552.
Date of creation: 01 Jun 2011
Date of revision:
Forecasting; Forecast-error taxonomies; Location shifts; Open models;
Find related papers by JEL classification:
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-06-25 (All new papers)
- NEP-CBA-2011-06-25 (Central Banking)
- NEP-FOR-2011-06-25 (Forecasting)
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