Forecasting breaks and forecasting during breaks
AbstractSuccess in accurately forecasting breaks requires that they are predictable from relevant information available at the forecast origin using an appropriate model form, which can be selected and estimated before the break.� To clarify the roles of these six necessary conditions, we distinguish between the information set for 'normal forces' and the ones for 'break drivers', then outline sources of potential information.� Relevant non-linear, dynamic models facing multiple breaks can have more candidate variables than observations, so we discuss automatic model selection.� As a failure to accurately forecast breaks remains likely, we augment our strategy by modelling breaks during their progress, and consider robust forecasting devices.
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Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 535.
Date of creation: 01 Feb 2011
Date of revision:
Economic forecasting; Structural breaks; Information sets; Non-linearity;
Find related papers by JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-03-05 (All new papers)
- NEP-CBA-2011-03-05 (Central Banking)
- NEP-ECM-2011-03-05 (Econometrics)
- NEP-ETS-2011-03-05 (Econometric Time Series)
- NEP-FOR-2011-03-05 (Forecasting)
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