Success 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 one for 'break drivers', then outline sources of potential information. Relevant non-linear, dynamic models facing multiple breaks can have more

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... ate 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. JEL classifications: C1, C53.