This review provides an overview of forecasting methods that can help researchers forecast in the presence of nonstationarities caused by instabilities. The emphasis of the review is both theoretical and applied, and we provide several examples of interest to economists. We show that modeling instabilities can help, but it depends on how they are modeled. We also demonstrate how to robustify a model against instabilities.


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