Forecasting in Nonstationary Environments: What Works and What Doesn’t in Reduced-Form and Structural Models
这篇综述梳理了在数据不稳定（非平稳）时如何进行预测的方法，结合理论和实例，说明建模不稳定性有时有用但取决于建模方式，并展示了如何让模型对不稳定性更稳健。
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.