Does modeling a structural break improve forecast accuracy?
研究了在预测中是否应建模结构断点，提出了一个检验方法来判断建模断点能否提高预测精度，发现宏观经济时间序列中与预测相关的断点远少于现有检验所显示的。
Mean square forecast error loss implies a bias–variance trade-off that suggests that structural breaks of small magnitude should be ignored. In this paper, we provide a test to determine whether modeling a structural break improves forecast accuracy. The test is near optimal even when the date of a local-to-zero break is not consistently estimable. The results extend to forecast combinations that weight the post-break sample and the full sample forecasts by our test statistic. In a large number of macroeconomic time series, we find that structural breaks that are relevant for forecasting occur much less frequently than existing tests indicate.