A Near Optimal Test for Structural Breaks When Forecasting Under Square Error Loss
TI 2017-039/III Tinbergen Institute Discussion Paper
56 Pages Posted: 19 Apr 2017
Date Written: April 12, 2017
Abstract
We propose a near optimal test for structural breaks of unknown timing when the purpose of the analysis is to obtain accurate forecasts under square error loss. A bias-variance trade-off exists under square forecast error loss, which implies that small structural breaks should be ignored. We study critical break sizes, assess the relevance of the break location, and provide a test to determine whether modeling a break will improve forecast accuracy. Asymptotic critical values and near optimality properties are established allowing for a break under the null, where the critical break size varies with the break location. The results are extended to a class of shrinkage forecasts with our test statistic as shrinkage constant. Empirical results on a large number of macroeconomic time series show that structural breaks that are relevant for forecasting occur much less frequently than indicated by existing tests.
Keywords: structural break test, forecasting, squared error loss
JEL Classification: C12, C53
Suggested Citation: Suggested Citation