A near optimal test for structural breaks when forecasting under square error loss

Tom Boot () and Andreas Pick ()
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Tom Boot: University of Groningen
Andreas Pick: Erasmus University Rotterdam, De Nederlandsche Bank and CESifo Institute

No 17-039/III, Tinbergen Institute Discussion Papers from Tinbergen Institute

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 (search for similar items in EconPapers)
JEL-codes: C12 C53 (search for similar items in EconPapers)
Date: 2017-04-18
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20170039

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