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Improved Tests for Forecast Comparisons in the Presence of Instabilities
Author(s) -
Martins Luis Filipe,
Perron Pierre
Publication year - 2016
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/jtsa.12179
Subject(s) - mathematics , econometrics , monotonic function , null hypothesis , relevance (law) , wald test , statistics , statistical hypothesis testing
Of interest is comparing the out‐of‐sample forecasting performance of two competing models in the presence of possible instabilities. To that effect, we suggest using simple structural change tests, sup‐Wald and UDmax for changes in the mean of the loss differences. It is shown that Giacomini and Rossi ([Giacomini R, 2010]) tests have undesirable power properties, power that can be low and non‐increasing as the alternative becomes further from the null hypothesis. On the contrary, our statistics are shown to have higher monotonic power, especially the UDmax version. We use their empirical examples to show the practical relevance of the issues raised.