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http://hdl.handle.net/10071/12874
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Title: Improved tests for forecast comparisons in the presence of instabilities
Authors: Martins, L. F.
Perron, P.
Keywords: Non-monotonic power
Structural change
Forecasts
Long-run variance
Issue Date: 2016
Publisher: Wiley
Abstract: 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 (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.
Peer reviewed: yes
URI: http://hdl.handle.net/10071/12874
DOI: 10.1111/jtsa.12179
ISSN: 0143-9782
Ciência-IUL: https://ciencia.iscte-iul.pt/id/ci-pub-31656
Accession number: WOS:000380913600004
Appears in Collections:BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

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