Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/153464 
Year of Publication: 
2009
Series/Report no.: 
ECB Working Paper No. 1030
Publisher: 
European Central Bank (ECB), Frankfurt a. M.
Abstract: 
We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the benchmark. Our procedures compare the bench-mark to all the alternative models simultaneously rather than sequentially, and do not require re-estimation of models as part of a bootstrap procedure. Both procedures adjust MSPE differences in accordance with Clark and West (2007); one procedure then examines the maximum t-statistic, the other computes a chi-squared statistic. Our simulations examine the proposed procedures and two existing procedures that do not adjust the MSPE differences: a chi-squared statistic, and White’s (2000) reality check. In these simulations, the two statistics that adjust MSPE differences have most accurate size, and the procedure that looks at the maximum t-statistic has best power. We illustrate, our procedures by comparing forecasts of different models for U.S. inflation.
Subjects: 
Inflation forecasting
multiple model comparisons
Out-of-Sample
prediction
testing
JEL: 
C32
C53
E37
Document Type: 
Working Paper

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