The Mean Squared Prediction Error Paradox

Pablo Pincheira and Nicolas Hardy

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper, we show that traditional comparisons of Mean Squared Prediction Error (MSPE) between two competing forecasts may be highly controversial. This is so because when some specific conditions of efficiency are not met, the forecast displaying the lowest MSPE will also display the lowest correlation with the target variable. Given that violations of efficiency are usual in the forecasting literature, this opposite behavior in terms of accuracy and correlation with the target variable may be a fairly common empirical finding that we label here as "the MSPE Paradox." We characterize "Paradox zones" in terms of differences in correlation with the target variable and conduct some simple simulations to show that these zones may be non-empty sets. Finally, we illustrate the relevance of the Paradox with two empirical applications.

Keywords: Mean Squared Prediction Error; Correlation; Forecasting; Time Series; Random Walk. (search for similar items in EconPapers)
JEL-codes: C1 C10 C12 C18 C2 C22 C4 C40 C5 C52 C53 C58 E0 E00 E30 E31 E37 E44 E47 E52 E58 F30 F31 F37 G00 G12 G15 G17 Q0 Q00 Q02 Q1 Q2 Q3 Q33 Q4 Q43 Q47 (search for similar items in EconPapers)
Date: 2021-04-24
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Journal Article: The mean squared prediction error paradox (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:107403

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