A Power Booster Factor for Out-of-Sample Tests of Predictability

Pablo Pincheira

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper we introduce a “power booster factor” for out-of-sample tests of predictability. The relevant econometric environment is one in which the econometrician wants to compare the population Mean Squared Prediction Errors (MSPE) of two models: one big nesting model, and another smaller nested model. Although our factor can be used to improve the power of many out-of-sample tests of predictability, in this paper we focus on boosting the power of the widely used test developed by Clark and West (2006, 2007). Our new test multiplies the Clark and West t-statistic by a factor that should be close to one under the null hypothesis that the short nested model is the true model, but that should be greater than one under the alternative hypothesis that the big nesting model is more adequate. We use Monte Carlo simulations to explore the size and power of our approach. Our simulations reveal that the new test is well sized and powerful. In particular, it tends to be less undersized and more powerful than the test by Clark and West (2006, 2007). Although most of the gains in power are associated to size improvements, we also obtain gains in size-adjusted power. Finally we present an empirical application in which more rejections of the null hypothesis are obtained with our new test.

Keywords: Time-series; forecasting; inference; inflation; exchange rates; random walk; out-of-sample (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 C58 E17 E27 E37 E47 F37 (search for similar items in EconPapers)
Date: 2017-02
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-mac
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Related works:
Journal Article: A Power Booster Factor for Out-of-Sample Tests of Predictability (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:77027

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