The Out-of-sample Performance of an Exact Median-Unbiased Estimator for the Near-Unity AR(1) Model

Carlos A. Medel () and Pablo Pincheira

MPRA Paper from University Library of Munich, Germany

Abstract: We analyse the multihorizon forecasting performance of several strategies to estimate the stationary AR(1) model in a near-unity context. We focus on the Andrews' (1993) exact median-unbiased estimator (BC), the OLS estimator, and the driftless random walk (RW). In addition, we explore the forecasting performance of pairwise combinations between these individual strategies. We do this to investigate whether the Andrews' (1993) correction of the OLS downward bias helps in reducing mean squared forecast errors. Via simulations, we find that BC forecasts typically outperform OLS forecasts. When BC is compared to the RW we obtain mixed results, favouring the latter as the persistence of the true process increases. Interestingly, we also find that the combination of BC and RW performs well when the persistence of the process is high.

Keywords: Near-unity autoregression; median-unbiased estimation; unbiasedness; unit root model; forecasting; forecast combinations (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 C63 (search for similar items in EconPapers)
Date: 2015-03-04
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Related works:
Journal Article: The out-of-sample performance of an exact median-unbiased estimator for the near-unity AR(1) model (2016)
Working Paper: The Out-of-Sample Performance of An Exact Median-Unbiased Estimator for the Near-Unity Ar(1)Model (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:62552

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