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Modified Information Criteria and Selection of Long Memory Time Series Models

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Modified Information Criteria and Selection of Long Memory Time Series Models

Richard T. Baillie, George Kapetanios & Fotis Papailias

Computational Statistics & Data Analysis
Volume 76, August 2014, Pages 116-131


Abstract. The problem of model selection of a univariate long memory time series is investigated once a semi parametric estimator for the long memory parameter has been used. Standard information criteria are not consistent in this case. A Modified Information Criterion (MIC) that overcomes these difficulties is introduced and proofs that show its asymptotic validity are provided. The results are general and cover a wide range of short memory processes. Simulation evidence compares the new and existing methodologies and empirical applications in monthly inflation and daily realized volatility are presented.

Keywords. Long memory, ARFIMA models, Modified information criteria

DOI. 10.1016/j.csda.2013.04.012


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