Modified Information Criteria and Selection of Long Memory Time Series Models

Richard Baillie; George Kapetanios; Fotis Papailias

doi:10.1016/j.csda.2013.04.012

Modified Information Criteria and Selection of Long Memory Time Series Models

Richard Baillie, George Kapetanios, Fotis Papailias

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

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.

Original language	English
Pages (from-to)	116-131
Journal	Computational Statistics & Data Analysis
Volume	76
Early online date	03 May 2013
DOIs	https://doi.org/10.1016/j.csda.2013.04.012
Publication status	Published - Aug 2014

Keywords

Long memory
ARFIMA models
Modified Information Criteria

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title = "Modified Information Criteria and Selection of Long Memory Time Series Models",

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.",

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AU - Kapetanios, George

AU - Papailias, Fotis

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N2 - 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.

AB - 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.

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KW - ARFIMA models

KW - Modified Information Criteria

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DO - 10.1016/j.csda.2013.04.012

M3 - Article

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SP - 116

EP - 131

JO - Computational Statistics & Data Analysis

JF - Computational Statistics & Data Analysis

SN - 0167-9473

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