Error and Model Misspecification in ARFIMA Process

Authors

  • Valderio A. Reisen Departamento de Estatistica, CCE and PPGEA-CT-UFES, Vitoria - ES, Brazil
  • Manoel R. Sena Jr. Departamento de Estatlstica, CCEN - UFPE, Recife - PE, Brazil
  • Silvia R. C . Lopes Departamento de Estatistica, IM - UFRGS, Porto Alegre - RS, Brazil

DOI:

https://doi.org/10.12660/bre.v21n12001.3193

Keywords:

Fractional differencing, Long memory, Smoothed periodogram regression, Periodogram regression, Whittle maximum likelihood procedure, non-normality, misspecification

Abstract

In developing the long and short memory estimation, it is usually assumed that the innovations in the ARFIMA model are normally distributed. However, circumstances may occur where this assumption is not true. This paper uses Monte Carlo simulation to evaluate the robustness of different estimators of the fractional parameter in stationary and invertible ARFIMA processes to the misspecification of the error distribution. In particular, we consider misspecification against heavy-tailed, skewed and bimodal distributions. The study is also extended for the incorrect ARFIMA specification.

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Published

2001-05-01

Issue

Vol. 21 No. 1 (2001)

Section

Articles