A Comparative Note about Estimation of the Fractional Parameter under Additive Outliers

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Abstract

In recent articles, Fajardo et al. (2009) and Reisen and Fajardo (2012) propose an alternative semiparametric estimator of the fractional parameter in ARFIMA models which is robust to the presence of additive outliers. The results are very interesting, however, they use samples of 300 or 800 observations which are rarely found in macroeconomics. In order to perform a comparison, I estimate the fractional parameter using the procedure of Geweke and Porter-Hudak (1983) augmented with dummy variables associated with the (previously) detected outliers using the statistic τd suggested by Perron and Rodríguez (2003). Comparing with Fajardo et al. (2009) and Reisen and Fajardo (2012), I found better results for the mean and bias of the fractional parameter when T = 100 and the results in terms of the standard deviation and the MSE are very similar. However, for higher sample sizes such as 300 or 800, the robust procedure performs better. Empirical applications for seven monthly Latin-American inflation series with very small sample sizes contaminated by additive outliers are discussed.

Original languageEnglish
Pages (from-to)207-221
Number of pages15
JournalCommunications in Statistics: Simulation and Computation
Volume45
Issue number1
DOIs
StatePublished - 2 Jan 2016

Keywords

  • ARFIMA Errors
  • Additive Outliers
  • Inflation
  • Long Memory
  • Semiparametric estimation

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