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Comparing the bias and misspecification in ARFIMA models
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Smith, Jeremy, Taylor, Nick and Yadav, Sanjay (1997) Comparing the bias and misspecification in ARFIMA models. Journal of Time Series Analysis, Volume 18 (Number 5). pp. 507-527. doi:10.1111/1467-9892.00065 ISSN 0143-9782.
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Official URL: http://dx.doi.org/10.1111/1467-9892.00065
Abstract
We investigate the bias in both the short-term and long-term parameters for a range of autoregressive fractional integrated moving-average (ARFIMA) models using both semi-parametric and maximum likelihood (ML) estimation methods. The results suggest that, provided the correct model is estimated, the ML method outperforms the semi-parametric methods in terms of the bias and smaller mean square errors in both the long-term and short-term parameter estimates. These biases often cause model selection criteria to select an incorrect ARFIMA specification. Taking account of the potential misspecification the biases associated with the ML procedure tend to increase, although it continues to have a smaller worst-case bias than either of the semi-parametric procedures.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Social Sciences > Economics | ||||
Journal or Publication Title: | Journal of Time Series Analysis | ||||
Publisher: | Wiley-Blackwell Publishing Ltd. | ||||
ISSN: | 0143-9782 | ||||
Official Date: | 1997 | ||||
Dates: |
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Volume: | Volume 18 | ||||
Number: | Number 5 | ||||
Page Range: | pp. 507-527 | ||||
DOI: | 10.1111/1467-9892.00065 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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