Inference and Forecasting for ARFIMA Models With an Application to US and UK Inflation

@inproceedings{Doornik2004InferenceAF,
  title={Inference and Forecasting for ARFIMA Models With an Application to US and UK Inflation},
  author={Jurgen A. Doornik and Marius Ooms},
  year={2004}
}
Practical aspects of likelihood-based inference and forecasting of series with long memory are considered, based on the arfima(p; d; q) model with deterministic regressors. Sampling characteristics of approximate and exact first-order asymptotic methods are compared. The analysis is extended using modified profile likelihood analysis, which is a higher-order asymptotic method suggested by Cox and Reid (1987). The relevance of the differences between the methods is investigated for models and… CONTINUE READING

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