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

Abstract:

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 ...

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Journal:
Studies in Nonlinear Dynamics and Econometrics
Volume:
8
Issue:
2
Publication date:
2004-01-01
URN:
uuid:316e201b-773e-414b-b45b-f2dac3921c40
Local pid:
oai:economics.ouls.ox.ac.uk:12884

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