caa a22 4500 378929836 CHVBK 20180305123626.0 cr unu---uuuuu 161128e20040518xx s 000 0 eng 10.2202/1558-3708.1218 doi (NATIONALLICENCE)gruyter-10.2202/1558-3708.1218 Inference and Forecasting for ARFIMA Models With an Application to US and UK Inflation [Elektronische Daten] [Jurgen A Doornik, Marius Ooms] 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 forecasts of monthly core consumer price inflation in the US and quarterly overall consumer price inflation in the UK. ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston Doornik Jurgen A. Nuffield College, Oxford, jurgen.doornik@nuffield.ox.ac.uk aut Ooms Marius Free University Amsterdam, mooms@feweb.vu.nl aut Studies in Nonlinear Dynamics & Econometrics De Gruyter 8/2(2004-05-18) 8:2 2004 8 snde https://doi.org/10.2202/1558-3708.1218 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.2202/1558-3708.1218 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Doornik Jurgen A. Nuffield College, Oxford, jurgen.doornik@nuffield.ox.ac.uk aut NATIONALLICENCE 700 1- Ooms Marius Free University Amsterdam, mooms@feweb.vu.nl aut NATIONALLICENCE 773 0- Studies in Nonlinear Dynamics & Econometrics De Gruyter 8/2(2004-05-18) 8:2 2004 8 snde CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter