Kenny, Geoff (Central Bank and Financial Services Authority of Ireland) Meyler, Aidan (Central Bank and Financial Services Authority of Ireland) Quinn, Terry (Central Bank and Financial Services Authority of Ireland)
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This paper outlines the practical steps which need to be undertaken to use autoregressive integrated moving average (ARIMA) time series models for forecasting Irish inflation. A framework for ARIMA forecasting is drawn up. It considers two alternative approaches to the issue of identifying ARIMA models - the Box Jenkins approach and the objective penalty function methods. The emphasis is on forecast performance which suggests more focus on minimising out-of-sample forecast errors than on maximising in-sample 'goodness of fit'. Thus, the approach followed is unashamedly one of 'model mining' with the aim of optimising forecast performance. Practical issues in ARIMA time series forecasting are illustrated with reference to the harmonised index of consumer prices (HICP) and some of its major sub-components.
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Paper provided by Central Bank & Financial Services Authority of Ireland (CBFSAI) in its series Research Technical Papers with number
3/RT/98.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Michael F. Bryan & Stephen G. Cecchetti, 1994.
"Measuring Core Inflation,"
NBER Chapters,
in: Monetary Policy, pages 195-219
National Bureau of Economic Research, Inc.
[Downloadable!]
Other versions:
Michael F. Bryan & Stephen G. Cecchetti, 1993.
"Measuring Core Inflation,"
NBER Working Papers
4303, National Bureau of Economic Research, Inc.
[Downloadable!] (restricted)
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)