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Forecasting irish inflation using ARIMA models

  • Meyler, Aidan
  • Kenny, Geoff
  • Quinn, Terry

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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File URL: http://mpra.ub.uni-muenchen.de/11359/1/MPRA_paper_11359.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 11359.

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Date of creation: Dec 1998
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Publication status: Published in Central Bank and Financial Services Authority of Ireland Technical Paper Series 3/RT/98.1998(1998): pp. 1-48
Handle: RePEc:pra:mprapa:11359
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Web page: http://mpra.ub.uni-muenchen.de

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  1. Dotsey, Michael & Ireland, Peter, 1996. "The welfare cost of inflation in general equilibrium," Journal of Monetary Economics, Elsevier, vol. 37(1), pages 29-47, February.
  2. Martin Feldstein, 1996. "The Costs and Benefits of Going from Low Inflation to Price Stability," NBER Working Papers 5469, National Bureau of Economic Research, Inc.
  3. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian VAR Models for Forecasting Irish Inflation," MPRA Paper 11360, University Library of Munich, Germany.
  4. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
  5. Michael F. Bryan & Stephen G. Cecchetti, 1993. "Measuring Core Inflation," NBER Working Papers 4303, National Bureau of Economic Research, Inc.
  6. Víctor Gómez & Agustín Maravall, 1998. "Automatic Modeling Methods for Univariate Series," Banco de Espa�a Working Papers 9808, Banco de Espa�a.
  7. Stephen G. Cecchetti, 1995. "Inflation Indicators and Inflation Policy," NBER Working Papers 5161, National Bureau of Economic Research, Inc.
  8. Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
  9. Stockton, David J & Glassman, James E, 1987. "An Evaluation of the Forecast Performance of Alternative Models of Inflation," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 108-17, February.
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