Forecasting irish inflation using ARIMA models
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.
|Date of creation:||Dec 1998|
|Publication status:||Published in Central Bank and Financial Services Authority of Ireland Technical Paper Series 3/RT/98.1998(1998): pp. 1-48|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
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- Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998.
"Bayesian VAR Models for Forecasting Irish Inflation,"
11360, University Library of Munich, Germany.
- Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian Var Models for Forecasting Irish Inflation," Research Technical Papers 4/RT/98, Central Bank of Ireland.
- Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
- Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
- Michael F. Bryan & Stephen G. Cecchetti, 1994. "Measuring Core Inflation," NBER Chapters, in: Monetary Policy, pages 195-219 National Bureau of Economic Research, Inc.
- Michael F. Bryan & Stephen G. Cecchetti, 1993. "Measuring Core Inflation," NBER Working Papers 4303, National Bureau of Economic Research, Inc.
- Stephen G. Cecchetti, 1995. "Inflation Indicators and Inflation Policy," NBER Chapters, in: NBER Macroeconomics Annual 1995, Volume 10, pages 189-236 National Bureau of Economic Research, Inc.
- Stephen G. Cecchetti, 1995. "Inflation Indicators and Inflation Policy," NBER Working Papers 5161, National Bureau of Economic Research, Inc.
- Martin S. Feldstein, 1997. "The Costs and Benefits of Going from Low Inflation to Price Stability," NBER Chapters, in: Reducing Inflation: Motivation and Strategy, pages 123-166 National Bureau of Economic Research, Inc.
- 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.
- 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 108-117, February.
- 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.
- Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
- 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.
- Michael Dotsey & Peter N. Ireland, 1994. "The welfare cost of inflation in general equilibrium," Working Paper 94-04, Federal Reserve Bank of Richmond.
- Víctor Gómez & Agustín Maravall, 1998. "Automatic Modeling Methods for Univariate Series," Working Papers 9808, Banco de España;Working Papers Homepage.
- Tom Doan, "undated". "GMAUTOFIT: RATS procedure to perform automated ARIMA model selection (seasonal models)," Statistical Software Components RTS00078, Boston College Department of Economics.