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Forecasting irish inflation using ARIMA models

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

Abstract

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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Bibliographic Info

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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Keywords: NAIRU; inflation; unobserved components; kalman filter;

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References

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  1. 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.
  2. Stephen G. Cecchetti, 1995. "Inflation Indicators and Inflation Policy," NBER Working Papers 5161, National Bureau of Economic Research, Inc.
  3. 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.
  4. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, Econometric Society, vol. 57(6), pages 1361-1401, November.
  5. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian Var Models for Forecasting Irish Inflation," Research Technical Papers 4/RT/98, Central Bank of Ireland.
  6. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
  7. Michael F. Bryan & Stephen G. Cecchetti, 1993. "Measuring Core Inflation," NBER Working Papers 4303, National Bureau of Economic Research, Inc.
  8. Michael Dotsey & Peter Ireland, 1994. "The welfare cost of inflation in general equilibrium," Working Paper, Federal Reserve Bank of Richmond 94-04, Federal Reserve Bank of Richmond.
  9. Víctor Gómez & Agustín Maravall, 1998. "Automatic Modeling Methods for Univariate Series," Banco de Espa�a Working Papers 9808, Banco de Espa�a.
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Citations

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Cited by:
  1. repec:asg:wpaper:1014 is not listed on IDEAS
  2. Gatt, William, 2013. "Forecasting inflation at the Central Bank of Malta�," MPRA Paper 56876, University Library of Munich, Germany.
  3. Friedrich Fritzer & Gabriel Moser & Johann Scharler, 2002. "Forecasting Austrian HICP and its Components using VAR and ARIMA Models," Working Papers 73, Oesterreichische Nationalbank (Austrian Central Bank).
  4. Meyler, Aidan, 1999. "A statistical measure of core inflation," MPRA Paper 11362, University Library of Munich, Germany.
  5. Quinn, Terry & Kenny, Geoff & Meyler, Aidan, 1999. "Inflation Analysis: An Overview," MPRA Paper 11361, University Library of Munich, Germany.
  6. Meyler, Aidan, 1999. "The Non-Accelerating Inflation Rate of Unemployment (NAIRU) in a Small Open Economy: The Irish Context," Research Technical Papers 5/RT/99, Central Bank of Ireland.
  7. Benalal, Nicholai & Diaz del Hoyo, Juan Luis & Landau, Bettina & Roma, Moreno & Skudelny, Frauke, 2004. "To aggregate or not to aggregate? Euro area inflation forecasting," Working Paper Series 0374, European Central Bank.
  8. Akhter, Tahsina, 2013. "Short-Term Forecasting of Inflation in Bangladesh with Seasonal ARIMA Processes," MPRA Paper 43729, University Library of Munich, Germany.
  9. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian VAR Models for Forecasting Irish Inflation," MPRA Paper 11360, University Library of Munich, Germany.
  10. Feridun, Mete, 2006. "Forecasting Inflation in Developing Nations: The Case of Pakistan," MPRA Paper 1024, University Library of Munich, Germany, revised 2006.
  11. repec:asg:wpaper:1027 is not listed on IDEAS
  12. Aguilar, Ruben & Valdivia, Daney, 2011. "Precios de exportación de gas natural para Bolivia: Modelación y pooling de pronósticos
    [Bolivian natural gas export prices: Modeling and forecast pooling]
    ," MPRA Paper 35485, University Library of Munich, Germany.
  13. KUMAR Manoj & ANAND Madhu, 2014. "An Application Of Time Series Arima Forecasting Model For Predicting Sugarcane Production In India," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 9(1), pages 81-94, April.
  14. Jeff Tayman & Stanley Smith & Jeffrey Lin, 2007. "Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models," Population Research and Policy Review, Springer, vol. 26(3), pages 347-369, June.

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