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Bayesian VAR Models for Forecasting Irish Inflation

Author

Listed:
  • 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)

Abstract

In this paper we focus on the development of multiple time series models for forecasting Irish Inflation. The Bayesian approach to the estimation of vector autoregressive (VAR) models is employed. This allows the estimated models combine the evidence in the data with any prior information which may also be available. A large selection of inflation indicators are assessed as potential candidates for inclusion in a VAR. The results confirm the significant improvement in forecasting performance which can be obtained by the use of Bayesian techniques. In general, however, forecasts of inflation contain a high degree of uncertainty. The results are also consistent with previous research in the Central Bank of Ireland which stresses a strong role for the exchange rate and foreign prices as a determinant of Irish prices.

Suggested Citation

  • Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian VAR Models for Forecasting Irish Inflation," Research Technical Papers 4/RT/98, Central Bank of Ireland.
  • Handle: RePEc:cbi:wpaper:4/rt/98
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    References listed on IDEAS

    as
    1. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Forecasting Irish inflation using ARIMA models," Research Technical Papers 3/RT/98, Central Bank of Ireland.
    2. 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.
    3. Victor Zarnowitz & Phillip Braun, 1993. "Twenty-two Years of the NBER-ASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance," NBER Chapters,in: Business Cycles, Indicators and Forecasting, pages 11-94 National Bureau of Economic Research, Inc.
    4. Robert B. Litterman, 1984. "Forecasting and policy analysis with Bayesian vector autoregression models," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
    5. 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.
    6. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    7. Alberola, Enrique & Tyrväinen, Timo, 1998. "Is there scope for inflation differentials in EMU : An empirical evaluation of the Balassa-Samuelsson model in EMU countries," Research Discussion Papers 15/1998, Bank of Finland.
    8. 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.
    9. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
    10. Kenny, Geoff & McGettigan, Donal, 1997. "A Monetary Approach to the Analysis of Inflation in Ireland," Research Technical Papers 4/RT/97, Central Bank of Ireland.
    11. Callan, Tim & FitzGerald, John, 1989. "Price Determination in Ireland: Effects of Changes in Exchange Rates and Exchange Rate Regimes," Papers ME179, Economic and Social Research Institute (ESRI).
    12. Kenny, Geoff & McGettigan, Donal, 1999. "Modelling Traded, Non-traded and Aggregate Inflation in a Small Open Economy: The Case of Ireland," Manchester School, University of Manchester, vol. 67(1), pages 60-88, January.
    13. 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.
    14. Stephen K. McNees, 1986. "The accuracy of two forecasting techniques: some evidence and an interpretation," New England Economic Review, Federal Reserve Bank of Boston, issue Mar, pages 20-31.
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    Citations

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    Cited by:

    1. Caraiani, Petre, 2010. "Forecasting Romanian GDP Using a BVAR Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 76-87, December.
    2. Matkovskyy, Roman, 2012. "The Index of the Financial Safety (IFS) of South Africa and Bayesian Estimates for IFS Vector-Autoregressive Model," MPRA Paper 42173, University Library of Munich, Germany.
    3. Rumler, Fabio & Valderrama, Maria Teresa, 2010. "Comparing the New Keynesian Phillips Curve with time series models to forecast inflation," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 126-144, August.
    4. Cindrella Shah & Nilesh Ghonasgi, 2016. "Determinants and Forecast of Price Level in India: a VAR Framework," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 57-86, June.
    5. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Forecasting Irish inflation using ARIMA models," Research Technical Papers 3/RT/98, Central Bank of Ireland.
    6. Quinn, Terry & Kenny, Geoff & Meyler, Aidan, 1999. "Inflation Analysis: An Overview," MPRA Paper 11361, University Library of Munich, Germany.
    7. 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).
    8. Patricio Jaramillo, 2009. "Estimación de Var Bayesianos para la Economía Chilena," Revista de Analisis Economico – Economic Analysis Review, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines, vol. 24(1), pages 101-126, Junio.
    9. Matkovskyy, Roman, 2012. "Прогнозування розвитку економіки України на основі баєсівських авторегресійних (BVAR) моделей з різними priors
      [Forecasting Economic Development of Ukraine based on BVAR models with different prior
      ," MPRA Paper 44725, University Library of Munich, Germany, revised Nov 2012.
    10. Roma, Moreno & Skudelny, Frauke & Benalal, Nicholai & Diaz del Hoyo, Juan Luis & Landau, Bettina, 2004. "To aggregate or not to aggregate? Euro area inflation forecasting," Working Paper Series 374, European Central Bank.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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