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Forecasting inflation in the euro area using monthly time series models and quarterly econometric models

  • Espasa, Antoni
  • Albacete, Rebeca
Registered author(s):

    Economic agents and financial authorities require frequent updates to a path of accurate inflation forecasts and need forecasts to include an explanation of the factors by which they are determined. This paper studies how to approach this need, developing a method for analysing inflation in the euro area, measured according to HICP. Time series models using the most recent information on prices and an important functional and geographically disaggregation can provide monthly forecasts which are reasonably accurate, but they do not provide an explanation of the factors by which the forecast is determined. In this respect, it is important to enlarge the data set used considering explanatory variables and build congruent econometric models including variables which, following previous works by D. Hendry, capture disequilibria on different markets, goods and services, labour, monetary and international. The final result of this work shows that combining the forecasts from a monthly time series vector model, constructed on price subindexes from a disaggregation of the HICP by countries and sectors, with the forecasts derived from a quarterly econometric vector model on aggregate inflation and other economic variables, very accurate forecasts are obtained. Both vector models are specified including empirical cointegration restrictions, which in the first case capture the constrains necessary present between the trends of the price subindexes and in the second approximate the long-run restrictions postulated by economic theory.

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    Paper provided by Universidad Carlos III de Madrid. Departamento de Estadística in its series DES - Working Papers. Statistics and Econometrics. WS with number ws050401.

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    Date of creation: Jan 2005
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    Handle: RePEc:cte:wsrepe:ws050401
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    1. Hubrich, Kirstin, 2003. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Working Paper Series 0247, European Central Bank.
    2. Anindya Banerjee & Lynne Cockerell & Bill Russell, 2001. "An I(2) analysis of inflation and the markup," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 221-240.
    3. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
    4. Jordi Galí & Mark Gertler & J. David López-Salido, 2000. "European Inflation Dynamics," Working Papers 0020, Banco de España;Working Papers Homepage.
    5. Gordon de Brouwer & Neil R. Ericsson, 1995. "Modelling Inflation in Australia," RBA Research Discussion Papers rdp9510, Reserve Bank of Australia.
    6. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    7. Bowdler, Christopher & Jansen, Eilev S., 2004. "A markup model of inflation for the euro area," Working Paper Series 0306, European Central Bank.
    8. 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.
    9. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
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    11. James G. MacKinnon, 1990. "Critical Values for Cointegration Tests," Working Papers 1227, Queen's University, Department of Economics.
    12. Dreger, Christian, 2003. "A macroeconometric model for the Euro economy," IWH Discussion Papers 181, Halle Institute for Economic Research (IWH).
    13. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2003. "Leading Indicators for Euro Area Inflation and GDP Growth," CEPR Discussion Papers 3893, C.E.P.R. Discussion Papers.
    14. Ard Reijer & Peter Vlaar, 2006. "Forecasting Inflation: An Art as Well as a Science!," De Economist, Springer, vol. 154(1), pages 19-40, 03.
    15. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March.
    16. Espasa, Antoni & Albacete, Rebeca, 2004. "Econometric modelling for short-term inflation forecasting in the EMU," DES - Working Papers. Statistics and Econometrics. WS ws034309, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. repec:zbw:iwhdps:181 is not listed on IDEAS
    18. Charles I. Jones, 1995. "Time Series Tests of Endogenous Growth Models," The Quarterly Journal of Economics, Oxford University Press, vol. 110(2), pages 495-525.
    19. Jones, Charles I, 1995. "R&D-Based Models of Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 759-84, August.
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