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A multi-country trend indicator for euro area inflation: computation and properties

In: Empirical studies of structural changes and inflation

  • Elena Angelini

    (European Central Bank)

  • Jérôme Henry

    (European Central Bank)

  • Ricardo Mestre

    (European Central Bank)

This paper applies the 'diffusion indices' approach proposed by Stock and Watson [1998] to the euro area. Following their methodology a set of factors are extracted from a balanced and unbalanced panel dataset comprising nominal variables for 11 countries of the euro area. The estimated factors appear to be fairly stable over time. It is also shown that the first factor is cointegrated with area wide HICP and private consumption deflator supporting the idea that it represents 'a common trend of inflation' for the euro area. The other factors, which are stationary instead, seem to capture dispersion of inflation across countries. There is moreover evidence of unilateral causality from the first factor with respect to HICP, suggesting that this factor could be valuably employed in forecasting euro area inflation JEL Classification: E52, E58

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This chapter was published in:
  • Bank for International Settlements, 2001. "Empirical studies of structural changes and inflation," BIS Papers, Bank for International Settlements, number 03, March.
  • This item is provided by Bank for International Settlements in its series BIS Papers chapters with number 03-04.
    Handle: RePEc:bis:bisbpc:03-04
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    1. Vogelsang, T.I. & Perron, P., 1991. "Nonstationary and Level Shifts With An Application To Purchasing Power Parity," Papers 359, Princeton, Department of Economics - Econometric Research Program.
    2. Mark A. Wynne, 1999. "Core inflation: a review of some conceptual issues," Working Papers 9903, Federal Reserve Bank of Dallas.
    3. Davis, E Philip & Fagan, Gabriel, 1997. "Are Financial Spreads Useful Indicators of Future Inflation and Output Growth in EU Countries?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(6), pages 701-14, Nov.-Dec..
    4. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-47, February.
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    7. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
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    11. Stephen G. Cecchetti, 1996. "Measuring Short-Run Inflation for Central Bankers," NBER Working Papers 5786, National Bureau of Economic Research, Inc.
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    13. Hall, S G, 1991. "The Effect of Varying Length VAR Models on the Maximum Likelihood Estimates of Cointegrating Vectors," Scottish Journal of Political Economy, Scottish Economic Society, vol. 38(4), pages 317-23, November.
    14. Phillips, P. C. B. & Ouliaris, S., 1988. "Testing for cointegration using principal components methods," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 205-230.
    15. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
    16. Fagan, Gabriel & Henry, Jérôme & Mestre, Ricardo, 2001. "An area-wide model (AWM) for the euro area," Working Paper Series 0042, European Central Bank.
    17. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
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