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Regional Inflation Dynamics within and across Euro Area and a Comparison with the US

  • Guenter Beck

    (Goethe University Frankfurt Kirstin Hubrich, Research Department, European Central Bank)

  • Massimiliano Marcellino

    (IEP-Bocconi University, IGIER and CEPR)

We investigate co-movements in inflation dynamics within and across euro area regions and find it important for monetary policy to monitor regional inflation dynamics to enhance the understanding of aggregate inflation. We employ a model where regional inflation dynamics are explained by common euro area and country specific factors and an idiosyncratic regional component. We find substantial common area wide component, that can be related to common euro area monetary policy, to exchange rate and oil prices changes. The effects of the area wide factors differ across regions, however. We also find a substantial national component. Our findings do not differ substantially before and after EMU. Analysing US regional inflation developments yields similar results regarding the relevance of common US factors.

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File URL: http://repec.org/sce2006/up.5654.1141119179.pdf
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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 338.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:338
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  1. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
  2. Hendry, David F & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
  3. James G. MacKinnon, 2010. "Critical Values for Cointegration Tests," Working Papers 1227, Queen's University, Department of Economics.
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  7. Forni, Mario & Reichlin, Lucrezia, 2001. "Federal policies and local economies: Europe and the US," European Economic Review, Elsevier, vol. 45(1), pages 109-134, January.
  8. Kirstin Hubrich, 2004. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Computing in Economics and Finance 2004 230, Society for Computational Economics.
  9. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
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  12. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
  13. Banerjee, A. & Marcellino, M. & Osbat, C., 2000. "Some Cautions on the Use of Panel Methods for Integrated Series of Macro-economic Data," Economics Working Papers eco2000/20, European University Institute.
  14. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
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  16. Carlo Ambrogio Favero & Massimilano Marcellino & Francesca Neglia, . "Principal components at work: The empirical analysis of monetary policy with large datasets," Working Papers 223, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  17. Mario Forni & Domenico Giannone & Marco Lippi & Lucrezia Reichlin, 2007. "Opening the Black Box: Structural Factor Models with Large Cross-Sections," Center for Economic Research (RECent) 008, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
  18. Stephen G. Cecchetti & Nelson C. Mark & Robert J. Sonora, 2002. "Price Index Convergence Among United States Cities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1081-1099, November.
  19. George Kapetanios & Massimiliano Marcellino, 2003. "A Comparison of Estimation Methods for Dynamic Factor Models of Large Dimensions," Working Papers 489, Queen Mary University of London, School of Economics and Finance.
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