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Forecasting inflation in the European Monetary Union: A disaggregated approach by countries and by sectors

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Author Info
A. Espasa
E. Senra
R. Albacete
Abstract

Inflation in the European Monetary Union is measured by the Harmonized Indices of Consumer Prices (HICP) and it can be analysed by breaking down the aggregate index in two different ways. One refers to the breakdown into price indexes corresponding to big groups of markets throughout the European countries and another considers the HICP by countries. Both disaggregations are of interest because in each one, the component prices are not fully cointegrated, having more than one common factor in their trends. The paper shows that the breakdown by group of markets improves the European inflation forecasts and constitutes a framework in which general and specific indicators can be introduced for further improvements.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal The European Journal of Finance.

Volume (Year): 8 (2002)
Issue (Month): 4 (December)
Pages: 402-421
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Handle: RePEc:taf:eurjfi:v:8:y:2002:i:4:p:402-421

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Related research
Keywords: Core Inflation; Cointegration; Common Factor; Univariate Models; Veqcm; Bottom-UP; Approach;

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  2. Garcia-Ferrer, Antonio, et al, 1987. "Macroeconomic Forecasting Using Pooled International Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 53-67, January.
  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. [Downloadable!] (restricted)
  4. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254. [Downloadable!] (restricted)
  5. Tobias, Justin & Zellner, Arnold, 2004. "A Note on Aggregation, Disaggregation and Forecasting Performance," Staff General Research Papers 12024, Iowa State University, Department of Economics.
    Other versions:
  6. Balke, Nathan S & Fomby, Thomas B, 1994. "Large Shocks, Small Shocks, and Economic Fluctuations: Outliers in Macroeconomic Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 181-200, April-Jun. [Downloadable!] (restricted)
    Other versions:
  7. Zellner, Arnold & Hong, Chansik, 1989. "Forecasting international growth rates using Bayesian shrinkage and other procedures," Journal of Econometrics, Elsevier, vol. 40(1), pages 183-202, January. [Downloadable!] (restricted)
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  8. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics. [Downloadable!]
  2. Kitov, Ivan, 2007. "Inflation, unemployment, labor force change in European countries," MPRA Paper 14557, University Library of Munich, Germany. [Downloadable!]
  3. Jan Babecky & Jiri Podpiera, 2008. "Inflation Forecasts Errors in the Czech Republic: Evidence from a Panel of Institutions," Occasional Publications - Chapters in Edited Volumes, in: Katerina Smidkova (ed.), Evaluation of the Fulfilment of the CNB's Inflation Targets 1998-2007, chapter 6, pages 77-85 Czech National Bank, Research Department. [Downloadable!]
  4. Carlos Capistrán & Christian Constandse & Manuel Ramos Francia, 2009. "Using Seasonal Models to Forecast Short-Run Inflation in Mexico," Working Papers 2009-05, Banco de México. [Downloadable!]
  5. Juan de Dios Tena & Antoni Espasa & Gabriel Pino, 2008. "Forecasting Spanish inflation using information from different sectors and geographical areas," Statistics and Econometrics Working Papers ws080101, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
  6. David F. Hendry & Kirstin Hubrich, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank. [Downloadable!]
    Other versions:
  7. Antoni Espasa & Rebeca Albacete, 2004. "Econometric Modelling For Short-Term Inflation Forecasting In The Emu," Statistics and Econometrics Working Papers ws034309, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
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