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Econometric modelling for short-term inflation forecasting in the euro area

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Author Info
Antoni Espasa (Departamento de Estadística, Universidad Carlos III de Madrid, Spain)
Rebeca Albacete (Departamento de Economía Aplicada, Universidad Autónoma de Madrid)
Abstract

This paper examines the problem of forecasting macro-variables which are observed monthly (or quarterly) and result from geographical and sectorial aggregation. The aim is to formulate a methodology whereby all relevant information gathered in this context could provide more accurate forecasts, be frequently updated, and include a disaggregated explanation as useful information for decision-making. The appropriate treatment of the resulting disaggregated data set requires vector modelling, which captures the long-run restrictions between the different time series and the short-term correlations existing between their stationary transformations. Frequently, due to a lack of degrees of freedom, the vector model must be restricted to a block-diagonal vector model. This methodology is applied in this paper to inflation in the euro area, and shows that disaggregated models with cointegration restrictions improve accuracy in forecasting aggregate macro-variables. Copyright © 2007 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1021
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 26 (2007)
Issue (Month): 5 ()
Pages: 303-316
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:jof:jforec:v:26:y:2007:i:5:p:303-316

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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