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

  • Antoni Espasa

    (Departamento de Estadística, Universidad Carlos III de Madrid, Spain)

  • Rebeca Albacete

    (Departamento de Economía Aplicada, Universidad Autónoma de Madrid)

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    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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    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 26 (2007)
    Issue (Month): 5 ()
    Pages: 303-316

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    Handle: RePEc:jof:jforec:v:26:y:2007:i:5:p:303-316
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