Forecasting Euro Area Aggregates with Bayesian VAR and VECM Models
AbstractThis paper focuses on Bayesian Vector Auto-Regressive (BVAR) models for the euro area. A modified hyperparameterization scheme based on the Minnesota prior that takes into account the economic nature of the variables in the model is used. The merits of incorporating long-run relationships are also discussed. Alternative methods to estimate eventual cointegrating relations in the variables are considered, and the problem of choice of appropriate prior distributions for BVAR with Error Correction Mechanism (BECM) models is addressed. Results show that using a flat prior on factor loadings can seriously endanger the forecasting performance of BECM models. Overall, the BVAR model in levels outperforms all other models across variables and forecasting horizons. This is in contrast with other empirical studies where some gains could be obtained when incorporating long-run relationships in the model.
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Bibliographic InfoPaper provided by Banco de Portugal, Economics and Research Department in its series Working Papers with number w200304.
Date of creation: 2003
Date of revision:
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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