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BVAR models in the context of cointegration: A Monte Carlo experiment


Author Info

  • Luis J. Álvarez

    (Banco de España)

  • Fernando C. Ballabriga



The kind of prior typically employed in Bayesian vector autoregression (BVAR) analysis has aroused widespread suspicion about the ability of these models to capture long-run patterns. This paper specifies a bivariate cointegrated stochastic process and conducts a Monte Carlo experiment to assess the small sample performance of two classical and two Bayesian estimation methods commonly applied to VAR models. In addition, a proposal to introduce a new dimension to the prior information in order to allow for explicit account of long-run restrictions is suggested and evaluated in the light of the experiment. The results of the experiment show that: the Minnesota -type prior with hyperparameter search performs well, suggesting that the prevalent suspicion about the inability of this prior to capture long-run patterns is not well-grounded; the fine-tunning of the prior is crucial; and adding long-run restrictions to the prior does not provide improvements in the case analyzed.

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Bibliographic Info

Paper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 9405.

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Length: 41 pages
Date of creation: 1994
Date of revision:
Handle: RePEc:bde:wpaper:9405

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Keywords: Bayesian vector autoregression; cointegration; Monte Carlo experiment;

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Cited by:
  1. Andrea Nobili, 2005. "Forecasting Output Growth And Inflation In The Euro Area: Are Financial Spreads Useful?," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area 544, Bank of Italy, Economic Research and International Relations Area.
  2. Ballabriga, Fernando & Sebastian, Miguel & Valles, Javier, 1999. "European asymmetries," Journal of International Economics, Elsevier, Elsevier, vol. 48(2), pages 233-253, August.
  3. Enrique M. Quilis(1), . "Modelos Bvar: Especificación, Estimación E Inferencia," Working Papers, Instituto de Estudios Fiscales 8-02 Classification-JEL :, Instituto de Estudios Fiscales.
  4. Ricardo Mourinho Félix & Luís Catela Nunes, 2003. "Forecasting Euro Area Aggregates with Bayesian VAR and VECM Models," Working Papers, Banco de Portugal, Economics and Research Department w200304, Banco de Portugal, Economics and Research Department.
  5. Sonsoles Castillo & Fernando C. Ballabriga, 2003. "BBVA-ARIES: a forecasting and simulation model for EMU," Journal of Forecasting, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 22(5), pages 411-426.
  6. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2014. "Forecasting with Bayesian Global Vector Autoregressive Models: A Comparison of Priors," Working Papers, Oesterreichische Nationalbank (Austrian Central Bank) 189, Oesterreichische Nationalbank (Austrian Central Bank).
  7. Matteo Ciccarelli & Alessandro Rebucci, 2003. "Bayesian Vars," IMF Working Papers 03/102, International Monetary Fund.


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