IMF Working Papers

Bayesian Vars: A Survey of the Recent Literature with An Application to the European Monetary System

By Matteo Ciccarelli, Alessandro Rebucci

May 1, 2003

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Matteo Ciccarelli, and Alessandro Rebucci. Bayesian Vars: A Survey of the Recent Literature with An Application to the European Monetary System, (USA: International Monetary Fund, 2003) accessed November 21, 2024
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

This paper reviews recent advances in the specification and estimation of Bayesian Vector Autoregressive models (BVARs). After describing the Bayesian principle of estimation, we first present the methodology originally developed by Litterman (1986) and Doan et al. (1984) and review alternative priors. We then discuss extensions of the basic model and address issues in forecasting and structural analysis. An application to the estimation of a system of time-varying reaction functions for four European central banks under the European Monetary System (EMS) illustrates how some of the results previously presented may be applied in practice.

Subject: Banking, Bayesian models, Econometric analysis, Estimation techniques, Financial services, Monetary systems, Money, Short term interest rates, Vector autoregression

Keywords: Bayesian models, Bayesian VAR, Data well, EMS, Estimation procedure, Estimation result, Estimation techniques, Gibbs sampling, Law of motion, Model parameter, Monetary systems, Mover accent, Parameter vector, Point estimate, Point estimates of the population moment, Sample data, Short term interest rates, Time series, Time- Varying Reaction Function, U.S. dollar, VAR estimation, Vector autoregression, WP

Publication Details

  • Pages:

    44

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2003/102

  • Stock No:

    WPIEA1022003

  • ISBN:

    9781451852639

  • ISSN:

    1018-5941

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