GIBBSVAR—Gibbs Sampling for BVAR
GIBBSVAR—Gibbs Sampling for BVAR
GIBBSVAR.RPF is an example of Gibbs sampling applied to a Bayesian VAR with a "Minnesota" prior. A newer version of this has been posted as GIBBSVARBUILD.RPF
Re: GIBBSVAR—Gibbs Sampling for BVAR
Is there any reference to a paper/textbook that uses Gibbs Sampling for BVAR model?
Re: GIBBSVAR—Gibbs Sampling for BVAR
Lots of them, but probably the first to look at it carefully is
Kadiyala, K., & Karlsson, S. (1997). "Numerical Methods for Estimation and Inference in Bayesian VAR-Models." Journal of Applied Econometrics, 12(2), 99-132.
Kadiyala, K., & Karlsson, S. (1997). "Numerical Methods for Estimation and Inference in Bayesian VAR-Models." Journal of Applied Econometrics, 12(2), 99-132.
Re: GIBBSVAR—Gibbs Sampling for BVAR
Karlsson has a fairly exhaustive survey in the Handbook of Economic Forecasting published several years ago:
Sune Karlsson,
Chapter 15 - Forecasting with Bayesian Vector Autoregression,
Editor(s): Graham Elliott, Allan Timmermann,
Handbook of Economic Forecasting,
Elsevier,
Volume 2, Part B,
2013,
Pages 791-897,
ISSN 1574-0706,
ISBN 9780444627315,
https://doi.org/10.1016/B978-0-444-62731-5.00015-4.
(http://www.sciencedirect.com/science/ar ... 7315000154)
Abstract: This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and special attention is given to the implementation of the simulation algorithm.
Keywords: Markov chain Monte Carlo; Structural VAR; Cointegration; Conditional forecasts; Time-varying parameters; Stochastic volatility; Model selection; Large VAR
Sune Karlsson,
Chapter 15 - Forecasting with Bayesian Vector Autoregression,
Editor(s): Graham Elliott, Allan Timmermann,
Handbook of Economic Forecasting,
Elsevier,
Volume 2, Part B,
2013,
Pages 791-897,
ISSN 1574-0706,
ISBN 9780444627315,
https://doi.org/10.1016/B978-0-444-62731-5.00015-4.
(http://www.sciencedirect.com/science/ar ... 7315000154)
Abstract: This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and special attention is given to the implementation of the simulation algorithm.
Keywords: Markov chain Monte Carlo; Structural VAR; Cointegration; Conditional forecasts; Time-varying parameters; Stochastic volatility; Model selection; Large VAR
Last bumped by TomDoan on Thu Mar 21, 2024 11:01 am.
Todd Clark
Economic Research Dept.
Federal Reserve Bank of Cleveland
Economic Research Dept.
Federal Reserve Bank of Cleveland