Numerical Aspects of Bayesian VAR-modeling

In Bayesian analysis of VAR-models, and especially in forecasting applications, the Minnesota prior of Litterman is frequently used. In many cases other prior distributions provide better forecasts and are preferable from a theoretical standpoint. This paper considers the numerical procedures needed to implement these prior distributions. In addition we also report on the forecasting performance of the different prior distributions considered in the paper.

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Year of publication:	1994-03
Authors:	Kadiyala, K. Rao ; Karlsson, Sune
Institutions:	Economics Institute for Research (SIR), Handelshögskolan i Stockholm
Subject:	Monte Carlo integration \| importance sampling \| Gibbs sampling \| antithetic variates \| forecasting

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Extent:	application/zip text/plain
Series:	SSE/EFI Working Paper Series in Economics and Finance.
Type of publication:	Book / Working Paper
Notes:	Published in Journal of Applied Econometrics, 1997, pages 99-132 The text is part of a series Working Paper Series in Economics and Finance Number 12 43 pages
Classification:	C11 - Bayesian Analysis ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C32 - Time-Series Models ; C53 - Forecasting and Other Model Applications
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005649366