Markov-chain approximations of vector autoregressions: Application of general multivariate-normal integration techniques

Discrete Markov chains are helpful for approximating vector autoregressive processes in computational work. We relax G. Tauchen (1986) [Finite state Markov-chain approximations to univariate and vector autoregressions. Economics Letters 20, 177–181] in practice using multivariate-normal integration...

Full description

Saved in:
Bibliographic Details
Published in:Economics letters 2011, Vol.110 (1), p.4-6
Main Authors: Terry, Stephen J., Knotek, Edward S.
Format: Article
Language:English
Subjects:
Cointegration
Econometric models
Markov approximation
Markov approximation Non-diagonal Singular covariance
Markovian processes
Non-diagonal
Singular covariance
Vector-autoregressive models
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Discrete Markov chains are helpful for approximating vector autoregressive processes in computational work. We relax G. Tauchen (1986) [Finite state Markov-chain approximations to univariate and vector autoregressions. Economics Letters 20, 177–181] in practice using multivariate-normal integration techniques to allow for arbitrary positive-semidefinite covariance structures. Examples are provided for non-diagonal and singular non-diagonal error covariances.
ISSN:0165-1765
1873-7374
DOI:10.1016/j.econlet.2010.09.008