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 techniques to allow for arbitrary positive-semidefinite covariance structures. Examples are provided for non-diagonal and singular non-diagonal error covariances.
Year of publication: |
2011
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Authors: | Terry, Stephen J. ; Knotek II, Edward S. |
Published in: |
Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 110.2011, 1, p. 4-6
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Publisher: |
Elsevier |
Subject: | Markov approximation Non-diagonal Singular covariance |
Saved in:
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