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.
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Volume (Year): 110 (2011)
Issue (Month): 1 (January)
Pages: 4-6
| Handle: | RePEc:eee:ecolet:v:110:y:2011:i:1:p:4-6 |
| Contact details of provider: | Web page: http://www.elsevier.com/locate/ecolet
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- Tauchen, George & Hussey, Robert, 1991. "Quadrature-Based Methods for Obtaining Approximate Solutions to Nonlinear Asset Pricing Models," Econometrica, Econometric Society, vol. 59(2), pages 371-96, March.
- Tauchen, George, 1986. "Finite state markov-chain approximations to univariate and vector autoregressions," Economics Letters, Elsevier, vol. 20(2), pages 177-181.
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