A new method for approximating vector autoregressive processes by finite-state Markov chains
This paper proposes a new method for approximating vector autoregressions by a finite-state Markov chain. The method is more robust to the number of discrete values and tends to outperform the existing methods over a wide range of the parameter space, especially for highly persistent vector autoregressions with roots near the unit circle.
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| Date of creation: | 08 Jun 2011 |
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| Handle: | RePEc:pra:mprapa:33827 |
| Contact details of provider: | Postal: Phone: +49-(0)89-2180-2219 Fax: +49-(0)89-2180-3900 Web page: http://mpra.ub.uni-muenchen.de More information through EDIRC
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- Kopecky, Karen A. & Suen, Richard M. H., 2009. "Finite State Markov-Chain Approximations to Highly Persistent Processes," MPRA Paper 15122, University Library of Munich, Germany.
- Karen A. Kopecky & Richard M. H. Suen, 2009. "Finite State Markov-Chain Approximations to Highly Persistent Processes," Working Papers 200904, University of California at Riverside, Department of Economics, revised May 2009.
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