A new method for approximating vector autoregressive processes by finite-state Markov chains
Nikolay Gospodinov () and
MPRA Paper from University Library of Munich, Germany
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.
Keywords: Markov Chain; Vector Autoregressive Processes; Functional Equation; Numerical Methods; Moment Matching; Numerical Integration (search for similar items in EconPapers)
JEL-codes: C10 C15 C60 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:33827
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