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.

MoreLess

Year of publication:	2011-06-08
Authors:	Gospodinov, Nikolay ; Lkhagvasuren, Damba

freely available

Full text |

More access options

Check Google Scholar

In German libraries (KVK)

I need help

More details

Type of publication:	Book / Working Paper
Language:	English
Notes:	Gospodinov, Nikolay and Lkhagvasuren, Damba (2011): A new method for approximating vector autoregressive processes by finite-state Markov chains.
Classification:	C10 - Econometric and Statistical Methods: General. General ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C60 - Mathematical Methods and Programming. General
Source:	BASE

Persistent link: https://www.econbiz.de/10015228782