English, Article, Journal or magazine article edition: Discretization of Highly-Persistent Correlated AR(1) Shocks Damba Lkhagvasuren; Ragchaasuren Galindev

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Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Discretization of Highly-Persistent Correlated AR(1) Shocks
Author
  • Damba Lkhagvasuren
  • Ragchaasuren Galindev
Physical Description
  • preprint
Notes
  • The finite state Markov-Chain approximation method developed by Tauchen (1986) and Tauchen and Hussey (1991) is widely used in economics, finance and econometrics in solving for functional equations where state variables follow an autoregressive process. For highly persistent processes, the method requires a large number of discrete values for the state variables to produce close approximations which leads to an undesirable reduction in computational speed, especially in multidimensional case. This paper proposes an alternative method of discretizing vector autoregressions. The method works well as an approximation and its numerical efficiency applies to a wide range of the parameter space.
  • Finite State Markov-Chain Approximation, Transition Matrix, Numerical Methods, VAR,
  • RePEc:crd:wpaper:08012
Language
  • English
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