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Discretization of highly persistent correlated AR(1) shocks
Ist Teil von
Journal of economic dynamics & control, 2010-07, Vol.34 (7), p.1260-1276
Ort / Verlag
Amsterdam: Elsevier B.V
Erscheinungsjahr
2010
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
The finite state Markov-chain approximation methods developed by
Tauchen (1986) and
Tauchen and Hussey (1991) are widely used in economics, finance and econometrics to solve functional equations in which state variables follow autoregressive processes. For highly persistent processes, the methods require 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 a multivariate case. This paper proposes an alternative method of discretizing multivariate autoregressive processes. This method can be treated as an extension of
Rouwenhorst's (1995) method which, according to our finding, outperforms the existing methods in the scalar case for highly persistent processes. The new method works well as an approximation that is much more robust to the number of discrete values for a wide range of the parameter space.