A Note on the Accuracy of Markov-Chain Approximations to Highly Persistent AR(1)-Processes

Martin Flodén

No 656, SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics

Abstract: This note examines the accuracy of methods that are commonly used to approximate AR(1)-processes with discrete Markov chains. The quadrature-based method suggested by Tauchen and Hussey (1991) generates excellent approximations with a small number of nodes when the autocorrelation is low or modest. This method however has problems when the autocorrelation is high, as it typically is found to be in recent empirical studies of income processes. I suggest an alternative weighting function for the Tauchen-Hussey method, and I also note that the older method suggested by Tauchen (1986) is relatively robust to high autocorrelation.

Keywords: numerical methods; income processes; autoregressive process (search for similar items in EconPapers)
JEL-codes: C60 (search for similar items in EconPapers)
Pages: 9 pages
Date: 2007-03-12
New Economics Papers: this item is included in nep-ets
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: A note on the accuracy of Markov-chain approximations to highly persistent AR(1) processes (2008)
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