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Markov-chain approximations of vector autoregressions: application of general multivariate-normal integration techniques

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  • Edward S. Knotek II
  • Stephen Terry

Abstract

Discrete Markov chains can be useful to approximate vector autoregressive processes for economists doing computational work. One such approximation method first presented by Tauchen (1986) operates under the general theoretical assumption of a transformed VAR with diagonal covariance structure for the process error term. We demonstrate one simple method of more conveniently treating this approximation problem in practice using readily available multivariate-normal integration techniques to allow for arbitrary positive-semidefinite covariance structures. Examples are provided using processes with non-diagonal and singular non-diagonal error covariances.

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Paper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number RWP 08-02.

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Date of creation: 2008
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Handle: RePEc:fip:fedkrw:rwp08-02

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  1. Tauchen, George & Hussey, Robert, 1991. "Quadrature-Based Methods for Obtaining Approximate Solutions to Nonlinear Asset Pricing Models," Econometrica, Econometric Society, vol. 59(2), pages 371-96, March.
  2. Tauchen, George, 1986. "Finite state markov-chain approximations to univariate and vector autoregressions," Economics Letters, Elsevier, vol. 20(2), pages 177-181.
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Cited by:
  1. Lkhagvasuren, Damba & Galindev, Ragchaasuren, 2008. "Discretization of highly persistent correlated AR(1) shocks," MPRA Paper 22523, University Library of Munich, Germany.
  2. Juan Carlos Hatchondo & Leonardo Martinez & Juan M. Sanchez, 2011. "Mortgage defaults," Working Paper 11-05, Federal Reserve Bank of Richmond.
  3. Di Nicolo, G. & Gamba, A. & Lucchetta, M., 2011. "Capital Regulation, Liquidity Requirements and Taxation in a Dynamic Model of Banking," Discussion Paper 2011-090, Tilburg University, Center for Economic Research.
  4. : Andrea Gamba & : Alexander J. Triantis, 2013. "Corporate Risk Management: Integrating Liquidity, Hedging and Operating Policies," Working Papers wpn13-07, Warwick Business School, Finance Group.
  5. Gospodinov, Nikolay & Lkhagvasuren, Damba, 2011. "A new method for approximating vector autoregressive processes by finite-state Markov chains," MPRA Paper 33827, University Library of Munich, Germany.
  6. Edward S. Knotek II & Stephen Terry, 2008. "Alternative methods of solving state-dependent pricing models," Research Working Paper RWP 08-10, Federal Reserve Bank of Kansas City.
  7. Pedro Gete and Paolo Porchia, 2011. "Fertility and Consumption when Having a Child is a Risky Investment," Working Papers gueconwpa~11-11-03, Georgetown University, Department of Economics.
  8. Gospodinov, Nikolay & Lkhagvasuren, Damba, 2013. "A moment-matching method for approximating vector autoregressive processes by finite-state Markov chains," Working Paper 2013-05, Federal Reserve Bank of Atlanta.

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