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A new method for approximating vector autoregressive processes by finite-state Markov chains

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  • Gospodinov, Nikolay
  • Lkhagvasuren, Damba

Abstract

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.

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File URL: http://mpra.ub.uni-muenchen.de/33827/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 33827.

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Date of creation: 08 Jun 2011
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Handle: RePEc:pra:mprapa:33827

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Keywords: Markov Chain; Vector Autoregressive Processes; Functional Equation; Numerical Methods; Moment Matching; Numerical Integration;

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  1. Edward S. Knotek II & Stephen Terry, 2008. "Markov-chain approximations of vector autoregressions: application of general multivariate-normal integration techniques," Research Working Paper RWP 08-02, Federal Reserve Bank of Kansas City.
  2. Floden, Martin, 2007. "A Note on the Accuracy of Markov-Chain Approximations to Highly Persistent AR(1)-Processes," Working Paper Series in Economics and Finance 656, Stockholm School of Economics.
  3. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-80, July.
  4. Kopecky, Karen A. & Suen, Richard M. H., 2009. "Finite State Markov-Chain Approximations to Highly Persistent Processes," MPRA Paper 17201, University Library of Munich, Germany.
  5. Damba Lkhagvasuren & Ragchaasuren Galindev, 2008. "Discretization of Highly-Persistent Correlated AR(1) Shocks," Working Papers 08012, Concordia University, Department of Economics, revised Nov 2008.
  6. Tauchen, George, 1986. "Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained from Financial Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(4), pages 397-416, October.
  7. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
  8. 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.
  9. 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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