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

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  • Terry, Stephen J.
  • Knotek II, Edward S.

Abstract

Discrete Markov chains are helpful for approximating vector autoregressive processes in computational work. We relax G. Tauchen (1986) [Finite state Markov-chain approximations to univariate and vector autoregressions. Economics Letters 20, 177-181] in practice using multivariate-normal integration techniques to allow for arbitrary positive-semidefinite covariance structures. Examples are provided for non-diagonal and singular non-diagonal error covariances.

Suggested Citation

  • Terry, Stephen J. & Knotek II, Edward S., 2011. "Markov-chain approximations of vector autoregressions: Application of general multivariate-normal integration techniques," Economics Letters, Elsevier, vol. 110(1), pages 4-6, January.
  • Handle: RePEc:eee:ecolet:v:110:y:2011:i:1:p:4-6
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    References listed on IDEAS

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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 371-396, 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. Carlos Hatchondo, Juan & Martinez, Leonardo & Sánchez, Juan M., 2015. "Mortgage defaults," Journal of Monetary Economics, Elsevier, vol. 76(C), pages 173-190.
      • Hatchondo, Juan Carlos & Martinez, Leonardo & Sánchez, Juan M., 2011. "Mortgage defaults," Working Papers 2011-019, Federal Reserve Bank of St. Louis, revised 31 Jul 2015.
      • Leonardo Martinez & Juan Carlos Hatchondo & Juan M. Sanchez, 2012. "Mortgage Defaults," IMF Working Papers 12/26, International Monetary Fund.
      • Juan Carlos Hatchondo & Leonardo Martinez & Juan M. Sanchez, 2011. "Mortgage defaults," Working Paper 11-05, Federal Reserve Bank of Richmond.
      • Juan Carlos Hatchondo & Leonardo Martinez & Juan M. Sanchez, 2015. "Mortgage Defaults," Caepr Working Papers 2015-011 Classification-D, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
    2. 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.
    3. Galindev, Ragchaasuren & Lkhagvasuren, Damba, 2010. "Discretization of highly persistent correlated AR(1) shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 34(7), pages 1260-1276, July.
    4. 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.
    5. Groneck, Max & Wallenius, Johanna, 2017. "It Sucks to Be Single! Marital Status and Redistribution of Social Security," SSE Working Paper Series in Economics 2017:1, Stockholm School of Economics.
    6. Nikolay Gospodinov & Damba Lkhagvasuren, 2014. "A Moment‐Matching Method For Approximating Vector Autoregressive Processes By Finite‐State Markov Chains," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 843-859, August.
    7. Gete, Pedro & Porchia, Paolo, 2010. "Fertility and Consumption when Having a Child is a Risky Investment," MPRA Paper 27885, University Library of Munich, Germany.
    8. Sergio J. Rey & Wei Kang & Levi Wolf, 2016. "The properties of tests for spatial effects in discrete Markov chain models of regional income distribution dynamics," Journal of Geographical Systems, Springer, vol. 18(4), pages 377-398, October.
    9. Andrea Gamba & Alexander J. Triantis, 2014. "Corporate Risk Management: Integrating Liquidity, Hedging, and Operating Policies," Management Science, INFORMS, vol. 60(1), pages 246-264, January.
    10. Edward S. Knotek & Stephen J. Terry, 2008. "Alternative methods of solving state-dependent pricing models," Research Working Paper RWP 08-10, Federal Reserve Bank of Kansas City.

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