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Discretization of Highly-Persistent Correlated AR(1) Shocks

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Abstract

The finite state Markov-Chain approximation method developed by Tauchen (1986) and Tauchen and Hussey (1991) is widely used in economics, finance and econometrics in solving for functional equations where state variables follow an autoregressive process. For highly persistent processes, the method requires 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 multidimensional case. This paper proposes an alternative method of discretizing vector autoregressions. The method works well as an approximation and its numerical efficiency applies to a wide range of the parameter space.

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Bibliographic Info

Paper provided by Concordia University, Department of Economics in its series Working Papers with number 08012.

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Length: 35 pages
Date of creation: Sep 2008
Date of revision: Nov 2008
Handle: RePEc:crd:wpaper:08012

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Keywords: Finite State Markov-Chain Approximation; Transition Matrix; Numerical Methods; VAR;

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References

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  1. Kopecky, Karen A. & Suen, Richard M. H., 2009. "Finite State Markov-Chain Approximations to Highly Persistent Processes," MPRA Paper 15122, University Library of Munich, Germany.
  2. Dale T. Mortensen & Christopher A. Pissarides, 1993. "Job Creation and Job Destruction in the Theory of Unemployment," CEP Discussion Papers dp0110, Centre for Economic Performance, LSE.
  3. 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.
  4. 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.
  5. Tauchen, George, 1986. "Finite state markov-chain approximations to univariate and vector autoregressions," Economics Letters, Elsevier, vol. 20(2), pages 177-181.
  6. Flodén, Martin, 2008. "A note on the accuracy of Markov-chain approximations to highly persistent AR(1) processes," Economics Letters, Elsevier, vol. 99(3), pages 516-520, June.
  7. Lu Zhang, 2005. "The Value Premium," Journal of Finance, American Finance Association, vol. 60(1), pages 67-103, 02.
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Cited by:
  1. Viktor Tsyrennikov & Serhiy Stepanchuk & Katrin Rabitsch, 2013. "International Portfolios: A Comparison of Solution Methods," 2013 Meeting Papers 1146, Society for Economic Dynamics.
  2. Karen A. Kopecky & Richard M. H. Suen, 2009. "Finite State Markov-Chain Approximations to Highly Persistent Processes," Working Papers 200904, University of California at Riverside, Department of Economics, revised May 2009.
  3. Fatih Guvenen, 2011. "Macroeconomics with hetereogeneity : a practical guide," Economic Quarterly, Federal Reserve Bank of Richmond, issue 3Q, pages 255-326.
  4. 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.
  5. repec:fip:fedreq:y:2011:i:3q:p:255-326:n:vol.97no.3 is not listed on IDEAS
  6. Damba Lkhagvasuren, 2005. "Big Locational Differences in Unemployment Despite High Labor Mobility," Working Papers 12002, Concordia University, Department of Economics, revised Feb 2012.
  7. Lkhagvasuren, Damba, 2014. "Education, mobility and the college wage premium," European Economic Review, Elsevier, vol. 67(C), pages 159-173.
  8. Paul Gomme & Damba Lkhagvasuren, 2013. "The Cyclicality of Search Intensity in a Competitive Search Model," Working Papers 13002, Concordia University, Department of Economics, revised Sep 2013.
  9. Zhao, Yan, 2013. "Borrowing constraints and the trade balance–output comovement," Economic Modelling, Elsevier, vol. 32(C), pages 34-41.
  10. 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.

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