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Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models

  • Kenneth Judd
  • Lilia Maliar
  • Serguei Maliar

We develop numerically stable stochastic simulation approaches for solving dynamic economic models. We rely on standard simulation procedures to simultaneously compute an ergodic distribution of state variables, its support and the associated decision rules. We differ from existing methods, however, in how we use simulation data to approximate decision rules. Instead of the usual least-squares approximation methods, we examine a variety of alternatives, including the least-squares method using SVD, Tikhonov regularization, least-absolute deviation methods, principal components regression method, all of which are numerically stable and can handle ill-conditioned problems. These new methods enable us to compute high-order polynomial approximations without encountering numerical problems. Our approaches are especially well suitable for high-dimensional applications in which other methods are infeasible.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 15296.

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Date of creation: Aug 2009
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Publication status: published as Kenneth L. Judd, Lilia Maliar and Serguei Maliar, (2011). “Numerically Stable and Accurate Stochastic Simulation Methods for Solving Dynamic Models" and "Supplement", Quantitative Economics 2, 173-2010.
Handle: RePEc:nbr:nberwo:15296
Note: EFG TWP
Contact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
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  1. Santos, Manuel S., 1999. "Numerical solution of dynamic economic models," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 5, pages 311-386 Elsevier.
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  8. Lilia Maliar & Serguei Maliar, 2002. "The Representative Consumer In The Neoclassical Growth Model With Idiosyncratic Shocks," Working Papers. Serie AD 2002-20, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
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  14. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
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