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Envelope condition method versus endogenous grid method for solving dynamic programming problems

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  • Maliar, Lilia
  • Maliar, Serguei

Abstract

We introduce an envelope condition method (ECM) for solving dynamic programming problems. The ECM method is simple to implement, dominates conventional value function iteration and is comparable in accuracy and cost to Carroll’s (2005) endogenous grid method. Codes are available.

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Bibliographic Info

Article provided by Elsevier in its journal Economics Letters.

Volume (Year): 120 (2013)
Issue (Month): 2 ()
Pages: 262-266

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Handle: RePEc:eee:ecolet:v:120:y:2013:i:2:p:262-266

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Web page: http://www.elsevier.com/locate/ecolet

Related research

Keywords: Numerical dynamic programming; Value function iteration; Endogenous grid; Envelope condition; Curse of dimensionality; Large scale;

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  1. Maliar, Serguei & Maliar, Lilia & Judd, Kenneth, 2011. "Solving the multi-country real business cycle model using ergodic set methods," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 207-228, February.
  2. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
  3. Francisco Barillas & Jesús Fernández-Villaverde, 2006. "A Generalization of the Endogenous Grid Method," Levine's Bibliography 122247000000001200, UCLA Department of Economics.
  4. S. Boragan Aruoba & Jesus Fernandez-Villaverde & Juan Francisco Rubio-Ramirez, 2003. "Comparing solution methods for dynamic equilibrium economies," Working Paper 2003-27, Federal Reserve Bank of Atlanta.
  5. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2011. "Numerically stable and accurate stochastic simulation approaches for solving dynamic economic models," Quantitative Economics, Econometric Society, vol. 2(2), pages 173-210, 07.
  6. Villemot, Sébastien, 2012. "Accelerating the resolution of sovereign debt models using an endogenous grid method," Dynare Working Papers 17, CEPREMAP.
  7. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2012. "Merging Simulation and Projection Approaches to Solve High-Dimensional Problems," NBER Working Papers 18501, National Bureau of Economic Research, Inc.
  8. Cai, Yongyang & Judd, Kenneth L., 2012. "Dynamic programming with shape-preserving rational spline Hermite interpolation," Economics Letters, Elsevier, vol. 117(1), pages 161-164.
  9. 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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Cited by:
  1. Kenneth Judd & Lilia Maliar & Rafael Valero & Serguei Maliar, 2013. "Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain," Working Papers. Serie AD 2013-06, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  2. Anastasios Karantounias, 2012. "Optimal fiscal policy with recursive preferences," 2012 Meeting Papers 1085, Society for Economic Dynamics.

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