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Solving the Stochastic Growth Model by Using Quadrature Methods and Value-Function Iterations

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  • Tauchen, George

Abstract

This article presents a solution algorithm for the capital growth model. The algorithm uses value-function iterations on a discrete state space. The quadrature method is used to set the grid for the exogenous process, and a simple equispaced scheme in logarithms is used to set the grid for the endogenous capital process. The algorithm can produce a solution to within four-digit accuracy using a state space composed of 1,800 points in total.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 8 (1990)
Issue (Month): 1 (January)
Pages: 49-51

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Handle: RePEc:bes:jnlbes:v:8:y:1990:i:1:p:49-51

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Cited by:
  1. Paul McNelis & John Duffy, 1998. "Approximating and Simulating the Stochastic Growth Model: Parameterized Expectations, Neural Networks, and the Genetic Algorithm," GE, Growth, Math methods 9804004, EconWPA, revised 04 May 1998.
  2. 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.
  3. S. Sirakaya & Stephen Turnovsky & M. Alemdar, 2006. "Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks," Computational Economics, Society for Computational Economics, vol. 27(2), pages 185-206, May.
  4. Zhu, Junjun & Xie, Shiyu, 2011. "Asymmetric Shocks, Long-term Bonds and Sovereign Default," MPRA Paper 28236, University Library of Munich, Germany.
  5. Kenneth L. Judd, 1991. "Minimum weighted residual methods for solving aggregate growth models," Discussion Paper / Institute for Empirical Macroeconomics 49, Federal Reserve Bank of Minneapolis.
  6. Wilfredo L. Maldonado & Benar F. Svaiter, 2002. "On the accuracy of the estimated policy function using the Bellman contraction method," Computing in Economics and Finance 2002 30, Society for Computational Economics.
  7. John Rust, 1997. "A Comparison of Policy Iteration Methods for Solving Continuous-State, Infinite-Horizon Markovian Decision Problems Using Random, Quasi-random, and Deterministic Discretizations," Computational Economics 9704001, EconWPA.
  8. Michel Juillard & Tarik Ocaktan, 2008. "Méthodes de simulation des modèles stochastiques d'équilibre général," Économie et Prévision, Programme National Persée, vol. 183(2), pages 115-126.

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