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Numerical Strategies for Solving the Nonlinear Rational Expectations Commodity Market Model

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Author Info
Miranda, Mario J

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Abstract

In this paper, I compare the accuracy, efficiency and stability of different numerical strategies for computing approximate solutions to the nonlinear rational expectations commodity market model. I find that polynomial and spline function collocation methods are superior to the space discretization, linearization and least squares curve-fitting methods that have been preferred by economists in the past. Citation Copyright 1998 by Kluwer Academic Publishers.

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Publisher Info
Article provided by Springer in its journal Computational Economics.

Volume (Year): 11 (1998)
Issue (Month): 1-2 (April)
Pages: 71-87
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Handle: RePEc:kap:compec:v:11:y:1998:i:1-2:p:71-87

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Web page: http://www.springerlink.com/link.asp?id=100248

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  1. R. Kato & S. Nishiyama, 2002. "Optimal Monetary Policy When Interest Rates are Bounded at Zero," Computing in Economics and Finance 2002 8, Society for Computational Economics. [Downloadable!]
    Other versions:
  2. Peterson, Hikaru H. & Tomek, William G., 2003. "How Much Of Commodity Price Behavior Can A Rational Expectations Storage Model Explain?," Staff Papers 30712, Kansas State University, Department of Agricultural Economics. [Downloadable!]
  3. Vedenov, Dmitry, 2003. ""Irrational" Planting Behavior As Rational Expectations Of Government Support," 2003 Annual Meeting, February 1-5, 2003, Mobile, Alabama 35237, Southern Agricultural Economics Association. [Downloadable!]
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