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.
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Miranda, M.J. Numerical Strategies for Solving the Nonlinear Rational Expectations Commodity Market Model. Computational Economics 11, 71–87 (1997). https://doi.org/10.1023/A:1008610311740
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DOI: https://doi.org/10.1023/A:1008610311740