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Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods

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  • John B. Taylor
  • Harald Uhlig

Abstract

The purpose of this paper is to report on a comparison of several alternative numerical solution techniques for nonlinear rational expectations models. The comparison was made by asking individual researchers to apply their different solution techniques to a simple representative agent, optimal, stochastic growth model. Decision rules as well as simulated time series are compared. The differences among the methods turned out to be quite substantial for certain aspects of the growth model. Therefore, researchers might want to be careful not to rely blindly on the results of any chosen numerical solution method in applied work.

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File URL: http://www.nber.org/papers/w3117.pdf
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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 3117.

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Date of creation: Sep 1990
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Publication status: published as Journal of Business & Economic Statistics, Vol. 8, No. 1, pp. 1-17, (January 1990).
Handle: RePEc:nbr:nberwo:3117

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  1. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  2. Sims, Christopher A, 1990. "Solving the Stochastic Growth Model by Backsolving with a Particular Nonlinear Form for the Decision Rule," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 45-47, January.
  3. Baxter, Marianne & Crucini, Mario J & Rouwenhorst, K Geert, 1990. "Solving the Stochastic Growth Model by a Discrete-State-Space, Euler-Equation Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 19-21, January.
  4. Ingram, Beth Fisher, 1990. "Equilibrium Modeling of Asset Prices: Rationality versus Rules of Thumb," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 115-25, January.
  5. Coleman, Wilbur John, II, 1990. "Solving the Stochastic Growth Model by Policy-Function Iteration," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 27-29, January.
  6. McGrattan, Ellen R, 1990. "Solving the Stochastic Growth Model by Linear-Quadratic Approximation," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 41-44, January.
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  1. > Schools of Economic Thought, Epistemology of Economics > Economic Methodology > Dynamic Stochastic General Equilibrium > Solution Methods for DSGE models
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  1. Quantitative Macroeconomics and Real Business Cycles (QM&RBC)

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