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Revisiting deterministic extended-path: a simple and accurate solution method for macroeconomic models

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  • David R.F. Love

Abstract

The deterministic extended-path (EP) method for solving dynamic stochastic optimisation problems approximates conditional expectations instead of approximating a model's complex non-linear dynamics. For a benchmark real business cycle model we show that this straightforward approach provides excellent accuracy and uniform performance across the entire state space. Our implementation requires roughly four-fold more computer time than Galerkin projection, but the method has offsetting simplicity and generality.

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  • David R.F. Love, 2010. "Revisiting deterministic extended-path: a simple and accurate solution method for macroeconomic models," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 1(3/4), pages 309-316.
  • Handle: RePEc:ids:ijcome:v:1:y:2010:i:3/4:p:309-316
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    References listed on IDEAS

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    1. Gagnon, Joseph E, 1990. "Solving the Stochastic Growth Model by Deterministic Extended Path," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 35-36, January.
    2. Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-1185, July.
    3. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    4. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
    5. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    6. Heer, Burkhard & Maußner, Alfred, 2008. "Computation Of Business Cycle Models: A Comparison Of Numerical Methods," Macroeconomic Dynamics, Cambridge University Press, vol. 12(5), pages 641-663, November.
    7. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
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    Cited by:

    1. Shantayanan Devarajan & Yazid Dissou & Delfin S. Go & Sherman Robinson, 2017. "Budget Rules and Resource Booms and Busts: A Dynamic Stochastic General Equilibrium Analysis," The World Bank Economic Review, World Bank, vol. 31(1), pages 71-96.
    2. Ajevskis, Viktors, 2019. "Nonlocal Solutions To Dynamic Equilibrium Models: The Approximate Stable Manifolds Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 23(6), pages 2544-2571, September.
    3. Devarajan, Shantayanan & Dissou, Yazid & Go, Delfin S. & Robinson, Sherman, 2014. "Budget rules and resource booms : a dynamic stochastic general equilibrium analysis," Policy Research Working Paper Series 6984, The World Bank.

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