Skip to main content
×
Home
    • Aa
    • Aa
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 29
  • Cited by
    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    BROADIE, MARK and SHEN, WEIWEI 2016. HIGH-DIMENSIONAL PORTFOLIO OPTIMIZATION WITH TRANSACTION COSTS. International Journal of Theoretical and Applied Finance, Vol. 19, Issue. 04, p. 1650025.


    Maliar, Lilia and Maliar, Serguei 2015. Merging simulation and projection approaches to solve high-dimensional problems with an application to a new Keynesian model. Quantitative Economics, Vol. 6, Issue. 1, p. 1.


    Judd, Kenneth L. Maliar, Lilia Maliar, Serguei and Valero, Rafael 2014. Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain. Journal of Economic Dynamics and Control, Vol. 44, p. 92.


    Lan, Hong and Meyer-Gohde, Alexander 2014. Solvability of perturbation solutions in DSGE models. Journal of Economic Dynamics and Control, Vol. 45, p. 366.


    Maliar, Lilia and Maliar, Serguei 2014. Handbook of Computational Economics Vol. 3.


    Richter, Alexander W. Throckmorton, Nathaniel A. and Walker, Todd B. 2014. Accuracy, Speed and Robustness of Policy Function Iteration. Computational Economics, Vol. 44, Issue. 4, p. 445.


    Bréchet, Thierry Hritonenko, Natali and Yatsenko, Yuri 2013. Adaptation and Mitigation in Long-term Climate Policy. Environmental and Resource Economics, Vol. 55, Issue. 2, p. 217.


    Lan, Hong and Meyer-Gohde, Alexander 2013. Solving DSGE models with a nonlinear moving average. Journal of Economic Dynamics and Control, Vol. 37, Issue. 12, p. 2643.


    Maliar, Lilia Maliar, Serguei and Villemot, Sébastien 2013. Taking Perturbation to the Accuracy Frontier: A Hybrid of Local and Global Solutions. Computational Economics, Vol. 42, Issue. 3, p. 307.


    Kompas, Tom and Chu, Long 2012. Comparing approximation techniques to continuous-time stochastic dynamic programming problems: Applications to natural resource modelling. Environmental Modelling & Software, Vol. 38, p. 1.


    Judd, Kenneth L. Maliar, Lilia and Maliar, Serguei 2011. Numerically stable and accurate stochastic simulation approaches for solving dynamic economic models. Quantitative Economics, Vol. 2, Issue. 2, p. 173.


    Kollmann, Robert Maliar, Serguei Malin, Benjamin A. and Pichler, Paul 2011. Comparison of solutions to the multi-country Real Business Cycle model. Journal of Economic Dynamics and Control, Vol. 35, Issue. 2, p. 186.


    Lontzek, Thomas S. and Narita, Daiju 2011. Risk-Averse Mitigation Decisions in an Unpredictable Climate System*. The Scandinavian Journal of Economics, Vol. 113, Issue. 4, p. 937.


    Maliar, Serguei Maliar, Lilia and Judd, Kenneth 2011. Solving the multi-country real business cycle model using ergodic set methods. Journal of Economic Dynamics and Control, Vol. 35, Issue. 2, p. 207.


    Pichler, Paul 2011. Solving the multi-country Real Business Cycle model using a monomial rule Galerkin method. Journal of Economic Dynamics and Control, Vol. 35, Issue. 2, p. 240.


    Cosimano, Thomas F. 2008. Optimal experimentation and the perturbation method in the neighborhood of the augmented linear regulator problem. Journal of Economic Dynamics and Control, Vol. 32, Issue. 6, p. 1857.


    Esteban-Bravo, Mercedes and Nogales, Francisco J. 2008. Solving dynamic stochastic economic models by mathematical programming decomposition methods. Computers & Operations Research, Vol. 35, Issue. 1, p. 226.


    Kim, Jinill Kim, Sunghyun Schaumburg, Ernst and Sims, Christopher A. 2008. Calculating and using second-order accurate solutions of discrete time dynamic equilibrium models. Journal of Economic Dynamics and Control, Vol. 32, Issue. 11, p. 3397.


    Aruoba, S. Borağan Fernández-Villaverde, Jesús and Rubio-Ramírez, Juan F. 2006. Comparing solution methods for dynamic equilibrium economies. Journal of Economic Dynamics and Control, Vol. 30, Issue. 12, p. 2477.


    Corrado, Luisa and Holly, Sean 2006. The Linearisation and Optimal Control of Large Non-Linear Rational Expectations Models by Persistent Excitation. Computational Economics, Vol. 28, Issue. 2, p. 139.


    ×

SOLVING LARGE-SCALE RATIONAL-EXPECTATIONS MODELS

  • JESS GASPAR (a1) and KENNETH L. JUDD (a2)
  • DOI: http://dx.doi.org/10.1017/S1365100597002022
  • Published online: 01 January 1997
Abstract

We explore alternative approaches to numerical solutions of large rational-expectations models. We discuss and compare several current alternatives, focusing on the trade-offs in accuracy, space, and speed. The models range from representative-agent models with many goods and capital stocks, to models of heterogeneous agents with complete or incomplete asset markets. The methods include perturbation and projection methods. We show that these methods are capable of analyzing moderately large models even when we use only elementary, general-purpose numerical methods.

Copyright
Corresponding author
Address correspondence to: Ken Judd, Hoover Institution, Stanford, CA 94305, USA; e-mail: judd@hoover.stanford.edu.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Macroeconomic Dynamics
  • ISSN: 1365-1005
  • EISSN: 1469-8056
  • URL: /core/journals/macroeconomic-dynamics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords: