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Linear Time Iteration

Author

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  • Rendahl, Pontus

    (University of Cambridge, Faculty of Economics)

Abstract

This paper proposes a simple iterative method – time iteration – to solve linear rational expectation models. I prove that this method converges to the solution with the smallest eigenvalues in absolute value, and provide the conditions under which this solution is unique. In particular, if conditions similar to those of Blanchard and Kahn (1980) are met, the procedure converges to the unique stable solution. Apart from its transparency and simplicity of implementation, the method provides a straightforward approach to solving models with less standard features, such as regime switching models. For large-scale problems the method is 10-20 times faster than existing solution methods.

Suggested Citation

  • Rendahl, Pontus, 2017. "Linear Time Iteration," Economics Series 330, Institute for Advanced Studies.
  • Handle: RePEc:ihs:ihsesp:330
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    File URL: https://irihs.ihs.ac.at/id/eprint/4351
    File Function: First version, 2017
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    References listed on IDEAS

    as
    1. Christiano, Lawrence J, 2002. "Solving Dynamic Equilibrium Models by a Method of Undetermined Coefficients," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 21-55, October.
    2. King, Robert G & Watson, Mark W, 2002. "System Reduction and Solution Algorithms for Singular Linear Difference Systems under Rational Expectations," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 57-86, October.
    3. Reiter, Michael, 2009. "Solving heterogeneous-agent models by projection and perturbation," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 649-665, March.
    4. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    5. Gauti B. Eggertsson, 2011. "What Fiscal Policy Is Effective at Zero Interest Rates?," NBER Chapters, in: NBER Macroeconomics Annual 2010, volume 25, pages 59-112, National Bureau of Economic Research, Inc.
    6. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
    7. Farmer, Roger E.A. & Waggoner, Daniel F. & Zha, Tao, 2009. "Understanding Markov-switching rational expectations models," Journal of Economic Theory, Elsevier, vol. 144(5), pages 1849-1867, September.
    8. Binder,M. & Pesaran,H.M., 1995. "Multivariate Rational Expectations Models and Macroeconomic Modelling: A Review and Some New Results," Cambridge Working Papers in Economics 9415, Faculty of Economics, University of Cambridge.
    9. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
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    Cited by:

    1. Papp, Tamás K. & Reiter, Michael, 2020. "Estimating linearized heterogeneous agent models using panel data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
    2. Gregor Boehl & Cars Hommes, 2021. "Rational vs. Irrational Beliefs in a Complex World," CRC TR 224 Discussion Paper Series crctr224_2021_287, University of Bonn and University of Mannheim, Germany.
    3. Barrdear, John, 2017. "The calm policymaker," Bank of England working papers 653, Bank of England.
    4. Boehl, Gregor, 2022. "Efficient solution and computation of models with occasionally binding constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).

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    More about this item

    Keywords

    Linear systems; rational expectation models; fixed point iteration;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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