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Solving Rational Expectations Models with Informational Subperiods: A Comment

Author

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  • Frank Hespeler

    (Sciences Po)

  • Marco M. Sorge

    (University of Salerno, University of Göttingen and CSEF)

Abstract

Kormilitsina (Comput Econ 41(4): 525–555, 2013) develops a perturbation-based algorithm to solve up to the second order of approximation rational expectations models with informational subperiods (timing restrictions). It is there claimed that the restricted framework inherits equilibrium (non)uniqueness properties from its unrestricted counterpart. This comment provides an example where timing restrictions cause non-existence of dynamically stable equilibria, even though the model’s unrestricted counterpart exhibits saddle-path stability. Implications for the execution of Kormilitsina’s algorithm are discussed.

Suggested Citation

  • Frank Hespeler & Marco M. Sorge, 2019. "Solving Rational Expectations Models with Informational Subperiods: A Comment," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1649-1654, April.
    • Handle: RePEc:kap:compec:v:53:y:2019:i:4:d:10.1007_s10614-018-9829-2
    DOI: 10.1007/s10614-018-9829-2
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    References listed on IDEAS

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    1. 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.
    2. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    3. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
    4. 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.
    5. Anna Kormilitsina, 2013. "Solving Rational Expectations Models with Informational Subperiods: A Perturbation Approach," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 525-555, April.
    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. Laurence Broze & Ariane Szafarz, 1991. "The Econometric Analysis of Non-Uniqueness in Rational Expectations Models," ULB Institutional Repository 2013/649, ULB -- Universite Libre de Bruxelles.
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    Citations

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    Cited by:

    1. Sorge Marco M., 2020. "Computing sunspot solutions to rational expectations models with timing restrictions," The B.E. Journal of Macroeconomics, De Gruyter, vol. 20(2), pages 1-10, June.
    2. Angelini, Giovanni & Sorge, Marco M., 2021. "Under the same (Chole)sky: DNK models, timing restrictions and recursive identification of monetary policy shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).

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    More about this item

    Keywords

    Rational expectations models; Timing restrictions;

    JEL classification:

    • 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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