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Comparison of solutions to the multi-country real business cycle model

Author

Listed:
  • Robert Kollmann

    (LERISS - Laboratoire d'étude et de recherche en instrumentation, signaux et systèmes - EA412 - UPEC UP12 - Université Paris-Est Créteil Val-de-Marne - Paris 12)

  • Serguei Maliar

    (Hoover Institution - Hoover Institution, Dept. of Fundamentos del Analisis Economico - Universidad de Alicante)

  • Benjamin A. Malin
  • Paul Pichler

    (Dept. of Economics - University of Vienna [Vienna])

Abstract

We compare the performance of perturbation, projection, and stochastic simulation algorithms for solving the multi-country RBC model described in Den Haan, Judd and Juillard (2010). The main challenge of solving this model comes from its large number of continuous-valued state variables, ranging between four and twenty in the specifications we consider. The algorithms differ substantially in terms of speed and accuracy, and a clear trade-off exists between the two. Perturbation methods are very fast but invoke large approximation errors except at points close to the steady state; the projection methods considered are accurate on a large area of the state space but are very slow for specifications with many state variables; stochastic simulation methods have lower accuracy than projection methods, but their computational cost increases only moderately with the state-space dimension. Simulated series generated by different methods can differ noticeably, but only small differences are found in unconditional moments of simulated variables. On the basis of our comparison, we identify the factors that account for differences in accuracy and speed across methods, and we suggest directions for further improvement of some approaches.

Suggested Citation

  • Robert Kollmann & Serguei Maliar & Benjamin A. Malin & Paul Pichler, 2010. "Comparison of solutions to the multi-country real business cycle model," Post-Print hal-00765825, HAL.
  • Handle: RePEc:hal:journl:hal-00765825
    DOI: 10.1016/j.jedc.2010.09.013
    Note: View the original document on HAL open archive server: https://hal.science/hal-00765825
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    References listed on IDEAS

    as
    1. Kollmann, Robert & Kim, Jinill & Kim, Sunghyun H., 2011. "Solving the multi-country Real Business Cycle model using a perturbation method," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 203-206, February.
    2. Juillard, Michel & Villemot, Sébastien, 2011. "Multi-country real business cycle models: Accuracy tests and test bench," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 178-185, February.
    3. Maliar, Serguei & Maliar, Lilia & Judd, Kenneth, 2011. "Solving the multi-country real business cycle model using ergodic set methods," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 207-228, February.
    4. Kenneth Judd & Lilia Maliar & Serguei Maliar, 2009. "Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models," NBER Working Papers 15296, National Bureau of Economic Research, Inc.
    5. Lilia Maliar & Serguei Maliar, 2005. "Parameterized Expectations Algorithm: How to Solve for Labor Easily," Computational Economics, Springer;Society for Computational Economics, vol. 25(3), pages 269-274, June.
    6. Den Haan, Wouter J. & Judd, Kenneth L. & Juillard, Michel, 2011. "Computational suite of models with heterogeneous agents II: Multi-country real business cycle models," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 175-177, February.
    7. Pichler, Paul, 2011. "Solving the multi-country Real Business Cycle model using a monomial rule Galerkin method," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 240-251, February.
    8. Den Haan, Wouter J., 2010. "Comparison of solutions to the incomplete markets model with aggregate uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 4-27, January.
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    More about this item

    Keywords

    C63; Numerical solutions; Simulations; Approximations; Algorithms;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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