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A Note on Parallelizing the Parameterized Expectations Algorithm

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Abstract

The parameterized expectations algorithm (PEA) involves a long simulationand a nonlinear least squares (NLS) fit, both embedded in a loop. Both steps are natural candidates for parallelization.This note shows that parallelization can lead to important speedups forthe PEA.I provide example code for a simple model that can serve as a templatefor parallelization of more interesting models, as well as a download linkfor an image of a bootable CD that allows creation of a cluster and executionof the example code in minutes, with no need to install any software.

Suggested Citation

  • Michael Creel, 2005. "A Note on Parallelizing the Parameterized Expectations Algorithm," UFAE and IAE Working Papers 651.05, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    • Handle: RePEc:aub:autbar:651.05
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    1. Christiano, Lawrence J. & Fisher, Jonas D. M., 2000. "Algorithms for solving dynamic models with occasionally binding constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 24(8), pages 1179-1232, July.
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    1. Michael Creel, 2004. "ParallelKnoppix Tutorial," UFAE and IAE Working Papers 626.04, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 07 Oct 2005.

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    More about this item

    Keywords

    parameterized expectations; parallel computing;

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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