Using parallelization to solve a macroeconomic model: A parallel parameterized expectations algorithm

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Abstract

Solving nonlinear macroeconomic models with rational expectations can be time-consuming. This paper shows how the parameterized expectations algorithm (PEA) can be parallelized to reduce the time needed to solve a simple model by more than 80%. The general idea of using parallelization applies naturally to other algorithms, as well. This paper is illustrative of the speedup that can be obtained, and it provides computer code that may serve as an example for parallelization of other algorithms. For those who would like to use the parallelized PEA, the implementation does not confront end users with the details of parallelization. To solve a model, it is only necessary to provide ordinary serial code that simulates data from the model. All needed code is available, on a standalone basis, or pre-installed on ParallelKnoppix (Creel, J Appl Economet 22:215-223, 2007). © Springer Science+Business Media, LLC. 2008.
Original languageEnglish
Pages (from-to)343-352
JournalComputational Economics
Volume32
DOIs
Publication statusPublished - 28 Apr 2008

Keywords

  • Nonlinear rational expectations
  • Parallel computing
  • Parameterized expectations algorithm
  • Solving macroeconomic models

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