Computational Economics

, Volume 26, Issue 2, pp 107–128 | Cite as

User-Friendly Parallel Computations with Econometric Examples

Article

Abstract

This paper shows how a high-level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of parallelization is done in a way such that an investigator may use the programs without any knowledge of parallel programming. A bootable CD that allows rapid creation of a cluster for parallel computing is introduced. Examples show that parallelization can lead to important reductions in computational time. Detailed discussion of how the Monte Carlo problem was parallelized is included as an example for learning to write parallel programs for Octave.

Key words

bootstrapping GMM kernel regression maximum likelihood Monte Carlo parallel computing 

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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Department of Economics and Economic History, Edifici BUniversitat Autònoma de BarcelonaBellaterra, BarcelonaSpain

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