User-Friendly Parallel Computations with Econometric Examples

Michael Creel ()
Additional contact information
Michael Creel: http://pareto.uab.es/mcreel

UFAE and IAE Working Papers from Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC)

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.

Keywords: parallel computing; Monte Carlo; bootstrapping; maximum likelihood; GMM; kernel regression (search for similar items in EconPapers)
JEL-codes: C13 C14 C15 C63 C87 (search for similar items in EconPapers)
Pages: 25
Date: 2005-01-10
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://pareto.uab.es/wp/2005/63705.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aub:autbar:637.05

Access Statistics for this paper

More papers in UFAE and IAE Working Papers from Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC) Contact information at EDIRC.
Bibliographic data for series maintained by Xavier Vila ().