Maximum Likelihood Estimation Using Parallel Computing: An Introduction to MPI

Authors:
Christopher A. Swann
Affiliations:
Department of Economics, SUNY-Stony Brook, Stony Brook, NY 11794, U.S.A. E-mail: chris.swann@sunysb.edu
Venue:
Computational Economics
Year:
2002

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Abstract

The computational difficulty of econometric problems has increased dramatically in recent years as econometricians examine more complicated models and utilize more sophisticated estimation techniques. Many problems in econometrics are `embarrassingly parallel' and can take advantage of parallel computing to reduce the wall clock time it takes to solve a problem. In this paper I demonstrate a method that can be used to solve a maximum likelihood problem using the MPI message passing library. The econometric problem is a simple multinomial logit model that does not require parallel computing but illustrates many of the problems one would confront when estimating more complicated models.