Two-stage least squares and indirect least squares algorithms for simultaneous equations models

descriptionPublicationkeyboard_double_arrow_right Article 01 Sep 2012 English Publisher:Elsevier BVJournal:Journal of Computational and Applied Mathematics, volume 236, pages 3,676-3,684 (issn: 0377-0427,

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Authors: Jose-Juan López-Espín; Antonio M. Vidal; Domingo Giménez;

doi: 10.1016/j.cam.2011.07.005

Two-stage least squares and indirect least squares algorithms for simultaneous equations models

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Abstract

This paper analyzes the solution of simultaneous equations models. Efficient algorithms for the two-stage least squares method using QR-decomposition are developed and studied. The reduction of the execution time when the structure of the matrices in each equation is exploited is analyzed theoretically and experimentally. An efficient algorithm for the indirect least squares method is developed. Some techniques are used to accelerate the solution of the problem: parallel versions for multicore systems, and extensive use of the MKL library, thus obtaining efficient, portable versions of the algorithms. © 2011 Elsevier B.V. All rights reserved.

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Keywords

Parallel computing, Least Square, Numerical solutions to overdetermined systems, pseudoinverses, Execution time, Least squares algorithm, least squares method, Least squares approximations, algorithms, Least squares methods, econometrics, Parallel architectures, simultaneous equations models, CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL, Econometrics, Applications of statistics to economics, numerical examples, QR-decomposition, parallel computing, Parallel processing systems, Parallel numerical computation, Simultaneous equations model, Parallel version, Simultaneous equations models, Multi-core systems, Algorithms

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