Two-stage least squares and indirect least squares algorithms for simultaneous equations models
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https://riunet.upv.es/handle/10251/38822
Cita bibliográfica
López Espín, JJ.; Vidal Maciá, AM.; Giménez ., D. (2012). Two-stage least squares and indirect least squares algorithms for simultaneous equations models. Journal of Computational and Applied Mathematics. 236(15):3676-3684. doi:10.1016/j.cam.2011.07.005
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Resumen
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.
Palabras clave
Econometrics, Parallel computing, QR-decomposition, Simultaneous equations models, Execution time, Least Square, Least squares algorithm, Least squares methods, Multi-core systems, Parallel version, Simultaneous equations model, Algorithms, Parallel architectures, Parallel processing systems, Least squares approximations
Fuente
Journal of Computational and Applied Mathematics issn: 0377-0427
