Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/49186
Title: Model selection via genetic algorithms illustrated with cross-country growth data
Authors: Acosta González, Eduardo 
Fernández-Rodríguez, Fernando 
Keywords: Regressions
Issue Date: 2007
Publisher: 0377-7332
Journal: Empirical Economics 
Abstract: We provide a new simple procedure for selecting econometric models, which is used to select the regressors of the cross-country growth model regression. This procedure is based on a heuristic approach called genetic algorithms which are used to explore the universe of models made available by a General Unrestricted Model. This search process of the correct model is only guided by the Schwarz information criterion, which acts as the loss function of the genetic algorithm in order to rank the models. Our procedure shows good performance relative to other alternative methodologies when they are compared in a simulation environment.
URI: http://hdl.handle.net/10553/49186
ISSN: 0377-7332
DOI: 10.1007/s00181-006-0104-3
Source: Empirical Economics[ISSN 0377-7332],v. 33, p. 313-337
Appears in Collections:Artículos
Show full item record

SCOPUSTM   
Citations

20
checked on Nov 3, 2024

WEB OF SCIENCETM
Citations

16
checked on Nov 3, 2024

Page view(s)

95
checked on Oct 5, 2024

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.