A Comparison of Complementary Automatic Modeling Methods: RETINA and PcGets

Teodosio Perez-Amaral (), Giampiero M. Gallo () and Halbert White
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Teodosio Perez-Amaral: Universidad Complutense de Madrid, Departamento de Economía Cuantitativa, http://www.ucm.es/info/ecocuan/tpa/

Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti"

Abstract: In Perez-Amaral, Gallo, and White (2003), the authors proposed an automatic predictive modelling tool called Relevant Transformation of the Inputs Network Approach (RETINA). It is designed to embody flexibility (using nonlinear transformations of the predictors of interest), selective search within the range of possible models, control of collinearity, out-of-sample forecasting ability, and computational simplicity. In this paper we compare the characteristics of RETINA with PcGets, a well-known automatic modeling method proposed by David Hendry. We point out similarities, differences, and complementarities of the two methods. In an example using US telecommunications demand data we find that RETINA can improve both in- and out-of-sample over the usual linear regression model, and over some models suggested by PcGets. Thus, both methods are useful components of the modern applied econometrician’s automated modelling tool chest.

Keywords: Model selection; cross-validation; flexible modelling; information criteria; forecasting. (search for similar items in EconPapers)
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Date: 2004-10-04
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Journal Article: A COMPARISON OF COMPLEMENTARY AUTOMATIC MODELING METHODS: RETINA AND PcGets (2005)
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