A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)* Teodosio Perez-Amaral , Giampiero M. Galloà and Halbert White§  Departamento de Analisis Economico, Universidad Complutense de Madrid 28223 Madrid, Spain (e-mail: teodosio@ccee.ucm.es) àDipartimento di Statistica ‘G. Parenti’, Universita ` di Firenze, Viale G.B. Morgagni, 59 50134 Firenze, Italy (e-mail: gallog@ds.unifi.it) §Department of Economics, University of California, San Diego, 9500 Gilman Drive La Jolla, CA 92093-0508, USA (e-mail: hwhite@weber.ucsd.edu) Abstract A new method, called Relevant Transformation of the Inputs Network Approach is proposed as a tool for model building. It is designed around flexibility (with nonlinear transformations of the predictors of interest), selective search within the range of possible models, out-of-sample forecasting ability and computational simplicity. In tests on simulated data, it shows both a high rate of successful retrieval of the data generating process, which increases with the sample size and a good performance relative to other alternative procedures. A telephone service demand model is built to show how the procedure applies on real data. I. Introduction In the process of model building, a decision must be made as to which among several specifications (possibly belonging to different classes of models) *Comments by participants in the 13th EC 2 conference ‘Model Selection and Evaluation’ are gratefully acknowledged. The referees’ comments were very insightful and led (we hope) to a better presentation of the material here. Thanks are also due to Niels Haldrup for his suggestions and his patience and for giving us encouragement and support throughout the revision process. The usual disclaimer applies. JEL Classification numbers: C52, C53, C45. OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 65, SUPPLEMENT (2003) 0305-9049 821 Ó Blackwell Publishing Ltd, 2003. Published by Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.