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A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)

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  • Teodosio Perez-Amaral
  • Giampiero M. Gallo
  • Halbert White

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. Copyright 2003 Blackwell Publishing Ltd.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1046/j.0305-9049.2003.00096.x
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Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 65 (2003)
Issue (Month): s1 (December)
Pages: 821-838

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Handle: RePEc:bla:obuest:v:65:y:2003:i:s1:p:821-838
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  1. David Hendry & Hans-Martin Krolzig, 2000. "Computer Automation of General-to-Specific Model Selection Procedures," Economics Series Working Papers 3, University of Oxford, Department of Economics.
  2. Raffaella Giacomini & Halbert White, 2003. "Tests of Conditional Predictive Ability," Econometrics 0308001, EconWPA.
  3. Kevin Hoover & Stephen J. Perez, 2003. "Data Mining Reconsidered: Encompassing And The General-To-Specific Approach To Specification Search," Working Papers 9727, University of California, Davis, Department of Economics.
  4. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  5. Sin, Chor-Yiu & White, Halbert, 1996. "Information criteria for selecting possibly misspecified parametric models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 207-225.
  6. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May.
  7. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  8. Clive Granger & Allan Timmermann, 1999. "Data mining with local model specification uncertainty: a discussion of Hoover and Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 220-225.
  9. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-84, September.
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Cited by:

  1. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
  2. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
  3. Marcin Blazejowski & Pawel Kufel & Tadeusz Kufel, 2009. "Automatic Procedure of Building Congruent Dynamic Model in Gretl," EHUCHAPS, Universidad del País Vasco - Facultad de Ciencias Económicas y Empresariales.
  4. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
  5. Massimiliano Marinucci & Teodosio Pérez-Amaral, 2005. "Econometric Modeling of Business Telecommunications Demand using RETINA and Finite Mixtures," Econometrics 0505003, EconWPA, revised 14 May 2005.
  6. Andreas Sachs & Frauke Schleer, 2013. "Labour market performance in OECD countries: A comprehensive empirical modelling approach of institutional interdependencies," WWWforEurope Working Papers series 7, WWWforEurope.
  7. Gernot Doppelhofer & Xavier Sala I Martin & Melvyn Weeks, 2005. "Jointness of Determinants of Economics Growth," Money Macro and Finance (MMF) Research Group Conference 2005 54, Money Macro and Finance Research Group.
  8. Ivan Savin & Peter Winker, 2010. "Heuristic Optimization Methods for Dynamic Panel Data Model Selection. Application on the Russian Innovative Performance," Working Papers 027, COMISEF.
  9. Ivan Savin, 2010. "A comparative study of the Lasso-type and heuristic model selection methods," Working Papers 042, COMISEF.
  10. David Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Economics Series Working Papers 2004-W17, University of Oxford, Department of Economics.
  11. Gernot Doppelhofer & Melvyn Weeks, 2007. "Jointness of Growth Determinants," CESifo Working Paper Series 1978, CESifo Group Munich.
  12. Eduardo Acosta-González & Fernando Fernández-Rodríguez, 2014. "Forecasting Financial Failure of Firms via Genetic Algorithms," Computational Economics, Society for Computational Economics, vol. 43(2), pages 133-157, February.

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