Skip to main content Accessibility help
×
Home
Hostname: page-component-55597f9d44-t4qhp Total loading time: 0.387 Render date: 2022-08-14T16:05:20.065Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "useRatesEcommerce": false, "useNewApi": true } hasContentIssue true

A COMPARISON OF COMPLEMENTARY AUTOMATIC MODELING METHODS: RETINA AND PcGets

Published online by Cambridge University Press:  08 February 2005

Teodosio Perez-Amaral
Affiliation:
Universidad Complutense de Madrid
Giampiero M. Gallo
Affiliation:
Università de Firenze
Halbert White
Affiliation:
University of California at San Diego

Abstract

In Perez-Amaral, Gallo, and White (2003, Oxford Bulletin of Economics and Statstics 65, 821–838), the authors proposed an automatic predictive modeling 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 U.S. 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 modeling tool chest.

Type
Research Article
Copyright
© 2005 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Campos, J., N.R. Ericsson, & D.F. Hendry (2004) General-to-Specific Modeling. Edward Elgar.
Hendry, D.F. & H.-M. Krolzig (2001) Automatic Econometric Model Selection with PcGets. Timberlake Consultants Press.
Hendry, D.F. & H.-M. Krolzig (2003) New developments in automatic general-to-specific modeling. In B.P. Stigum (ed.), Econometrics and the Philosophy of Economics, pp. 379419. Princeton University Press.
Hendry, D.F. & H.-M. Krolzig (2004) Sub-sample model selection procedures in general-to-specific modelling. In R. Becker & S. Hurn (eds.), Contemporary Issues in Economics and Econometrics: Theory and Applications, pp. 5375. Edward Elgar.
Hoover, K. & S. Perez (1999) Data mining reconsidered: Encompassing and the general-to-specific approach to specification search. Econometrics Journal 2, 167191.Google Scholar
Krolzig, H.-M. & D.F. Hendry (2001) Computer automation of general-to-specific model selection procedures. Journal of Economic Dynamics and Control 25, 831866.Google Scholar
Perez-Amaral, T., G.M. Gallo, & H. White (2003) A flexible tool for model building: The Relevant Transformation of the Inputs Network Approach (RETINA). Oxford Bulletin of Economics and Statistics 65, supplement 1, 821838.Google Scholar
Ploberger, W. & P.C.B. Phillips (2003) Empirical limits for time series econometric models. Econometrica 71, 627673.Google Scholar
White, H. (1998) Artificial Neural Network and Alternative Methods for Assessing Naval Readiness. Technical Report, NeuralNet R&D Associates, San Diego.
White, H. (1989) Learning in artificial neural networks: A statistical perspective. Neural Computation 1, 425464. Reprinted in H. White (1992) Artificial Neural Networks: Approximation and Learning Theory pp. 90–131. Blackwell.Google Scholar
16
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

A COMPARISON OF COMPLEMENTARY AUTOMATIC MODELING METHODS: RETINA AND PcGets
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

A COMPARISON OF COMPLEMENTARY AUTOMATIC MODELING METHODS: RETINA AND PcGets
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

A COMPARISON OF COMPLEMENTARY AUTOMATIC MODELING METHODS: RETINA AND PcGets
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *