A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks

Norman R. Swanson and Halbert White
Additional contact information
Norman R. Swanson: Penn State University

Macroeconomics from University Library of Munich, Germany

Abstract: We take a model selection approach to real-time macroeconomic forecasting using linear and nonlinear models. True ex-ante forecasting are constructed by using unrevised as opposed to fully revised data. Model selection as well as model performance measures are considered.

Keywords: Artificial Neural Networks; Ex-ante Forecasting (search for similar items in EconPapers)
JEL-codes: E (search for similar items in EconPapers)
Date: 1995-03-27
Note: postscript file
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

Downloads: (external link)
https://econwpa.ub.uni-muenchen.de/econ-wp/mac/papers/9503/9503004.ps.gz (application/postscript)
https://econwpa.ub.uni-muenchen.de/econ-wp/mac/papers/9503/9503004.pdf (application/pdf)

Related works:
Journal Article: A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks (1997)
Working Paper: A Models Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks (1995)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpma:9503004

Access Statistics for this paper

More papers in Macroeconomics from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ( this e-mail address is bad, please contact ).