A Models Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks
AbstractWe 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.
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Bibliographic InfoPaper provided by Pennsylvania State - Department of Economics in its series Papers with number 04-95-12.
Length: 39 pages
Date of creation: 1995
Date of revision:
Contact details of provider:
Postal: PENNSYLVANIA STATE UNIVERSITY, DEPARTMENT OF ECONOMICS, UNIVERSITY PARK PENNSYLVANIA 16802 U.S.A.
Web page: http://econ.la.psu.edu/
More information through EDIRC
MACROECONOMICS; ECONOMIC FORECASTING;
Other versions of this item:
- Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November.
- Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, EconWPA.
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