๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Using Neural Nets to Forecast the Unemployment Rate

โœ Scribed by Rolando Pelaez


Book ID
111849530
Publisher
Springer
Year
2006
Tongue
English
Weight
110 KB
Volume
41
Category
Article
ISSN
0007-666X

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


A latent variable approach to forecastin
โœ Chew Lian Chua; G. C. Lim; Sarantis Tsiaplias ๐Ÿ“‚ Article ๐Ÿ“… 2011 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 219 KB

## ABSTRACT A forecasting model for unemployment is constructed that exploits the time series properties of unemployment while satisfying the economic relationships specified by Okun's law and the Phillips curve. In deriving the model, we jointly consider the problem of obtaining estimates of the u

Using neural nets to look for chaos
โœ A.M. Albano; A. Passamante; T. Hediger; Mary Eileen Farrell ๐Ÿ“‚ Article ๐Ÿ“… 1992 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 579 KB
Time-series forecasting of the German un
โœ PD Dr. Michael Funke ๐Ÿ“‚ Article ๐Ÿ“… 1992 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 810 KB

The purpose of the paper is to investigate the accuracy of forecasts derived from univariate and multivariate time-series models. An iterative method to adjust for impact assessment in univariate ARIMA models is discussed and illustrated for the German unemployment rate. Finally, we also examine the