Journal of International Information Management
Article Title
Abstract
Forecasting national unemployment is one of the most important problems of modern economies, and most researchers have relied upon statistical techniques with their stringent data assumptions and low accuracy rates to predict changes in this macroeconomic data. This paper describes how a neural network using leading economic indicator data can help to predict civilian unemployment rates. Results show that the neural network provides superior estimates of rates one month into the future compared to multi-linear regression and two naive forecasting techniques.
Recommended Citation
Aiken, Milam
(1996)
"A neural network to predict civilian unemployment rates,"
Journal of International Information Management: Vol. 5:
Iss.
1, Article 3.
Available at:
https://scholarworks.lib.csusb.edu/jiim/vol5/iss1/3