Forecasting the Gross Domestic Product (GDP) of the United States is one of many estimates to predict the economic health of the country. Current forecasting techniques use consensus estimates of experts, econometric models, or other statistical methods. Relatively little research has been devoted to how artificial neural networks may improve these forecasts, however. This paper describes how a neural network using leading economic indicator data predicted annual GDP percentage changes one year into thefiiture more accurately than competing techniques over a ten-year period.
"Forecasting the United States gross domestic product with a neural network,"
Journal of International Information Management: Vol. 9
, Article 7.
Available at: https://scholarworks.lib.csusb.edu/jiim/vol9/iss1/7