Using Neural Nets to Forecast the Unemployment Rate

Abstract

The paper identifies leading indicators of the unemployment rate. Forecasts of the unemployment rate are obtained with an econometric model, and with an artificial neural network. Both model-based forecasts outperform forecasts from the Survey of Professional Forecasters. This is important because the unemployment rate forecast from the Survey of Professional Forecasters has outperformed other forecasts based on time-series models to the point that some observers view it as a proxy for a full-information forecast.