Forecasting the U.S. Unemployment Rate
比较多种线性和非线性时间序列模型预测美国失业率的表现，重点考察经济扩张和收缩期的预测效果，并引入首次申请失业救济人数作为领先指标，同时与专业预测者调查的共识预测进行对比。
Abstract This article presents a comparison of forecasting performance for a variety of linear and nonlinear time series models using the U.S. unemployment rate. Our main emphases are on measuring forecasting performance during economic expansions and contractions by exploiting the asymmetric cyclical behavior of unemployment numbers, on building vector models that incorporate initial jobless claims as a leading indicator, and on utilizing additional information provided by the monthly rate for forecasting the quarterly rate. Comparisons are also made with the consensus forecasts from the Survey of Professional Forecasters. In addition, the forecasts of nonlinear models are combined with the consensus forecasts. The results show that significant improvements in forecasting accuracy can be obtained over existing methods.