Prediction of the U.S. Employment Links: An Application of an Empirical Bayes Procedure
使用经验贝叶斯方法预测美国大都市统计区的月度就业链接（当月就业人数与上月之比），并与现有估计量比较，在均方误差和平均绝对相对误差上表现更优。
An empirical Bayes procedure is used to adaptively predict monthly employment links (a link being the ratio of all employee counts in a particular month to the corresponding figure in the previous month) for the Metropolitan Statistical Areas (MSA's) throughout the United States. By comparing with the true link of a month that is available only 9 to 13 months after the month has passed, our prediction is substantially and uniformly superior in MSA's, months, and states to existing estimators in terms of the average of squared deviations or the average of the absolute relative errors.