Using Bayesian Techniques for Data Pooling in Regional Payroll Forecasting
将跨国预测技术应用于美国俄亥俄州七个都市区的工资预测，比较贝叶斯合并方法与岭估计的表现，发现岭估计的预测效果不逊于新方法，可作为评估数据合并信息价值的基准。
Abstract This article adapts to the regional level a multicountry technique recently used by Garcia-Ferrer, Highfield, Palm, and Zellner (1987) and extended by Zellner and Hong (1987) to forecast the growth rates in gross national product across nine countries. This forecasting methodology is applied to the regional level by modeling payroll formation in seven Ohio metropolitan areas. We compare the forecasting performance of these procedures with that of a ridge estimator and find that the ridge estimator produces forecasts equal to or better than those from the newly proposed estimators. We conclude that the ridge estimator, which does not reference the pooled data information introduced by the newly proposed techniques, may serve as a benchmark against which to judge the relative importance of this kind of information in improving forecasts. KEY WORDS: Econometric modeling of metropolitan payrollExchangeable priorLeading indicator variablesRidge estimator