AN EMPIRICAL COMPARISON OF METHODS FOR FORECASTING USING MANY PREDICTORS

AN EMPIRICAL COMPARISON OF METHODS FOR FORECASTING USING MANY PREDICTORS
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使用多种预测因子进行预测的方法的实证比较

DOI:
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发表时间:
2005
期刊:
影响因子:
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通讯作者:
M. Watson
M. Watson
中科院分区:
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文献类型:
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作者:
J. Stock;M. Watson

文献摘要

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本文提供了一个简单的收缩表示,描述了各种预测方法,适用于当有大量的正交预测(如主成分)的操作特性。这些方法包括预测试方法,贝叶斯模型平均,经验贝叶斯和装袋。然后,我们在宏观经济预测(真实的活动和通货膨胀)的背景下,使用131个月度预测指标与月度美国经济时间序列数据(1959:1 - 2003:12),比较这些和其他多预测指标预测方法。理论上的收缩表示为我们提供了这些预测方法的经验比较。
This paper provides a simple shrinkage representation that describes the operational characteristics of various forecasting methods that are applicable when there are a large number of orthogonal predictors (such as principal components). These methods include pretest methods, Bayesian model averaging, empirical Bayes, and bagging. We then compare these and other many-predictor forecasting methods in the context of macroeconomic forecasting (real activity and inflation) using 131 monthly predictors with monthly U.S. economic time series data, 1959:1 - 2003:12. The theoretical shrinkage representations serve to inform our empirical comparison of these forecasting methods.