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Combination forecasts of output growth in a seven-country data set

机译:七国数据集中的产出增长组合预测

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This paper uses forecast combination methods to forecast output growth in a seven-country quarterly economic data set covering 1959-1999, with up to 73 predictors per country. Although the forecasts based on individual predictors are unstable over time and across countries, and on average perform worse than an autoregressive benchmark, the combination forecasts often improve upon amoregressive forecasts. Despite the unstable performance of the constituent forecasts, the most successful combination forecasts, like the mean, are the least sensitive to the recent performance of the individual forecasts. While consistent with other evidence on the success of simple combination forecasts, this finding is difficult to explain using the theory of combination forecasting in a stationary environment. Copyright (C) 2004 John Wiley Sons, Ltd.
机译:本文使用预测组合方法在涵盖1959-1999年的七国季度经济数据集中预测产出增长,每个国家最多有73个预测变量。尽管基于单个预测变量的预测随着时间的推移以及在整个国家范围内都是不稳定的,并且平均而言比自回归基准更差,但是组合预测通常会在更具预测性的情况下得到改善。尽管组成预测的表现不稳定,但最成功的组合预测(如均值)对单个预测的近期表现最不敏感。尽管与简单组合预测成功的其他证据相一致,但在固定环境中使用组合预测理论很难解释这一发现。版权所有(C)2004 John Wiley Sons,Ltd.

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