Forecast Combination and Encompassing
Forecast Combination and Encompassing
复制标题
预测组合与包容
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
David I. Harvey
中科院分区：
文献类型：
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作者：
Michael P. Clements;David I. Harvey
预测组合往往被发现，以提高预测精度。本章考虑不同类型的预测组合和预测测试。后者表明，在一系列情况下，组合预测何时比单个事后预测更准确：预测本身是感兴趣的对象;预测是从参数未知的模型中得出的;预测模型是嵌套的。我们认为预测包含测试框架的模型的估计参数，并认识到参数估计的不确定性影响预测的准确性，以及条件测试的包含。我们还研究了在何种条件下可以建立预测包含，而不管损失函数的形式如何。
Forecast combination is often found to improve forecast accuracy. This chapter considers different types of forecast combination and tests of forecast encompassing. The latter indicate when a combination is more accurate than an individual forecast ex post, in a range of circumstances: when the forecasts themselves are the objects of interest; when the forecasts are derived from models with unknown parameters; and when the forecast models are nested. We consider forecast encompassing tests which are framed in terms of the model’s estimated parameters and recognize that parameter estimation uncertainty affects forecast accuracy, as well as conditonal tests of encompassing. We also look at the conditions under which forecast encompassing can be established irrespective of the form of the loss function.