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Combination schemes for turning point predictions

机译:转折点预测的组合方案

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摘要

We propose new forecast combination schemes for predicting turning points of business cycles. The proposed combination schemes are based on the forecasting performances of a given set of models with the aim to provide better turning point predictions. In particular, we consider predictions generated by autoregressive (AR) and Markov-switching AR models, which are commonly used for business cycle analysis. In order to account for parameter uncertainty we consider a Bayesian approach for both estimation and prediction and compare, in terms of statistical accuracy, the individual models and the combined turning point predictions for the United States and the Euro area business cycles.
机译:我们提出了新的预测组合方案,以预测商业周期的转折点。提出的组合方案基于给定模型集的预测性能,目的是提供更好的转折点预测。特别是,我们考虑了通常用于业务周期分析的自回归(AR)和马尔可夫切换AR模型生成的预测。为了考虑参数不确定性,我们考虑了贝叶斯方法进行估计和预测,并在统计准确性方面比较了美国和欧元区经济周期的各个模型以及组合的转折点预测。

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