摘要翻译：
我们构造了单变量经济时间序列的时间聚合未来值的长期预测区间。在小样本约束下，我们提出了对现有方法的计算调整，以提高覆盖概率。一个伪样本外的评估表明，我们的方法至少与基于模型隐含的贝叶斯方法和自举的选择方法一样好。我们最成功的方法得出了八个宏观经济指标在几十年的范围内的预测间隔。
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英文标题：
《Long-term prediction intervals of economic time series》
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作者：
Marek Chudy, Sayar Karmakar, Wei Biao Wu
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最新提交年份：
2020
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  We construct long-term prediction intervals for time-aggregated future values of univariate economic time series. We propose computational adjustments of the existing methods to improve coverage probability under a small sample constraint. A pseudo-out-of-sample evaluation shows that our methods perform at least as well as selected alternative methods based on model-implied Bayesian approaches and bootstrapping. Our most successful method yields prediction intervals for eight macroeconomic indicators over a horizon spanning several decades.
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PDF链接：
https://arxiv.org/pdf/2002.05384