从固定事件到固定视界密度预测:从调查密度预测中获得多视界不确定性的度量

IF 1.2 3区 经济学 Q3 BUSINESS, FINANCE
GERGELY GANICS, BARBARA ROSSI, TATEVIK SEKHPOSYAN
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引用次数: 0

摘要

美国专业预测者调查对关键宏观经济变量进行准确及时的点预测。然而,伴随的密度预测大多是针对“固定事件”进行的。例如,在每个季度,小组成员预测本日历年和下一个日历年的产出增长和通货膨胀,因此预测范围随着每一轮调查而变化。这限制了预测对政策制定者、研究人员和市场参与者的有用性。我们提出了一种加权固定事件密度预测的密度组合方法,旨在获得正确校准的固定视界密度预测。我们表明,相对于广泛使用的替代方法,我们的方法产生了具有竞争力的密度预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From Fixed-Event to Fixed-Horizon Density Forecasts: Obtaining Measures of Multihorizon Uncertainty from Survey Density Forecasts

The U.S. Survey of Professional Forecasters produces precise and timely point forecasts for key macro-economic variables. However, the accompanying density forecasts are mostly conducted for “fixed events.” For example, in each quarter, panelists predict output growth and inflation for the current calendar year and the next, hence the forecast horizon changes with each survey round. This limits the forecasts' usefulness to policymakers, researchers, and market participants. We propose a density combination approach that weights fixed-event density forecasts, aiming at obtaining a correctly calibrated fixed-horizon density forecast. We show that our method produces competitive density forecasts relative to widely used alternatives.

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来源期刊
CiteScore
2.90
自引率
6.70%
发文量
98
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