IF 3.4 3区 经济学 Q1 ECONOMICS
Stephen G. Hall, George S. Tavlas, Lorenzo Trapani, Yongli Wang
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引用次数: 0

摘要

美联储(Fed)和欧洲央行(ECB)都被批评没有意识到 2020 年初爆发的 Covid 会导致 2020 年代初通胀的结构性变化。这两家央行都认为 2021 年最初的通胀飙升是暂时的,并将货币紧缩政策推迟到了 2022 年。我们认为,现有关于结构性断裂的文献对政策制定者并无用处,因为这些文献是以任意的方式确定断裂的。用于识别断裂的检验并不包含断裂可能已经发生的先验知识,因此检验发现发生在样本末期的断裂的能力非常有限。我们的研究表明,在发生重大冲击(如 Covid)的情况下,利用可能已经发生断裂的知识,并在获得新数据时以递归方式对断裂进行检验,本可以提醒政策制定者注意通货膨胀的断裂。我们进行了蒙特卡洛模拟,结果表明,我们的方法可以在 2020 年底之前发现通胀已经中断,这比政策制定者察觉到通胀中断要早得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Detection of Structural Breaks: The Case of the Covid Shock

Both the Federal Reserve (Fed) and the European Central Bank (ECB) have been criticized for not having perceived that the outbreak of Covid at the beginning of 2020 would lead to a structural change in inflation in the early 2020s. Both central banks viewed the initial inflation surge in 2021 as temporary and delayed monetary tightening until 2022. We argue that the existing literature on structural breaks could not have been useful to policymakers because it identifies the breaks in an arbitrary way. The tests used to identify breaks do not incorporate prior knowledge that a break may have occurred so that the tests have very little power to detect a break that occurs at the end of the sample. We show that, in the event of a major shock, such as Covid, using knowledge that a break may have occurred and testing for a break in a recursive way as new data become available could have alerted policymakers to the break in inflation. We conduct Monte Carlo simulations suggesting that our method would have identified that a break had occurred in inflation by the end of 2020, well before policymakers had perceived the break.

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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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