长期记忆模型和预测:来自美国历史上一系列通货膨胀的证据

IF 0.7 4区 经济学 Q3 ECONOMICS Studies in Nonlinear Dynamics and Econometrics Pub Date : 2020-10-26 DOI:10.1515/SNDE-2018-0116
H. Boubaker, G. Canarella, Rangan Gupta, S. Miller
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引用次数: 1

摘要

摘要本文报告了将几个长记忆模型应用于美国历史月度通货膨胀率序列的结果,并分析了它们在不同视域内的样本外预测性能。我们发现,时变方法估计通货膨胀的持久性优于假设一个恒定的长记忆过程的模型。此外,我们还研究了通货膨胀持续性与汇率制度之间的联系。我们的研究结果支持浮动汇率与通货膨胀持续性增加有关的假设。然而,这一发现在大缓和(Great Moderation)和美联储(Federal Reserve System)致力于通胀目标的时代就不那么明显了。
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Long-memory modeling and forecasting: evidence from the U.S. historical series of inflation
Abstract We report the results of applying several long-memory models to the historical monthly U.S. inflation rate series and analyze their out-of-sample forecasting performance over different horizons. We find that the time-varying approach to estimating inflation persistence outperforms the models that assume a constant long-memory process. In addition, we examine the link between inflation persistence and exchange rate regimes. Our results support the hypothesis that floating exchange rates associate with increased inflation persistence. This finding, however, is less pronounced during the era of the Great Moderation and the Federal Reserve System’s commitment to inflation targeting.
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
34
期刊介绍: Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.
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