如何衡量通胀波动性。一份报告

Alfredo García-Hiernaux, María T. González-Pérez, David E. Guerrero
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引用次数: 7

摘要

本文提出了一个统计模型和概念框架来估计假设理性不关注的通货膨胀波动,其中关注水平的衰减反映了市场消息的到来。我们使用2002年1月至2022年3月的月度数据估计了德国、西班牙、欧元区和美国的趋势通胀和条件通胀波动,并测试了这些地区在此期间的通胀是否等于或低于2%。我们将通胀波动分解为正意外和负意外成分,并描述了大金融危机、主权债务危机和后covid时期不同的通胀波动情景。我们的波动率测量优于GARCH(1,1)模型和滚动标准差在一步前的波动率预测样本内和样本外。本文提出的方法适用于估计宏观金融变量的条件波动。我们建议将这一措施纳入通货膨胀动态监测和预测工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How to measure inFLAtion volatility. A note
This paper proposes a statistical model and a conceptual framework to estimate inflation volatility assuming rational inattention, where the decay in the level of attention reflects the arrival of news in the market. We estimate trend inflation and the conditional inflation volatility for Germany, Spain, the euro area and the United States using monthly data from January 2002 to March 2022 and test whether inflation was equal to or below 2% in this period in these regions. We decompose inflation volatility into positive and negative surprise components and characterise different inflation volatility scenarios during the Great Financial Crisis, the Sovereign Debt Crisis, and the post-COVID period. Our volatility measure outperforms the GARCH(1,1) model and the rolling standard deviation in one-step ahead volatility forecasts both in-sample and out-of-sample. The methodology proposed in this article is appropriate for estimating the conditional volatility of macro-financial variables. We recommend the inclusion of this measure in inflation dynamics monitoring and forecasting exercises.
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