TREND EXTRACTION FROM ECONOMIC TIME SERIES WITH MISSING OBSERVATIONS BY GENERALIZED HODRICK-PRESCOTT FILTERS
TREND EXTRACTION FROM ECONOMIC TIME SERIES WITH MISSING OBSERVATIONS BY GENERALIZED HODRICK-PRESCOTT FILTERS
复制标题
通过广义霍德里克-普雷斯科特滤波器从缺少观测值的经济时间序列中提取趋势
DOI：
10.1017/s0266466621000189
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发表时间：
2021
影响因子：
0.8
通讯作者：
Yamada Hiroshi
中科院分区：
文献类型：
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作者：
Saroj Bhattarai;Konstantin Kucheryavyy;Yamada Hiroshi
Hodrick-Prescott（HP）滤波器是一种从经济时间序列中提取趋势的常用方法。然而，如果某些观测数据不可用，则不进行修改是不切实际的。本文对HP滤波器进行了改进，使其能够应用于此类场合。更确切地说，本文介绍了两种可供选择的广义HP滤波器，适用于此目的。我们提供了它们的属性和指定这些平滑参数的方法，所需的应用程序。此外，我们在数字上检查他们的表现。最后，根据我们的分析，我们建议其中一个应用研究。
The Hodrick–Prescott (HP) filter has been a popular method of trend extraction from economic time series. However, it is impractical without modification if some observations are not available. This paper improves the HP filter so that it can be applied in such situations. More precisely, this paper introduces two alternative generalized HP filters that are applicable for this purpose. We provide their properties and a way of specifying those smoothing parameters that are required for their application. In addition, we numerically examine their performance. Finally, based on our analysis, we recommend one of them for applied studies.