Nonparametric modeling for the time-varying persistence of inflation

被引：6
|
作者：
Yu, Deshui [1 ]
Chen, Li [2 ,3 ,4 ,6 ]
Li, Luyang [5 ]
机构：
[1] Hunan Univ, Coll Finance & Stat, Changsha, Peoples R China
[2] Xiamen Univ, Wang Yanan Inst Studies Econ, Xiamen, Peoples R China
[3] Xiamen Univ, Sch Econ, Dept Finance, Xiamen, Peoples R China
[4] Xiamen Univ, MOE Key Lab Econometr, Xiamen, Peoples R China
[5] Monash Univ, Dept Econ, Melbourne, Australia
[6] Xiamen Univ, Econ Bldg,422 Siming South Rd, Xiamen 361005, Fujian, Peoples R China
来源：
ECONOMICS LETTERS | 2023年 / 225卷
基金：
中国国家自然科学基金;
关键词：
Inflation persistence; Time -varying coefficient model; Locally stationary process; Local linear estimation; SERIES MODELS;
D O I：
10.1016/j.econlet.2023.111040
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
This article develops a novel nonparametric time-varying auto-regressive distributed lag model to estimate the persistence of inflation. The local linear estimation method is used to estimate the coefficients. Empirically, the persistence of the inflation process in the United States declined prior to the global financial crisis (GFC) of 2007-2009, but then rebounded strongly until 2022.(c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页数：7
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