Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/64092
Authors: 
Cheung, Yin-wong
Chung, Sang-Kuck
Year of Publication: 
2009
Series/Report no.: 
Working Papers, Santa Cruz Center for International Economics 09-10
Abstract: 
We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to characterize conditional heteroskedasticity. We find that the proposed model yields a good description of the salient features, including skewness and heteroskedasticity, of the US inflation data. Further, the performance of the proposed model compares quite favorably with, for example, ARMA and ARFIMA models with GARCH errors characterized by normal, symmetric and skewed Student-t distributions.
Subjects: 
conditional heteroskedasticity
skewness
inflation
long memory
normal mixture
JEL: 
C22
C51
C52
E31
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.