Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/86371
Authors: 
Bos, C.S.
Koopman, S.J.
Ooms, M.
Year of Publication: 
2007
Series/Report no.: 
Tinbergen Institute Discussion Paper 07-099/4
Abstract: 
We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic volatility process. We develop a Monte Carlo maximum likelihood method to obtain efficient estimates of the parameters using a monthly dataset of core inflation for which we consider different subsamples of varying size. Based on the new modelling framework and the associated estimation technique, we find remarkable changes in the variance, in the order of integration, in the short memory characteristics and in the volatility of volatility.
Subjects: 
Time varying parameters
Importance sampling
Monte Carlo simulation
Stochastic Volatility
Fractional Integration
JEL: 
C15
C32
C51
E23
E31
Document Type: 
Working Paper

Files in This Item:
File
Size
339.07 kB





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