Estimation of Mis-Specified Long Memory Models
Rohit S. Deo and
Willa W. Chen
No 2004,03, Papers from Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE)
We study the asymptotic behaviour of frequency domain maximum likelihood estimators of mis-specified models of long memory Gaussian series. We show that even if the long memory structure of the time series is correctly specified, mis-specification of the short memory dynamics may result in parameter estimators which are slower than pn consistent. The conditions under which this happens are provided and the asymptotic distribution of the estimators is shown to be non-Gaussian. Conditions under which estimators of the parameters of the mis-specified model have the standard pn consistent and asymptotically normal behaviour are also provided.
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