Estimation of mis-specified long memory models

Willa Chen and Rohit Deo ()
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Willa Chen: Texas A&M University

Econometrics from University Library of Munich, Germany

Abstract: 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 estimators of both long- and short-memory parameters that are slower than √n consistent for the pseudo-true parameter values, which in general differ from the true values. 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 √n consistency for the pseudo-true values and are asymptotically normal are also provided.

Keywords: long memory; model mis-specification (search for similar items in EconPapers)
JEL-codes: C13 C22 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2005-01-11
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-fin
Note: Type of Document - pdf; pages: 24
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Estimation of mis-specified long memory models (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0501004

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