Semiparametric Estimation of the Intensity of Long Memory in Conditional Heteroskedasticity

Liudas Giraitis (), P. Kokoszka, R. Leipus and G. Teyssiere

G.R.E.Q.A.M. from Universite Aix-Marseille III

Abstract: The paper is concerned with the estimation of the long memory parameter in a conditionally heteroskedastic model proposed by Giraitis, Robinson and Surgailis (1999). We consider methods based on the partial sums of the squared observations which are similar in spirit to the classicla R/S analysis as well as spectral domain approximate maximum likelihood estimators. The finite sample performance of the estimators is examined by means of a Monte Carlo study.

Keywords: ESTIMATOR; ECONOMETRICS; HETEROSKEDASTICITY (search for similar items in EconPapers)
JEL-codes: C13 C14 C22 (search for similar items in EconPapers)
Pages: 13 pages
Date: 1999
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Journal Article: Semiparametric Estimation of the Intensity of Long Memory in Conditional Heteroskedasticity (2000)
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