Semiparametric spectral methods are valuable in that they yield inference on time series under very broad assumptions. This contribution analyzes the averaged periodogram statistic in the framework of a generalized linear process with (possibly long memory) conditional heteroscedasticity in the innovations. It is shown that the averaged periodogram statistic is appropriate for asymptotically normal estimation of the spectrum of a weakly dependent process at frequency zero and for consistent estimation of long memory and stationary cointegration in strongly dependent processes.
|Translated title of the contribution||Spectral estimatioin with long memory conditional heteroscedasticity|
|Number of pages||4|
|Journal||Comptes Rendus de l'Academie des Sciences - Series I: Mathematics|
|State||Published - Jan 1 1999|
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