QUASI-MAXIMUM LIKELIHOOD ESTIMATION OF LONG-MEMORY LIMITING AGGREGATE PROCESSES

We consider the application of the limiting aggregate model derived by Tsai and Chan (2005d) for modeling aggregated long-memory data. The model is characterized by the fractional integration order of the original process and may be useful for (i) modeling discrete-time data with sucien tly long sampling intervals, for example, annual data, and/or (ii) studying the fractional integration order of the original process. The fractional integration parameter is estimated by maximizing the Whittle likelihood. It is shown that the quasi-maximum likelihood estimator is asymptotically normal, and its nite-sample properties are studied through sim- ulation. The ecacy of the proposed approach is demonstrated with three data analyses.

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