Robinson, Peter M. and Zaffaroni, Paolo (1997) Modelling nonlinearity and long memory in time series. Econometrics; EM/1997/319 (EM/1997/319). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.
Full text not available from this repository.Abstract
We discuss models that impart a form of long memory in raw time series xt or instantaneous functions thereof, in particular . on the basis of a linear or nonlinear model. The capacity of linear models for xt to imply long-memory in nonlinear functions of xt is discussed. Empirical observation motivates investigation of models which lead to short memory, or even white noise, xt but a long memory . One such model which we describe is based on the long memory generalized ARCH model introduced by Robinson (1991b). The other is an extension of the nonlinear moving average model of Robinson (1977).
| Item Type: | Monograph (Discussion Paper) |
|---|---|
| Official URL: | http://sticerd.lse.ac.uk |
| Additional Information: | © 1997 the authors |
| Divisions: | Economics STICERD |
| Subjects: | H Social Sciences > HB Economic Theory |
| JEL classification: | C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models |
| Date Deposited: | 27 Apr 2007 |
| Last Modified: | 11 Dec 2024 18:23 |
| URI: | http://eprints.lse.ac.uk/id/eprint/2065 |
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