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Modelling nonlinearity and long memory in time series

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 School of Economics and Political Science, London, UK.

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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
Library of Congress subject classification: H Social Sciences > HB Economic Theory
Journal of Economic Literature Classification System: C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models
Sets: Collections > Economists Online
Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Identification Number: EM/1997/319
Date Deposited: 27 Apr 2007
URL: http://eprints.lse.ac.uk/2065/

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