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Modelling Nonlinear Economic Time Series$
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Timo Teräsvirta, Dag Tjøstheim, and Clive W. J. Granger

Print publication date: 2010

Print ISBN-13: 9780199587148

Published to Oxford Scholarship Online: May 2011

DOI: 10.1093/acprof:oso/9780199587148.001.0001

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Nonlinear and nonstationary models

Nonlinear and nonstationary models

Chapter:
(p.279) 11 Nonlinear and nonstationary models
Source:
Modelling Nonlinear Economic Time Series
Author(s):

Timo Teräsvirta

Dag Tjøstheim (Contributor Webpage)

W. J. Granger

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199587148.003.0011

Long memory, unit root models and cointegration are important in linear modelling of nonstationary processes, not the least in econometrics. Recently, nonlinear generalizations of these concepts have been attempted. The framework is mathematically demanding, requiring tools that can handle both nonstationarity and nonlinearity. Two such tools are local times and null recurrent Markov chains. These are reviewed in parametric and non‐parametric cases.

Keywords:   long memory, unit root, cointegration, nonlinear regression, nonstationary regression, nonparametric estimation, nonstationarity

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