Nonlinear Persistence and Copersistence
AbstractIn a nonlinear framework, temporal dependence of time series is sensitive to transformations. The aim of this paper is to examine in detail the relationships between various forms of persistence and nonlinear transformations of stationary and nonstationary processes. We introduce the concept of persistence space and use it to define the degrees of persistence of univariate or multivariate processes. For illustration, we examine and compare the persistence structure of a fractionally integrated process and a beta mixture of AR(1) processes. The study of multivariate processes is focused on nonlinear comovements between the components, called the copersistence directions, or cointegration directions in the nonstationary case. We nd that, in general, there is a multiplicity of such directions, causing an identi cation problem in the analysis of nonlinear cointegration.
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Bibliographic InfoPaper provided by York University, Department of Economics in its series Working Papers with number 2000_1.
Length: 34 pages
Date of creation: Nov 1999
Date of revision:
Nonlinear Autocorrelogram; Canonical Analysis; Persistence; Chaos; Unit Root; Cointegration;
Other versions of this item:
- Christian Gourieroux & Joanna Jasiak, 1999. "Nonlinear Persistence and Copersistence," Working Papers 99-63, Centre de Recherche en Economie et Statistique.
- Gourieroux, Christian & Josiak, Joann, 1999. "Nonlinear persistence and copersistence," CEPREMAP Working Papers (Couverture Orange) 9920, CEPREMAP.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:
- Non-linear Functions of Non-Stationary Data Can be Stationary
by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2013-02-26 21:17:00
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