Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/192681 
Year of Publication: 
2012
Series/Report no.: 
Discussion Papers No. 699
Publisher: 
Statistics Norway, Research Department, Oslo
Abstract: 
This article introduces the concept of co-non-linearity. Co-non-linearity is an example of a common feature in time series (Engle and Koziciki, 1993, J. Bus. Econ. Statist.) and an extension of the concept of common nonlinear components (Anderson and Vahid, 1998, J. Econometrics). If some time series follow a non-linear process but there exists a linear relationship between the levels of these series that removes the non-linearity, then this relationship is said to be a co-non-linear relationship. In this article I show how to determine the number of such co-non-linear relationships. Furthermore, I show how to formulate hypothesis tests on the co-non-linear relationships in a full maximum likelihood framework.
Subjects: 
Common features
non-linearity
reduced rank regression
JEL: 
C32
E43
Document Type: 
Working Paper

Files in This Item:
File
Size
241.39 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.