Testing for co-non-linearity

Håvard Hungnes

Discussion Papers from Statistics Norway, Research Department

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.

Keywords: Common features; non-linearity; reduced rank regression (search for similar items in EconPapers)
JEL-codes: C32 E43 (search for similar items in EconPapers)
Date: 2012-07
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (1)

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Journal Article: Testing for co-nonlinearity (2015)
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