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Testing for co-nonlinearity

  • Håvard Hungnes EMAIL logo

Abstract

This article introduces the concept of co-nonlinearity. Co-nonlinearity is an example of a common feature in time series [Engle, Robert F., and Sharon Kozicki. 1993. “Testing for Common Features.” Journal of Business & Economic Statistics 11 (4): 369–380] and an extension of the concept of common nonlinear components [Anderson, Heather M., and Farshid Vahid. 1998. “Testing Multiple Equation Systems for Common Nonlinear Components.” Journal of Econometrics 84 (1): 1–36]. If some time series follow a nonlinear process but where a linear relationship between the levels of these series removes the nonlinearity, such a relationship is defined as co-nonlinear. In this article I show how to determine the number of such co-nonlinear relationships. Furthermore, I show how to formulate hypothesis tests on the co-nonlinear relationships in a full maximum likelihood framework. The framework for identifying co-nonlinear relationships is illustrated in a system of Norwegian interest rates.

JEL Classification: C32; E43

Corresponding author: Håvard Hungnes, Research Department, Statistics Norway, P.O.B. 8131 Dep, N-0033 Oslo, Norway, e-mail: . Websites: http://people.ssb.no/hhu and http://www.hungnes.net

Acknowledgments

Thanks to Pål Boug, Thomas von Brasch, Neil Ericsson, Arvid Raknerud, Terje Skjerpen, Timo Teräsvirta and an anonymous referee for valuable comments on an earlier version of this article.

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Supplemental Material

The online version of this article (DOI: https://doi.org/10.1515/snde-2013-0092) offers supplementary material, available to authorized users.


Published Online: 2014-11-04
Published in Print: 2015-06-01

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