Abstract
This paper provides a very appealing approach to testing for nonlinear cointegration in a way that avoids a drawback faced by standard tests, which will often reject the null of cointegration in the presence of nonlinear cointegration. Unlike previous work on nonlinear cointegration (e.g. Granger and Teräsvirta, 1993; Granger, 1995; Granger, Inoue, and Morin, 1997; Swanson, Corradi, and White, 1997), the test is based on ranks. For a time series x t , t=1, …, T,R T (x t ) is the rank of x t in the sample of size T. To test the null of no nonlinear cointegration between x t and y t , one forms where d t = R T (y t ) −R T (x t ) is the difference in ranks. More sophisticated statistics are proposed, based on standardizing in reasonable ways, but it suffices for the present discussion to limit attention to these straightforward statistics.
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References
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© 1998 Springer Science+Business Media Dordrecht
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White, H. (1998). Comments on “A Nonparametric Test For Nonlinear Cointegration” By Jörg Breitung. In: Refenes, AP.N., Burgess, A.N., Moody, J.E. (eds) Decision Technologies for Computational Finance. Advances in Computational Management Science, vol 2. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5625-1_9
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DOI: https://doi.org/10.1007/978-1-4615-5625-1_9
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