A Powerful Test for Linearity When the Order of Integration is Unknown
AbstractIn this paper we propose a test of the null hypothesis of time series linearity against a nonlinear alternative, when uncertainty exists as to whether or not the series contains a unit root. We provide a test statistic that has the same limiting null critical values regardless of whether the series under consideration is generated from a linear I(0) or linear I(1) process, and is consistent against nonlinearity of either form, being asymptotically equivalent to the efficient test in each case. Finite sample simulations show that the new procedure has better size control and offers substantial power gains over the recently proposed robust linearity test of Harvey and Leybourne (2007).
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Bibliographic InfoArticle provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.
Volume (Year): 12 (2008)
Issue (Month): 3 (September)
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Web page: http://www.degruyter.com
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- Yavuz, Nilgün Çil & Yilanci, Veli, 2012. "Testing For Nonlinearity In G7 Macroeconomic Time Series," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 69-79, September.
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- Cuestas, Juan Carlos & Regis, Paulo José, 2013. "Purchasing power parity in OECD countries: Nonlinear unit root tests revisited," Economic Modelling, Elsevier, vol. 32(C), pages 343-346.
- Paulo M.M. Rodrigues & A. M. Robert Taylor, 2009. "The Flexible Fourier Form and Local GLS De-trended Unit Root Tests," Working Papers w200919, Banco de Portugal, Economics and Research Department.
- Aslan, Alper, 2011. "Does natural gas consumption follow a nonlinear path over time? Evidence from 50 US States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4466-4469.
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