A powerful test for linearity when the order of integration is unknown [Revised to become No. 07/06 above]
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 good size control and offers substantial power gains over the recently proposed robust linearity test of Harvey and Leybourne (2007).
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Bibliographic InfoPaper provided by University of Nottingham, Granger Centre for Time Series Econometrics in its series Discussion Papers with number 07/01.
Date of creation: Oct 2007
Date of revision:
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Postal: School of Economics University of Nottingham University Park Nottingham NG7 2RD
Phone: (44) 0115 951 5620
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Web page: http://www.nottingham.ac.uk/economics/grangercentre/
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Nonlinearity testing; Wald tests; unit root tests; stationarity tests;
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