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dc.contributor.authorKapetanios, Georgeen_US
dc.description.abstractInterest in the interface of nonstationarity and nonlinearity has been increasing in the econometric literature. The motivation for this development maybe be traced to the perceived possibility that processes following nonlinear models maybe mistakenly taken to be unit root or long-memory nonstationary. This paper considers the possibility that processes may exhibit both long memory and nonlinearity. We test against the possibility that the process ut in the model (1-L)dyt = ut is nonlinear. We do not assume a particular parametric form for the nonlinear process but construct a pure significance test. Clearly, such a test could be straightforwardly constructed if d were known. Unfortunately, if a linear model is assumed while estimating d the power of the test will be reduced. We propose new more powerful tests for this problem. We present Monte Carlo evidence on the performance of the new tests and apply them to Yen real exchange rates.en_US
dc.publisher|aQueen Mary, Univ. of London, Dep. of Economics |cLondonen_US
dc.relation.ispartofseries|aWorking Paper, Department of Economics, Queen Mary, University of London |x473en_US
dc.subject.keywordLong memory, Nonlinearity, Neural networksen_US
dc.subject.stwNeuronale Netzeen_US
dc.subject.stwNichtlineares Verfahrenen_US
dc.titleTesting for neglected nonlinearity in long memory modelsen_US
dc.typeWorking Paperen_US

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