Testing for Neglected Nonlinearity in Long Memory Models
U of London Queen Mary Economics Working Paper No. 473
21 Pages Posted: 14 Jan 2003
Date Written: November 2002
Interest 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 u_t in the model (1-L)^d y_t = u_t 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.
Keywords: Long Memory, Nonlinearity, Neural Networks, Real Exchange Rates
JEL Classification: C22, C12, F31
Suggested Citation: Suggested Citation