Non-normal errors or nonlinearity? performance of unit root tests

This paper investigates how unit root tests that are designed for non-normal errors perform in the presence of unknown forms of nonlinearity. This allows us to examine whether any neglected nonlinearity in an estimation procedure could be reflected, at least partly, in the form of non-normality. Our simulation study shows that in general, univariate tests that exploit the information in non-normal errors remain relatively powerful compared to well-known nonlinear unit root tests under various forms of nonlinear alternatives. We also investigate the unit root properties of the real effective exchange rates and real interest rates for 60 countries. The results support the findings in the simulation that the neglected non-normality or nonlinearity in the existing tests is captured and used in the linearized testing procedures as a source of power improvement.