Bootstrap Unit Root Tests for Nonlinear Threshold Models

While a number of unit root testing procedures have been developed to account for nonlinearity under the alternative hypothesis of stationarity, almost all available tests assume a linear DGP under the unit root null hypothesis. This paper establishes some theoretical results relating to the inclusion of nonlinear terms in an ADF regression and proposes two new unit root tests that allow the process to be nonlinear under the null hypothesis. More specifically, block and model-based bootstrap procedures are developed for smooth transition threshold models. Simulations show that the latter is preferred and the model-based bootstrap test delivers a good size performance across all specifications, including linear and effectively abrupt transition models. The modelbased test also dominates the standard ADF test in terms of power and an application to the US unemployment rate shows that it can overturn conclusions based on an erroneous linearity assumption.

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