A Gini-Based Test for Unit Root

We suggest a Gini-based statistical test for unit root. This test is based on the well-known Dickey-Fuller test, where the ordinary least squares (OLS) regression is replaced by the semi-parametric Gini regression in modeling the AR process. A residual-based bootstrap is used for finding critical values. The Gini methodology is a rank-based methodology that takes into account both the variate values and the ranks. Therefore, it provides robust estimators that are rank-based, while avoiding loss of information. Furthermore, the Gini methodology relies on first-order moment assumptions, which makes it valid for a wide range of distributions. Simulation results validate the Gini-based test and indicate its superiority in some design settings, when compared to other available procedures. The Gini-based test opens the door for further developments such as a Gini-based cointegration test