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A Gini-based unit root test

Amit Shelef

Computational Statistics & Data Analysis, 2016, vol. 100, issue C, 763-772

Abstract: A Gini-based statistical test for a unit root is suggested. 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 to find 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 validates its use for a wide range of distributions. Simulation results validate the Gini-based test and indicate its superiority in some design settings in comparison to other available procedures. The Gini-based test opens the door for further developments such as a Gini-based cointegration test.

Keywords: Time series analysis; Unit root tests; Gini regression; Bootstrap (search for similar items in EconPapers)
Date: 2016
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Handle: RePEc:eee:csdana:v:100:y:2016:i:c:p:763-772