Robust Rank Tests of the Unit Root Hypothesis
The authors consider a family of rank tests based on the regression rank score process introduced by C. Gutenbrunner and J. Jureckova (1992) to test the unit root hypothesis in economic time series. In contrast to tests based on least-squares methods, the rank tests are asymptotically Gaussian under the null hypothesis, and have excellent power--particularly under innovation exhibiting heavy tails. These regression rank scores arise as a vector of solutions of the dual form of the linear program required to compute the regression quantile statistics of R. W. Koenker and G. Bassett (1978). For location model, they are simple ranks of the sample observations.
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Volume (Year): 65 (1997)
Issue (Month): 1 (January)
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