A family of nonparametric unit root tests for processes driven by infinite variance innovations

Gogebakan Kemal Caglar ()
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Gogebakan Kemal Caglar: Department of Economics, Bilkent University, Ankara, Turkey

Studies in Nonlinear Dynamics & Econometrics, 2022, vol. 26, issue 5, 705-721

Abstract: This paper presents extensions to the family of nonparametric fractional variance ratio (FVR) unit root tests of Nielsen (2009. “A Powerful Test of the Autoregressive Unit Root Hypothesis Based on a Tuning Parameter Free Statistic.” Econometric Theory 25: 1515–44) under heavy tailed (infinite variance) innovations. In this regard, we first develop the asymptotic theory for these FVR tests under this setup. We show that the limiting distributions of the tests are free of serial correlation nuisance parameters, but depend on the tail index of the infinite variance process. Then, we compare the finite sample size and power performance of our FVR unit root tests with the well-known parametric ADF test under the impact of the heavy tailed shocks. Simulations demonstrate that under heavy tailed innovations, the nonparametric FVR tests have desirable size and power properties.

Keywords: heavy tailed innovation; infinite variance distribution; nonparametric test; unit root test (search for similar items in EconPapers)
JEL-codes: C14 C15 C22 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1515/snde-2021-0058

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