Del Barrio Castro, T and Rodrigues, PMM and Taylor, AMR (2015) Semi-Parametric Seasonal Unit Root Tests. UNSPECIFIED. Essex Finance Centre Working Papers.
Del Barrio Castro, T and Rodrigues, PMM and Taylor, AMR (2015) Semi-Parametric Seasonal Unit Root Tests. UNSPECIFIED. Essex Finance Centre Working Papers.
Del Barrio Castro, T and Rodrigues, PMM and Taylor, AMR (2015) Semi-Parametric Seasonal Unit Root Tests. UNSPECIFIED. Essex Finance Centre Working Papers.
Abstract
It is well known that (seasonal) unit root tests can be seriously affected by the presence of weak dependence in the driving shocks when this is not accounted for. In the non-seasonal case both parametric (based around augmentation of the test regression with lagged dependent variables) and semi-parametric (based around an estimator of the long run variance of the shocks) unit root tests have been proposed. Of these, the M class of unit root tests introduced by Stock (1999), Perron and Ng (1996) and Ng and Perron (2001), appear to be particularly successful, showing good finite sample size control even in the most problematic (near-cancellation) case where the shocks contain a strong negative moving average component. The aim of this paper is threefold. First we show the implications that neglected weak dependence in the shocks has on lag un-augmented versions of the well known regression based seasonal unit root tests of Hylleberg et al. (1990). Second, in order to complement extant parametrically augmented versions of the tests of Hylleberg et al. (1990), we develop semi-parametric seasonal unit root test procedures, generalising the methods developed in the non-seasonal case to our setting. Third, we compare the finite sample size and power properties of the parametric and semi-parametric seasonal unit root tests considered. Our results suggest that the superior size/power trade-off offered by the M approach in the non-seasonal case carries over to the seasonal case.
Item Type: | Monograph (UNSPECIFIED) |
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Uncontrolled Keywords: | Seasonal unit roots; weak dependence; lag augmentation; long run variance estimator; demodulated process |
Subjects: | H Social Sciences > HG Finance |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 26 May 2016 22:05 |
Last Modified: | 16 May 2024 18:45 |
URI: | http://repository.essex.ac.uk/id/eprint/16807 |
Available files
Filename: 10 semi-parametric.pdf