Effects of Applying Linear and Nonlinear Filters on Tests for Unit Roots with Additive Outliers
AbstractConventional univariate Dickey-Fuller tests tend to produce spurious stationarity when there exist additive outlying observations in the time series. Correct critical values are usually obtained by adding dummy variables to the Dickey-Fuller regression. This is a nice theoretical result but not attractive from the empirical point of view since almost any result can be obtained just by a convenient selection of dummy variables. In this paper we suggest a robust procedure based on running Dickey-Fuller tests on the trend component instead of the original series. We provide both finite-sample and large-sample justifications. Practical implementation is illustrated through an empirical example based on the US/Finland real exchange rate series.
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Bibliographic InfoPaper provided by Universidad Carlos III, Departamento de Economía in its series Economics Working Papers with number we20091101.
Date of creation: Sep 2002
Date of revision: Nov 2009
Additive outliers; Dickey-Fuller test; Linear and nonlinear filtering; Bootstrap;
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- Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011.
"Modelling Electricity Prices: International Evidence,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
- Alvaro Escribano & Juan Ignacio Peña & Pablo Villaplana, 2002. "Modeling Electricity Prices: International Evidence," Economics Working Papers we022708, Universidad Carlos III, Departamento de Economía.
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