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Unit root testing via the stationary bootstrap
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DOI：10.1016/j.jeconom.2005.06.008.png)
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Abstract
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A nonparametric, residual-based stationary bootstrap procedure is proposed for unit root testing in a time series. The procedure generates a pseudoseries which mimics the original, but ensures the presence of a unit root. Unlike many others in the literature, the proposed test is valid for a wide class of weakly dependent processes and is not based on parametric assumptions on the data-generating process. Large sample theory is developed and asymptotic validity is shown via a bootstrap functional central limit theorem. The case of a least squares statistic is discussed in detail, including simulations to investigate the procedure's finite sample performance. (c) 2005 Elsevier B.V. All rights reserved.
Keywords:
autocorrelation
integrated time series
resampling
stationary bootstrap
unit root testing
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