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Econometric Reviews
Article . 2013 . Peer-reviewed
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Detrending Bootstrap Unit Root Tests

Authors: Smeekes Stephan;

Detrending Bootstrap Unit Root Tests

Abstract

The role of detrending in bootstrap unit root tests is investigated. When bootstrapping, detrending must not only be done for the construction of the test statistic, but also in the first step of the bootstrap algorithm. It is argued that the two issues should be treated separately. Asymptotic validity of sieve bootstrap augmented DickeyFuller (ADF) unit root tests is shown for test statistics based on full sample and recursive ordinary least squares (OLS) and generalized least squares (GLS) detrending. It is also shown that the detrending method in the first step of the bootstrap may differ from the one used in the construction of the test statistic. A simulation study is conducted to analyze the effects of detrending on finite sample performance of the bootstrap test. It is found that full sample OLS detrending should be preferred based on power in the first step of the bootstrap algorithm, and that the decision about the detrending method used to obtain the test statistic should be based on the power properties of the corresponding asymptotic tests.

Country
Netherlands
Related Organizations
Keywords

TREND, Deterministic trends, INITIAL CONDITION, SIEVE BOOTSTRAP, POWER, econometrics;, NONSTATIONARY VOLATILITY, AUTOREGRESSIVE TIME-SERIES, UNCERTAINTY, Sieve bootstrap, RECURSIVE MEAN ADJUSTMENT, Unit root test, REGRESSION, C15, C22

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Average
hybrid