2011
DOI: 10.1016/j.jeconom.2010.11.010
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Cross-sectional dependence robust block bootstrap panel unit root tests

Abstract: JEL classification: C15 C23Keywords: Block bootstrap Panel unit root test Cross-sectional dependence a b s t r a c t In this paper we consider the issue of unit root testing in cross-sectionally dependent panels. We consider panels that may be characterized by various forms of cross-sectional dependence including (but not exclusive to) the popular common factor framework. We consider block bootstrap versions of the groupmean (Im et al., 2003) and the pooled (Levin et al., 2002) unit root coefficient DF tests f… Show more

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Cited by 87 publications
(83 citation statements)
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“…In this context, in case of an existence of CSD among the constituent units of panel, first generation panel unit root tests do not provide the consistent results (Hadri, 2000;Levin et al, 2002;Im et al, 2003;etc. ) whereas second generation panel unit root tests providing more consistent results (Taylor and Sarno, 1998;Breuer et al, 2002;Pesaran, 2007;Palm et al, 2011;Hadri and Kurozumi, 2012;Pesaran et al, 2013;etc. ) can be used.…”
Section: Econometric Methodology and Findingsmentioning
confidence: 86%
“…In this context, in case of an existence of CSD among the constituent units of panel, first generation panel unit root tests do not provide the consistent results (Hadri, 2000;Levin et al, 2002;Im et al, 2003;etc. ) whereas second generation panel unit root tests providing more consistent results (Taylor and Sarno, 1998;Breuer et al, 2002;Pesaran, 2007;Palm et al, 2011;Hadri and Kurozumi, 2012;Pesaran et al, 2013;etc. ) can be used.…”
Section: Econometric Methodology and Findingsmentioning
confidence: 86%
“…The Stationary Bootstrap is a block bootstrap scheme where the resampled pseudo-series are stationary; this scheme chains blocks of observations of the original series starting at random locations, and the length of each block is randomly chosen from a geometric distribution. Following Palm et al [24], the mean block length can be computed as a function of the length of the time sample; by some exploratory simulations we verify the robustness of the tests to different block sizes, so we report results for blocks 1.75…”
Section: Empirical Applicationsmentioning
confidence: 98%
“…We follow Ng and Perron (2001) and use the modified Akaike information criterion (MAIC) (with maximum lag of 12(T/100) 1/4 ), which is an information criterion that has been tailored to particular unit root testing situation considered here. 22 Next, the block length is set equal to b = 1.75T 1/3 , as in as in Palm et al (2011). The testing is carried out at the 5 % significance level.…”
Section: Technical Issues and Alternative Testsmentioning
confidence: 99%