Exploiting Cross Section Variation for Unit Root Inference in Dynamic Data

Danny Quah ()

FMG Discussion Papers from Financial Markets Group

Abstract: This paper considers unit root regressions in data having simultaneously extensive cross section and time-eries variation. The standard least squares estimators in such data structures turn out to have an asymptotic distribution that is neither Dickey-Fuller, nor normal and asymptotically unbiased. Instead, the estimator turns out to be consistent and asymptotically normal, but has a nonvanishing bias in its asymptotic distribution.

Date: 1993-10
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Related works:
Working Paper: Exploiting Cross Section Variation for Unit Root Inference in Dynamic Data (1993)
Journal Article: Exploiting cross-section variation for unit root inference in dynamic data (1994)
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Persistent link: http://EconPapers.repec.org/RePEc:fmg:fmgdps:dp171

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