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