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Exploiting Cross Section Variation for Unit Root Inference in Dynamic Data

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Danny Quah

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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.

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Paper provided by Financial Markets Group in its series FMG Discussion Papers with number dp171.

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Date of creation: Oct 1993
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Handle: RePEc:fmg:fmgdps:dp171

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This page was last updated on 2009-11-16.


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