Exploiting Cross Section Variation for Unit Root Inference in Dynamic Data
AbstractThis 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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Bibliographic InfoPaper provided by Financial Markets Group in its series FMG Discussion Papers with number dp171.
Date of creation: Oct 1993
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Web page: http://www.lse.ac.uk/fmg/
Other versions of this item:
- Quah, Danny, 1994. "Exploiting cross-section variation for unit root inference in dynamic data," Economics Letters, Elsevier, vol. 44(1-2), pages 9-19.
- Quah, D., 1993. "Exploiting Cross Section Variation for Unit Root Inference in Dynamic Data," Papers 549, Stockholm - International Economic Studies.
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