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 InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 44 (1994)
Issue (Month): 1-2 ()
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Web page: http://www.elsevier.com/locate/ecolet
Other versions of this item:
- Danny Quah, 1993. "Exploiting Cross Section Variation for Unit Root Inference in Dynamic Data," FMG Discussion Papers dp171, Financial Markets Group.
- Quah, D., 1993. "Exploiting Cross Section Variation for Unit Root Inference in Dynamic Data," Papers 549, Stockholm - International Economic Studies.
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