ESTIMATION OF THE LONG-RUN AVERAGE RELATIONSHIP IN NONSTATIONARY PANEL TIME SERIES

Yixiao Sun

Econometric Theory, 2004, vol. 20, issue 06, pages 1227-1260

Abstract: This paper proposes a new class of estimators of the long-run average relationship in nonstationary panel time series. The estimators are based on the long-run average variance estimate using bandwidth equal to T. The new estimators include the pooled least squares estimator and the fixed effects estimator as special cases. It is shown that the new estimators are consistent and asymptotically normal under both the sequential limit, wherein T followed by n , and the joint limit where T,n simultaneously. The rate condition for the joint limit to hold is relaxed to , which is less restrictive than the rate condition n T 0, as imposed by Phillips and Moon (1999, Econometrica 67, 1057 1111). By exponentiating existing kernels, this paper introduces a new approach to generating kernels and shows that these exponentiated kernels can deliver more efficient estimates of the long-run average coefficient.I am grateful to Bruce Hansen, Peter Phillips, Zhijie Xiao, and three anonymous referees for constructive comments and suggestions. All errors are mine alone.

Date: 2004
View citations in EconPapers

Downloads: (external link)
http://journals.cambridge.org/abstract_S0266466604206077 link to article abstract page (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:20:y:2004:i:06:p:1227-1260_20

Access Statistics for this article

More articles in Econometric Theory from Cambridge University Press
Address: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Series data maintained by Mike Eden ().