Consistency of kernel variance estimators for sums of semiparametric linear processes
James Davidson () and
Robert de Jong
Econometrics Journal, 2002, vol. 5, issue 1, 160-175
Conditions are derived for the consistency of kernel estimators of the variance of a sum of dependent heterogeneous random variables, with a representation as moving averages of near-epoch dependent functions of a mixing process. Fourth moments are not generally required. The conditions permit more dependence than a purely non-parametric representation allows, and may be close to those of the best-known conditions for the functional central limit theorem. The class of permitted kernel functions is different from those usually considered, but can approximate most of the usual choices arbitrarily closely, and can be extended to include them subject to a seemingly innocuous extra condition on the random process. Copyright Royal Economic Society 2002
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
http://www.blackwell-synergy.com/servlet/useragent ... &year=2002&part=null link to full text (text/html)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:5:y:2002:i:1:p:160-175
Ordering information: This journal article can be ordered from
Access Statistics for this article
Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms
More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing ().