EconPapers    
Economics at your fingertips  
 

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

Abstract: 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

Date: 2002
References: Add references at CitEc
Citations: View citations in EconPapers (4)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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: 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
http://www.ectj.org

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 () and Christopher F. Baum ().

 
Page updated 2025-03-19
Handle: RePEc:ect:emjrnl:v:5:y:2002:i:1:p:160-175