EconPapers    
Economics at your fingertips  
 

The Henderson Smoother in Reproducing Kernel Hilbert Space

Estelle Dagum and Silvia Bianconcini ()

Journal of Business & Economic Statistics, 2008, vol. 26, 536-545

Abstract: The Henderson smoother has been traditionally applied for trend-cycle estimation in the context of nonparametric seasonal adjustment software officially adopted by statistical agencies. This study introduces a Henderson third-order kernel representation by means of the reproducing kernel Hilbert space (RKHS) methodology. Two density functions and corresponding orthonormal polynomials have been calculated. Both are shown to give excellent representations for short- and medium-length filters. Theoretical and empirical comparisons of the Henderson third-order kernel asymmetric filters are made with the classical ones. The former are shown to be superior in terms of signal passing, noise suppression, and revision size.

Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://pubs.amstat.org/doi/abs/10.1198/073500107000000322 full text (application/pdf)
Access to full text is restricted to subscribers.

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:bes:jnlbes:v:26:y:2008:p:536-545

Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano

More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().

 
Page updated 2025-03-22
Handle: RePEc:bes:jnlbes:v:26:y:2008:p:536-545