This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Local Multiplicative Bias Correction for Asymmetric Kernel Density Estimators

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Matthias HAGMANN () (HEC-University of Lausanne and FAME)
Olivier SCAILLET () (HEC-University of Geneva and FAME)

Additional information is available for the following registered author(s):

Abstract

We consider semiparametric asymmetric kernel density estimators when the unknown density has support on [0, ¥). We provide a unifying framework which contains asymmetric kernel versions of several semiparametric density estimators considered previously in the literature. This framework allows us to use popular parametric models in a nonparametric fashion and yields estimators which are robust to misspecification. We further develop a specification test to determine if a density belongs to a particular parametric family. The proposed estimators outperform rival non- and semiparametric estimators in finite samples and are simple to implement. We provide applications to loss data from a large Swiss health insurer and Brazilian income data.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.swissfinanceinstitute.ch/rp91_revised.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by International Center for Financial Asset Management and Engineering in its series FAME Research Paper Series with number rp91.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: Sep 2003
Date of revision:
Handle: RePEc:fam:rpseri:rp91

Contact details of provider:
Postal: 40 bd. du Pont d'Arve, Case postale 3, CH - 1211 Geneva 4
Phone: 41 22 / 312 09 61
Fax: 41 22 / 312 10 26
Web page: http://www.swissfinanceinstitute.ch
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Marilyn Barja).

Related research
Keywords: semiparametric density estimation; asymmetric kernel; income distribution; loss distribution; health insurance; specification testing;

Other versions of this item:

Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods

This paper has been announced in the following NEP Reports:

Statistics
Access and download statistics

Did you know? All bibliographic data on IDEAS has been put in the public domain by the publishers.

This page was last updated on 2009-12-15.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.