Robust estimation in linear regression models with fixed effects

Isabel Molina and Betsabé Pérez
Authors registered in the RePEc Author Service: Daniel Peña

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: In this work we extend the procedure proposed by Peña and Yohai (1999) for computing robust regression estimates in linear models with fixed effects. We propose to calculate the principal sensitivity components associated to each cluster and delete the set of possible outliers based on an appropriate robust scale of the residuals. Some advantage of our robust procedure are: (a) it is computationally low demanding, (b) it is able to avoid the swamping effect often present in similar methods, (c) it is appropriate for contamination in the error term (vertical outliers) and possibly masked high leverage points (horizontal outliers). The performance of the robust procedure is investigated through several simulation studies.

Keywords: Fixed; effects; models; Outlier; detection; Principal; sensitivity; vectors (search for similar items in EconPapers)
Date: 2009-12
New Economics Papers: this item is included in nep-ecm
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://e-archivo.uc3m.es/rest/api/core/bitstreams ... 9f98fe11fd64/content (application/pdf)

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:cte:wsrepe:ws098827

Access Statistics for this paper

More papers in DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística
Bibliographic data for series maintained by Ana Poveda ().