A Score Test for Individual Heteroscedasticity in a One-way Error Components Model

Alberto Holly and Lucien Gardiol

Cahiers de Recherches Economiques du Département d'économie from Université de Lausanne, Faculté des HEC, Département d’économie

Abstract: The purpose of this paper is to derive a Rao's efficient score statistic for testing for heteroscedasticity in an error components model with only individual effects. We assume that the individual effect exists and therefore do not test for it. In addition, we assume that the individual effects, and not the white noise term may be heteroscedastic. Finally, we assume that the error components are normally distributed. We first establish, under a specific set of assumptions, the asymptotic distribution of the Score under contiguous alternatives. We then derive the expression for the Score test statistic for individual heteroscedasticity. Finally, we discuss the asymptotic local power of this Score test statistic.

Keywords: panel data; error components model; score test; individual heteroscedasticity: contiguous alternatives; asymptotic local power (search for similar items in EconPapers)
JEL-codes: C12 C23 (search for similar items in EconPapers)
Pages: 18 pages
Date: 1999-09
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.hec.unil.ch/deep/textes/9915.pdf (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:lau:crdeep:9915

Access Statistics for this paper

More papers in Cahiers de Recherches Economiques du Département d'économie from Université de Lausanne, Faculté des HEC, Département d’économie Université de Lausanne, Faculté des HEC, Département d’économie, Internef, CH-1015 Lausanne. Contact information at EDIRC.
Bibliographic data for series maintained by Christina Seld ().