Count data models with variance of unknown form: an application to a hedonic model of worker absenteeism

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dc.contributor.author Delgado, Miguel A.
dc.contributor.author Kniefner, Thomas J.
dc.date.accessioned 2009-06-24T12:51:47Z
dc.date.available 2009-06-24T12:51:47Z
dc.date.issued 1997
dc.identifier.bibliographicCitation Review of Economics and Statistics, 1997, vol. 79, nº 1, p. 41-49
dc.identifier.issn 0034-6535
dc.identifier.uri http://hdl.handle.net/10016/2435
dc.description.abstract We examine an econometric model of counts of worker absences due to illness in a sluggishly adjusting hedonic labor market. We compare three estimators that parameterize the conditional variance?least squares, Poisson, and negative binomial pseudo maximum likelihood?to generalized least squares (GLS) using nonparametric estimates of the conditional variance. Our data support the hedonic absenteeism model. Semiparametric GLS coefficients are similar in sign, magnitude, and statistical significance to coefficients where the mean and variance of the errors are specified ex ante. In our data, coefficient estimates are sensitive to a regressor list but not to the econometric technique, including correcting for possible heteroskedasticity of unknown form.
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher MIT Press
dc.title Count data models with variance of unknown form: an application to a hedonic model of worker absenteeism
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1162/003465397556520
dc.subject.eciencia Economía
dc.identifier.doi 10.1162/003465397556520
dc.rights.accessRights openAccess
dc.type.version publishedVersion
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