Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/20082 
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dc.contributor.authorSchnedler, Wendelinen
dc.date.accessioned2009-01-28T16:11:28Z-
dc.date.available2009-01-28T16:11:28Z-
dc.date.issued2003-
dc.identifier.urihttp://hdl.handle.net/10419/20082-
dc.description.abstractThis article considers a wide class of censoring problems and presents a construction rule for an objective function. This objective function generalises the ordinary likelihood as well as particular ?likelihoods? used for estimation in several censoring models. Under regularity conditions the maximiser of this generalised likelihood has all the properties of a maximumlikelihood estimator: it is consistent and the respective root-n estimator is asymptotically efficient and normally distributed.en
dc.language.isoengen
dc.publisher|aInstitute for the Study of Labor (IZA) |cBonnen
dc.relation.ispartofseries|aIZA Discussion Papers |x837en
dc.subject.jelC13en
dc.subject.jelC24en
dc.subject.ddc330en
dc.subject.keywordcensored variablesen
dc.subject.keywordM-estimationen
dc.subject.keywordmultivariate methodsen
dc.subject.keywordrandom censoringen
dc.subject.keywordgeneralised likelihooden
dc.subject.stwTobit-Modellen
dc.subject.stwSchätztheorieen
dc.subject.stwTheorieen
dc.titleWhat You Always Wanted to Know About Censoring But Never Dared to Ask - Parameter Estimation for Censored Random Vectors-
dc.typeWorking Paperen
dc.identifier.ppn367381028en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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