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https://hdl.handle.net/10419/20082
Kompletter Metadatensatz
DublinCore-Feld | Wert | Sprache |
---|---|---|
dc.contributor.author | Schnedler, Wendelin | en |
dc.date.accessioned | 2009-01-28T16:11:28Z | - |
dc.date.available | 2009-01-28T16:11:28Z | - |
dc.date.issued | 2003 | - |
dc.identifier.uri | http://hdl.handle.net/10419/20082 | - |
dc.description.abstract | This 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.iso | eng | en |
dc.publisher | |aInstitute for the Study of Labor (IZA) |cBonn | en |
dc.relation.ispartofseries | |aIZA Discussion Papers |x837 | en |
dc.subject.jel | C13 | en |
dc.subject.jel | C24 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | censored variables | en |
dc.subject.keyword | M-estimation | en |
dc.subject.keyword | multivariate methods | en |
dc.subject.keyword | random censoring | en |
dc.subject.keyword | generalised likelihood | en |
dc.subject.stw | Tobit-Modell | en |
dc.subject.stw | Schätztheorie | en |
dc.subject.stw | Theorie | en |
dc.title | What You Always Wanted to Know About Censoring But Never Dared to Ask - Parameter Estimation for Censored Random Vectors | - |
dc.type | Working Paper | en |
dc.identifier.ppn | 367381028 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
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