The Tobit Model with a Non-Zero Threshold

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dc.contributor.author Carson, Richard en_US
dc.contributor.author Sun, Yixiao en_US
dc.contributor.editor en_US
dc.date.accessioned 2012-02-02T11:02:32Z
dc.date.available 2012-02-02T11:02:32Z
dc.date.issued 2007 en_US
dc.identifier 2010000878 en_US
dc.identifier.citation Carson Richard and Sun Yixiao 2007, 'The Tobit Model with a Non-Zero Threshold', Wiley-Blackwell Publishing Ltd., vol. 10, no. 3, pp. 488-502. en_US
dc.identifier.issn 1368-4221 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/15744
dc.description.abstract The standard Tobit maximum likelihood estimator under zero censoring threshold produces inconsistent parameter estimates, when the constant censoring threshold I? is nonzero and unknown. Unfortunately, the recording of a zero rather than the actual censoring threshold value is typical of economic data. Non-trivial minimum purchase prices for most goods, fixed cost for doing business or trading, social customs such as those involving charitable donations, and informal administrative recording practices represent common examples of nonzero constant censoring threshold where the constant threshold is not readily available to the econometrician. Monte Carlo results show that this bias can be extremely large in practice. A new estimator is proposed to estimate the unknown censoring threshold. It is shown that the estimator is superconsistent and follows an exponential distribution in large samples. Due to the superconsistency, the asymptotic distribution of the maximum likelihood estimator of other parameters is not affected by the estimation uncertainty of the censoring threshold. en_US
dc.language en_US
dc.publisher Wiley-Blackwell Publishing Ltd. en_US
dc.relation.isbasedon http://dx.doi.org/10.1111/j.1368-423X.2007.00218.x en_US
dc.title The Tobit Model with a Non-Zero Threshold en_US
dc.parent The Econometrics Journal en_US
dc.journal.volume 10 en_US
dc.journal.number 3 en_US
dc.publocation United Kingdom en_US
dc.identifier.startpage 488 en_US
dc.identifier.endpage 502 en_US
dc.cauo.name BUS.Faculty of Business en_US
dc.conference Verified OK en_US
dc.for 140300 en_US
dc.personcode 100722 en_US
dc.personcode 0000065788 en_US
dc.percentage 100 en_US
dc.classification.name Econometrics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Exponential distribution, Maximum likelihood, Order statistic, Threshold determination. en_US


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