What you always wanted to know about censoring but never dared to ask
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 maximum likelihood estimator: it is consistent and the respective root-n estimator is asymptotically e±cient and normally distributed.
|Date of creation:||Jul 2003|
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Nelson, Forrest D., 1977. "Censored regression models with unobserved, stochastic censoring thresholds," Journal of Econometrics, Elsevier, vol. 6(3), pages 309-327, November.
- Amemiya, Takeshi, 1973. "Regression Analysis when the Dependent Variable is Truncated Normal," Econometrica, Econometric Society, vol. 41(6), pages 997-1016, November.
- Orazio P. Attanasio, 2000. "Consumer Durables and Inertial Behaviour: Estimation and Aggregation of (S, s) Rules for Automobile Purchases," Review of Economic Studies, Oxford University Press, vol. 67(4), pages 667-696.
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