What You Always Wanted to Know About Censoring But Never Dared to Ask - Parameter Estimation for Censored Random Vectors

Arbeitspapier

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 efficient and normally distributed.

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• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IZA Discussion Papers ; No. 837

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Single Equation Models; Single Variables: Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
• Subject: censored variables ; M-estimation ; multivariate methods ; random censoring ; generalised likelihood ; Tobit-Modell ; Schätztheorie ; Theorie

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Schnedler, Wendelin
• Event: Veröffentlichung
• (who): Institute for the Study of Labor (IZA)
• (where): Bonn
• (when): 2003

Further information

• Handle: http://hdl.handle.net/10419/20082