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On the Identification of the Censored Regression Model with a Stochastic and Unobserved Treshold

We show that a sufficient condition for the identification of all parameters of the censored regression model with a stochastic and unobserved threshold is that the errors are jointly normally distributed. Exclusion restrictions are not needed. <BR><BR>
Year of publication:
1998-03-23
Authors: Ridder, Geert ; Montfort, Kees van
Institutions: Tinbergen Institute
Extent:
application/pdf
Series:
Type of publication: Book / Working Paper
Notes:
The text is part of a series Tinbergen Institute Discussion Papers Number 98-034/4
Classification: C34 - Truncated and Censored Models
Source:
Persistent link: https://www.econbiz.de/10005795565
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