Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/211145 
Year of Publication: 
2019
Series/Report no.: 
cemmap working paper No. CWP52/19
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
We establish nonparametric identification in a class of so-called index models using a novel approach that relies on general topological results. Our proof strategy imposes very weak smoothness conditions on the functions to be identified and does not require any large support conditions on the regressors in our model. We apply the general identification result to additive random utility and competing risk models.
Subjects: 
nonparametric identification
discrete choice
competing risks
index
JEL: 
C14
C35
C36
C41
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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