Identification of a class of index models: A topological approach
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Summary We establish nonparametric identification in a class of so-called index models by using a novel approach that relies on general topological results. Our proof strategy requires substantially weaker conditions on the functions and distributions characterising the model than those required by existing strategies; in particular, it does not require any large-support conditions on the regressors of our model. We apply the general identification result to additive random utility and competing risk models.
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An improved nonparametric estimator of sub-distribution function for bivariate competing risk models
2014 ◽
Vol 132
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pp. 229-241
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2020 ◽
2012 ◽
Vol 3
(8)
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pp. 152-154
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1990 ◽
Vol 5
(1)
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pp. 1-28
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2002 ◽
Vol 4
(2)
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pp. 157-170
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