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 model
