论文标题
识别一类索引模型：拓扑方法
Identification of a class of index models: A topological approach
论文作者
论文摘要
我们使用依赖一般拓扑结果的新方法在一类所谓的指数模型中建立非参数识别。与现有策略相比，我们的证明策略要求对模型的功能和分布的条件大大较弱；特别是，它不需要在我们模型的回归器上进行任何较大的支持条件。我们将一般识别结果应用于添加剂随机效用和竞争风险模型。
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 requires substantially weaker conditions on the functions and distributions characterizing the model compared to 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.
