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Binary choice models with discrete regressors: Identification and misspecification

机译:具有离散回归的二元选择模型:识别和错误指定

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This paper explores the inferential question in semiparametric binary response models when the continuous support condition is not satisfied and all regressors have discrete support. I focus mainly on the models under the conditional median restriction, as in Manski (1985). I find sharp bounds on the components of the parameter of interest and outline several applications. The formulas for bounds obtained using a recursive procedure help analyze cases where one regressor's support becomes increasingly dense. Furthermore, I investigate asymptotic properties of estimators of the identification set. I describe a relation between the maximum score estimation and support vector machines and propose several approaches to address the problem of empty identification sets when the model is misspecified. (c) 2013 Elsevier B.V. All rights reserved.
机译:本文探讨了不满足连续支持条件且所有回归变量具有离散支持的半参数二元响应模型中的推论问题。我主要关注条件中位数约束下的模型,如Manski(1985)。我在感兴趣的参数的组件上找到了界限,并概述了几种应用。使用递归过程获得的边界公式有助于分析一个回归者的支持变得越来越密集的情况。此外,我研究了识别集的估计量的渐近性质。我描述了最高分估计和支持向量机之间的关系,并提出了几种方法来解决模型指定不正确时空标识集的问题。 (c)2013 Elsevier B.V.保留所有权利。

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