论文标题
内源选择模型中的单调性和对调查的应用
Relaxing monotonicity in endogenous selection models and application to surveys
论文作者
论文摘要
本文考虑了内源选择模型，特别是非参数。当人们使用仪器变量时，可以估计结果的无条件定律。使用在一维无法观察到的可分离的选择方程有时具有仪器单调性的不良属性。我们提出了允许非单调性的模型，并基于非参数随机系数指数。我们讨论了他们的非参数识别，并将这些结果应用于非线性统计数据的推论，例如在调查中的Gini指数等非响应时没有随机丢失。
This paper considers endogenous selection models, in particular nonparametric ones. Estimating the unconditional law of the outcomes is possible when one uses instrumental variables. Using a selection equation which is additively separable in a one dimensional unobservable has the sometimes undesirable property of instrument monotonicity. We present models which allow for nonmonotonicity and are based on nonparametric random coefficients indices. We discuss their nonparametric identification and apply these results to inference on nonlinear statistics such as the Gini index in surveys when the nonresponse is not missing at random.
