【主讲】洪圣杰 助教授 (清华大学经济与管理学院)
【主题】Inference on Moment Inequalities with Unknown Functions
【时间】2014年4月16日 (周三) 10：30-12：00
【地点】上海财经大学经济学院楼801室
【语言】英文
【摘要】In this paper, we consider inference on conditional moment inequalities, in which the unknown parameter may contain infinite-dimensional components. We propose using the sieve minimum of a Kolmogorov-Smirnov type statistic as the test statistic, and derive its asymptotic distribution. A penalized bootstrap procedure, which incorporates a moment selection mechanism, is developed to get critical values. Our methods are robust to partial identification, and allow for the moment functions to be nonsmooth. We extend Hong’s (2012) analysis on conditional moment equalities in the following two directions: First, by allowing for moment inequality constraints, our inference method has a lot more applications; Second, the consistency of our test holds uniformly over a broad family of data generating processes.
