报告题目：Partial Identification in Moment Equality Models with Auxiliary Data

报 告 人：范延琴 教授

报告时间：7月20日（星期四）10:30

报告地点：清水河校区主楼A1-512

Abstract: In this paper we study identification and inference for a finite dimensional parameter defined by a finite number of moment equalities when the sample information comes from two separate data sets. Unlike existing work in the literature assuming the same data structure, we allow some or all functions to be non-additively separable. By an application of the continuous version of the monotone rearrangement inequality, we convert moment equalities corresponding to non-additively separable moment functions to moment inequalities with unknown functions. As a result, we obtain a set of moment equalities/inequalities with unknown functions characterizing the parameter of interest. Two main examples that motivate our model are: a generalized two-sample IV model and a generalized linear projection model. Via a detailed analysis of the identified set of the unknown parameter in both models, we demonstrate that incorprating moment inequalities help shrink the identified set and may help identify the sign of the parameter of interest which is not identified otherwise. Moreover using both models we illustrate how existing inference procedures such as those in Andrews and Soares (2010) can be modified to account for the first step estimation of the unknown functions appearing in the moment inequalities.

报告人简介：范延琴教授，现为美国Universit of Washtington (Seattle)大学经济系 Castor Professor。现为Journal of Econometrics,Journal of Financial Econometrics, and Econometric Reviews等刊物副主编. 研究领域包括非参数统计和计量经济. 在 Econometrica, Review of Economic Studies, JASA, and Journal of Econometrics等国际统计和计量经济刊物发表多篇文章。