【主讲】Shakeeb Khan (Duke University)
【主题】Informational Content of Factor Structures in Simultaneous Discrete Response Models
【时间】2016年6月24日 (周五) 13：30-15：00
【地点】上海财经大学经济学院楼701室
【语言】英文
【摘要】We study the informational content of factor structures in discrete triangular sys-tems. Factor structures have been employed in a variety of settings in cross sectional and panel data models, and in this paper we attempt to formally quantify their informa-tional content in a bivariate system often employed in the treatment e↵ects literature. Our main findings are that under the factor structures often imposed in the literature, point identification of parameters of interest, such as both the treatment e↵ect and the factor load, is attainable under weaker assumptions than usually required in these sys-tems. For example, we show is that an exclusion restriction, requiring an explanatory variable in the outcome equation not present in the treatment equation is no longer necessary for identification. Furthermore, we show support conditions of included in-struments in the outcome equation can be substantially weakened, resulting in settings where the identification results become regular. Under such settings we propose a esti-mators for the treatment e↵ect parameter, the factor load, and the average structural function that are root-n consistent and asymptotically normal. The estimators’ finite sample properties are demonstrated through a simulation study and in an empirical application, where we implement our method to the estimation of the civic returns to college, revisiting the work by Dee (2004).
