How Likely to Be Caught: Identification and Estimation of Strategic Misreporting-厦门大学经济学院统计学与数据科学系

How Likely to Be Caught: Identification and Estimation of Strategic Misreporting

主讲人: Shengjie Hong
主讲人简介:

Assistant Professor, Department of Economics, Tsinghua University.

Prof. Shengjie Hong's CV 

主持人: Shan Zhou
简介:

Data of self-reported variables are prone to measurement errors due to misreporting behaviors. We consider economic environments where the self-reporting behavior is determined by: 1) The payoff structure, i.e., benefits from misreporting and penalties; and 2) The detection rate, i.e., the probability of being caught for misreporting. Under regularity conditions, we achieve nonparametric identification of the detection rate function, and proposed a three-step procedure to consistently estimation it. A desirable feature of our methods is that they do not rely on the specification of the payoff structure. As an empirical illustration, we apply our methods to study financial fraudulent reporting in China.

时间:2016-11-03(Thursday)16:40-18:00
地点:N303, Econ Building
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类型:系列讲座
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