中国人民大学

　　伦敦大学秦朵教授在中国人民经济学院举行了一场题为时间揭秘内生性偏差的讲座，讲座的主要内容是：

　　这项研究揭示在确定内生性偏差由相关解释变量和回归模型的误差项之间的缺陷。通过剖析这些都导致了纠缠测量误差，同时性偏差，遗漏变量偏见和自我选择偏差的链接，该漏洞被发现从实际与单一解释变量的模型是一个乌托邦式的不匹配阻止。随之而来的估计为中心的路线，以规避相关被示为犯III型误差。使用单变量基于“一致”估计没有模型与数据的一致性会导致实质利率的因果公设显著失真。这一战略错误是追查到这些因果公设翻译亏损适当条件模型作为联合分布的分解。从亏损历史教训突出利用数据信息在适当的实证模型设计的因果推理的重要性。

　　秦朵, 伦敦大学亚非学院教授。她的主要研究方向为新兴市场的宏观、计量经济学发展、实证金融学以及国际经济学等， 已经在国内外领先经济学杂志上发表多篇文章。

　　原文：This study exposes the flaw in defining endogeneity bias by correlation between an explanatory variable and the error term of a regression model. Through dissecting the links which have led to entanglement of measurement errors, simultaneity bias, omitted variable bias and self-selection bias, the flaw is revealed to stem from a Utopian mismatch of reality with single explanatory variable models. The consequent estimation-centred route to circumvent the correlation is shown to be committing a type III error. Use of single variable based ‘consistent’ estimators without consistency of model with data can result in significant distortion of causal postulates of substantive interest. This strategic error is traced to a loss in translation of those causal postulates to appropriate conditional models as decompositions of joint distributions. Historical lessons from the loss highlight the importance of utilising data information in adequate empirical model designs for causal inference.