倫敦大學秦朵教授在中國人民經(jīng)濟學院舉行了一場題為時間揭秘內(nèi)生性偏差的講座，講座的主要內(nèi)容是：

　　這項研究揭示在確定內(nèi)生性偏差由相關(guān)解釋變量和回歸模型的誤差項之間的缺陷。通過剖析這些都導致了糾纏測量誤差，同時性偏差，遺漏變量偏見和自我選擇偏差的鏈接，該漏洞被發(fā)現(xiàn)從實際與單一解釋變量的模型是一個烏托邦式的不匹配阻止。隨之而來的估計為中心的路線，以規(guī)避相關(guān)被示為犯III型誤差。使用單變量基于“一致”估計沒有模型與數(shù)據(jù)的一致性會導致實質(zhì)利率的因果公設(shè)顯著失真。這一戰(zhàn)略錯誤是追查到這些因果公設(shè)翻譯虧損適當條件模型作為聯(lián)合分布的分解。從虧損歷史教訓突出利用數(shù)據(jù)信息在適當?shù)膶嵶C模型設(shè)計的因果推理的重要性。

　　秦朵, 倫敦大學亞非學院教授。她的主要研究方向為新興市場的宏觀、計量經(jīng)濟學發(fā)展、實證金融學以及國際經(jīng)濟學等， 已經(jīng)在國內(nèi)外領(lǐng)先經(jīng)濟學雜志上發(fā)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.