基地研究员吴震星老师参与的金融学顶刊Journal of Finance众包式论文“Non-Standard Errors”即将发表。这一研究共有来自金融领域不同背景的342位合作者、164个团队和34位同行评估者共同参与。

摘要: 

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

教师简介

吴震星，中南财经政法大学金融学院年薪制副教授，数字技术与现代金融学科创新引智基地研究员。研究领域包含市场微观结构理论在国际金融，资产定价与公司金融议题上的应用。研究成果发表于Journal of International Money and Finance, Journal of Corporate Finance, Pacific-Basin Finance Journal等国际期刊。