Navigating the Methodological Frontier in Capital Market Research
更新了Gippel等人(2015)提出的内生性分析框架，聚焦差分差分法和自然实验的最新趋势，探讨结构估计等新方法如何提升因果推断的稳健性，并讨论如何分离公告中的新闻效应与价值效应，为金融研究者提供实用指南。
This paper revisits the issue of endogeneity in accounting and finance research by updating the framework initially proposed by Gippel et al . (2015), focusing on recent trends in the use of difference‐in‐differences (DiD) and natural experiments. We examine new requirements for rigorous endogeneity control, especially the structural estimation methods that extend beyond traditional ordinary least squares (OLS), two‐stage least squares (2SLS), instrumental variables (IV), and system GMM (generalized method of moments) approaches. These expanded expectations surrounding DiD assumptions and the need for structural estimation models allow for more robust causal inference and enable researchers to explore hypothetical scenarios. Additionally, we discuss the challenges of announcements with unresolved uncertainty and outline methods to separate news effects from value effects, particularly in cases involving options data. This paper serves as a practical guide for researchers to meet heightened standards in the finance literature and underlines the importance of theoretical modelling and multiple treatments in contemporary causal analysis.