Causal Inference in Accounting Research
探讨会计研究者如何利用观察数据做出因果推断，指出当前准实验方法的局限，并建议加强描述性研究、因果机制分析和结构建模，为严谨的会计研究提供可行路径。
ABSTRACT This paper examines the approaches accounting researchers adopt to draw causal inferences using observational (or nonexperimental) data. The vast majority of accounting research papers draw causal inferences notwithstanding the well‐known difficulties in doing so. While some recent papers seek to use quasi‐experimental methods to improve causal inferences, these methods also make strong assumptions that are not always fully appreciated. We believe that accounting research would benefit from more in‐depth descriptive research, including a greater focus on the study of causal mechanisms (or causal pathways) and increased emphasis on the structural modeling of the phenomena of interest. We argue these changes offer a practical path forward for rigorous accounting research.