Causal Inference in Accounting Research

被引:156
|
作者
Gow, Ian D. [1 ]
Larcker, David F. [2 ]
Reiss, Peter C. [2 ]
机构
[1] Harvard Univ, Business Sch, Cambridge, MA 02138 USA
[2] Stanford Grad Sch Business, Rock Ctr Corp Governance, Stanford, CA 94305 USA
关键词
C18; C190; C51; M40; M41; Causal inference; accounting research; quasi-experimental methods; structural modeling; POLITICAL CONNECTIONS; CORPORATE GOVERNANCE; COMPENSATION; INFORMATION; MANAGEMENT; EARNINGS; IDENTIFICATION; STATISTICS; DISCLOSURE; SMOKING;
D O I
10.1111/1475-679X.12116
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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.
引用
收藏
页码:477 / 523
页数:47
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