控制(管理)
控制变量
会计
会计研究
变量
计量经济学
选择偏差
工具变量
计算机科学
变量(数学)
选择(遗传算法)
统计
经济
数学
人工智能
数学分析
机器学习
作者
Robert Lowell Whited,Quinn Thomas Swanquist,Jonathan E. Shipman,James Moon
标识
DOI:10.2308/tar-2019-0637
摘要
ABSTRACT In the absence of random treatment assignment, the selection of appropriate control variables is essential to designing well-specified empirical tests of causal effects. However, the importance of control variables seems under-appreciated in accounting research relative to other methodological issues. Despite the frequent reliance on control variables, the accounting literature has limited guidance on how to select them. We evaluate the evolution in the use of control variables in accounting research and discuss some of the issues that researchers should consider when choosing control variables. Using simulations, we illustrate that more control is not always better and that some control variables can introduce bias into an otherwise well-specified model. We also demonstrate other issues with control variables, including the effects of measurement error and complications associated with fixed effects. Finally, we provide practical suggestions for future accounting research. Data Availability: All data used are publicly available from sources cited in the text. JEL Classifications: M40; M41; C18; C52.
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