失控:会计研究中控制的(过度)使用

Robert L. Whited, Quinn T. Swanquist, Jonathan E. Shipman, James R. Moon
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引用次数: 61

摘要

在没有随机处理分配的情况下,选择适当的控制变量对于设计明确规定的因果效应实证检验至关重要。然而,相对于其他方法论问题,控制变量在会计研究中的重要性似乎被低估了。尽管经常依赖控制变量,但会计文献对如何选择控制变量的指导有限。我们评估了会计研究中控制变量使用的演变,并讨论了研究人员在选择控制变量时应考虑的一些问题。通过模拟,我们说明了更多的控制并不总是更好的,一些控制变量可以引入偏差到一个其他良好指定的模型。我们还演示了控制变量的其他问题,包括测量误差的影响和与固定效应相关的并发症。最后,对今后的会计研究提出了切实可行的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Out of Control: The (Over)use of Controls in Accounting Research
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 underappreciated 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 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. Lastly, we provide practical suggestions for future accounting research.
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