Back to Papers

Out of Control: The (Over) Use of Controls in Accounting Research

Robert Lowell Whited, Quinn Thomas Swanquist, Jonathan E. Shipman, James MoonAccounting管理会计UTD24
The Accounting Review2021-07-14North Carolina State University; University of Alabama; University of Arkansas at Fayetteville; Georgia Institute of TechnologyDOI
Citations181
References28
Semantic Scholar
TL;DR

To guide future accounting research, the widely-used “Libby Box” framework is modified to incorporate control variable selection and construct to control variable mapping and is used to demonstrate the implications of these issues.

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.

Control (management)Control variableAccountingAccounting researchVariablesEconometricsSelection biasInstrumental variableComputer scienceVariable (mathematics)Selection (genetic algorithm)Statistics