A1 Journal article (refereed)
The choice of control variables in empirical management research : How causal diagrams can inform the decision (2024)
Hünermund, P., Louw, B., & Rönkkö, M. (2024). The choice of control variables in empirical management research : How causal diagrams can inform the decision. Leadership Quarterly, Early online, Article 101845. https://doi.org/10.1016/j.leaqua.2024.101845
JYU authors or editors
Publication details
All authors or editors: Hünermund, Paul; Louw, Beyers; Rönkkö, Mikko
Journal or series: Leadership Quarterly
ISSN: 1048-9843
eISSN: 1873-3409
Publication year: 2024
Publication date: 02/12/2024
Volume: Early online
Article number: 101845
Publisher: Elsevier
Publication country: Netherlands
Publication language: English
DOI: https://doi.org/10.1016/j.leaqua.2024.101845
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/98805
Abstract
The Leadership Quarterly and the management community more broadly prioritize identifying causal relationships to inform effective leadership practices. Despite the availability of more refined causal identification strategies, such as instrumental variables or natural experiments, control variables remain a common strategy in leadership research. The current literature generally agrees that control variables should be chosen based on theory and that these choices should be reported transparently. However, the literature provides little guidance on how specifically potential controls can be identified, how many control variables should be used, and whether a potential control variable should be included. Consequently, the current empirical literature is not fully transparent on how controls are selected and may be contaminated with bad controls that compromise causal inference. Causal diagrams provide a transparent framework to address these issues. This article introduces causal diagrams for leadership and management researchers and presents a workflow for finding an appropriate set of control variables.
Keywords: causality; leadership (properties); management culture; management systems; research methods; variables; regression analysis
Free keywords: control variables; directed acyclic graphs; structural causal models; regression analysis; causal inference
Contributing organizations
Ministry reporting: Yes
VIRTA submission year: 2024
Preliminary JUFO rating: 3