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 editorsHünermund, Paul; Louw, Beyers; Rönkkö, Mikko

Journal or seriesLeadership Quarterly

ISSN1048-9843

eISSN1873-3409

Publication year2024

Publication date02/12/2024

VolumeEarly online

Article number101845

PublisherElsevier

Publication countryNetherlands

Publication languageEnglish

DOIhttps://doi.org/10.1016/j.leaqua.2024.101845

Publication open accessOpenly available

Publication channel open accessPartially 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.


Keywordscausalityleadership (properties)management culturemanagement systemsresearch methodsvariablesregression analysis

Free keywordscontrol variables; directed acyclic graphs; structural causal models; regression analysis; causal inference


Contributing organizations


Ministry reportingYes

VIRTA submission year2024

Preliminary JUFO rating3


Last updated on 2025-31-01 at 08:58