The Choice of Control Variables: How Causal Graphs Can Inform the Decision

Paul Hünermund, Beyers Louw, Mikko Rönkkö

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Control variables have a central role when empirical data are used to support causal claims in management research. The current literature has been intransparent in so far as to how control variables should be chosen, how many control variables should be chosen and whether a potential control variable should be included. Causal diagrams provide a transparent framework on how to select control variables for causal identification. This article delineates how causal graphs can inform researchers in leadership and management in finding the correct set of control variables and possible solutions in the case that causal identification is not possible or when causal identification requires unobserved variables.
Original languageEnglish
Title of host publicationProceedings of the Eighty-second Annual Meeting of the Academy of Management
EditorsSonja Taneja
Number of pages6
Place of PublicationBriarcliff Manor, NY
PublisherAcademy of Management
Publication date2022
Article number294
Publication statusPublished - 2022
EventThe Academy of Management Annual Meeting 2022: Creating a Better World Together - Seattle, United States
Duration: 5 Aug 20229 Aug 2022
Conference number: 82


ConferenceThe Academy of Management Annual Meeting 2022
Country/TerritoryUnited States
Internet address
SeriesAcademy of Management Proceedings


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