The Choice of Control Variables : How Causal Graphs Can Inform the Decision
Hünermund, P., Louw, B., & Rönkkö, M. (2022). The Choice of Control Variables : How Causal Graphs Can Inform the Decision. In Academy of Management Proceedings 2022 (2022). Academy of Management. Academy of Management Annual Meeting Proceedings. https://doi.org/10.5465/AMBPP.2022.294
Published in
Academy of Management Annual Meeting ProceedingsDate
2022Discipline
Basic or discovery scholarshipStrategia ja yrittäjyysBasic or discovery scholarshipStrategy and EntrepreneurshipCopyright
© 2022 Academy of Management
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.
Publisher
Academy of ManagementConference
Academy of Management Annual MeetingIs part of publication
Academy of Management Proceedings 2022ISSN Search the Publication Forum
0065-0668Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/165006190
Metadata
Show full item recordCollections
- Kauppakorkeakoulu [1376]
License
Related items
Showing items with similar title or keywords.
-
The choice of control variables in empirical management research : How causal diagrams can inform the decision
Hünermund, Paul; Louw, Beyers; Rönkkö, Mikko (Elsevier, 2024)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 ... -
To Omit or to Include? Integrating the Frugal and Prolific Perspectives on Control Variable Use
Mändli, Fabian; Rönkkö, Mikko (SAGE Publications, 2023)Over the recent years, two perspectives on control variable use have emerged in management research: the first originates largely from within the management discipline and argues to remain frugal, to use control variables ... -
Estimation of causal effects with small data in the presence of trapdoor variables
Helske, Jouni; Tikka, Santtu; Karvanen, Juha (Wiley-Blackwell, 2021)We consider the problem of estimating causal effects of interventions from observational data when well-known back-door and front-door adjustments are not applicable. We show that when an identifiable causal effect is ... -
Evolutionary game theory of continuous traits from a causal perspective
Lehtonen, Jussi; Otsuka, Jun (The Royal Society Publishing, 2023)Modern evolutionary game theory typically deals with the evolution of continuous, quantitative traits under weak selection, allowing the incorporation of rich biological detail and complicated nonlinear interactions. While ... -
Enhancing Identification of Causal Effects by Pruning
Tikka, Santtu; Karvanen, Juha (MIT Press, 2018)Causal models communicate our assumptions about causes and e ects in real-world phenomena. Often the interest lies in the identification of the e ect of an action which means deriving an expression from the observed ...